Keywords: Product Family Design, Production Cost Estimation Framework, Activity Based Costing, Product Family Structure, Resource Sharing Methods

Transcription

1 DEVELOPMENT OF A PRODUCTION COST ESTIMATION FRAMEWORK TO SUPPORT PRODUCT FAMILY DESIGN Jaeil Park 1 and Timothy W. Simpson 2* Department of Industrial & Manufacturing Engineering Penn State University, University Park, PA USA ABSTRACT The main task of a product family designer is to decide the right components/design variables to share among products to maintain economies of scale with minimum sacrifice in the performance of each product in the family. The decisions are usually based on several criteria, but production cost is of primary concern. Estimating the production cost of a family of products involves both estimating the production cost of each product in the family and the costs incurred by common and variant components/design variables in the family. To estimate these costs consistently and accurately, we propose a production cost estimation framework to support product family design based on Activity-Based Costing (ABC) that consists of three stages: (1) allocation, (2) estimation, and (3) analysis. In the allocation stage, the production activities and resources needed to produce the entire products in a family are identified and classified with an activity table, a resource table, and a production flow. To help allocate product data for production, a product family structure is represented by a hierarchical classification of products that form the product family. In the estimation stage, production costs are estimated with cost estimation methods selected based on the type of information available. In the analysis stage, components/design variables possible for product family design are investigated with resource sharing methods through activity analysis. As an example, the proposed framework is applied to estimate the production cost of a family of cordless power screwdrivers that share different components within the family. Keywords: Product Family Design, Production Cost Estimation Framework, Activity Based Costing, Product Family Structure, Resource Sharing Methods Version: February 29, 2004 (Revised: July 7, 2004) Submitted to: International Journal of Production Research 1 Graduate Research Assistant. 2* Associate Professor of Mechanical and Industrial Engineering and Member ASME. Corresponding Author: 329 Leonhard Building, Penn State University, University Park, PA 16802, USA. tws8@psu.edu. Phone/fax: (814) /

2 1. INTRODUCTION Increasing competition in today s global marketplace has forced many firms to investigate new design strategies for providing a variety of products, lowering production costs, and reducing the time taken to introduce new products [1]. In this context, product family design is a cost-effective design strategy that can bring a variety of products to market to satisfy various customer wants and needs at a competitive price [2]. This strategy has created an environment where designers have taken responsibility of how components are shared to reduce production costs while considering downstream production operations. The shared components reduce not only the production costs by improving economies of scale, but also the number and types of components in inventory and other production support activities [3,4]. However, the shared components may lead to a lack of distinctiveness, and shared components in one product can often exceed the requirements of other products, which can incur additional production costs [5]. Consequently, it is critical that the trade-offs involved with product family design should be evaluated in terms of production costs [6]. At the early product family development stage, production costs can be estimated by a set of production activities and resources related to producing a family of products, but it is not certain that the costs are estimated with consistency and accuracy since the costs vary depending on decisions made on what production activities are included and how to estimate the costs associated with them. In particular, it is widely accepted that a decision made on a production activity during the early development stages significantly influences the costs later in development [7]. To make cost estimation for product family design more consistent and accurate in the early development stages, it is necessary to develop a cost estimation framework. In estimating production costs, designers are required to understand the cost implications of selecting the most appropriate components/design variables possible for a family of products and to build cost functions by synthesizing the implication from the initial design representation to production. Many attempts in product family design have been made to quantitatively measure the cost implications by making cost functions. The cost functions are represented by (1) the empirical relationships between design variables and production processes based on historical and operating data and past experience [8-10], (2) engineering relationships between design and process variables including economic factors [11,12], and (3) statistical relationships between design variables and process characteristics [13,14]. These cost functions are, however, 2

3 developed by assuming that the costs are related to one (or more) of the design variables even if some of the estimated costs are not related to the design variables. Production costs for product family design provide good design guidelines for designers decision making process when the costs are linked to a set of production activities [15,16]. Understanding how these activities are allocated to the resources consumed by activities is a key factor in estimating production costs. Activity-Based Costing (ABC) has been introduced to foster the understanding using hierarchical activities ranging from unit-level through batch-level and product-sustaining level to facility-sustaining level [17-19]. The following five steps are currently suggested to measure production costs in a production system in ABC [20]. 1. Identify and measure the resource spending at the four different activity levels. 2. Measure the costs of resources used to perform activities. 3. Identify cost drivers and measure resource-consumption rates. 4. Use the cost drivers to assign activity costs to products by multiplying the use of the cost drivers by the resource-consumption rates. 5. Analyze the profitability of products at the four different activity levels. One of the primary objectives when using ABC for cost estimation is to identify and analyze opportunities to reduce production costs by performing the following activity analysis [21]. 1. Activity elimination: find ways not to do an activity at all or reduce usage of the activity. 2. Activity reduction: reduce the time and resource needed by an activity. 3. Activity selection: design products to use less expensive activities. 4. Activity sharing: create economies of scale by using the same activities over instead of using new activities. Activity analysis plays an important role in identifying the production activities that cause less efficient activities and helping designers concentrate their cost reduction efforts in those areas. In this section we have briefly addressed the need of a production cost estimation framework and what requirements are necessary in the framework. However, theses attempts to incorporate the requirements into the framework are at present incomplete. In addition, various production cost estimation methods have been developed in the literature, but none are readily extendable to product family design. To improve product family costing and integrate production costs into decision-making for product family design, we propose a production cost estimation framework based on ABC. In the next section, we introduce the production cost estimation framework that consists of three analysis stages: (1) allocation, (2) estimation, and (3) analysis. In the allocation 3

4 stage, production activities and resources are identified, and a product family structure is constructed (see Section 2.1). In the estimation stage, production costs are estimated using one or more cost estimation methods selected as discussed in Section 2.2. The analysis stage analyzes the production activities and suggests possible commonality information by using resource sharing methods (see Section 2.3). In Section 3, the production cost estimation framework is demonstrated with a family of cordless power screwdrivers. Closing remarks and future work are discussed in Section PROPOSED PRODUCTION COST ESTIMATION FRAMEWORK To build the production cost estimation framework to support for product family design, we begin with the following problem definition, requirements, and scope of the production cost estimation framework. Problem Definition: The production cost estimation framework is used to estimate the production costs of the product family in the early development stage. Requirements: Some of production costs are directly linked to design variables so that designers can understand the influence of the design variables on the production costs, which are called linked costs. Other costs are allocated to activities by tracing resource costs to activities, which are called allocated costs. Scope: The production cost estimation framework includes the most common costs used in industry at the product development stage. Based on this problem definition, requirements, and scope, the proposed production cost estimation framework is developed as illustrated in Figure 1. The cost estimation framework is described in three stages: (1) allocation, (2) estimation, and (3) analysis. In the allocation stage, the production activities that are carried out during the process of getting raw materials, transforming them into finished products, and delivering them to customers are modeled. The production activities and the corresponding resources are identified with (1) an activity table, (2) a resource table, and (3) a production flow. When an activity consumes resources, a cost is incurred. Factors that incur the cost are called cost drivers, which are used to estimate allocated costs. The linked costs are estimated by transforming a set of product data for production into explicit cost information that describes the economics of producing the product family. The product data required at the estimation stage can be categorized as engineering, process, and production data. The engineering data is represented by a bill of materials (BOM), which is a 4

5 structured specification list for the products (e.g., design specifications), the process data outlines the specification of the processes to produce the products (e.g., process speeds), and production data includes overall information about the operation (e.g., production volume). Product family data is represented by a set of individual product data and potential components/design variables for product family design. Both the cost drivers and product family data are combined into a product family structure capturing the products in the family, their assemblies, and relationships. Modeling a Production System Production Flow Activity Table Resource Table Product Data Allocation Stage Product Family Data Alternative Derivative Products, Xv,i, i=1 p Product Platform Alternative, Xc Cost Drivers Product Family Structure Cost Estimation Total Production Costs Facility-Level Costs Product-Level Costs Unit-& Batch-Level Costs Inventory Costs Design Variables for Platform Level Estimation Stage Assembly-Level Costs Platform-Level Costs Component-Level Costs Feature-Level Costs Production Costs Components/Design Variables for Product Family Design Sharing Methods Activity Analysis Analysis Stage Resource Data Resource Capabilities Learning Effects Discount Rates Past Accounting Costs Figure 1. Proposed Production Cost Estimation Framework In the estimation stage, production costs are estimated by estimation methods selected based on the available information. When past accounting costs are available, allocated costs are dominantly used, and they are described at the hierarchy of activities: unit-, batch-, product-, and facility-level activities. A major change is that the unit- and batch-level costs of ABC are further divided into feature-, component-, platform-, and assembly-level costs in this paper. If designers intend to investigate the cost incurred by an inventory activity, the cost driver of the activity is determined at the allocation stage, and the inventory cost is estimated either as linked or 5

6 allocated cost depending on the cost estimation method. This estimation process appears in Figure 2. An allocated resource consumption rate is determined by measuring the resource cost per the cost driver of an activity, which is related to an allocated cost. An estimated resource consumption rate is modeled using design variables, which affects a linked cost (e.g., processing cost ($/part)). Technical cost modeling is an extension of conventional process modeling, with particular emphasis on capturing the cost implications of process operation data and economic parameters (e.g., a technical cost model for stamped parts). For higher-level activities, allocated costs are commonly used to estimate costs. At the unit-level activities, however, either allocated or linked costs are used to estimate costs. Technical costs are built with cost information of all levels of activities. The resource data includes resource capabilities, learning effects, discount rates, past accounting costs, etc. Production Activities Activities Resources Design Cost Drivers X Allocated Resource Consumption Rates = Allocated Costs Cost Drivers X Estimated Resource Consumption Rates = Linked Costs Technical Cost Models = Technical Costs Figure 2. Cost Estimation Process Finally, in the analysis stage, potential components/design variables possible for product family design are investigated with resource sharing methods through activity analysis. The sharing methods are a set of methods that lead to reducing or eliminating the resources consumed by the activities and provide new design variables for estimating production costs at the platform level. The three stages of the production cost estimation framework are elaborated in the following sections ALLOCATION STAGE In the allocation stage, designers need to identify and classify the production activities and resources of a production system to estimate general production costs and/or specific production 6

7 costs that they intend to investigate. As input data for estimation, a product family structure needs to be constructed. Modeling a production system and constructing a product family structure are described next MODELING A PRODUCTION SYSTEM The purpose of this step is to break down a part of a production system and form the design focus into a hierarchy of activities. To measure activity costs, activities in a production system need to be identified and classified. Each process is made up of a number of activities, which designers list in more or less detail depending upon the objective of the production costs. Once an activity list is developed for the most common production system, it provides a template for identifying and measuring relevant resource costs at all level. Table 1 shows a listing of example activities in a production system and possible cost drivers that incur direct and indirect (overhead) costs in a production system within ABC. Normally, batch-, product-, and facilitylevel activities are classified as overhead activities, which are traced by identifying physical resources that support various overhead activities, and most unit-level activities are involved in direct costs. For the purpose of understanding the influence of design variables on production costs, the costs that are estimated based on design variables are classified as linked costs in this paper; otherwise, costs are estimated as allocated costs. For example, activity U1 belongs to the unit-level activity and makes injection-molded parts, and its allocated cost is estimated with the cost driver such as the number of parts and allocated resource consumption rate of the activity. As one of the linked costs of the activity, the processing cost can be estimated by estimating the resource consumption rate (i.e., processing time), which is determined by the geometry and material (design variables). The indirect labor cost of the maintenance of the machine U1 is, under an assumption that the maintenance cost is proportional to the processing time, classified as a linked cost as well. 7

8 Table 1. Example Activity Table of a Production System Cost Activity Class Basic Cost Activities Cost Drivers Index Unit level Injection Number of parts U1 Die casting Number of parts U2 Machining Number of parts U3 Stamping Number of parts U4 Packaging Number of parts U5 Assembling Number of assembling hours U6 Auxiliary operation Number of parts U7 Purchasing Number of parts U8 Batch level Setup Number of production runs B1 Material transfer (MT) Number of transfers B2 Material handling (MH) Number of handlings B3 Inspection Number of inspections B4 Work-in-process (WIP) Number of parts in WIP per batch B5 Purchase order Number of orders B6 Product level Product engineering Number of products or engineering hours/product P1 Process engineering Number of fixtures or engineering hours/product P2 Engineering change order Number of change orders P3 Facility level Facility engineering Number of processes or engineering hours/facility F1 Facility maintenance Production hours/facility F2 Facility management Number of laborers F3 Specific level Raw material (RM) inventory Number of RM stored S1 Final-finished product (FFP) inventory Number of FFP stored S2 Resources may include materials, laborers, equipment, space, and other things of value that are consumed by activities. They are classified by resource type: material processors (MP), material handlers (MH), material transporters (MT), tools (TL), laborers (LA), materials (MA), capital (C), energy (EN) and others (OT). A partial list of resources is given in Table 2. 8

9 Table 2. Resource Table Resource Class Basic Resources Index Resource Class Basic Resources Index Material Process or (MP) Injection Die casting Machining MP-I MP-D MP-M Tool (TL) Tool Fixture Tool holder TL-T TL-F TL-TH Stamping MP-S Special tools TL-ST Assembling Packaging Auxiliary equipment MP-A MP-P MP-AE Laborer (LA) Low-skilled laborer Intermediate-skilled laborer High-skilled laborer LA-L LA-I LA-H Material Handler (M H) Robot AS/RS Special M Hs MH-R MH-A MH-S Material (M A) Raw material Semi-finished part Finished part MA-R MA-SF MA-F Scrap MA-S Secondary material MA-SM WIP M A-W IP FFP MA-FFP Material Transfer (M T) AGV Conveyer MT-A MT-C Capital (C) Energy (EN) Capital Gas Electricity C EN-G EN-E Truck Lifter MT-T MT-L Others (OT) Building Storage OT-B OT-S Special M Ts MT-S With the activity and resource table, a production flow indicating the relationships between the activities and resources can be constructed. Figure 3 shows an example of the production flow of a production system that contains an injection molding, a die casting, a machining process, and a final assembly line using some of the activities in Table 1 and resources in Table 2. The control volume in the flow defines the areas where the activities to be investigated occur. A circle represents an activity, and the resources consumed by the activity are represented by boxes above each circle. A production flow is represented by connecting activities to the material flow occurring in a production system. Several resources consumed by an activity are depicted by multiple small boxes in a main resource. As an example, an production flow for diecasting process is defined using the control volume as shown in Figure 3, which contains diecasting process (U2), setup (B1), material transfer (B2), material handling (B3), purchase order (B7), inventories (S1, B5, and S2), and assembly (U6) activities. In the raw material stage, three activities occur and consume low-skilled laborer (LA-L), storage (OT-S), and capital (C) resources. In the process stage, activity U2 consumes die-casting machine (MP-D), low-skilled laborer (LA-L), raw material (MA-R), tool (TL-T), electricity (EN-E), and capital (C) resources. This production flow shows the activities necessary to cast parts along with the corresponding resources while providing a graphical view on how activities and resources are connected. 9

10 Product Activities Facility Activities LA-H LA-H P1 P2 P3 F1 F2 F3 OT-B LA -H MP-M LA-L MA-R TL-T EN-E C MA -WIP LA -L B1 U3 B5 B2 Control Volume LA -L C OT-S LA -L LA -H MP-D LA-L MA-R TL-T EN-E C MA -WIP LA -L LA -L MP-A TL-F LA-L EN-E C OT-S B7 S1 B3 B1 U2 B5 B2 B3 U6 S2 LA -H MP-I LA-L TL-T MA-R EN-E C MA -WIP LA -L B1 U1 B5 B2 Resource Activity Activity flow Figure 3. Production flow Example PRODUCT FAMILY STRUCTURE A product is produced by a set of activities and the resources consumed by the activities. As the number of products increases in a family, the products need to be organized in a tree structure to be able to investigate components/design variables possible for product family design. A product family structure also needs to be constructed as a database to accommodate a set of product data and costs of a product family. The product family structure is generally constructed with a hierarchical classification of the items that form multiple products [22] and relationships of the items in the family [23-25]. Figure 4 illustrates an example of the proposed product family structure. The hierarchical classification is closely related to the hierarchical levels of the production activities, and their product data for estimation can be identified according to the product development cycle [26]. 10

11 Product Family Facility Level Product 1000 Product 2000 Product p000 Product Level Components Functions Product Assembly Level Function 1100 Function 1200 Function 1300 Plat Plat Plat Platform Level Com Com Com Component Level 1 2 F F F Plat 0120 Com F 1212 F 1213 (p,j,i,k) is the index of (product, function, component, feature) F: Feature, Com: Component, Plat: Platform 1 1 Feature Level Cost Geometry Material Process Planning Production Planning Common Unique Figure 4. Product Family Structure to Support Production Cost Estimation To identify relationships among the products and incorporate the production activities associated with the relationships, platform-level activities are introduced into the framework. The information of the platform-level activities is determined through activity analysis, which is described in Section 2.3. The geometry data is used to identify geometrical characteristics in the product family, which have three geometrical types: (1) unique, (2) common, and (3) variant. The material data contains information on the sharing methods selected by the activity analysis. The process planning data is used to plan manufacturing processes for components in the geometric relationships. The production planning data is used to allocate resources that are available to produce the components in the geometric relationships. The product-level activities include: (1) product engineering (e.g., product designs), (2) process engineering (e.g., fixturing design), and (3) engineering change order (e.g., design changes for customers). The facilitylevel activities are used to address facility-sustaining activities such as (1) facility engineering (e.g., layout design), (2) facility management (e.g., administration), and (3) facility maintenance (e.g., utilities). 11

12 The costs allocated to the structure are calculated at the lowest level possible. The costs at the component level can be calculated by adding the costs at the feature level and the costs incurred at the component level. As an illustrative example shown in Figure 4, a simple calculation is conducted: a component (1210) consists of features (1211), (1212), and (1213), and its cost becomes $5 by adding $3 at the feature level and $2 at the component level. If the component can be shared with component (2210) of the product (2000) in the family, the cost at the platform level can be reduced to, say, $8 for the two common components due to an increased production volume and other savings caused by sharing higher-level activities (see Section 2.3 for examples). Therefore, the cost of component (1210) is reduced to $4. Total production cost of product (1000) is obtained by accumulating all component costs; production cost (1000) without commonality becomes $13 but is only $12 with commonality. Additional savings that are possible at the product- and facility-sustaining levels are not shown in this figure. The product data and cost drivers in the product family structure are key influencers on estimating production costs at unit- and batch-levels. At the unit-level, either product data is used to estimate linked costs or cost drivers are used to estimate allocated costs. At the batchlevel, the product data provides information on how to produce a batch of components to cost estimation for allocated costs. The data contains setup, material handling, working-in-process, inspection information, etc. For more accurate cost estimation including indirect costs, it is necessary to have information on product data that occur later in the product development cycle, such as process planning and production planning. These costs can be estimated using past accounting costs [20], but they need to be investigated in more detail as to their impact of product family design. As the number of products to be produced increases, the production costs at the product-sustaining and facility-sustaining level activities are shared across more products and contribute to economies of scale. Product families need to be focused more on product- and facility-level activities than individual products because product families are developed in efforts to reduce the product- and facility-level activities of individual products. Example product data and cost drivers at each level are illustrated in Figure 5. 12

13 Activity level Product data /Cost drivers Feature Level Component Level Platform Level Assembly Level Geometry Feature geometry Component geometry The number of parts Unique, Variant, Common geometry The number of parts Assembly geometry The number of parts Material - Material The number of parts Sharing Methods The number of parts Material used in Assembly The number of parts Process Planning Process Processes Setup WIP MH MT Inspection Purchased order The number of batches Processes Setup WIP MH MT Inspection Purchased order The number of batches Processes Setup WIP MH MT Inspection Purchased order The number of batches Production Planning Resource allocation planning Resource allocation planning Resource allocation planning Resource allocation planning Cost Type Linked cost Allocated cost Linked cost Allocated cost Linked cost Allocated cost Linked cost Allocated cost Activity level Activities Cost Drivers Product Level Product engineering Process engineering Engineering change order The number of product The number of process The number of change order Facility Level Facility engineering Maintenance Management The number of engineering hours The number of production hours The number of employees Cost Type Allocated costs Allocated costs Figure 5. Cost Divers in Production Information Structure 2.2. ESTIMATION STAGE In the estimation stage, costs are estimated based on the product family structure and resource data and assigned back to the product family structure. Costs are usually classified into linked and allocated costs, which are determined by the available information. The cost drivers and product data are identified and collected for cost estimation methods at the feature-, component-, and assembly-level for individual products in a family and at the platform-level for the product family. Total production costs are obtained by collecting all costs occurring within the hierarchical levels COST ESTIMATION METHODS Linked costs are estimated by identifying the relationship between design variables and resource consumption rates. The cost estimation methods of the liked costs are classified into variant-, generative-, simulation-, and hybrid-based cost estimation methods based on how to define the relationships between design variables and resource consumption rates. 13

14 Variant-based cost estimation methods use similarities among components to retrieve relative cost information in terms of design variables [27,28]. Generative-based cost estimation methods estimate production costs by synthesizing and analyzing manufacturing processes and systems. There are two types of generative-base cost estimation methods. One is to estimate part of production costs by estimating resource consumption rates such as processing time [25,29]. The other is to estimate production costs, with particular emphasis on capturing the cost implications of process operation data and economic parameters [11,12], which is called Technical Cost modeling (TCM). TCM is becoming used extensively to accurately identify the major direct costs by formulating the costs with respect to design variables. In particular, TCM is useful in making economic comparisons between different processes with different design variables. Simulation-based cost estimation methods provide accurate cost estimation for the operation of a factory including every operational cost occurring on the factory floor [30-33] and can assess the production costs incurred by direct and indirect production activities as follows: Direct costs: materials, labor, and processing time Indirect costs: indirect materials and labor, work-in-process inventory, setup, material handling and transfer. Finally, hybrid-based cost estimation methods combine any the three aforementioned methods. Production information for products can vary depending on the stage of the development cycle. At the early development stage, the variant- and/or generative-based cost estimation methods are more likely to be used because most costs are incurred by design and the corresponding manufacturing processes rather than by indirect activities in the production system. In the later development stages, simulation-based cost estimation is often used to address various costs incurred by statistical design variables. For the cost estimation method of allocated costs, activities are first identified and classified from past accounting costs and then cost drivers are properly selected. The change of a cost driver affects the level of activity performed, then its use of resources, and consequently its cost. To find the relationship between the number of cost drivers used and costs, it is necessary to collect cost information about each activity level, which comes from accounting data incurred by producing a family of products. Using regression analysis or account analysis, resource consumption rates can be estimated and allocated to activity costs of products. 14

15 RESOURCE DATA Total production cost is obtained by summing the costs of all the resources consumed in the production system. Identifying resource data relies on identification of production activities, choice of cost estimation, and accuracy requirements. Resource data is broadly classified as (1) resource capabilities, (2) learning effects, (3) discount rates, and (4) past accounting costs. The past accounting costs are classified in terms of resource class as listed in Table 3, but resource capabilities, learning effects, and discount rates are not investigated in detail in this paper. Table 3. Resource Data Resource Class Basic Resources Past Accounting Costs for Allocated Costs Type Unit Cost Driver Resource Costs/Consumption Rates for Linked Costs Material Processor (MP) MP-I, MP-D, MP-M, MP-S, MP-A, MP-P, MP-AE MP costs Unit rates C MP ($) U MP ($/hr) Product type MP-Cost =f(cost drivers) e.g., design variables = material, geometry Material Handler (MH) MH-R, MH-A, MH-S MH costs Unit rates C MH ($) U MH ($/hr) The number of batches MH-Cost =f(cost drivers) e.g., design variables = material, geometry Material Transfer (MT) MT-A, MT-C, MT-T, MT-L, MT-S MT costs Unit rates C MT ($) U MT ($/hr) The number of batches MT-Cost =f(cost drivers) e.g., design variables = material, geometry Tool (TL) TL-T, TL-F, TL- TH, TL-ST TL costs Unit rates C TL ($) U TL ($/hr) Product type TL-Cost =f(cost drivers) e.g., design variables = material, geometry Laborer (LA) LA-L, LA-I. LA- H LA costs Unit rate C LA ($) U LA ($/hr) The number of part/batch/prod uct/facility MH-Unit Cost =f(cost drivers) e.g., design variables = material, geometry Material (MA) MA-R, MA-SF, MA-S, MA-SM MA-R costs Unit rate C MA-R ($) U MA ($/hr) The number of part MA-Unit Cost =f(cost drivers) e.g., design variables = weight MA-F MA-F costs Unit rate C MA-F ($) U MA-F ($/hr) The number of part MA-F Unit Cost =f( cost drivers) e.g., design variables = part type, discount rate MA-WIP MA-WIP costs Unit rate C MA-WIP ($) U WIP ($/part) The number of batch MA-W IP Unit Cost =f(cost drivers) e.g., design variables = number of WIP MA-FFP MA-FFP costs Unit rate C MA-FFP ($) U FFP ($/part) The number of batch MA-FFP Unit Cost =f(cost drivers) e.g., design variables = number of FFP Capital (C) C C costs Unit rate C($) U c ($/part) The number of part C-Cost =f(cost drivers) e.g., design variables = interest and recovery years Energy (EN) EN-G, EN-E EN costs Unit rate C EN ($) U EN ($/hr) The number of part EN-Unit Cost =f(cost drivers) e.g., design variables = processing time Others (OT) OT-B, OT-S OT costs Unit rate C OT ($) U OT ($/hr) The number of part/batch/prod uct/facility OT-Cost =f(cost drivers) e.g., design variables = floor area used For instance, material class (MA) consists of raw material (MA-R), semi-finished part (MA- SF), finished part (MA-F), scrap (MA-S), secondary material (MA-SM), work-in-process (MA- 15

16 WIP), and final finished product (MA-FFP). If an activity to purchase a finished part occurs, the activity cost is estimated by total purchasing cost of the finished part (e.g., C MA-F ) divided by the cost driver of the activity (e.g., the number of parts). On the other hand, a linked cost can be expressed as a function of the design variable (e.g., material weight used). This cost function is generally used in optimization to estimate overall production costs when the material weight turns out to be the major variable in estimating production costs. Table 3 illustrates the estimated resource costs and resource consumption rates as well. At the batch level, batch costs regarding setup, MH, MT, WIP, and inspection can be estimated by cost drivers and the corresponding resource costs. For example, the cost of FFP is estimated by cost drivers such as the number of product types in inventory and the resource cost for inventory. The FFP cost can also be estimated by a technical cost model that has a cost relationship between inventory cost and the number of products in inventory [34]. This resource data enables designers to determine which information is available and what type of costs is used for better cost estimation TOTAL PRODUCTION COST CALCULATION Using the product family structure, all production costs can be allocated to the product family. At the feature level, the production cost usually relies on cost activities associated with specific features. For simplicity, different features are grouped into a single feature if all different features are produced with a single tool. A component with two features means that two different tools are needed to process the component. The production cost at the component level is composed of the cost of making all of the features associated with the component, material cost, tooling cost, and setup, work-in-process (WIP), and material handing cost if products are produced in a batch. At the platform level, the production cost relies on the cost activities of producing components in the family relationship. If the relationship type is unique, processing costs at the platform level are the same as those at the component level. In the case where the relationship type is variant, the process planning plans the manufacturing processes required to manufacture the variant component effectively, and the cost is estimated. Common components are produced like a single component so that the same cost drivers are applied to all the components, and direct and indirect cost savings are estimated with increased production volumes The production cost for the assembly level consists of the cost activities incurred by assembly [35]. 16

17 2.3. ANALYSIS STAGE Up to now, we have presented a systematic way of estimating total production costs including the effect of commonality on the production costs in the proposed framework. In addition to estimating production costs, designers need information as to which components or design variables should be examined for possible commonality based on production activities. According to product family design, multiple products performing identical or similar functions could be made a family by sharing some components based on product rationalization through analyzing process compatibility, customer needs, historical sales, indirect costs, or design compatibility [36]. During product rationalization, there are three aspects to reduce production costs in producing multiple products in a family: (1) design, (2) process, and (3) management. Design aspects involve redesigning unique components in a family to be common or variant in order to share, reduce, and eliminate resources consumed at all levels of activities. Process aspects seek to redesign the batch-level activities to accommodate various unique components by adding flexibility. The added costs should be justified by cost savings and improvements of resource utilization at the batch-level and higher levels. Management aspects are to decide strategically to share resources at the product- and facility-levels with an expectation of cost reduction. In terms of design aspects, three resource sharing methods are identified: (1) material sharing (MS), (2) partial feature sharing (PFS), and (3) tooling sharing (TS). In terms of process aspects, there are four methods: (1) setup sharing (SS), (2) inventory sharing (IS), (3) material handling sharing (MHS), and (4) material transfer sharing (MTS). In terms of management aspects, two sharing methods are identified: (1) process sharing (PS) and (2) facility sharing (FS). These sharing methods are detailed later in this section. The proposed framework does not necessarily provide production cost information reduced by commonality even if it is implemented properly because each cost estimate is not necessarily performed with the connection between its cost benefits and the sharing methods. In some cases, production cost is reduced less than expected when introducing commonalty. To investigate the cost benefits for commonality more systematically, it is necessary to indicate where cost benefits occur and how to connect them in the production system. For example, sharing components in the family to reduce tooling cost can incur other sharing methods such as process sharing (PS), facility sharing (FS), and even setup (SS) as a result of the primary sharing method (e.g., tooling sharing (TS)). To clarify the cause-and-effect relationships in the sharing methods, a resource sharing method matrix is utilized (see Table 4). A sharing method that triggers other sharing 17

18 methods is called a main sharing method ( x in the matrix). Other sharing methods affected by the main sharing method are called resultant sharing methods ( o s in the matrix). The cost savings by the sharing methods should be considered to estimate production costs for the product family; however, their specific relationships cannot be generalized in that the cost savings by the sharing methods are both product- and process-dependent. Consequently, specific relationships between resource sharing methods must be developed on a product-by-product basis. Table 4. Resource Sharing Method Matrix Sharing methods PFS MS TS PS FS SS IS MHS MTS Partial Feature Sharing (PFS) x Material Sharing (MS) x Tooling Sharing (TS) x o o o Process Sharing (PS) x Facility Sharing (FS) x Setup Sharing (SS) x Inventory Sharing (IS) x Material Handling Sharing (MHS) x Material Transfer Sharing (MTS) x Cost effect at the platform level by: Common features Common material Common tool Common process Common Facility Common Setup Common inventory Common MH Common MT To detail the cause-and-effect relationship in the sharing method matrix, a virtual design is introduced as shown in Figure 6. The resource sharing methods are determined by activity analysis in consideration of resource data. As mentioned in Section 1, activity analysis is composed of: (1) activity sharing, (2) activity selection, (3) activity reduction, and (4) activity elimination. When designers design new components to be unique in a family, new activities are generated that need to produce the new components such as new material, tooling, process setup, inventory, and material handling and transfer. By sharing the components, which is caused by material sharing (MS) and tooling sharing (TS), this activity generation can be eliminated. By selecting a set of features to be common to eliminate setup operations, which is triggered by partial feature sharing (PFS), the setup operations are eliminated. In this case, the main purpose of PFS is to eliminate the setup operation, but additional benefits such as MHS and MTS can be expected due to using the common features as the fixturing method of MH and MT. The resource sharing methods provide designers with guidelines to investigate production activities 18

19 from the manufacturer s perspective. If any possibility to share resources can be found leading to cost reduction, designers need to investigate the possibility for product family design. Activity generation: Material, tooling, setup, inventory, MH, MT Fb2 Fb1 B Activity Sharing: Activity Selection: Activity Reduction: Activity Elimination: Fa2 Fa1 A Fa 2 Fa1 A Activity Sharing: Activity Selection: PFS Activity Reduction: MTS, MHS Activity Elimination: SS Fa2 Fa1 A Activity Sharing: MS, TS Activity Selection: Activity Reduction: Activity Elimination: SS, IS, MTS, MHS Figure 6. Activity Analysis Example The key role of activity analysis for a production system can be found in managing product variety. In a study of product variety in the bicycle industry, Randall and Ulrich [37] investigated why bicycle manufacturers chose the different design variables (attributes) for variety to position their products in the target market and found that when producing a variety of bicycles, variation in material incurs huge effects on production costs but small effects on marketing, but variation in geometry/size incurs small effects on production costs but huge effects on marketing. This differential effect is caused mainly by the production system where the incremental variety investment for job shops in materials is the most expensive among material, geometry/size, components and colors. As a result, activity analysis is of importance in helping analyze a production system and select cost-effective components/design variables (attributes) to share within a product family. From the resource sharing matrix identified through activity analysis, components/design variables for product family design are suggested as shown in Table 5. The matrix places components, main causes for variety, and activity costs in the vertical axis. For each component, activity analysis is performed, and resource sharing methods are identified. The identified 19

20 sharing methods further provide components/design variables to designers. If additional costs are required to add flexibility, the costs should be justified by expected cost reduction. For the components affected by sharing methods, the costs are again calculated in the framework. Finally, the cost-effective components/design variables are provided to designers as design guidelines for product family design, along with the expected cost reduction. Both the component/design variable selection matrix and resource sharing method matrix help to understand the relationship of cost benefits and sharing methods in the early development stages. Examples and details of each sharing method are discussed in the following sections. Table 5. Component/Design Variable Selection Matrix Funct ion Compo nents Main Causes for Variety Activity Costs ($) Direct Indirect Activity Analysis (Resource Sharing) Components/Design Variables for Product Family Design Additional Costs ($) Costs($) for Sharing Costs($) for Variant Expected Cost Reduction($) F1 C11 Material, Geometry 5 3 Main: TS Resultant: PS, FS, SS C11 (Component) C12 Geometry (Features) 10 6 Main: PFS Resultant: TS, SS, IS,MHS, MTS F121 (Feature) C13 Geometry (Setup) 0 8 Main: SS Resultant: MHS, MTS No RAW MATERIAL SHARING (MS) Material cost per unit may decline if a sufficient number of parts are produced to justify a discount in the purchase price of material. There are two different sharing methods of material to reduce material cost. One is to share the same material type (grade) for different components; the other is to share the size (shape) to be purchased, which is process-specific. For example, sharing material among unique components in casting process leads to avoiding the setup of changing material and cleaning equipment (SS). Using the same thickness of sheet metal can reduce loading and unloading operations (MHS) if components could be produced from the same sheet, resulting in higher machine utilization PARTIAL FEATURE SHARING (PFS) Sharing some features around standard production tools may reduce tool changes (SS) or utilize a single tool (TS) in some cases. For example, most sheet metal bends, which do not need to be designed with any specific value, can be shared with a single bend radius, which leads to one single tool without setup changes. In fixturing problems, sharing certain features also provides a consistent fixturing method in which fixturing geometries are the same for different 20

21 components. During assembly, the features to be held by the fixturing tools should be shared so as not to incur additional fixturing changes TOOLING SHARING (TS) Tooling sharing expedites customization by eliminating the setup to locate and change tools needed in a manufacturing process. Tooling should be shared on readily available tools when similar components are designed as one common component by eliminating unusual or extra features. Tooling sharing needs to be investigated in term of its tool life. As an example, consider two components A and B, which have each production volume of 100,000 and tool life of 200,000. If the components are shared, cost benefit occurs due to eliminating the extra tool. In the case where each production volume of component A and B is increased to 200,000, and the tool lives are 300,000, the cost benefit does not occur since the tool lives are less than the total production volume. In other words, to produce the shared component, two identical tools are still needed (Non-TS) PROCESS SHARING (PS) Process sharing involves sharing different manufacturing processes to avoid an extra investment and increases machine utilization rates for processes. Process sharing is determined through investigating processing compatibility and machine utilization rates for a range of components that have similar design requirements but different geometries and/or materials. The machine utilization rates improve with increasing batch sizes due to reduced idle times. Dedicated (DD) machines expect to have 100% machine utilization, but machines do not run 100% of the time because of demand fluctuation and/or forecasting errors. Sharing the underutilized DD machines can improve machine utilization rates and reduce investment cost for the machines. Machine utilization rates of more than 100% do not yield cost benefits (Non-PS) by PS FACILITY SHARING (FS) Facility sharing can occur when unique components are produced at different locations or purchased from multiple suppliers. The components are often classified as outsourcing or standard components. Ordering the components from each facility or supplier causes setup (order), inventory, and material handling costs associated with each. Sharing the components may reduce the costs by less frequent ordering, reduced storage in inventory and material 21

22 handling, and reduced unit costs if a sufficient number of the components are ordered. If common components are designed but produced or purchased from a single shop over time, it is a similar case where different components are produced or purchased from different facilities. Cost savings like FS are not expected (Non-FS) SETUP SHARING (SS) Setup sharing is important when setup is tedious, difficult, and/or time consuming. Setup sharing can be done by establishing a setup method to be shared among different processes and redesigning existing components to fit the current setup method. The former is done by adding flexibility using auxiliary tools and machines. The latter is done by a result of sharing methods such as partial feature sharing (PFS) and tooling sharing (TS) INVENTORY SHARING (IS) Inventory sharing benefits a business that handles lots of inventoried goods such as distributors, dealers, and manufacturers factory. The business s concern is to reduce the storage amount and type through inventory sharing. Inventory sharing is done mainly by the design aspects such as MS, PFS, TS, PS, and FS, which can reduce the holding and carrying costs such as inventory administration, floor space, obsolescence, deterioration, and transportation [36]. For the process aspects, inventory sharing can be done by adding more flexibility to an inventory system such as automated storage and retrieval so as to be insensitive to a variety of products MATERIAL HANDLING SHARING (MHS) & MATERIAL TRANSFER SHARING (MTS) Material handling and transfer often require expensive material handling and transfer equipment, such as carousels, conveyors, robots, lifters, etc. to move components from one location to another. The equipment adds more flexibility to the factory that handles a variety of products. From a design aspect, designing common or variant components can enable single handling and transfer equipment and reduce the number of handling and transfer operation, leading to cost benefits. 3. CASE STUDY OF CORDLESS SCREWDRIVERS We apply the proposed production cost estimation framework to a set of cordless screwdrivers as a part of our efforts to determine right components for the product family design. In fact, the aim of this case study is to provide the production cost information that designers need for designing the products as a family and investigate the benefits of commonality in product family 22

23 design with sharing different components. The screwdriver family consists of five products (P1- P5) and is broken down into components as shown in Figure 7, and the bill of materials (BOM) for the product P5 is included in the Appendix to this paper as an example. P1 1 2 P2 P3 P4 P B1 B2 B3 B4 B5 Batteries in the Screwdriver Family 1. Bit 2. Drive train housing 3. Collet 4. Collet rocking assembly 5. P lan et arm 6. M e ta l pl ane t g ea rs 7. P lan et arm 8. P las tic pla ne t ge a rs 9. Moto r 10. Bu tton 11. Switch 12. B attery 13. Co llet housing 14. C ase 15. F olding loc king a sse m bl y 16. Ligh ting assembly 17. Ligh ting hou sing 18. W iring Figure 7. Products and Batteries in the Screwdriver Family The products consist of custom components manufactured using traditional manufacturing processes and standard components, which can be purchased from suppliers for use by any number of companies. The purchasing costs of the standard components significantly vary depending on purchasing volume due to discounting, and we assume that the discount rates have characteristics similar to learning curves. The product and assembly data is collected for DFMA through product dissection. On the basis of the product data, manufacturing processes are identified. In the components of the family, battery and motors can be candidates for commonality because they are classified as functional components that are not visible to the end user. The following section details the application of the proposed production cost estimation framework to this family APPLICATION OF PROPOSED COST ESTIMATION FRAMEWORK Determining all production activities is one of the most challenging aspects of the proposed production cost estimation framework since there can be hundreds of production activities that describe how each product is manufactured. In order to get the proper information, we need to contact engineers working on the manufacturing shop floor, but such information is usually proprietary and limited to researchers. As a best guess, linked costs can be estimated by DFMA (Design for Manufacturing and assembling) techniques, which are widely accepted in cost 23