OmegaPS Analyzer. Supportability Modeling for: LORA SPARING - LCC

Transcription

1 OmegaPS Analyzer Introduction to R4 Supportability Modeling for: LORA SPARING - LCC Pennant Software Services Limited Pennant Canada Limited Pennant Australasia Pty Ltd

2 OmegaPS Analyzer R4 OmegaPS Analyzer is a comprehensive supportability analysis tool. Using an integrated data management system the user can select options to determine the cost effective Level of Repair (LORA), identify an optimal Sparing solution, and calculate the equipment life cycle cost (LCC). With these models the analyst can test solution sensitivity and cost riss as well as determining best choices through trade off analysis. Output reports and graphs display the results in user friendly ways to support engineering reports. OmegaPS Analyzer is a ey piece of any serious supportability analyst s tool it! Cost Effective Support In these days of economic constraint and increasing demand for performance, the challenge of cost effective equipment support is pushed to the limits. Two of the most desired objectives in the operation of complex assets are: Increase equipment availability and Reduce operating costs. Is This Really Achievable? Yes it is! Proper analysis and systematic processes are applied to develop Performance Based Supportability. In these processes, analytical tools are used to develop, store and evaluate information about operational equipment and the support environment. The Canadian Department of National Defence (DND) has developed a set of analytical models over the past 15 years. In a teaming arrangement with Pennant Information Services, these products have been brought to the commercial maret. Three in One OmegaPS Analyzer R4 Is a Windows based product that provides the power of a modern GUI and the sophistication of the embedded proven DND algorithms. OmegaPS Analyzer can determine the best repair policy for equipment and reduce the cost of spare parts. OmegaPS Analyzer comprises three analysis models: Sparing, LORA and LCC. Pennant International Group 2 P a g e

3 OmegaPS Analyzer is a stand-alone software tool. However, Pennant has integrated OmegaPS Analyzer with OmegaPS LSAR to provide much of the equipment structure and relevant data for modeling. The Sparing Model Sparing is primarily designed to determine the optimal allocation of the quantity of repairable spares within a defined maintenance organization, resulting in, minimum inventory requirements for a stated equipment measure of effectiveness (MOE) or, maximum MOE for a given spares investment. In other words desired availability for least spares cost! It handles replaceable units that will drive the Prime Equipment effectiveness and consumables stocing policies for reorder points and reorder quantities. The LORA Model The Level of Repair Analysis (LORA) model, determines the most cost-effective maintenance policy for each replaceable unit of a Prime Equipment. LORA examines the costs of labour, training, test equipment, contractor repair, transportation, inventory, and documentation for every disassembly and repair option possible within the specified capability of the Maintenance Organization. After maing the initial repair versus discard decision, LORA will select the optimal location for repair of the defective unit. As a multiindenture model, LORA will determine the repair options for the whole assembly of a removed item (e.g. LRU, SRU, SSRU, etc). The LCC Model The Analyzer model was designed to determine the Life Cycle Cost (LCC) of an operation and support scenario. The basic cost breadown structure for R&D, Acquisition, In-Service Pennant International Group 3 P a g e

4 and Disposal is developed with particular emphasis placed on the support activity costs during the In-service phase. The cost of allocated spares recommended by the Sparing model can also be taen into consideration. The LCC model will determine cost variance over a number of years. The basic model calculations can be extended with user defined cost classes and customized costs. Cost results are analyzed by using Sensitivity or Trade-off analyses and by applying cost Ris analysis. Defining Analysis Scenarios The analyses within OmegaPS Analyzer are all based on user defined operation and support Scenarios. A Scenario is the combination of Prime Equipment, each with defined logistics structures (e.g. LRU, SRU) and of different variants, applied to a described logistics support organization. Operation and Support Organization An important part of the supportability model is the ability to define the logistics support organization and to specify where, within that organization the Prime Equipment will be operated. The OmegaPS Analyzer support organization is multi-echelon and contains depots, intermediate worshops and operational sites, all supported by a main Contractor. Essentially it is a 4 line support organization. Pennant International Group 4 P a g e

5 Prime Equipment Structures A Prime Equipment is the major system that is operated to provide a certain capability to an Equipment System. A Prime Equipment is operated at first line operational sites and is considered unavailable when a failure occurs. The PE usually is repaired by the remove and replace of a removable part (this is generally nown as the Line Replaceable Unit LRU). LRUs are built with their own replaceable units that can be removed and replaced to return the LRU to a functional state (these are generally nown as Shop Replaceable Units SRUs), which in turn have Sub SRUs or discard components. This multi-indenture structure permits complex equipment to be modelled and analyzed. OmegaPS Analyzer starts with a Physical representation of the Prime Equipment. This can be entered directly, imported from the LSAR or through an Excel Template provided. The Physical structure is then parsed and the logistical items identified. Saving this tagged version creates multiple logistical representations of the PE, which are then available for analyses. Analysis Scenarios Once the Support Organizations and Prime Equipment logistical structures are defined they are combined to create analysis scenarios. Many scenarios can be saved for the same Prime Equipment and Organizational Structures permitting comprehensive analysis of the required capability. Pennant International Group 5 P a g e

6 Data Sets The core to any model is the definition and management of data. OmegaPS Analyzer provides a very intuitive GUI and data model for the data sets to be entered. However, the downside of a model is the amount of data needed to mae meaningful analysis. Through years of experience and testing, the developers of OmegaPS Analyzer have determined the right amount of data to allow early analyses yet be meaningful for all life phases. Equipment Data Equipment data is defined through a series of screens. Each screen is functionally grouped to permit logical data entry. Also, a grid view is available for entering data in more of a spreadsheet format. The data forms above show the area where basic data is entered for the part. For example, the Diesel Engine is tagged as a LRU and has a cost of $12,367 1, weight of 500 Kg and 1 The labels on the forms (e.g. $) are user definable Pennant International Group 6 P a g e

7 Volume 1.2 m 3. Quantity in Parent permits the study of multiple common occurrences of a part and Duty Cycle refines the Prime Equipment operating time to this part. The MTBR is the Mean Time Between Removal of the part, which can be entered directly in that field (often as a basic MTBF) or, when the extended data exists, through a Demand Calculator. The Demand Calculator is shown open and indicates how additional failure metrics can adjust a basic MTBF to determine MTBR. The Demand Calculator is also the place where Scheduled Replacements of a part are identified. SM replacement should have some impact on failures of the part, which can be identified through the Survived Items rate. A repair organization might have different repair capabilities at different sites (Lines). Analyzer permits the allocation of repair tass through Repair Capability fractions to each LOM. Then at each repair LOM the actual repair requirements (e.g. Labour) can be described. A Use LOM inputs non-economic aspects to the LORA process. Support Organization The Support Organization is defined through the basic screen that displays the echelon hierarchy as an indentured tree for clear indication of relationships. Pennant International Group 7 P a g e

8 Each site has a set of shipping distance and cost data to all the supporting level sites where shipping cost can be a rate or a fixed price. At each first line site any number of PE types can be assigned for operations. In the sample below the PE called Vehicle is assigned by defining the Qty of PE and the Operating Hours/PE/Month. The Site Reliability Stress Factor allows the analyst to mae localized site based adjustments to the reliability of any parts within the Prime Equipment based on environmental factors. Pennant International Group 8 P a g e

9 Cost and Project Data Global data defines values that are used to determine labour and training requirements. It is also the place to indicate the order and holding costs for spares. Running the Models The Supportability Models run following some basic principles. applied by the three core modelling methods. Each is important and Basic Principles Two basic principles in supportability analyses are Resupply Times causing delays to replenishing front line stoc that sustains Prime Equipment operations, and the Repair cycles that restore failed items as woring stoc. Pennant International Group 9 P a g e

10 Resupply Times are built from a collection of possible delays that could include: Order and Ship Times Contractor Turn Around Times Procurement Lead Times Repair Cycle Times Bac Order rates The more these delays are incurred the longer the spares pipeline is said to be. The longer the pipeline the more spares are required to satisfy the measure of effectiveness (e.g. Operational Availability) of the Prime Equipment. The more spares the higher the cost. Repair Cycles are created when a multi-echelon support organization exists. When a defective part (LRU) is removed and replaced from the Prime Equipment it is sent to the first level maintenance organization. Based on their repair capability, the repair might be completed at that site or sent on to the second line shop. This process iterates through all repair fractions and part indentures to discover the best location to repair failed parts. Multi-Site Organization OmegaPS Analyzer permits the analyst to define a full operating, repair and stocage organization. In this organization individual sites at a defined Line of Maintenance can have unique data sets to provide a more accurate analysis when this information is nown. Pennant International Group 10 P a g e

11 Multi-PE Scenarios The scenarios developed for analysis can have multiple PE assigned at any of the operating sites. This permits the analyst to evaluate a Prime Equipment that has multiple variants, or a capability provided by different equipment types. Each PE can have a different Ao target assigned to indicate importance of the parts of an operational capability. Sparing Analysis Effective sparing analysis optimizes the allocation and quantity of spares to achieve a desired system goal at minimum cost. Sparing is important since spare parts frequently account for 25% to 50% of the cost of equipment. Poor sparing can result in overspending (when unnecessary spares are bought), decreased effectiveness of the system (if wrong spares are bought,) and even mission failure (if the necessary spares are unavailable). It is essential that the investment in spare items provides the required level of availability of the supported system for minimum cost. Input the required availability and OmegaPS Analyzer will indicate the spares required to meet that availability at minimum cost. Input a spares budget and OmegaPS Analyzer will optimize the spares to maximize the availability within that budget. OmegaPS Analyzer produces reports, which indicate: Pennant International Group 11 P a g e

12 Spares to be purchased Where to stoc the spares Measure of Effectiveness Cost Effectiveness Curve Sparing Analysis Modes The sparing analsyis can be run in different modes based on the desired outcomes or operations of interest. System Analysis, the default mode, defines the number of spares required for each item; an optimal allocation of these spares to meet a specified system MOE at minimum spares investment or to meet a specified spares budget with a maximum system MOE. Mission Analysis mode assumes a number of equipment will be sent on a mission for a specified duration and that only on-site maintenance will be possible. The module provides a list of the spares required to maintain the equipment at a specified "Measure of Effectiveness", such as probability of mission success. Single Item Analysis option was developed for use during initial procurement to quicly provide estimations of the number of spares required for an item, optimal allocations for the spares organization and cost of the spares. It provides a worst case spares scenario for the planner. Single Item Analysis will optimize on the trade-off between components of a given subsystem. Measures of Effectiveness Effectiveness is a function of many different factors such as repair capability, stoc on hand, and supply delay time. For example, the supply department may be trying to meet their goal of satisfying 90% of all orders received, whereas operations may be trying to ensure that 75% of a fleet is operational on any given day. The MOE to choose is the one that best demonstrates whether the desired system goal is being met. The OmegaPS Analyzer user can select from possible MOEs: Expected System Delay Time Expected Number of System Bacorders Operational Availability Probability of Mission Accomplishment Pennant International Group 12 P a g e

13 Level of Repair Systems need to be maintained if they are to be ready for use when required. When new equipment is fielded, decisions must be made as to whether a failed item should be repaired or discarded. OmegaPS Analyzer enables the user to choose a maintenance policy based on experience and design, and then use the LORA model to improve it. LORA maes its decision based on the total assembly cost of an LRU permitting the influence of lower level components in the comparative analyses. Cost Savings The LORA model compares costs between the optimal disassembly and repair policy and the cost of the original maintenance policy. It provides the user with the possible net savings (if any) for each component and the total savings possible if every maintenance recommendation is adopted. The user has the capability of assessing the inflationary effects on the maintenance policy, essential for long term planning. Inflation categories apply to different parts of the model or as assigned and are: Consumables Manpower Maintenance Transportation Administration Substantial savings can be realized when an optimal disassembly and repair policy is chosen. The LORA model provides disassembly levels for all components of the Prime Equipment. It compares the cost of the optimal disassembly policy with the cost of the original disassembly policy provided by the user. In the case of any replaceable unit, the optimal disassembly policy is conditional on the disassembly policy of its parent. Shared Assets Support and Test Equipment that can be shared among several items have their allocation to echelons coordinated with the maintenance plans of these items, with infeasible combinations being eliminated. A special STE module in LORA evaluates the best mix of shared support assets. Pennant International Group 13 P a g e

14 Although fixed set-up costs are ignored in the analysis, the module does provide the user with the ability to perform marginal value analysis on the costs of facilities with respect to the number of repairs performed at a specified site. Life Cycle Costs Life Cycle Cost Analysis is used to determine the overall cost of the Prime Equipment with respect to supportability. By considering the life cycle phases of R&D, acquisition, in-service and disposal costs, the analyst can identify the least cost support solution for the equipment. At different times in the equipment support process varying depths of analysis are required. OmegaPS Analyzer allows for different LCC analysis modes. The model provides the Life Cycle Cost of the project along with details in the form of a cost breadown of recurring costs, a tally sheet of all fixed and recurring costs with the cost categories directly captured by the model and an annual expenditure summary. LCC also provides information on labour, i.e. the number of direct maintenance labour hours required by repair site and repair echelon. This helps to define the number and sill levels of equipment maintainers. Also, the annual cost of maintaining each item in the system is provided as a report and is useful for identifying the cost drivers in the Prime Equipment. Costs are evaluated by user selectable measures, for example, the full life cost, per operating unit, per PE and per failure. The model maes use of the number of spares per site recommended by Sparing. It accounts for acquisition costs of the spares and cost of transporting the spares to their maintenance or storage site. A full sparing analysis can be selected as part of the LCC analysis; this improves on just entering a cost of spares into a spreadsheet that so many LCC models need. Ris Analysis A capability to express uncertainty of cost and failure rate is provided. When used, a ris assessment is conducted to determine the uncertainty around the LCC estimates obtained. A cumulative probability distribution of LCC is calculated which expresses the lielihood that the life cycle cost does not exceed a given dollar amount. Ris analysis in the cost model uses a three point estimate analysis and presents a ris graph to indicate potential differences. Pennant International Group 14 P a g e

15 Customizing Life Cycle Costs Customization allows the user to define any other specific costs. The costs are defined based on the cost measure, cost class and cost type. With two modifiers available, this feature allows for almost any additional cost to be modeled accurately, expanded the LCC model to be suited to any level of project analysis. Analysis Techniques A good supportability model allows the analyst to apply several analysis techniques. These include sensitivity analyses, trade-off analysis and cost ris analysis. Sensitivity Analysis In cases where input data is based on engineering or contractor estimates as opposed to actual data, it is recommended that a study be conducted to determine how sensitive the solution is to variations in input parameters. OmegaPS Analyzer provides a convenient method of performing sensitivity analysis by providing the user with a wide range of sensitivity factors that are applied at run-time and do not affect the data stored in the Pennant International Group 15 P a g e

16 databases. Sensitivity analysis can be effected either globally on all values of a parameter or can automatically assess a sequence of changes to a specific value. Trade Off Analysis OmegaPS Analyzer provides for full trade of analysis to test the "what if?" scenarios. By comparing the results of a comparative analysis against the baseline, the user can determine the relative merit of different decisions through this analysis and estimate the benefit of accepting the change. Cost Ris Analysis Ris and cost estimation analysis using probability distributions of uncertain parameters has become the standard alternative to using single point estimates for input data. The process consists of determining the stochastic characteristics of an objective variable (OV) through those of the primary variables (PV's) maing up this OV. For LCC analysis the OV is the total life cycle cost whereas the PV s are the basic item level data such as MTBF, repair time etc. The premise is that it is easier and more accurate to estimate the stochastic characteristics of the PV's than it is to estimate those of the OV. During the development of Analyzer a number of methods were investigated for implementing ris analysis in a life cycle cost model. They were studied from the point of view of simplicity of input requirements, efficiency and accuracy of computation and their ability to handle dependencies. Pennant International Group 16 P a g e

17 In order to minimize the effort required in defining the uncertainty associated with primary variables the popular three-point approximation is used. This approach, which is also very useful when no data is available, specifies parameters of a distribution using just three estimates: a low value, a most liely value and a high value. Its popularity is obvious for busy managers because of the need to estimate only three well understood values. Output Reports and Graphs As a result of running analyses in OmegaPS Analyzer sets of output reports and graphs are generated. The following are some examples of these reports. Spares Provisioning Report Life Cycle Cost Reports Pennant International Group 17 P a g e

18 LCC Recurring Maintenance Cost breadowns Cost Envelope Graph Data Transfer The Data files, model Results output files and Project export files are generated in XML formats. These XML files can be used to review the data or use within other software products that read XML formats. Pennant International Group 18 P a g e

19 Mathematical Models Underlying the OmegaPS Analyzer supportability model is a set of sophisticated mathematical equations developed by scientists and modellers over many years. A brief overview follows, but the full equations are presented in system documentation with the product. Support Demands The whole of supportability analysis and cost estimation is predicated on the support demand. A support demand is generally based on a failure of a part within the equipment or a scheduled maintenance tas. Calculating Part Removals Part removals are measured as the Mean Units Between Removals. Supportability resource usage and costs are generated every time a removal is conducted. This removal is usually due to engineering failure but can also be caused by a perceived failure (i.e. No Defect) or an Induced failure. In some scenarios it might be necessary to indentify removals based on Damage Modes. Therefore, Mean Units Between Removal (MUBR) for a part is: MUBR p 1 MUBF 1 MUBF ( nodef) 1 1 MUBF ( ind) 1 MUBF Damage MUBF MUBF (no def) MUBF (ind) = Mean Units Between Failure of the part. This is also the inverse of the failure rate (1/λ) = MUBF when a no defect situation was treated lie a failure. This value decreases the MUBF, or increases the failure rate, to include phantom failure modes. Sometimes this value is provided as a no fault found rate (NFF%) indicating a ratio of the true MUBF. = MUBF when a failed item was induced by an external influence other than the random failure of the part. This value decreases the MUBF, or increases the failure rate, to include failure modes other than expected engineering failures. Pennant International Group 19 P a g e

20 MUBF (Damage) = MUBF when a failed item was caused by damage. This value is similar to induced, but may be used to distinguish external damage (e.g. military action) from maintenance or equipment induced failure. Type 1 and Type 2 Demands In Analyzer we differentiate between two types of failure and therefore the type of demand for support. Demands generated by a part at a Site i are first determined to be real or whether it is a No Fault Found (NFF or No Defect) situation. Genuine failures are managed by the remove and replace of sub-components (Type I) or repair of the item itself (Type II). These three situations are annotated by NDi, Ri and i respectively. The removals of child items, the Type I fraction TI, is calculated as a ratio of the removal rate of all the removable children to the removal rate of the part. The repairs of Type II failures are based on the failures that do not require a child replacement and are not NFF, whose fraction, T2 is therefore (1-TI-NFF). Therefore, And, These annual demands at site i can be expressed as: 0, if i I ND i AD NFF, if i I Pennant International Group 20 P a g e

21 0, if i I R i AD TI, if i I i 0, if i I AD T 2 rfi, if i I. Monthly Demand, MD The failure demand rate on its own is not sufficient. The demand for support is also dependant on the operational program. This basic demand is calculated for each part (p) in a PE at an operational site (i) by: 1 MDip *(1 PMSR) * TOHM PEi * QinPE p * DCext MUBR p Taing into account the removal rate (MUBR), the portion of failures that might be prevented (PMSR), the Total Operating Hours per Month (TOHM), the Quantity of the item in the PE (QinPE) and any Duty Cycles (DC). Monthly Demand can then be multiplied by the months per year the Prime Equipment operates at any specific site. This then becomes the primary driver into the cost equations. p Sparing Expected Bacorders The sparing solution is driven by the number of bac orders the system will experience. Or put another way, the number of Bac Orders permissible and still achieve the system operational goal. The expected number of bac orders can be calculated by taing the weighted average of the probabilities that a stoc of S spares would satisfy the expected demands during the resupply cycle (often referred to as the availability of spares, A(S; R)). Pennant International Group 21 P a g e

22 Pennant International Group 22 P a g e Complete descriptions of the models equations are provided in system documentation. Future Analyzer The modellers and scientists are continually woring at improving the models and OmegaPS Analyzer as a supportability tool. Since the first LCC equation was coded in 1971, continued effort has matured the models to today s standards. However, it doesn t end there; research and development is currently underway to include such things as LP Programming and Genetic Algorithms. Extensions for System Availability allocations and performance measurement to facilitate today s performance based support concepts are also being added. OmegaPS Analyzer is a User Driven software product. That means, you as a user can request enhancements and suggest upgrades. These are often discussed during our User Group forums, held regularly to bring users together for training, sharing application and designing the future! Currently OmegaPS Analyzer is used in many countries by both industry and Government organisations. For more information on OmegaPS Analyzer R4 or to boo a presentation please contact your local Pennant offices. ) (! ; 1 S R e R S B R S ) (! ) (! 0 0 S R e S R e R S R 0, 0 ), (! 1 0 S if R S if S R e S R R S