DISSERTATION A PROPOSAL OF IMPLEMENTING READINESS BASED SPARING MODEL IN THE CHILEAN NAVY

Transcription

1 DISSERTATION A PROPOSAL OF IMPLEMENTING READINESS BASED SPARING MODEL IN THE CHILEAN NAVY MASTER OF SCIENCE IN ASSET MANAGEMENT CONTROL INTERNATIONAL MASTERS SCHOOL Student: Ignacio Andrada B. Supervisor: Michel Kuijer Date: 23 of May, 2011.

2 Master Dissertation Page 2 of 79 AKNOWLEDGEMENTS This report is written in order to fulfill the requirements to obtain the Degree of in Asset Management Control on the Hogeschool Zeeland. First of all I would like to thank my wife Danitza and my kids Isabel and Joaquin for being patient during this dissertation phase and supporting me with my struggle. Furthermore I would like to thank professors Michel Kuijer and Willhem Vantspijker for giving me the opportunity to follow this master course and supporting me with his advice and for the cooperation during this dissertation phase. His criticism and experience force me to keep on track. I hope this dissertation will contribute to the Asset Management Control process within the Chilean Navy Organization.

3 Master Dissertation Page 3 of 79 EXECUTIVE SUMMARY The goal of this research is to present a proposal of implementing Readiness Based Sparing (RBS) methodology in the Chilean Navy with the objective to maximize asset s availability, within imposed budgetary constraints, by optimizing the selection of spares mix and allowances. One of the most important benefits of RBS model is its systemic approach to analyze inventories decisions. On traditional Demand based sparing models, as the Chilean Navy actual model, spare inventories decisions are made independently of other spares stock, without clarity of how it impacts the rest of the system and its final availability. RBS model has been used on US Armed Forces for the past 20 years with successful results. Different reports show that after this implementation backorders decreased until 44% with 46% less investment. Knowing those benefits, the objective of this research is to evaluate a possible implementation of this methodology on Chilean Navy for spares management process. To do it will be necessary to analyze current management model of spare parts for Chilean Navy, to present Readiness Based Sparing model and its implementation on US Armed Forces and present a proposal of how can RBS be implemented into CN for spare parts selection adding into it several concepts taken from theory. After the analysis made of the current sparing model of Chilean Navy and knowing the experience of USA Navy implementing RBS model, this research concludes that it is possible to implement RBS model on CN. In order to implement this methodology CN should develop a software application with the functionalities describe in this model (calculate optimal spares mix, calculate availability curves, etc.), and a portal to facilitate the communication of the LCM team that is also an important element of the proposal model. Previous such implementation CN Navy has to assure the quality and reliability of SALINO s data, otherwise the whole implementation would be useless. A rough estimation of the benefits that CN may have implementing this model can be taken extrapolating the results obtained by US Navy. According with that information Chilean Navy could achieve the same availability levels than actual with about 10 Million USD less of budget, generating about less backorders and about less spares items required. With the same budget that CN spent on year 2010, by implementing RBS model it could have achieved about 10% more availability on the same period. On future researches may be analyze better the design of those software application, how to assure SALINO s data quality and how to integrate other useful parameters for asset s effectiveness calculations as capability and reliability variables.

4 Master Dissertation Page 4 of 79 TABLE OF CONTENTS. TABLE OF FIGURES. 6 TABLE LIST. 7 INTRODUCTION 8 1 PROBLEM S DEFINITION Research question Primary Objective Secondary Objectives Sponsors and supervisors Chilean Navy Organization Problem s description ACTUAL CHILEAN NAVY SPARE PARTS MANAGEMENT Actual CN model for spare parts inventories management Phase 1. Asset s functionality analysis Phase 2. Item s priority classification Phase 3. Policies definition Phase 4. SALINO customization and suggestions Conclusions and problems of actual model 20 3 READINESS BASED SPARING MODEL (RBS) Historical review of USA RBS model RBS benefits RBS model description RBS Key Concepts Availability Readiness Indentured Structure Single site model and Multi-echelon problem Cannibalization US Navy RBS application Technological implementation of RBS TIGER ACIM RBS process Comparison of RBS and concepts 38 4 A RBS MODEL TO CHILEAN NAVY CN-RBS model proposal CN-RBS Participating Entities 44

5 Master Dissertation Page 5 of Data CN-RBS process CN-RBS technological development CNRBS expected benefits 54 5 CONCLUSIONS 56 6 RECOMMENDATIONS 57 7 LIST OF ABBREVIATIONS 58 8 GLOSSARY OF DEFINITIONS 59 9 BIBLIOGRAPHY 61 APPENDIX A 64 APPENDIX B 66 APPENDIX C 67 APPENDIX D 74 APPENDIX F 76 APPENDIX G 78 APPENDIX H 79

6 Master Dissertation Page 6 of 79 TABLE OF FIGURES. Figure 1. Problem s map 9 Figure 2. CN Organization 11 Figure 3. Government contribution to Chilean Military Forces. 12 Figure 4. Fiscal Contribution to Chilean Armed Forces. 13 Figure 5. Distribution among Chilean Forces 13 Figure 6. Distribution of CN Expenditures without salaries. 14 Figure 7. Comparation of Overhaul costs. 15 Figure 8. CN inventory process 17 Figure 9. Readiness to cost relationship for alternative MALSP packages 25 Figure 10. A typical budget-to-readiness cost curve 27 Figure 11. Multi indenture structure 29 Figure 12. Single site model 30 Figure 13. Multi-echelon model. Ragged tree case. 30 Figure 14. Multi-echelon model with lateral ressuply. 31 Figure 15. Major ILS Element Contributors 32 Figure 16. Input data for RBS model 33 Figure 17. RBD example 33 Figure 18. RBS implementation model 34 Figure 19. TIGER model 35 Figure 20. Example of RBS utilization 36 Figure 21. RBS process 37 Figure 22. model 39 Figure 23. model 39 Figure 24. Functional breakdown 40 Figure 25. ILS through asset s life cycle. 41 Figure 26. RBS and Concepts for CN-RBS model. 42 Figure 27. CN-RBS Scope 43 Figure 28. CN-RBS Model 44 Figure 29. LCM Team 45 Figure 30. CN-RBS process 48 Figure 31. Model of Functional Breakdown 49 Figure 32. Group of assets RBD 51 Figure 33. CNRBSIS inputs and output. 52 Figure 32. Typical Ao v/s GE curves 53 Figure 33. A typical budget-to-readiness cost curve 53 Figure 36. Analysis of Ao v/s cost curve 54 Figure 37. British defense spending as percentage of GDP. 64 Figure 38. Spanish defense budget. 64 Figure 39. U.S. Military Budget. (Sharp, 2010) 65 Figure 40. CN Expenditures 1. (Treasury Ministry of Chile) 66 Figure 41. CN Expenditures 2. (Treasury Ministry of Chile) 66 Figure 42. EOQ model 69 Figure 43. ROP model 71 Figure 44. Max/Min model 72 Figure 45. Optimal system availability v/s cost. 75 Figure 40. MERBS application model. 76 Figure 41. MERBS application interface. 77

7 Master Dissertation Page 7 of 79 TABLE LIST. Table 1. Chilean Navy Expenditures. (Thousand of Chilean Pesos). 14 Table 2.Priority levels 18 Table 3. Inventories Policies. 19 Table 4. RBS AVCAL statistics 22 Table 5. Aircraft mix 23 Table 6. RBS/DBS Comparison 24 Table 7. Expected RBS CN benefits. 55 Table 8. Criteria for item classification. 67 Table 9. Motor Butt Analysis Example 68 Table 10.Priority levels 68 Table 11. K Factor table. 71

8 Master Dissertation Page 8 of 79 INTRODUCTION As every organization in the world, Chilean Military Forces need a budget to operate. The amount of money that Chilean Government is assigning for defense purposes has been historically decreasing in terms of percentage of national GDP. In this context, Chilean Military Forces and particularly the Chilean Navy, are challenged to search ways to be more efficient and improve the way of the assets are managed; get the best performances with the minimum possible cost. It implies to be more efficient in its resources spending, deciding carefully how to spend its restricted budget. One of the main costs within CN budget is the money destined for sparing processes; therefore it is one of the main places for improvements. Actually Chilean Navy spare parts are managed with the assistance of its ERP called SALINO. The model that SALINO utilizes to manage inventories is Items oriented. Therefore inventories decisions are taken considering each item s demand, its criticality and logistic information regarding only that particular item. Items oriented models are focused to assure items availability (Lee J. Krajewski, 2000). The main deficiency of this type of models is that their analysis is centered at item level therefore they cannot optimize systems cost-effectiveness because do not have a global system approach. System approach models are not focused on satisfy particular items demand but on achieve global system effectiveness. These models propose that the organization does not need spares but readiness of its assets. In this context the gravitational center of sparing process is not any more on each spare s need but on achieve total system readiness. It prioritizes purchase decisions in order to achieve system readiness and it evaluates how each item contributes to this goal. System approach models for sparing process were developed by USA military forces to improve the efficiency of their spares management. Several variations of these models have been developed and implemented in this organization during the last 30 years. They started with METRIC and VARIMETRIC models on 1966 (Sherbrooke, 2004). After 30 years of improvements the model utilized today by USA military forces is the Readiness Based Sparing model (RBS). Since this is the most modern and actualized model it will be taken as reference for this research. RBS process determines what sparing levels are necessary to achieve a defined system operational availability using a system s approach. It allows to destine resources exactly toward they are going to produce more benefit, ensuring asset s availability. RBS is the establishment of an optimum range and quantity of spares and repair parts at all stockage and user locations in order to meet approved, quantifiable, weapon system readiness, operational availability, or fully mission capable objectives. (Department of Defense, 2003). With this type of models managers are able to choose efficient mix of spare parts stock that satisfies availability requirements within budget restrictions. In this context the objective of this research will be to present a proposal of implementing readiness based sparing methodology in the Chilean Navy to make more efficient spares mix definition processes for the assets in order to increment assets within budget constraints. RBS model will help on decision making processes to determine the optimal spare mix that maximizes asset s availability under budget restrictions. In other words, to define the best way of spending the available budget on spare parts that maximizes asset s availability. In this research it will be presented the RBS model used on US Navy and a proposal of its application to Chilean Navy enriched by elements out of.

9 Master Dissertation Page 9 of 79 1 PROBLEM S DEFINITION First chapter is dedicated to present the problem that motivates this research, the objectives, scope and the research questions. Next map summarizes the problem presented on the introduction and the justification to do this research. Figure 1. Problem s map 1.1 Research question. How can Readiness Based Sparing model be implemented into Chilean Navy in order to increment asset s availability by finding optimal spare mix for the assets?

10 Master Dissertation Page 10 of Primary Objective Define how Readiness Based Sparing model can be implemented into Chilean Navy as methodology to maximize asset s availability, within imposed budgetary constraints, by optimal selection of spares mix and allowances. 1.3 Secondary Objectives Analyze current management model of spare parts for Chilean Navy. Present Readiness Based Sparing model and its implementation on US Armed Forces. Present a proposal of how can RBS be implemented into CN for spare parts selection. Present the benefits of such implementation. 1.4 Sponsors and supervisors Academic supervisor: Michel Kuijer, change agent in Asset Management of Copernicos Group. Technical supervisor: Rene Ortega. Logistic Director of CN. 1.5 Chilean Navy Organization Before to present in detail the problem that motivates this research, since it is developed within Chilean Navy, it is necessary to introduce briefly CN organization in order to be in context regarding its different departments and hierarchy.

11 Master Dissertation Page 11 of 79 Figure 2. CN Organization CN is organized in four general directives plus one department of naval operations and one department that gather the fifth naval zones. Naval Operations Directive coordinates different type CN forces: squad, submarines, aviation, marines. Personnel directive is responsible for all the activities related with human resources including also education and health care. Services Directive gathers all support process and activities to operate the units: Engineering, supply, R&D, recovering units, maintenance. Finances Department is responsible for the economic issues. Maritime Territory Directive provides services regarding environment care, meteorological reports, tsunami alerts. Naval zones are the territorial classification of Chile. It considers five zones.

12 Master Dissertation Page 12 of Problem s description. As every organization in the world, Chilean Military Forces need a budget to operate. The amount of money that Chilean Government is assigning for defense purposes has been historically decreasing in terms of percentage of national GDP. It is shown on next figure: Figure 3. Government contribution to Chilean Military Forces. (Defense Ministry of Chile, 2010)p This graph presents how government contribution to armed forces has been decaying in terms of GDP; it means that the purchasing power of the CN is decreasing every year because of spares cost increment. In this period Chilean National GDP has growth 395%. (Central bank of Chile). Absolute amounts for last 5 years are shown on table 1. This situation is not only happening in Chile. United Kingdom, Spain and even United States are examples of how other countries have been also decreasing, as percentage of its GDP, its national budget for defense purposes. See Appendix A. The 510 M USD of absolute increment of budget for Chilean Military Forces have been divided: 78% for increments on salaries and only 22% to operations and investments. It is shown on Figure 5.

13 Master Dissertation Page 13 of 79 Figure 4. Fiscal Contribution to Chilean Armed Forces. (Defense Ministry of Chile, 2010) p.306 Focusing on Chilean Navy historical budget we can observe that situation is even worse. Next figure shows the percentage of total military budget that every military force has been receiving (Navy, Army and Air Force) for the past 33 years. This graph shows how the percentage of the total military budget assigned by the government to Chilean Navy has decreased from 36.87% to 33.09% for the past 33 years. Figure 5. Distribution among Chilean Forces (Defense Ministry of Chile, 2010) p.308 Deeping on Chilean Navy situation, Table 1 and next figures show a detail of the main expenditure items of Chilean Navy for the past five years. The report considers 8 items: 1. Personnel salaries: Salaries. 2. Consumer goods and services: Goods and Services to support the operation of CN. This is the item where are charged all spare parts costs. 3. Personnel health care: Financing of CN health care system for the personnel. 4. Current transferences: Money transferred to other Chilean Government departments for services.

14 Master Dissertation Page 14 of Assets' acquisition: Different type of asset s acquisitions (not only capital assets). 6. New investments: Initiatives of new investments. 7. Loans: Loans to CN personnel. 8. Debt services: Debts. Table 1. Chilean Navy Expenditures. (Thousand of Chilean Pesos). (Treasury Ministry of Chile) (Appendix B) One of the most important items on CN expenditure structure, showed on table 1, is Consumer goods and services, item for assets operations and maintenance. It covers almost 90% of the total costs, taking out the salaries, Figure 9. Figure 6. Distribution of CN Expenditures without salaries. (Treasury Ministry of Chile)

15 Master Dissertation Page 15 of 79 Inside of Consumer Goods and services there are hundreds of items. An important number of them are related with sparing processes (spare parts supply chain: quotation, acquisition, storing and distribution). The amount of money dedicated specifically to these items is a big quantity every year. Unfortunately it is no possible to show details of this data because it is classified information for CN but it is around 30% of Consumer Goods and services item, i.e thousand of Chilean Pesos. This number is very important because it is the scope which this research will be dealing with. Research objective is precisely how to define the best way to spend that amount of money because due the weight of this item has on total CN budget, any improvement on the way of this item is managed will be traduced on important benefits for CN. Going back to table 1 it is possible to observe that, in spite of salaries have been increasing regularly during the past years, the item Consumer Goods and Services has remained almost unchanged on the same period. On the other hand the cost of maintenance activities increases every year. Next figure gives an example of those increments by comparing the same overhauling of two generators on 2008 and 2010 year. The activities and spares used on both overhauls were exactly the same but the cost increased almost 70% on 2010 version. Figure 7. Comparation of Overhaul costs. (Supply Department of CN) In this context, Chilean Military Forces and particularly the Chilean Navy, are challenged to search ways to be more efficient and improve the way of the assets are managed; get the best performances with the minimum possible cost. It implies to be more efficient in its resources spending, deciding carefully how to spend its restricted budget. Actually Chilean Navy spare parts inventories are managed with the help of its ERP called SALINO. SALINO is a MIMS based platform, provided by Mincom Company, with origin in mining industry. The model that SALINO utilizes to manage inventories is Items oriented. Therefore inventories decisions are taken considering each item s demand, its criticality and logistic information regarding only that particular item. Items oriented models are focused to assure items availability (Lee J.

16 Master Dissertation Page 16 of 79 Krajewski, 2000). Their main concern is to define the moment and the quantity of units that an item has to be reordered to assure item s stock available on the warehouse. The main deficiency of this type of models is that their analysis is centered at item level therefore they cannot optimize systems cost-effectiveness because do not have a global system approach. System approach models are not focused on satisfy particular items demand but on achieve global system effectiveness. These models propose that the organization does not need spares but readiness of its assets. In this context the gravitational center of sparing process is not any more on each spare s need but on achieve total system readiness. It prioritizes purchase decisions in order to achieve system readiness and it evaluates how each item contributes to this goal. One System Approach for sparing process is the Readiness Based Sparing model (RBS) utilized by US Navy. RBS process determines what sparing levels are necessary to achieve a defined system operational availability using a system s approach. It allows to destine resources exactly toward they are going to produce more benefit, ensuring asset s availability. RBS is the establishment of an optimum range and quantity of spares and repair parts at all stockage and user locations in order to meet approved, quantifiable, weapon system readiness, operational availability, or fully mission capable objectives. (Department of Defense, 2003) With this type of models managers are able to choose efficient mix of spare parts stock that satisfies availability requirements within budget restrictions. Having in mind the budget restrictions that Chilean Navy is facing, presented on previous pages, RBS seems to be an interesting model that could improve the efficiency of how spare parts inventories of CN are managed. In this context the objective of this research will be to present a preliminary proposal of implementing readiness based sparing methodology in the Chilean Navy to make more efficient spares mix definition processes for the assets in order to increment assets within budget constrains.

17 Master Dissertation Page 17 of 79 2 ACTUAL CHILEAN NAVY SPARE PARTS MANAGEMENT In this chapter the method used actually by Chilean Navy to manage its spare parts is presented. This chapter is important because it will show the problems of actual spares management model on CN and, therefore, the motives to propose a new methodology. It will be presented the actual model for spares management with its different phases, the functionalities of SALINO ERP System and the problems of the actual methodology. 2.1 Actual CN model for spare parts inventories management. The processes regarding spares management are located on Services Directive particularly on Engineering and Supply departments. One of the most important processes in this area is spare s inventories level definition. Spares inventories management is the process in which spare s stocks are defined and maintained in order to assure the maximum asset s availability. It means to answer following questions: WHAT, WHEN AND HOW MANY spares to buy. These processes are leaded by Engineering department but considering the experience and opinion of Operational and Supply departments. The phases that considers this process are shown on next figure. Figure 8. CN inventory process (Supply Department of CN)

18 Master Dissertation Page 18 of Phase 1. Asset s functionality analysis First stage is to define the missions of the asset and its functionalities. It is necessary because each spare s criticality and policy is defined according how it contributes final asset s missions. Here a basic functional analysis of the asset is made decomposing it on its main installations Phase 2. Item s priority classification. This phase objective is to define which policy will be applied to each spare. It is to answer the question WHAT to reorder. Previous to assign policies and priorities it is necessary to classify items. To do it Chilean Navy develops an analysis called ABC analysis which classifies items according different criteria (See Appendix C for list of criterion). Finally a priority level is assigned to each spare from next table. P. Group Description P1 Extremely Critical spares P2 Critical spares P3 Important spares but not critical P4 Ordinary spares Table 2.Priority levels Priority level is a categorization of each asset s priority taking into account general criteria evaluation. The category that each spare belongs is defined subjectively by the expert s opinion. There is not quantitative formula to assign priority class for the spares (See Appendix C). Each spare s category is decided by the experts looking at the ABC categorization and assigned subjectively Phase 3. Policies definition Inventory policies are the strategies that govern the different activities to define stock spares levels (Reorder point, EOQ, etc). In Chilean Navy Case inventory policies are defined according previous Priority Classification table. SALINO, CN information system, has the capabilities to calculate automatically stock safety levels, EOQ, ROP and generate alarms suggesting purchase orders once the stock goes under those safety levels. However, since SALINO is a platform developed for mining industry, these options can t be fully applied in CN because a Navy organization has to take into account many other subjective considerations intrinsic to armed forces like war scenarios, country alliances, suppliers risks, war armament obsolesce and so on. Due these considerations, CN has defined different inventories strategies according with each Priority Groups previously defined. They are:

19 Master Dissertation Page 19 of 79 P4 and P3. Ordinary and Important Spares but not critical Policy: Stock Zero / Under Demand: For these types of items the policy is to buy only when the spare is required and only the quantity needed. It means Zero stock policy. Since those spares are not critical and many of them are COTS (Commercial off the shelf), can be bought on local markets, it is not problem to wait the time to acquire the asset. This policy allows CN to reduce acquisition and storage costs and also diminish workload of the logistic personnel because they only have to take care of this spares when they are required for a particular unit. P2. Critical Spares Policy: SALINO suggestions/under demand. To manage these kind of spares coexist two strategies; SALINO suggestions system and also acquisition under demand in case when an exceptional order is received. When SALINO system generates an alarm, logistic operators evaluates the suggestions and contact engineering department and operational officer to confirm the real need of that order, once it is confirmed the purchase order is sent to the supplier. How SALINO generates de suggestions will be explained on next subtitle. P1. Extremely Critical spares. Policy: Manual control / SALINO suggestions In case of the most critical spares the inventory is strictly controlled because it affects directly the availability of the assets. To do it SALINO is set with high security levels and the engineers are constantly reviewing stocks levels. In this case also when a SALINO suggestion is generated logistic department consults engineering and operational units but almost hundred percent of the orders are finally generated. Next table resumes different policies. P. Group Description Policy Inventory management P1 Extremely Critical spares Stock guaranteed Manual control / SALINO suggestions P2 Critical spares Moderate stock levels SALINO suggestions/under demand P3 Important spares but not critical Stock Zero Under demand P4 Ordinary spares Stock Zero Under demand Table 3. Inventories Policies.

20 Master Dissertation Page 20 of Phase 4. SALINO customization and suggestions. As it was told before SALINO is the Chilean Navy ERP. It has a module dedicated to manage spares inventories. It has the property to calculate the most important parameters related with spares management like Reorder Quantity (EOQ), Reorder Point (ROP), Forecast demands, etc. Based on these calculations SALINO sends automatically suggestions to Supply department operators to advice purchase orders. Acquisitions department decides if the purchase has to be executed (consulting operational experts) and if it has the budget available. To know more how SALINO makes de calculations of these parameters refer Appendix D. More information about SALINO reports on Appendix E 2.2 Conclusions and problems of actual model To manage spare parts Chilean Navy utilizes a traditional item oriented model. Items are classified using different levels of criticality, for low critical items the policy is stock zero inventory, for critical spares the organization calculates stock parameters, like reorder point (ROP) and Economic Order Quantity (EOQ), using traditional formulas of Wilson Model (Silver, Edward; Pyke, David; Peterson, Rein., 1998). The formulas are implemented on SALINO ERP Software therefore this system each has the capability to arise an alarm each time that a spare needs to be replaced. These suggestions are analyzed by logistic department in coordination with operational personnel to finally make decision of buying that item. The major problem of using an item oriented model is how to prioritize inventory needs facing budget restrictions. Maintenance budget is assigned to each asset at the beginning of the year, once it is received the main question is: Which spares do I have to buy? Where do I have to assign priorities? Items oriented models cannot answer that question because do not have a systemic view since they are designed to assure only items availability. It is a strong contradiction because what the organization needs are not spares but its assets availability. This is the goal and this is what sparing models have to pursue. Other important problem comes from the fact that there is not clearness how each spare contributes to asset availability therefore its criticality classification is made according subjective opinions. Many times the budget is spent in spares that provide less benefit, to final asset s availability, than others spares that are leaved out and could have increase asset s availability in better way. Mission policies and sparing policies are not aligned because sparing process is focused on stock reposition of spares according its logistic formulas but not necessarily it is coordinated with what the asset needs to develop its mission. Another problem is the model used, EOQ, was designed for demands constant and known but the reality in Chilean Navy is the demand is unpredictable and fuzzy therefore the model is not much precise in its calculations.

21 Master Dissertation Page 21 of 79 3 READINESS BASED SPARING MODEL (RBS) Third chapter is dedicated to present the main concepts of Readiness based sparing model utilized on US Military forces. The chapter will start with a historical review of how United States forces have implemented this model and some references with the benefits that they have estimated after this implementation. After presenting a general description of this model are commented its key concepts. Later is introduced the application of RBS on US Navy (for later on to be able to compare with the Chilean Navy) with its processes and some technological requirements. To finalize the chapter, since it is a Master thesis of Asset Management Control (), a comparison is made between the RBS model and concepts. 3.1 Historical review of USA RBS model Readiness Based Sparing is the model used by US Armed Forces to manage logistic processes for their assets support. This model has been gradually implemented on this country from Their previous model was a traditional Demand Based Model (DBS) item oriented. (Spignesi, 1998) Some of the other models utilized by US forces on sparing processes were DRIVE (Distribution and repair in Variable Environments) (Miller, 1992), SESAME, (French, 1994) ARROWS (F.C. Strauch, 1982), METRIC, VARI-METRIC (Sherbrooke, 2004) Making an historical review of RBS implementation in USA we can find the first documents on 1982 when the assistant Secretary of defense, Manpower Julian, published a memorandum standing: The traditional approaches to determining inventory levels and measuring supply performance have been related to the satisfaction of demands for items of supply. Such approaches do not normally identify the degree to which various secondary items contribute to the operational availability of weapon systems. We are now attempting to relate stockage decisions to the effect they have on weapon system readiness. This concept represents a significant departure from traditional supply management in that it shifts the materiel manager s concern from item-oriented inventory performance to a weapon system performance I can t overemphasize the significance of this effort of the magnitude of changes to our materiel management policies and processes that it offers (Kingman, 1982) On 1985 was published a Secretary of defense s directive which directed the services to adapt a weapons system inventory management concept that would tie together end items, readiness and cost: Improving the material readiness and sustainability of our combat forces is a top priority of the Department. In order to accomplish this, we must develop and implement innovative approaches to inventory management that enables us to focus our attention and resource on the ideas that enhance end item readiness. Weapon systems management is the approach that provides greatly improved systems management capabilities. Implementation to this approach will be a long range, incremental effort and will require changes in the area of supply, procurement maintenance, transportation, and financial management. However, implementation of weapon system management will improve material readiness significantly and will provide the capability to utilize defense resources more effectively (Dudley Knox Library, 1985)

22 Master Dissertation Page 22 of 79 Since 1985 US Army, Navy and Air Force have developed inventory models that have incorporated Readiness Based Sparing models using different algorithms that provide recommend stock levels through the use of the marginal analysis technique. Air force was the first to implement this new methodology, after was followed by US Navy, later was incorporated by the Army and finally by Marine Corps. Several analyses showed after different implementations a decrease in backorders and fewer investments than previous inventory models. It will be shown on next subtitle. Having into account the experience of more than 15 years and the good results Readiness Based Model was defined as the unique model to manage logistic process for all the US Forces, which are working now to integrate all different forces in a common RBS system to generate synergy and reduce costs. It has been established on instructive DoD (Department of Defense, 2003) This instructive provides the standard specifications for the Secondary Item Stratification to ensure the uniform portrayal of materiel requirements and assets of individual secondary items at the wholesale and retail levels among all DoD Components 3.2 RBS benefits To comment the benefits of RBS implementation on US military forces it is shown, as example, an analysis made on the AVCAL performances (Aviation Consolidated Allowance List) for the aircraft carrier USS AMERICA to support its airwing during 1993 and 1994 (Hale A., 1994). The survey is made comparing the performance, in terms of availability and costs, of the same AVCAL using RBS and DBS models An AVCAL consists of repairable airborne organizational-level removable components called weapon replaceable assemblies (WRAs) and their lower indenture repairable and consumable subcomponents. The RBS method was used to determine allowances for mission-critical WRAs only. AVCAL allowances for the subcomponents were not changed. The survey is published by Anne Hale in 1994 from the Center of Naval Analyses. Next table shows the comparison of the results of both models in terms on cost and number of items required. Table 4. RBS AVCAL statistics (Hale A. J., 1992) This research showed that RBS model took $33 million and 332 less items than the DBS AVCAL to achieve the same level of availability.

23 Master Dissertation Page 23 of 79 On DBS model the AVCAL took 129 MUSD while with RBS took 96 MUSD, achieving the same availability. In terms of amount of items, RBS needed units while DBS model used items obtaining the same availability level. Those results confirm how RBS model can achieve same availability levels but using significantly less resources than traditional methods: a decrease of 26% on spares cost and 20% on items quantity. Other interesting research developed by the Center of Naval Analyses is Implementing RBS in the Marine Aviation Logistic Support Program (Geis, 1995) that makes a simulation of different methods to ensure that Marines could rapidly deploy aviation logistic support needed to sustain flight operations in war time. In this context they define two main types of spare packages: FISP: Fly in support packages, designed to provide the spare parts needed for the first 30 days of contingency. CSP: Contingency support packages that contain the spare parts needed to establish an Intermediate level capability of repair. The simulation is made using a mix of different 160 aircrafts deployed on Middle East to 4 months war. Aircraft mix is: Table 5. Aircraft mix (Geis, 1995) The survey compares DBS performance with several variations of RBS methodology, they are: RBS READP: RBS with protection levels (Maximum and minimum levels). RBS READ: RBS without protection levels.

24 Master Dissertation Page 24 of 79 RBS COSTP: RBS cost oriented instead of readiness oriented (RBS model where the independent variable is cost instead of readiness) with protection levels. RBS COST: RBS cost oriented instead or readiness, without protection levels. Next table shows the results of a spare parts packages definition using DBS model and different types of RBS Methodologies Table 6. RBS/DBS Comparison (Geis, 1995) This report shows the cost of different spares packages to support the aircrafts during 4 months of war providing all of them same availability levels. The results of this report confirm the benefits of RBS methodology. Spare part packages, that obtain same availability level, are considerably cheaper on different RBS model than the ones using traditional DBS methodology. In fact the most expensive RBS model costs 85 MUSD less than DBS package. It means that RBS model can save, at least, 85 million of USD obtaining same asset s availability than traditional DBS methodology. It means a reduction around 35% on spares cost. From the readiness or availability point of view this research also shows how RBS implementation improves assets availability at the lowest cost. (Geis, 1995) Following graphs shows comparisons of readiness versus cost using DBS model and the alternative RBS models with each selected spares packages. The x-axis shows the average difference in costs for an ACE (Aviation combat element) and the y-axis the average difference in readiness between different sparing models.

25 Master Dissertation Page 25 of 79 Figure 9. Readiness to cost relationship for alternative MALSP packages (Geis, 1995) (FISP and CISP combined) It is possible see clearly on this figure how RBS spare parts packages are most cost-effective than the DBS packages. For the same amount of money that is spent on spare parts on DBS model using any alternative of RBS methodology can be increased asset s readiness by about 10% points on average. It means that RBS models can increase readiness and availability of the asset using the same amount of money. Air force analyses showed also improvements after implementing RBS model. On reports presented at Brem s research (Brem R., 1997) the average number of backorders decreased by 44% with an investment 46% less than inventory models previously utilized. Backorders are unfilled spare demands (Kingler, 1994). Using daily demand data and actual repair times from the same test period and the same level of investment, RBS model achieved 32% higher fill rate with corresponding 39% reduction of backorders (Brem R., 1997). Fill rate is the probability that at least one spare item is available on the warehouse shelf when a demand for an item occurs: it is the probability that the number of demands during the resupply time is strictly less than the spare stock level backorder. (Kingler, 1994) This report shows that by implementing RBS model Air Force reduce until 44% de number of unfilled spare demands (backorders). It is complemented with a 46% less investment than previous inventory model and an increase of 32% higher probability of finding the spares required (fill rate). Summarizing the estimated RBS benefits are: An average decrease of 35% on spares cost to obtain same availability than DBS model. 20% of decrease on the amount of items required to obtain same availability than DBS model. Increment of 10% on availability level using the same amount of money than DBS model. An average decrease in backorders of 40% resulting in the same availability. 32 % higher fill rate.

26 Master Dissertation Page 26 of RBS model description. Readiness Based Sparing is a system approach whose goal is to maximize the operational availability of a weapon system within management imposed budgetary constraints. (Spignesi, 1998) One of the most important contributions of RBS model has been to offer a systemic approach to analyze inventories decisions. It is important because, as it was commented before, in traditional Demand Based Models spare inventories decisions are made independently of other spares stock. They are made according each spare s demand using the traditional formulas of EOQ and ROP but without clarity of how it impacts the rest of the system and its final availability. Other interesting definitions and comments of RBS model are: The establishment of an optimum range and quantity of spares and repair parts at all stockage and user locations in order to meet approved, quantifiable, weapon system readiness, operational availability, or fully mission-capable objectives. (DL ) (DOD M, 2009) RBS goes a step further of DBS models because, instead both use the same data and functions, it links the supply resources and their cost directly to the readiness of the individual assets. Specifically RBS does this one of two ways: To meet a cost objective for maximum readiness. To meet a readiness objective at the lowest cost. (Hale A. J., 1992) RBS is a business process and decision support system that provides the capability to achieve specified weapon system Availability or Fully Mission Capable (FMC) goals and minimize investment in spares inventories. It can also maximize readiness at a fixed cost. (CACI Company) RBS determines the marginal increase in operational performance per increase in unit spares cost, therefore the most cost-effective spares can be added until the operational performance requirement is adequately supported. (Spignesi, 1998) RBS is the process of calculating stock levels for locations with the objective of minimizing system EBOs (Expected Backorders). EBO depends on how many units of an item are in stock; the higher the stock level, the lower the expected backorders. (Burnworth, 2008). A system readiness-cost curve, as shown in next figure, is helpful to understand this concept. Next figure shows a typical theoretical cost v/s readiness curve.

27 Master Dissertation Page 27 of 79 Figure 10. A typical budget-to-readiness cost curve (Kinskie S., 1997) The curve presents the incremental cost in order to achieve certain level of readiness or higher one. This curve gives inventory manager the availability to see the difference in costs and how much availability can be attained within the budget constraints. 3.4 RBS Key Concepts. Readiness based sparing model uses several concepts, the most important are: Availability Availability is key concept on RBS model because it is the final goal to attain in this methodology. Every decision is taken in order to achieve the maximum asset s availability at minimum cost therefore it is the primary performance metric in RBS model. (Burnworth, 2008) In general Availability is defined as the expected percentage of time that an asset is not down for spares at a random point in time. i.e. is capable of performance its intended function. (O'Malley, 1983) One of the most extended formula to calculate Availability is (McMaster, 2000): Where: MTBF: Mean time between failure (Average time between successive failures) MTTR: Mean time to repair (Average time required to repair a system in its operating environment) MSRT: Mean Supply Response Time (Average time delay caused by the logistic support system).

28 Master Dissertation Page 28 of 79 Here is important to highlight that MTBF and MTTR are parameters defined on engineering process therefore the only variable which can be controlled by logistic department is MSRT. Therefore to increase Ao the challenge is to diminish MSRT; it can be made buying an infinite number of spares or applying intelligent methodologies, like RBS, to make more efficient logistic sparing process. MSRT equation is With: Where: D i represents the expected demand for item i. B i represents the expected number of backorders for item i. To see more information regarding Availability calculations refer Appendix D Readiness. Readiness is defined as (DOD M, 2009): A measure or measures of the ability of a system to undertake and sustain a specified set of missions at planned peacetime and wartime utilization rates. Measures take account of the effects of system design (reliability and maintainability), the characteristics of the support system, and the quantity and location of support resources. Examples of system readiness measures are combat sortie rate, fully mission capable rate, and operational availability. Other interesting definition is: Readiness is the capability of a product to perform its intended function when called upon is its operational readiness or its operational availability. The difference between readiness and availability is that the latter includes only operational and downtimes, while the former also includes free and storage times- that is, period when the product is not needed availability is often estimated by calculating the fraction of total need time in which the product is operational or capable of providing useful output. (Pecht, 1995) The readiness of a system is a function of that system s reliability, maintainability and supportability (Kinskie S., 1997). These terms are defined as follows: Reliability is the duration or probability of failure free system performance under a given set of conditions. Maintainability is the ability of an item to be retained in or restored to a specified operating condition when maintenance is performed by personnel having specified skill levels, using prescribed procedures and resources, at each prescribed level of maintenance and repair.

29 Master Dissertation Page 29 of 79 Supportability is the effectiveness of the logistics support provided for a system. It represents the remaining downtime where no active maintenance (including fault isolation) is being performed Indentured Structure RBS model cannot be implemented without understand the indentured structure decomposition of the assets. An indentured structure provides a hierarchy of parts in a manner similar to the way a typical organization char depicts a hierarchy of departments and units in an organization. (Spignesi, 1998). It corresponds to a physical breakdown of an asset. Lower indentured spares are common items that can be used in several different higher up items of the indenture structure. On US model first indenture units are called LRU (Line replaceable unit) because this activity takes place on operational line. Second indenture items are called SRU (Shop replaceable unit). (Sherbrooke, 2004). On every system also it is possible to find third, fourth and lower indenture parts. Since an item at particular indenture is composed of several lower indenture items, the cost of each lower indenture item is less than of its parents. This characteristic of the systems is what makes that optimal stock levels of different items are not independent. Figure 11. Multi indenture structure Single site model and Multi-echelon problem Single site is a model that looks at the spares selection only at a single base and disregards spares determinations made at other bases. The model considers a central supply center which receives the items and distributes to bases that work as maintenance centers with retail supply capabilities.

30 Master Dissertation Page 30 of 79 Figure 12. Single site model Real systems are usually more complicated as single site model because they have several intermediate sites of distribution, those systems are called Multi-echelon. In fact single site model is a particular case of Multi-echelon model with a number of echelons equal to one. Multi-echelon systems are representation of the hierarchical tree in which the items are moving from central supply center to maintenance units through intermediate sites and vice versa. Vice versa case regards with reverse logistic processes for equipment s repair. An example of this model is found on submarines management: some spare stock is kept on each submarine (the first echelon); some is kept on second-echelon supply ships that are periodically accessible by the submarines; these in turn are supported by the third-echelon home port facilities; and finally there are fourth-echelon Navy depots. (Sherbrooke, 2004) Figure 13. Multi-echelon model. Ragged tree case. (Sherbrooke, 2004) On real situations there are many times that supply process is made direct from supplier to bases or intermediate sites, also on CN situation some products are sent directly from suppliers to Talcahuano base without pass through the central warehouse in Valparaiso. The RBS model considers those cases with several models designed to define which the right place to store the spares is. Since the scope of this research is only bounded to spares mix definitions not has been researched the location models on RBS, it can be done in a later research projects. In this thesis the aim is to define which spares to buy but which the optimal place to keep them is has been left out for future researches.

31 Master Dissertation Page 31 of 79 A particular case of Multi-echelon model is when there is presence of lateral resupply. i.e. when a unit supplies units of the same echelon for example a base supplies other base with spares (Burnworth, 2008): Figure 14. Multi-echelon model with lateral ressuply. (Burnworth, 2008) A complete RBS implementation must considers Multi-echelon features because decisions must be made throughout the entire supply system in order to calculate the optimal spares levels to have on hand to satisfy Back Orders. In single site model all the bases would sub-optimize the total system because it would be ignoring like decisions at other bases. The Multi-Echelon Technique for recoverable Item Control (METRIC) is an example of such a multiechelon inventory model. (Sherbrooke, 2004) (Brem R. D., 1997) Cannibalization In maintenance of mechanical or electronic systems with interchangeable parts, "cannibalization" refers to the practice of removing parts or subsystems necessary for repair from another similar device, rather than from inventory, usually when resources become limited. The source system is usually crippled as a result, if only temporarily, in order to allow the recipient device to function properly again. Cannibalization is usually due to unavailability of spare parts, due to an emergency situation, long resupply times, physical distance, or insufficient planning or budget. Cannibalization can also be due to surplus inventory. At the end of World War II a large quantity of high quality, but unusable war surplus equipment such as radar devices made a ready source of parts to build radio equipment. (Wikipedia) On RBS implementation is important to consider the existence of cannibalization because it modifies the calculations regarding amount of spares needed for an assets at one particular place. Consider cannibalization will change optimal stock levels definition because it affects availability rate of the asset. Cannibalization effect is usually inserted on first echelon levels of the model because it is at maintenance unit levels that mainly this situation occurs.

32 Master Dissertation Page 32 of US Navy RBS application On previous subtitles it has been presented Readiness Based Sparing methodology. The next logical question is how this methodology can be implemented in real organizations, which components, procedures and products a organization needs to make reality the benefits of this conceptual model. In this report the implementation of RBS on US Navy will be consider. In complex organizations, as armed forces, where thousands of systems are involved and a multitude of different installations, to keep in control demands a solid logistic system to enable management. This system is usually called ILS (Integrated Logistic System) that may consider: Maintenance plan, sparing process, training, documentation, tools, test, facilities, software applications, and so on. A power point presentation founded on the webpage of the Office of the under secretary of defense for Acquisition, Technology and Logistics (USDAT&L Webpage) establishes that in order to implement RBS model the major ILS (Integrated Logistic Support) element contributors are: Reliability engineering: because it provides the information regarding reliability block diagrams which is a key input to RBS model. Supply support: because it provides the information about supply performances like Mean delay times and also failures records which are needed to calculate asset s availability. Configuration management: To provide mission definitions and functional breakdown of the assets to define critical spares. Figure 15. Major ILS Element Contributors (USDAT&L Webpage) Those areas contribute with data to build RBS model and provide following data: Configuration management: 1) Design Reference Mission: (Operating Profile - System Utilization)

33 Master Dissertation Page 33 of 79 2) Configuration information: SCLSIS (Ship config. and logistic information system), CDMD-OA (Config. data managers database open architecture), etc. Engineering: 3) Reliability and Maintainability: Reliability Block Diagrams with MTBF, MTTR, Duty Factors, Redundancies Supply support: 4) Provisioning: LSA (Logistic support Analysis), ICAPS (Navy interactive cataloging and provisioning system), WSF Level, Unit Prices, Quantities RBS Model Optimal Spare mix Figure 16. Input data for RBS model A special comment has to be made regarding RBD (reliability block diagram) because is a key component within RBS model. RBD is a graphical representation of the reliability and maintainability of a system. A Reliability Block Diagram (RBD) performs the system reliability and availability analyses on large and complex systems using block diagrams to show network relationships. The structure of the reliability block diagram defines the logical interaction of failures within a system that are required to sustain system operation. The input node flows to arrangements of series or parallel blocks that conclude to the output node at the right side of the diagram. Figure 17. RBD example Technological implementation of RBS

34 Master Dissertation Page 34 of 79 To implement RBS model US Navy uses a software application called MERBS. MERBS has been developed by CACI company (CACI Company) and it is composed of two main modules: TIGER and ACIM modules. Next figure show how TIGER and ACIM modules are connected inside MERBS application: Figure 18. RBS implementation model (CACI Company) TIGER provides to ACIM Readiness calculations using the inputs (Reliability Engineering data and configuration management) plus supply effectiveness data provided by Supply Department. ACIM defines optimal Spares mix which is recorded on a special Spares Parts database. This Database registers each COSAL mix used by operational department. The real utilization of those spare is Supply department to recalculate real Supply effectiveness TIGER TIGER is a computer simulation program to predict operational availability based on downtime attributable to: mission essential equipment failures, logistical and administrative delay times for replacement parts, and preventive maintenance. It is based on RMA model (Reliability, Maintainability and Availability) TIGER simulation is a time-continuous reconstruction of a platform s average mission which involves simultaneous consideration of system and platform events. The inputs to this software are: Equipment parameters: (MTBF, MTTR, Duty Cycle)

35 Master Dissertation Page 35 of 79 Operating rules: (Logistic Delays, Mission Timelines, System Configurations, Maintenance policy, Supply Effectiveness) The outputs are simulations of: Reliability Availability System downtime Figure 19. TIGER model (CACI Company) Once TIGER software has calculated RMA parameters next step is to find optimal spares mix that allow achieve desired availability. It is made using ACIM model and component ACIM The Availability Centered Inventory Model (ACIM) provides the optimal relationship between supply response and the cost of spare parts. ACIM is operated at the Equipment Type level in computing allowances to support the system or mission area readiness objective. ACIM produces a ranked list of spares by cumulative cost and calculated supply (gross) effectiveness of the spares. Supply (or Gross) Effectiveness is the probability that the part is available in the storeroom to restore the equipment to operational condition when occurs a failure (or downing). Supply effectiveness is combined with the system downtime information from TIGER. Spares are then selected across all equipments to build an A O v/s relationship for the system.

36 Master Dissertation Page 36 of 79 More information regarding MERBS software application and its outputs can be found on Appendix F. MERBS application helps decision makers to define spares mix by providing an interface that allow evaluating availability increments each time that is added a new spare to the mix. In next picture is shown a theoretical example of that evaluation. For instance, if it is added a 6th unit of spare A availability rate of the asset increases to 66,67%, if it is added a 11th unit of spare B availability rate increases to 66.69%, and so on. Figure 20. Example of RBS utilization With this application supply officers can evaluate the benefits, in terms of assets availability, of buying a new spare by playing different options and selecting which provides higher availability. Finally the application may define automatically optimal spare mix by using Montecarlo simulations and optimization techniques to determine the group of spares that produce the maximum availability within budget constrain. 3.6 RBS process The process of RBS model is composed of three main phases: 1. Readiness assessment phase 2. Sparing determination phase 3. LCM phase (Life cycle management) Each one of these phases contains several sub-phases. They are shown on next figure:

37 Master Dissertation Page 37 of 79 Where: Figure 21. RBS process (CACI Company) DRM: Design reference mission MSC: Maintenance Significant Components RBD: Reliability block diagram NSAF: Non Standard Allowance File SNSL: Stock number sequence list Therefore a summary of the most important stages of RBS process is (CACI Company): 1. Create a model of the system using RBD notation. 2. Define a list of critical spare parts 3. Collect empirical data from the fleet. a. Maintenance and parts usage data such as Ships' 3-M or CASREP b. Experience time. c. Validate data 4. Assign valid failures to blocks. 5. Calculate Availability s parameters: MTTR, MSRT, MTBF, and Supply Effectiveness. 6. Calculate Availability (TIGER) 7. Assign spares parts to RBD blocks. 8. Execute ACIM model 9. Generate Spares mix.

38 Master Dissertation Page 38 of 79 To calculate availability parameters the formulas used are: Gross (Supply) Effectiveness MTTR * Adjustable factor for converting man-hours to hours MSRT Logistic Response Time. MTBF 3.7 Comparison of RBS and concepts Since this thesis is to get a Master Diploma on Assets Management Control it is interesting to compare how RBS concepts are related with concepts and the similarities that can be found on both models. Availability v/s Cost analysis. One of the key concepts on RBS model is the analysis of asset s availability versus spare mix cost but really it is not very different from System cost-effectiveness concept of. On model the main goal is to achieve optimal asset s cost-effectiveness, i.e. to get the best performances at the lowest possible cost. As it is shown on next figure theory is interested on measure and improves asset performance and also to evaluate and diminish asset s costs. Mathematically speaking Cost-Effectiveness is a function of System Effectiveness and Costs. CE= f(se, Costs)

39 Master Dissertation Page 39 of 79 Figure 22. model (Stavenuiter, 2002) To calculate asset s performance model considers three variables: Availability Reliability Capability Figure 23. model (Stavenuiter, 2002) In this figure is shown how methodology calculates System Effectiveness. One of the main parameters to do it is asset s availability. In that sense model is very close to RBS methodology because it also compares in one side asset s availability and in the other side asset s cost. Instead of that, model offers a wider analysis than RBS methodology because it considers not only availability parameter but also reliability and capability variables. One of the reasons of this is

40 Master Dissertation Page 40 of 79 because RBS model is only focused on Sparing activities but looks over whole asset performance. Multi indenture structure Other important concept on RBS model is the multi indenture structure definition of the asset. It is the base for developing Reliability block diagrams. On theory also we can find a similar concept that is called Functional breakdown. See next figure. Figure 24. Functional breakdown (Stavenuiter, 2002) Functional breakdown of is similar analysis of multi indenture structure from RBS but only at physical level, not functional. Multi indenture decomposition of RBS is only a physical breakdown of the system. Functional analysis of goes beyond; it considers a physical decomposition (installations) but also integrates a functional breakdown (operational and technical functions). Functional analysis presents a most complete representation of the system because it allows understanding how different functionalities are divided or connected with the physical components of the asset. So it is easy and possible to assess how each component s failure will affect the effectiveness of the whole system. On RBS model, physical decomposition is complemented with Reliability block diagrams which incorporate functional analysis. ILS Integrated logistic support is also a concept found on RBS model. In this case the definition of ILS and is representation is identical of definition: approach for setting up the necessary logistic processes to support a capital asset throughout the life cycle. (Stavenuiter, 2002). It is shown on next figure:

41 Master Dissertation Page 41 of 79 Figure 25. ILS through asset s life cycle. (Stavenuiter, 2002) Formulas After a comparative revision of both models it is possible to conclude that the main formulas used on RBS model to calculate Availability, readiness, MTTB, MTTR are the same on both methodologies. To finish this chapter is added as appendix the actual situation of RBS implementation on US military forces (2008). It can be found on Appendix G.

42 Master Dissertation Page 42 of 79 4 A RBS model to Chilean Navy. The objective of this research is to present a preliminary proposal of the implementation of RBS model within Chilean Navy organization. Pretend to develop a Sparing model for an organization like Chilean Navy would be a very ambitious objective for one thesis master therefore, since this is a preliminary proposal, the model presented in this research project has been restricted to the application of several concepts from RBS model, complemented with Asset Management Concepts from body of knowledge (Stavenuiter, 2002) contextualized to Chilean Navy organization. Next figure summarizes which concepts are taken from both methodologies: Figure 26. RBS and Concepts for CN-RBS model. Some reasons why the model has been restricted to these concepts are: Single echelon system: To narrow the scope of this research the model will be restricted only to the first echelon of the supply chain i.e. reduced to define stock level of the spares at central warehouse. Posterior distribution will be not attended in this work and it will be part of suggestions to develop in the future.

43 Master Dissertation Page 43 of 79 Figure 27. CN-RBS Scope Readiness Based Sparing Model considers multiple variables and generates hundred of outputs that allows to manage the whole supply chain for spare parts. The scope of this research will be narrowed to the variables and outputs needed to calculate optimal spares mix which is the primordial application of RBS methodology. The calculations of spares allocations, multiechelon models, distribution models, etc are more complex and they will be left for future developments. The last version of Readiness Based Sparing Model on US armed forces considers functions that integrate all Armed Forces (Navy, Army and Aviations) in one Mega Logistic system with shared supply centers and common information systems. In this research the proposal has been restricted only to Chilean Navy Organization; do not consider integration with other armed forces. CN-RBS will only design for Critical and Extremely Critical spares due the other type of spares (Non critical) are managed with zero stock policy therefore it is not necessary a model to define stock levels. way of develop the functional breakdown of an asset is very clear, it is because it has been added to the model. LCM teams concepts are not present on US RBS model. It is a great contribution of theory because provides a multidisciplinary management platform for the assets where the most important viewpoints are considered.

44 Master Dissertation Page 44 of CN-RBS model proposal CN-RBS model considers the application of the most important RBS concepts but applied to Chilean Navy reality, structure and systems. The model is also enriched with the application of several concepts taken from body of knowledge. Next figure presents the proposal of CN-RBS model. Figure 28. CN-RBS Model The model will be explained on next subtitles explaining in detail: the entities that comprises it, the data that each entity has to provide and the process flow for spares mix definition CN-RBS Participating Entities In the CN-RBS participates the following entities: 1. Maintenance service department (SERVIMADA): This department is in charge of develop and coordinate maintenance plans and supervises all the maintenance information that is collected in SALINO from operational units. 2. Naval Operations personnel: Assets operation personnel is a crucial element on this model because they have to register each time that a failure appears and the maintenance activities

45 Master Dissertation Page 45 of 79 developed. They are responsible to get failures and maintenances information into SALINO s Databases. 3. Engineering department (DIRISNAV): This is the engineering department of the CN, they participate on assets requirements definition, technical buying process and the definition of the initial spare mix for the asset. 4. LCM Team (Organizational team): This concept has been taken from body of knowledge that still it is not implemented on Chilean Navy. It is composed of representative of asset s operation, asset s maintenance and asset s engineering design. This team is the entity responsible to control the asset s management from all its life cycle. It is one of the key concepts in assets management control and it will be very useful on a possible RBS implementation because in this team are gather the experts that known better the asset from different viewpoints. It will be very useful to define DRM and RBD models. Figure 29. LCM Team (Stavenuiter, 2002) Special mention has to be done in this point to remark the need to provide LCM teams with most powerful tools of communication like, for instance, an internal portal. A web portal presents information from diverse sources in a unified way. Essentially a web portal what does is to collect meaningful information from different databases and information systems to present it in unique interface for a specific group or team within the organization. One of the problems to implement LCM model in Chilean navy is the LCM team members are physically separated and the other is the actual ERP system is not able to present all the asset s information in one place visible for all the actors involved in this asset s life cycle. A web portal for LCM team management and collaboration could help to solve these problems. A web portal is a great option to solve the communication problems between LCM team members. The benefits of it are numerous: To gather all relevant information in one place. To enable a place for collaboration among LCM team members. To control and make visible internal process. To show the information in web interfaces visible for everybody. To manage common calendars and agenda. To implement Business Intelligence applications.

46 Master Dissertation Page 46 of Supply Department: This department is responsible for all the logistic activities and sparing processes therefore it will be the main user of a RBS implementation. This methodology is a tool to support decisions making processes so it will help them to define better which spares to acquire and to determine stock levels. 6. SALINO: SALINO is the ERP Chilean Navy Information System therefore almost all the data required to implement CN-RBS will be extracted from its databases. This entity is crucial on CN-RBS implementation because SALINOS data is the base of all the calculations, if this data it is not reliable whole Availability calculations (which is the aim of RBS model) may be wrong. Those entities are the main departments involved on a Readiness bases sparing implementation. In spite of that, there are other units that would be also benefit of it, e.g. finance department due the better administration of the resources, admirals staff because the increment on assets availability Data Data is one of the main issues to implement a RBS model for CN. If the data provided by operational personnel is not reliable MTTF, MTBF, etc calculations will be wrong and, therefore, also availability calculations will be wrong. Also if the logistic data regarding suppliers delays is not precise availability calculations will be also wrong. How to assure good quality of the data is not part of the scope of this thesis but definitely it is something that should be taken into account in a RBS implementation for CN because if the people do not trust on SALINOS data also the people will not trust on RBS calculations and spares suggestions therefore the whole work will be in vain. Below the description of the data that each entity provides to the CN-RBS model: 1. Maintenance service department (SERVIMADA): o Scheduled maintenances information. o Manufacturer maintenance information: used to This information is used for Availability parameters calculation (MTTF, MTBF, MTTR, etc) 2. Naval Operations personnel: o Failures information: Failure date, Down time, Causes, Labor Hours utilized, o Spares used to repair the failure. This information is also used for Availability parameters calculation (MTTF, MTBF, MTTR, etc). This data is also important for the criticality classification of the of the spares. 3. Engineering department (DIRISNAV): o Asset s Functional breakdown o Reliability block diagrams o Spares map in blocks, allocation into RBD.

47 Master Dissertation Page 47 of 79 Functional breakdown and RBD is one of the main inputs for RBS model. Asset s availability is calculated adding the availability of each installation using RBD Diagram. 4. LCM Team: o Design reference mission o Budget assign and constrains LCM team provides the orientations regarding the mission of each asset and the budget for it. It is used to develop availability v/s cost graphs. 5. Supply Department: o Supply delay times (MSD). Utilized as another input for availability calculations CN-RBS process RBS CN model process for spares mix definition has been designed taken as example the process found on US Navy organization (Figure 21). It is resumed on next picture:

48 Master Dissertation Page 48 of 79 Figure 30. CN-RBS process The differences with US RBS process model (Fig. 21) are basically located on difference of names, for instance on US Navy Critical Spares are called Maintenance significant components. Also TIGER and ACIM software are replacing by CNRBSIS and SALINO software which make the same calculations. On CN RBS model Reference Mission is done by LCM team while on US Navy model it is done by engineering department. Below CN RBS process is explained. 1. LCM TEAM DEFINES DRM The process starts with the definition of the mission DRM and main functionalities of the asset; it is done by LCM team. This document is very important because it gives the orientation regarding which are the most critical functionalities of the asset, its mission profile, also its constrains and the budget assigned to operate. 2. DIRISNAV develops functional breakdown of the asset.

49 Master Dissertation Page 49 of 79 A functional analysis of the asset is the base to develop later design of Reliability block diagrams. It helps to understand how each installation and, subsequently, each spare part contributes to asset s mission. To develop a functional analysis it proposed to use following notation taken from theory: Figure 31. Model of Functional Breakdown (Stavenuiter, 2002) To perform this analysis can be used AMICO software tool which is an application based on theory. AMICO was designed to calculate cost-effectiveness starting from asset s functional breakdown. 3. DIRISNAV develops Reliability Block Diagram (RBD) of the asset. Having in mind previous functional breakdown following step is to develop RBD to the main functionalities. Here it is important to define until which level it will be done because to extend too much this analysis would take too much time and energy. 4. DABA registers on SALINO information regarding supply delays. Supply personnel in DABA are every day registering on SALINO information regarding purchases and suppliers behavior. With this data SALINO can calculate Logistic delays and, therefore, Mean Supply Delay (MSD). They also register spares cost which is a very important data to calculate Availability v/s Cost curve. 5. Operational Personnel register failures on SALINO (It must considerer also spares utilization in each case) Operational personnel of the assets must register on SALINO each failure that is detected, the equipment failed and its reason. It also implies to register the spare parts needed to repair. This information will be used by SALINO to calculate MTTR, MTBF.

50 Master Dissertation Page 50 of Registration of Scheduled maintenance. SERVIMADA registers on SALINO information regarding scheduled maintenance activities using maintenance cards where is described all the information regarding that maintenance. This time is which design the maintenance plans. This information will be also used by SALINO to calculate MTTR, MTBF. 7. SALINO calculates MTTF, MTBF, MSD With the information previously mentioned, SALINO can calculate the parameters needed to calculate Asset s availability. This functionality should be developed by SALINO software administrators. 8. CNRBSIS calculates Availability To implement this model is required to develop a software application that may calculate Asset s Availability using MTTF, MTBF, MSD, RBD provided by previous phases. This application is called Chilean Navy Readiness Based Sparing Information System (CNRBSIS). On next subtitle will explained deeper the function of this system. 9. DIRISNAV allocates spares into RBD model. In order to calculate availability/cost curves is needed to define to which Reliability block on RBS corresponds each spare. It is made by Engineering (DIRISNAV) department. 10. CNRBSIS calculates Availability v/s cost curves CNRBSIS application calculates Availability curve as function of the increment on cost depending the spares considered on the mix. Mix definition can be done to one particular asset or to a group of them in case that the objective should be to define the optimal spare mix for a fleet. In that case group RBD should be developed as joining the final availability of each asset as it shown on next figure.

51 Master Dissertation Page 51 of 79 Figure 32. Group of assets RBD In this case, the spares will be selected as the mix that gets the optimal availability for the complete fleet. RBS model can be applied at asset level or at group of assets level. 11. DABA uses CNRBSIS application Supply personnel make sparing decisions, like the optimal spares mix with available budget, spares acquisition prioritization, etc. using CNRBSIS application and the curves provided by this system. 4.2 CN-RBS technological development CN-RBS implementation needs the support of a new software application capable of calculate availability v/s cost curves. To do it this software needs to integrate the data that comes from SALINO (MTTR, MTBF, MSD), Reliability diagrams developed by DIRISNAV and Spares information from DABA. This application has been called CNRBSIS. CNRBSIS has two main functionalities: Availability calculation Availability v/s Cost curves Inputs needed are:

52 Master Dissertation Page 52 of 79 Figure 33. CNRBSIS inputs and output. The inputs required to calculate asset s Availability are: MTTR, MTBF and MSD parameters delivered by SALINO RBD provided by engineering department. Each block has associated its own values of MTBF and MTTR Mission Timeline provided by LCM team. It comes from DRM document, it is consider as time sequences used to build the simulation timeline. Logistic support information provided by The last input is the Gross Effectiveness (GE), defined on 3.4 subtitle. It is the probability that, given a failure, the part needed is available. Formulas to calculate GE and other parameters are found on Appendix H. After this process the system must generate Ao v/s costs tables and curves as the following:

53 Master Dissertation Page 53 of 79 Figure 34. Typical Ao v/s GE curves (Kinskie S., 1997) Figure 35. A typical budget-to-readiness cost curve (Kinskie S., 1997) CNRBSIS allows visualizing the impact on availability of each spare that is added to the mix. It allows decision makers to define which is the spares mix that returns the best availability under current budget restrictions, also it helps to decide which component to buy when several spares are required; the one that increments the most asset s availability. It will impact on a more efficient distribution of the resources and lack useless spares on warehouses.

54 Master Dissertation Page 54 of 79 Figure 36. Analysis of Ao v/s cost curve RBSCNIS model will provide interesting information useful to determine the real contribution of each spare to global asset s availability. With this type of analyses it is possible to determine which the spares are that generate major return on asset s availability; those are the most profitable spares because investing less budget will generate high impact on asset s availability. Instead, on high part of the curve (saturated area) the incorporation of a new spare to the mix will produce a very small benefit on availability. These analyses will be very useful to support decision making process regarding spares investments. Since this master thesis is focused on propose a general model, are not presented in this chapter more details regarding formulas and methods for availability calculations. To know more of those mathematical calculations the reader can look at following references: (Burnworth, 2008), (French, 1994) (Kinskie S., 1997), (McMaster, 2000), (O'Malley, 1983), (Sherbrooke, 2004), (McMasters, Derivations of formulas for measures of effectiveness, 2000) 4.3 CNRBS expected benefits A quantitative approximation of the benefits of implementing RBS model on CN can be done by supposing that it will produce the same benefits that USA RBS implementation. Obviously it is only raft estimation because they are organizations with a tremendous difference on size, complexity and culture. The results of USA implementation, shown on subtitle 3.2 were:

55 Master Dissertation Page 55 of 79 An average decrease of 35% on spares cost to obtain same availability than DBS model. 20% of decrease on the amount of items required to obtain same availability than DBS model. Increment of 10% on availability level using the same amount of money than DBS model. An average decrease in backorders of 40% resulting in the same availability. 32 % higher fill rate. Historical data of Chilean Navy for the same variables on 2010 year are: backorders were generated on ,5 million USD spent on spare parts. Availability rate 73% (Fleet average) spare items required on Information about fill rate could not be gathered. Crossing the results of US RBS implementation with CN information, the expected benefits for CN organization could be estimated as follow: Table 7. Expected RBS CN benefits. Previous table shows the possible quantitative benefits after a RBS implementation on Chilean Navy: 1. Same availability could be achieved with 10 Million USD less of budget, generating less backorders, and less spares items required. 2. With the same budget CN could have achieved 10% more availability (from 73% to 83% on fleet average). 3. Fewer items requested also will imply to diminish the need on personnel on acquisition department and less warehouse space and personnel. It is difficult to quantify economically these benefits because in that case the personnel will be not fired but reassigned to other department. It is only raff estimation but it is interesting to see how with the implementation of a new methodology to manage spares, the Navy can save a significant amount of money and resources. This money can be destined to other items or invested on new assets.

56 Master Dissertation Page 56 of 79 5 CONCLUSIONS In this research it has been presented a proposal of implementation of a new model to manage spare parts for Chilean Nay Organization based on Readiness Based Sparing Model utilized on US Navy. RBS process determines what sparing levels are necessary to achieve a defined system operational availability using a system s approach. It allows to destine resources exactly toward they are going to produce more benefit, ensuring asset s availability. With this type of models managers are able to choose efficient mix of spare parts stock that satisfies availability requirements within budget restrictions. The main motive that impulse the need of a new model to manage spares on CN is based on the fact that for the past 10 years Chilean Navy budget for spares acquisition has remained unchangeable although, on the same period CN GDP has growth more than 395%. In this context Chilean Navy is challenged to search ways to be more efficient and improve the way of the assets are managed; get the best performances with the minimum possible cost. It implies to be more efficient in its resources spending, deciding carefully how to spend its restricted budget. Actually Chilean Navy spare parts inventories are managed with the help of its ERP called SALINO. The model that SALINO utilizes to manage inventories is Items oriented. Therefore inventories decisions are taken considering each item s demand, its criticality and logistic information regarding only that particular item. The main deficiency of this type of models is that their analysis is centered at item level therefore they cannot optimize systems cost-effectiveness because do not have a global system approach. System approach models, like RBS model, are not focused on satisfy particular items demand but on achieve global system effectiveness. After having analyzed Chilean Navy current model of sparing process (chapter 2) and presented Readiness Based Model on Chapter 3, a summary of the main conclusions is: 1. It is possible to implement RBS model on CN organization because the main input data needed to develop readiness and availability calculations, which are the base of RBS model, are stored on SALINO s Database and they are available. 2. Regarding SALINO s data is necessary to comment that to assure good quality of the data is not part of the scope of this thesis but definitely it is something that should be taken into account in a RBS implementation for CN because if the people do not trust on SALINOS data also the people will not trust on RBS calculations and spares suggestions therefore the whole work will be in vain. 3. According with the results obtained on US Navy implementation of this model, Chilean Navy could achieve same availability levels than actual with 10 Million USD less of budget, generating less backorders and less spares items required. 4. With the same budget that CN spent on last year it could have achieved 10% more availability on the same period by implementing RBS methodology. 5. Other benefits are related with the capacity to reduce space and personnel on warehouses and acquisition department, people that could be reassigned to other duties.

57 Master Dissertation Page 57 of Other important improvement of this model is related with the capacity of being in control of the sparing process by knowing exactly the impact and contribution that each spares does to asset s availability. This model allows decision makers to evaluate exactly which is the increment on availability that each spare generates when it is added to the mix. It improves enormously the process of how decision regarding spares acquisition is taken actually. 7. The implementation of RBS model on CN will required the development of a new software application. It would take different data inputs, that are considered in this methodology (RBD, MTTF, MSD, etc) providing the functionalities to develop different analysis: how each spare contributes to asset s availability, calculations of optimal spare mix, cost v/s availability curves, etc. 8. Since an important input of this model are the functional diagram of the assets, its mission definition, its Reliability block diagrams and other models that has to be generated by the LCM team (proposed on subtitle ) it will be highly beneficial that the implementation of RBS model will consider also the development of the LCM portal as a powerful tool to promote the Comunicación within this team. 6 RECOMMENDATIONS Some recommendations for future research are: As it was told on previous title SALINO s quality data is crucial issue in this project because if this data is no reliable the whole system will be useless. Cooperation between entities that participate on RBS mode (DIRISNAV, DABA, SERVIMADA, OPERATIONS, etc) is also crucial because they have to build and use models that have to be agreed among them. To facilitate this communication process is recommended to implement a LCM team portal. The model presented in this research has been developed restricting the problem to a single base supply center that distributes spares to the bases. It will be interesting to analyze the case when spares can be delivered directly to the bases without passing through the main center. Readiness based sparing model basically crosses spares cost with the availability that they generate. According with concepts availability is only one component to calculate asset effectiveness which is the highest asset s parameter because also considers reliability and capability values. It would be very interesting to extend RBS model to an Effectiveness Based Sparing Model (EBS) which crosses cost of the spares with the total effectiveness of the asset. This model would be very interesting because it would consider more parameters than actual RBS. Other interesting work that has to be done is to design the CN RBS Software application, how it can be really implemented, how it can be connected to actual SALINO system and databases, which technology it is necessary to use, user s permissions, etc.

58 Master Dissertation Page 58 of 79 It is necessary to evaluate carefully the cost of the possible RBS model implementation on CN and estimate better the real benefits that it will generate. Lamentably this analysis could not be deep in this research because the access to critical data is forbidden for civilians. 7 LIST OF ABBREVIATIONS : Assets management control ACIM: Availability Centered Inventory Model ACE: Aviation combat element AVCAL: Aviation Consolidated Allowance List CN: Chilean Navy SALINO: Chilean Navy ERP system CNRBSIS: Chilean Navy RBS information system CSP: Contingency support packages DBS: Demand based sparing DoD: Department of Defense DRM: Design reference mission DRIVE: Distribution and repair in Variable Environments EOQ: Economic Order Quantity DIRISNAV: Engineering deparment of CN FISP: Fly in support packages GDP: Growth domestic product ILS: Integrated Logistic Support LRU: Line replaceable unit LCM: Logistic cycle managment LSA: Logistic support Analysis MSC: Maintenance Significant Components MSD: Mean Supply Delay MSRT: Mean Supply Response MTBF: Mean time between failure MTTR: Mean time to repair MAD: Media Deviation Standard ICAPS: Navy interactive cataloging and provisioning system NSAF: Non Standard Allowance File RBS COSTP: RBS cost oriented RBS COST: RBS cost oriented RBS READP: RBS with protection levels (Maximum and minimum levels). RBS READ: RBS without protection levels. RBS: Readiness based sparing RBD: Reliability Block Diagram RMA: Reliability, Maintainability and Availability ROP: Reorder point ROQ: Reorder quantity SS: Safety stock SL: Service Level SRU: Shop replaceable unit SNSL: Stock number sequence list

59 Master Dissertation Page 59 of 79 GE: Supply (or Gross) Effectiveness DABA: Supply department of CN WRA: weapon replaceable assemblies 8 GLOSSARY OF DEFINITIONS AVAILABILITY: Availability is defined as the expected percentage of time that an asset is not down for spares at a random point in time. i.e. is capable of performance its intended function MTBF: Mean time between failures. It is the Average time between successive failures. MTTR: Mean time to repair. Average time required to repair a system in its operating environment MSRT: Mean Supply Response Time (Average time delay caused by the logistic support system). READINESS: Readiness is defined as a measure or measures of the ability of a system to undertake and sustain a specified set of missions at planned peacetime and wartime utilization rates. Measures take account of the effects of system design (reliability and maintainability), the characteristics of the support system, and the quantity and location of support resources. Examples of system readiness measures are combat sortie rate, fully mission capable rate, and operational availability. RELIABILITY is the duration or probability of failure free system performance under a given set of conditions. MAINTAINABILITY is the ability of an item to be retained in or restored to a specified operating condition when maintenance is performed by personnel having specified skill levels, using prescribed procedures and resources, at each prescribed level of maintenance and repair. SUPPORTABILITY is the effectiveness of the logistics support provided for a system. It represents the remaining downtime where no active maintenance (including fault isolation) is being performed. INDENTURED STRUCTURE provides a hierarchy of parts in a manner similar to the way a typical organization char depicts a hierarchy of departments and units in an organization. SINGLE SITE MODEL : Single site is a model that looks at the spares selection only at a single base and disregards spares determinations made at other bases. The model considers a central supply center which receives the items and distributes to bases that work as maintenance centers with retail supply capabilities. MULTI-ECHELON SYSTEMS are representation of the hierarchical tree in which the items are moving from central supply center to maintenance units through intermediate sites and vice versa. Vice versa case regards with reverse logistic processes for equipment s repair.

60 Master Dissertation Page 60 of 79 CANNIBALIZATION refers to the practice of removing parts or subsystems necessary for repair from another similar device, rather than from inventory, usually when resources become limited. TIGER is a computer simulation program to predict operational availability based on downtime attributable to: mission essential equipment failures, logistical and administrative delay times for replacement parts, and preventive maintenance. RBS: Readiness based sparing is a model to manage the spare parts processes in order to get the optimal availability for the assets.

61 Master Dissertation Page 61 of 79 9 BIBLIOGRAPHY Bailou. (2004). Logistics. Mexico City: Pearson. Brem, R. (1997). Army inventory policy, The Need for strategic change: An examination of RBS for retail parts supplu support. Monterrey, California.: Naval postgraduated school. Brem, R. D. (1997). Army inventory policy, an examination of RBS for reatil reapr parts supply support. Monterry, California.: Naval Postgraduate School. Burnworth, T. C. (2008). SIMULATED MULTI-ECHELON READINESS-BASED INVENTORY LEVELING WITH LATERAL RESUPPLY. Ohio: Air Force Institute of Technology. CACI Company. (n.d.). CACI company. Retrieved 12 10, 2010, from Central bank of Chile. (n.d.). Retrieved 8 15, 2010, from Correlates of War. (2008). National capabilities data set. Retrieved from Daganzo, C. (2005). Logistics systems analysis. Berkeley: Springer. Defense Ministry of Chile. (2010). Book of National Defense of Chile Santiago of Chile: Defense Ministry. Department of Defense. (2003). Directive R. Washington: Office of the Deputy under Secretary of Defense for logistics and Materiel Readiness. DOD M. (2009). Secondary item stratification manual. Washington DC: Office of the under secretary of defense for aquisition and technology. Dudley Knox Library. (1985). Monterrey, California.: Naval postgraduate School. F.C. Strauch. (1982). ARROW's Model Evaluation. Mechanicsburg: NAVY FLEET MATERIAL SUPPORT OFFICE. French, T. F. (1994). COMPARISON OF OPERATIONAL AVAILABILITY. Monterrey, California.: NAVAL POS9MRADUATE SCHOOL. Geis, M. B. (1995). Implementing RBS in the Marine Aviation Logistic Support Program. Alexandria, Virginia.: Center for Naval Analyses. Hale, A. (1994). Analysis of America's Readiness Based Sparing Aviation Consolidated Allowance List. Virginia: Center for Naval Analyses. Hale, A. J. (1992). A Comparison of ReadinessBased and Demand-Based Sparing. Virginia: Center for Naval Analyses. Kingler, K. M. (1994). The application of a Readiness-based sparing model to foreign military sales. Ohio: Air force institute of technology. Kingman, J. J. (1982). Defense Technical Information Center. Kinskie, S. (1997). An Evaluation of the budget and readiness impacts of battlegroup sparing. Monterrey, California: Naval postgraduate school.

62 Master Dissertation Page 62 of 79 Kinskie, S. W. (1997). An evaluation of hte budget and readiness impacts of battlegroup sparing. Monterrey, California.: Naval postgraduate school. Kinskie, S. W. (1997). An evaluation of the budget and readiness impacts of battelgoup sparing. Monterrey-California.: Naval postgraduate School. Kuijer, M. (2007, 3 3). Logistic Support Analysis M08. Lee J. Krajewski, L. P. (2000). Operations Administration: Estrategy and Anaylysis. Pearson Education. McMaster, A. W. (2000). A prelimanary evaluationof a RBS for the US Navy. Monterrey, California: Naval Postrgaduate School. McMasters, A. W. (2000). A preliminary evaluation of a readiness-based repairable item inventoy model for the US Navy. Monterrey, California: Naval Postgraduate School. McMasters, A. W. (2000). Derivations of formulas for measures of effectiveness. Monterey: Naval postgraduate school. Miller, L. W. (1992). DRIVE. Distribution and repair in Variable Environments. Santa Monica: RAND. Mincom International. (2000). Manual INVJH-02 Inventory Control SALINO. Valparaiso: Mincom. Office of the under secretary of Defense for Acquisition, T. a. (n.d.). ACQ. Retrieved 12 29, 2010, from O'Malley. (1983). The Aircraft availability model: Conceptual framework and Mathematics. Logistic Management Institue Report. Pecht, M. G. (1995). Product Reliability Maintainability Supportability Handbook. CRC- Press. Roy, R. N. (2005). A Modern Approach To Operations Management. New Delhi: New Age International Ltd. Publishers. sda. (234). iyrt. wsd: asd. Sharp, T. ( 2010). Defense Budget. Center for a new American Security.. Sherbrooke, C. C. (2004). Optimal INventory modeling of systems. New York: Kluwe Academic Publishers. Shim, J. K. (1999). Operations Management. New York: Barron s. Silver, Edward; Pyke, David; Peterson, Rein. (1998). Inventory Management and Production Planning and Scheduling. John Wiley & Sons. Slater, P. (2010). Smart Inventory Solutions: Improving the Management of Engineering Materials and Spare Part. New York: Industrial Press, Inc. Spanish defense blogspot. (n.d.). Retrieved 8 20, 2010, from Spignesi, N. A. (1998). Implementing readinnes based sparing in the US Marine Corps. Monterrey, California.: Naval Postgraduate School.

63 Master Dissertation Page 63 of 79 Stavenuiter, J. (2002). Cost Effective Management Control of Capital Assets. Lelystad, Netherlands.: Asset Management Control Research Foundation. Treasury Ministry of Chile. (n.d.). Budget Directorate of Chile. Retrieved 8 12, 2010, from USDAT&L Webpage. (n.d.). Office of the assitant secretary of l defense. Retrieved 12 29, 2010, from Varley, R. (2006). Retail product management: buying and merchandising. Routledge. Wikipedia. (n.d.). Wikipedia. Retrieved 12 29, 2010, from

64 Master Dissertation Page 64 of 79 APPENDIX A Reference of several military budgets British, Spain and US military budgets as percentage of its own national GDP. Figure 37. British defense spending as percentage of GDP. (Correlates of War, 2008) Figure 38. Spanish defense budget. (Spanish defense blogspot)

65 Master Dissertation Page 65 of 79 Figure 39. U.S. Military Budget. (Sharp, 2010)

66 Master Dissertation Page 66 of 79 APPENDIX B Graphs of CN expenditures Figure 40. CN Expenditures 1. (Treasury Ministry of Chile) Figure 41. CN Expenditures 2. (Treasury Ministry of Chile)

67 Master Dissertation Page 67 of 79 APPENDIX C ITEMS PRIORITY CLASSIFICATION ON CN Classification of spares items on CN actually is done using following criteria list: Criterion Consumption Physical Stock Suppliers availability Logistic time for acquisition Movement activity Storage requirements Replacebility Environmental factors and safety Criticality ABC classification A High consumption >5000 units per year B Moderated consumption >1000 units per year C Low consumption <1000 units per year A Over $ B Over $ C Lower than $ A Unique source B Few suppliers C Many suppliers A > 160 days of waiting time B days C <89 days (COTS) A 0 to 2 movements in 12 periods B 3 to 36 movements on 12 periods C 7 to 12 movements on 12 periods A Low lifetime B Moderated lifetime C Without attention A Without substitutes, high obsolescence factor. B Without substitutes, moderate obsolescence factor. C With substitutes, without obsolescence factor. A High environmental impacts or safety. B Moderate environmental impacts or safety. C No environmental impacts or safety. A Asset s mission detention B Asset s mission degradation C Without effects on asset s operation Table 8. Criteria for item classification. This list is not fixed and may be modified over time or adjusted to each asset analysis. Each spare importance is analyzed using these criteria. The simplest way is filling a table considering the impact of the asset on each criterion assigning an ABC level.

68 Master Dissertation Page 68 of 79 Example. SPARE PART IDENTIFICATION CODE Consumption Physical Stock Suppliers availability Logistic time for acquisition Movement activity Storage requirements Replacebility Environmental factors and safety Criticality PRIORITY GROUP Motor butt RG5679 ABC Classification B C C C B B A A B P2 Table 9. Motor Butt Analysis Example This evaluation is made by consulting experts opinions. The experts can be Navy officers and crew, asset s sellers or manufacturer, spares sellers, other navy s personnel, etc. Priority level is a categorization of each asset s priority taking into account general criteria evaluation. The category that each spare belongs is defined subjectively by the expert s opinion. There is not quantitative formula to assign priority class for the spares. Each spare s category is decided by the experts looking at the ABC categorization and assigned subjectively. The meaning of each priority level (P1, P2, P3 and P4) is: P. Group Description P1 Extremely Critical spares P2 Critical spares P3 Important spares but not critical P4 Ordinary spares Table 10.Priority levels

69 Master Dissertation Page 69 of 79 APPENDIX D SALINO SUPPLY CALCULATIONS EOQ (Economic Order Quantity) calculation: The amount of spares to request is calculated using the well known Wilson EOQ Model (Silver, Edward; Pyke, David; Peterson, Rein., 1998) which goal is to find the spare s quantity to reorder that generates minimum cost balancing ordering costs and holding costs. Next figure shows how the costs to order are lower as much amount of spares I order and, in the other hand, the costs of holding inventory are higher as much spares I have, therefore the optimal quantity of spares to reorder it will be the point where both functions intersect. Figure 42. EOQ model (Varley, 2006) Ordering costs considers an important amount of factors that are incurred during the process of ordering. (Mincom International, 2000). CN works with following ordering costs: Personnel Salaries and General Expenses of: Acquisition department, Reception department and Payment department. Those departments are part of Supply Department defined previously. The calculation is made using a formula that finally assigns a cost to each order (cost/order) Costs of Storage equipments, crane, pallets, etc. Both Purchase and Maintenance costs related with this items. A formula also calculates a storage cost for each order. Costs of spares itself (The cost of each Purchase Order). The cost of holding stock is the sum of all the costs incurred to keep stock in the warehouses. (Daganzo, 2005). To CN those are:

70 Master Dissertation Page 70 of 79 Salaries and expenses of Warehouse department (personnel salaries, equipments, shelf s, maintenance, etc.). Warehouse department is also part of Supply Department. It also considers the cost of warehouse s construction. This cost is finally calculated as cost/volume Spare s insurance (There are some spares that have insurances associated) Obsolescence. The lost of value to keep equipments in warehouse. It is calculated using the Depreciation of each spare. On profit organizations one of the most important holding cost is the Opportunity cost of the money, i.e. the cost to have money invested in spares storage in the warehouse that would be producing benefits if they would be invested in other project or business. In case of CN, since it is a non-profit organization and the budgets are stipulated by law and destined to each department or cost center therefore they cannot be reassigned to other activities so the concept of Opportunity cost can t be applied. With these parameters SALINO is capable to calculate EOQ of each spare. This option is in this moment only enabled for those spares that are labeled as Critical and Extremely Critical, the others are controlled with stock Zero policy therefore it is not necessary that SALINO calculates Orders quantification. The formula that SALINOS utilizes to calculate EOQ is (Bailou, 2004): Where: EOQ: Economic Order Quantity R: Annual Consumption P: Ordering cost C: Unitary price I: Holding cost of stock ROP/ROQ (Reorder point), Min/Max and Safety levels calculation: Other important parameter that SALINO calculates is the Reorder Point. When this option is enabled SALINO sends an alarm via mail to acquisition department when stock level of the spare is reaching the reorder level. A security level can be also defined to generate alarms once stock is descending to critical levels. ROP is the minimum stock level for Critical or Extremely Critical spares. It is the point when a purchase order has to be sent to avoid run out of stock. It is to answer the question: When do I have to order? ROP must be equal to demand estimated during lead time plus safety stock due to occasional over demand (Shim, 1999). Therefore ROP is calculated using a combination of Work stock (Consumption x Lead Time) and Safety stock. It is shown on next figure.

71 Master Dissertation Page 71 of 79 Figure 43. ROP model (Roy, 2005) Safety Stock is calculated according to each spare s criticality. The most critical spares need bigger safety stocks. The spares that are labeled as non critical do not need safety stocks. Safety Stock is calculated as: SS: Safety Stock MAD: Media Deviation Standard, which represents a measurement of the error between real demand and predicted demand. It is calculated using the formula: KFactor: It is a representation of the percentage of service level. K level usually fluctuates between 1,25 and 5 and it is nominated to each spare. Calculation is made using the formula: 1 Standard Deviation * K = Service Level. Following table shows different K Factors to different Service levels. STD K Factor Service Level 1,0 1,2 84,1 % 1,25 1,5 89,4 % 1,5 1,8 93,3 % 2,0 2,5 97,3 % 2,4 3,1 99,4 % 3,0 3,9 99,8 % 4,0 5,0 99,9 % Table 11. K Factor table.

72 Master Dissertation Page 72 of 79 As it was said before ROP level is related with minimum stock level allowed preventing run out of stock but there is also need to calculate other important parameters like maximum level. Maximum level is important because gives the alarm when a stock level is increasing out of prudential threshold. Max/Min model it is also used to control spares within CN. This model specifies a minimum level that is equal to ROP level but instead of ask for Reorder Quantity (ROQ) is reordered the Maximum. In this case maximum level is equal to ROP + EOQ. (Slater, 2010) Figure 44. Max/Min model (Roy, 2005) This technique is called Min/Max and it is utilized in CN to control spares of high criticality. Demand Predictions Other important application that provides SALINO is the capability to predict Spares Demand. It has integrated four techniques: Fixed Prediction: Simple method used when there is not predicted a deviation of the projection. Floating Mean Prediction: The new consumption is calculated using the mean values of previous periods. Average Smoothing weighted: Compares real historical consumption with historical predicted consumptions and averages them to get a weighted average. Adaptive Smoothing: Uses Smoothing Exponential technique. The logistic operator can execute different techniques predictions in order to enrich the information available during decision process of spares acquisition. (Mincom International, 2000)

73 Master Dissertation Page 73 of 79 APPENDIX E SALINO ABCD/XYZ Report One important functionality of SALINO is the suggestions of spares classification. This analysis is divided in two components ABCD analysis and XYZ analysis. ABCD value is calculated as: ABCD value =Annual consumption x Cost price. It classifies the inventory according its consumption in annual dollars. To do it the spares consumption are classified in four levels according its ABDC value: A > $ B > $ and <$ C > 0 and <$ D = 0 XYZ value is calculated as: Where: SOH: Actual Physical Stock. Cost Price: Cost price actual of the inventory. Total SOH: SOH total of the twelve previous months. Periods: Twelve months plus one to actual SOH. XYZ value classifies inventory according physical stock levels economically quantified: X > $ Y > $ and <$ Z < $ Having calculated ABCD and XYZ values for each spare is possible to generate several reports that help logistic administrators to classify the items identifying their priorities. All the reports and functionalities presented in this chapter are only decision support tools that help logistic operators to control stock levels but finally decision are taken by the human beings, nothing is made

74 Master Dissertation Page 74 of 79 APPENDIX D Availability definitions Some authors identify three different types of availability (Sherbrooke, 2004): Inherent Availability is to measure equipment s reliability and maintainability. It is not related with spares. Achieved Availability: It incorporates maintenance parameters to the formula of inherent availability. It also excludes spares delays. Where: MTBM: Mean time between Maintenance MCMT: Mean corrective maintenance time MPMT: Mean preventive maintenance time Operational Availability: Operational availability (Ao) is the percentage of time that a system is capable of performance its intended function. A system is operational if it is not down for either maintenance or supply. Where: MDT: Mean down time due to spares, maintenance or other delays resulting from maintenance actions. For calculations purposes operational availability is decomposed in two types of availabilities: Maintenance Availability: identical to achieved availability. and Supply Availability: This represents the percentage of time that the asset is unavailable to produce due of supply delays. Where: MSD: Mean supply delay (equal to MSRT)

75 Master Dissertation Page 75 of 79 If either maintenance availability or supply availability is high, then the calculation is a good approximation to operational availability. Each discrete point on the optimal availability vs. cost curve in next figure is the maximum availability for the specified cost, and also the minimum cost for that availability. Figure 45. Optimal system availability v/s cost. (Sherbrooke, 2004) It is a theoretical Ao v/s cost curve for a non specific asset.

76 Master Dissertation Page 76 of 79 APPENDIX F MERBS Application CACI developed MERBS Workstation and CRCS/CADS to provide the tools to evaluate weapon system improvements, to optimize the readiness oriented logistics support infrastructure and to reduce the total cost of weapons system ownership. This is accomplished through spares optimization focusing on expanding this methodology to take advantage of best commercial practices such as premium transportation and Contractor Logistic Support (CLS)/Performance Based Logistics (PBL). MERBS takes the RBS concept to an additional level providing a wide range of logistic support solutions, see next Figure. MERBS is a highly flexible methodology that can be applied to new or existing systems, both aviation and ground, and to commercial and non-developmental items. MERBS recognizes the interaction between wholesale and retail inventories, using the Logistics Response Time (LRT) as the link to optimize the total inventory. It optimizes the positioning of the spares by trading off between retail and wholesale stockage decisions. Next figure shows MERBS model inputs and outputs: Figure 46. MERBS application model. MERBS starts with the sparing decision based on RBS techniques including determining engineeringbased criticality, projection of demand considering increases and decreases in system population. Using cost it then optimizes against a given readiness objective. Once readiness targets are established MERBS considers the item's Order and Ship Time (OST), wholesale requisition response time and transportation alternatives, and makes decisions on the mix of stockage positioning. These tradeoffs result in limiting inventory investments but ensuring a full range of coverage at both the retail and wholesale levels, while maintaining a given level of readiness. Multi-Indenture RBS (MI-RBS) is an integrated spares computation that utilizes the weapon system parts breakdown, the parent/child relationships, to meet readiness objectives at least total cost. In support of a consumer chain that has a repair facility MI-RBS optimizes spares selection by trading off

77 Master Dissertation Page 77 of 79 components with their repair parts, as well as trading off among components. This optimized spares selection and allowance based on maintenance capability and required system readiness has been applied successfully in provisioning and in the development of stockage lists for major USN and USMC systems. This includes the Aviation Consolidated Allowance Lists (AVCALs) and the Marine Aviation Logistics Support Packages (MALSPs). This tried and proven process can also be linked to wholesale in a multi-echelon role, thus giving a multi-echelon, multi-indentured readiness-based sparing model. CRCS/CADS is a recently implemented client-server system that provides the ability to update all aviation usage rates and ITATs every quarter and to produce in a timely and flexible manner: Aviation Consolidated Allowance Lists (AVCAL) Shore Aircraft Consolidated Allowance Lists (SHORCAL) Consumables Consolidated Allowance Lists (CAVCAL) Marine Corps PCSP, FOSP and FISP allowances It is project oriented supporting configuration management, rates updates, allowance computation and project workflow management through a series of key events. It assigns users roles and access, links data sources and defines business rules and controls for the overall RBS systems. It fully integrates with the MERBS Workstation and thus provides the ability to target single indenture and multiindenture MERBS-based aviation readiness goals. Figure 47. MERBS application interface.