A cost-based methodology for evaluating product platform commonality sourcing decisions with two examples

As more US companies source tooling development and manufacturing overseas in countries like China and Taiwan, are the need and primary drivers for product platforms diminishing? As tooling cost is reduced to a very small percentage of the total project cost, combined with availability of inexpensive purchased components and low labour rates, the need to develop product platforms can decrease substantially. Low cost outsourcing has given firms the ability to develop and manufacture products cheaply without having to spend the additional time and effort to develop product platforms and families. In this paper, two examples involving two consumer product companies and their product lines are presented. Product family components and estimated tooling costs are analyzed, as well as development timing and profit margins to demonstrate why companies are moving away from product platforms in certain types of consumer products. A novel methodology using component commonality decisions relating to major cost drivers is introduced and applied to both examples. Based on the evidence from the examples presented in this paper, there appears to be little financial or functional benefit to develop product platforms that share common components or subsystems when these products are being manufactured offshore; however, even when considering outsourcing, platform-based product development principles can still yield tangible improvements in production costs over the life of the product.     

Cost estimation of a service family based on modularity

Companies are competing to offer high varieties of customised services on top of customised products to increase revenues and customer satisfaction. By adopting product family design methodologies, new concepts such as service families and service platforms are adopted in the service sectors. Despite that, increasing diversity in service offerings induces complexity and difficulty in service cost estimation. This research presents a service family cost estimation methodology that is based on service modularity and activity based costing (ABC). A service family is identified by selecting a set of similar services. Subsequently, activities of each service are identified with an activity diagram. The service family is then decomposed into functional and physical elements, where service modules are identified. Service activities are then mapped into relevant service modules using k-mean clustering algorithms, and activities of each service module are segregated into common and specific services using un-weighted pair group method with arithmetic mean. Finally, modified two-stage ABC methodology is applied to estimate the costs for a service family. To demonstrate the applicability of the proposed methodology, a case study is carried out to estimate the cost for a family of aircraft engines.     

Function-technology-based product platform formation

Product platforms have been effectively used by many successful companies for product family design. Technological advancements and changes in customer needs pose problems for robustly designing product platforms over a given planning horizon. To date, most product platform formation approaches are directed by structural (subassemblies and components) considerations and are seldom undertaken at the conceptual design stage. We argue that product platform design should commence at the conceptual design stage rather than the detailed design stage. It is noteworthy that physical structures are the end results of designs already frozen at higher level of functional abstraction. Hence, tackling the platform formation problem should start much before structures are materialized. We propose that the product platform formation approach should be considered at two different stages: (i) conceptual design stage; and (ii) detailed design stage. In reference to the Function?–?Behavior?–?Structure model proposed by Gero and Kannengiesser (Gero, J.S. and Kannengiesser, U., Function-behavior-structure: A model for social situated agents. Workshop on Cognitive Modeling of Agents and Multi-Agent Interactions, International Joint Conference on Artificial Intelligence 2003, Acapulco, Mexico, 2003, pp. 101–107), conceptual design would refer to the design of products at function and technology stage, whereas detailed design would refer to the design of products at the structure stage. This paper discusses a method to form product platforms at the Function-Technology stage which can be correspondingly mapped to the structural stages. Thus, forming product platforms at a higher level of abstraction would enable a better understanding of the complications met at structural level. The FT approach uses Function Technology Ant Colony Optimization (FTACO) method to determine product platform configuration(s). We demonstrate the proposed approach using the example of a computer mouse product family.     

A graph-based model for manufacturing complexity

This paper presents a graph-based model to measure the relative manufacturing complexity of and the manufacturing similarity of products in job shop manufacturing systems. This model depicts the impact of the complexity factors on the profit realisable from products based on their manufacturing process and required resources/skills. These resources deal with the process required for a component to reach assembly, the process of assembling the components to a whole product. This relative manufacturing complexity measure not only can support assembly and production cost estimation, but also can provide a guideline for creating a product with the most effective balance of manufacturing and assembly. Also, the results of this study can help improve budgeting and resource allocation, and the product life cycle cost estimation for future products. A numerical example is also presented to demonstrate the application of the proposed approach.     

Product platform design through clustering analysis and information theoretical approach

An effectively designed product platform is vital to the final product family derived from it. A product platform design consists of platform configuration to decide which variables to make common across the product family and to determining the optimal values for platform and scaling variables for all product variants. Many existing product family design methods assume a given platform configuration, i.e. the platform variables are specified a priori by designers. However, selecting the right combination of common and scaling variables is not trivial. Most approaches are single-platform methods, in which design variables are either shared across all product variants or not at all. While in multiple-platform design, platform variables can have special value with regard to a subset of product variants within the product family, offering opportunities for superior overall design. This paper proposes a quantitative method for scale-based multiple-platform design using clustering analysis and Shannon's Entropy theory. Optimization methods are used to design the product family by holding the values of platform variables constant and to find the best values of the scaling variables. An information theoretical approach is used to help select platform variables based on the clustering analysis of individually designed products. Validity analysis is performed to determine the optimal settings for platform variables. Local clustering is further performed on each platform variable, to establish subsets of variants such that variants within a subset are more similar to each other than they are to variants in other subsets and a common value is used to represent the various values of variants in each subset. A case study is used to illustrate the process of the proposed method, and the design solutions are compared with that found by other methods given in previous literature. The comparison results verified that the multiple-platform design can lead to superior solutions of product family.     

A Variation-Based Method for Product Family Design

Product family design entails all of the challenges of product design while adding the complexity of coordinating the design of multiple products in an effort to maximize commonality across a set of products without compromising their individual performance. This paper presents the Variation-Based Platform Design Method (VBPDM) for product family design, which aims to satisfy a range of performance requirements using the smallest variation of the product designs in the family. In the first stage of the VBPDM, the product platform around which the product family is to be developed is identified. The product platform is common to all of the products in the family and represents the maximum standardization possible considering the variety of performance requirements that must be satisfied. To satisfy the range of performance requirements for the product family, a ranged set of solutions is found using variation-based modeling. A compromise Decision Support Problem (DSP) is formulated to solve the tradeoff between satisfying the variety requirement and maximizing platform commonality. Platform commonality is achieved by introducing a commonality goal that seeks to minimize the deviation of the input design variables while satisfying the range of performance requirements. Those design variables that show small deviations are held constant to form the product platform. In the second stage of the VBPDM, each individual product is designed around the common platform such that the functional requirements for each product in the family are best satisfied. As an example, the proposed method is used to develop a family of universal electric motors designed to meet a range of torque requirements. The results are compared against previous work on the same example.     

Platform Design for Customizable Products as a Problem of Access in a Geometric Space

A product platform is a set of common components, modules or parts from which a stream of derivative products can be created. Product platform design is typically performed as redesign and consolidation of existing products to create more competitive product families by reducing part variety and standardizing components. The main disadvantage of such an approach is that the benefits of product platform design are achieved only after a number of parts have been designed and manufactured, with all the associated expenditure. A number of approaches, referred to as “top-down approaches”, have been proposed recently to design the platforms since the original design of the product families. However, current top-own approaches have two major limitations: (1) they do not enable multiple levels of commonality for different components and features, and (2) they have been applied to products that are variegated in one specification, whereas products are typically variegated in multiple specifications. This paper describes a rigorous top-down approach for synthesizing product platforms that facilitates the realization of a stream of customized product variants, and which accommodates naturally multiple levels of commonality and multiple customizable specifications. The proposed approach is based on the formulation of the platform design as a problem of access in a geometric space. The proposed approach is illustrated with a case example, namely, the design of a product platform for a line of customizable pressure vessels.     

New integrated model to estimate the manufacturing cost and production system performance at the conceptual design stage of helicopter blade assembly

This paper describes a new integrated model development to estimate the manufacturing cost and production system performance at the conceptual design stage. A fully automated conceptual framework for design for manufacturing (DFM) has been developed. An integrated product process design concept using activity based costing is applied in this paper. The new integrated model consists of four sub-modules: the geometric parameters generation module, processing time estimation module, activity based costing (ABC) module and production system performance module. All of the input-output data flows of developed modules are fully integrated for automated manufacturing cost analysis and production system performance. A developed integrated model is very useful for designers or integrated product development team to make a decision for evaluating the design alternatives and trade-offs between design and manufacturing phases at the conceptual design stage. A case study for a composite helicopter rotor blade is included.     

Solving the multiple platforms configuration problem

The focus of manufacturing has been shifting from mass production to mass customization and producers are seeking ways to reduce production costs, still offering a competitive basket of products. One approach for implementing mass customization is to develop or produce products based on platform architecture. Variant products make use of the product platform as the starting point and then add or remove components to change features of the base product. This allows the manufacturer to offer the variety of products that meet market demands without developing each product independently. In this paper, we propose multiple platforms for the production of a given product family while minimizing the overall production cost. The methodology considers the demand for each product variant, with the decision variables as the optimal number of platforms, optimal configuration of each platform, and assignment of the products to the platforms. The problem is formulated as a mixed integer program, and both the optimal formulation and an evolutionary strategy based on Genetic Algorithm are presented. The approach is illustrated with an example from a family of cordless drills.     

Using product family evaluation graphs in product family design

Product family design and platform-based product development have garnered much attention. They have been used to provide nearly customised products to satisfy individual customer requirements and simultaneously achieve economies of scale during production. The inherent challenge in product family design is to balance the trade-off between product commonality (how well the components and functions can be shared across a product family) and variety (the range of different products in a product family). Quantifying this trade-off at the product family planning stage in a way that supports the engineering design process has yet to be accomplished. In this paper, we introduce a graphical evaluation method, the product family evaluation graph (PFEG), that allows designers to choose the ‘best’ product family design option among sets of alternatives based on their performance with respect to an ideal commonality/variety trade-off determined by a company's particular competitive focus, and guides designers towards a more desirable trade-off between commonality and variety in an existing product family. Two necessary supporting pieces for developing the PFEG are also proposed. One piece is the development of commonality and variety indices to quantitatively capture the degree of commonality and variety in a product family and its functions and components. We introduce two sets of commonality and variety indices–the CDI (commonality versus diversity index) for commonality (CDI_C) and variety (CDI_V), and the CMC (comprehensive metric for commonality) for commonality (CMC_C) and variety (CMC_V)–to achieve this. The other supporting piece is the development of a quantitative representation of the ideal trade-off between commonality and variety in a product family, known as the commonality/variety trade-off angle α, based on the elements that characterise a company's competitive focus and their industry-wide competitors. A linear regression model is used to link the qualitative competitive focus to a quantitative engineering perspective, and then to estimate the ideal trade-off angle. The commonality/variety trade-off angle can then be applied to the PFEG to help designers evaluate a product family or compare product family design alternatives. Most importantly, the PFEG is not just the graph of the two sets of indices; it is the representation of the commonality/variety trade-off relative to the desired competitive focus. Four families of power tools are used to illustrate how the computation of such indices supports product family design evaluation in the PFEG. In this paper, we only use the CDI in the example application, but the CMC can be computed using the same approach.     

Effective Product Family Design Using Physical Programming

In response to today's highly competitive global marketplace, many companies are utilizing product families - groups of related products derived from a product platform - to maintain economies of scale while satisfying a variety of customer requirements. This paper focuses on scale-based product families and presents a new single-stage approach for simultaneously optimizing a product platform and the resulting family of products based on one or more scaling variables - variables that are used to instantiate the product platform by "stretching" or "shrinking" it in one or more dimensions to satisfy a variety of customer requirements. The proposed approach is also unique in that it employs the Physical Programming method, enabling designers to formulate the product family optimization problem in terms of physically meaningful terms and parameters. The design of a family of ten universal electric motors is used as an example to benchmark the effectiveness of the proposed approach against previous results. While the emphasis in this paper is on the design method rather than the results per se , performance gains are achieved in the motor family by using the proposed single-stage approach and Physical Programming.     

Minimizing Cost of Multiple Response Systems by Probabilistic Robust Design

In the design of products and processes, a methodology that helps adjust the means and tolerances of the design variables to both improve conformance and lower costs is a valuable tool. In this paper, the cost of a product at the manufacturing stage is the sum of the production cost, which includes known costs for tolerances, inspection, and so forth, plus any cost for scrapping or reworking products that do not conform to specifications. We call this added cost the so-called loss-of-quality cost and evaluate it as the probability of nonconformance (of the responses) times established scrap or rework costs. Accurate probability estimates are obtained using full distributions, limit-state functions, and first-order reliability methods (FORM). Probabilities are adjusted through probabilistic robust design. The production costs and the loss-of-quality cost are competing costs and thus their sum provides a single objective function in terms of the means and tolerances of the design variables. The need to satisfy the equations in both the product model and the workings of FORM introduce nonlinear equality constraints. The minimum of the objective function, hence the minimum cost, is obtained by solving a nonlinear, constrained, optimization problem. The design of a mechanism for controlling a grating diffraction spectroscope serves as a case study using the presented method. A minimum cost, the probability of conformance, and the respective parameter settings are found for both complete and zero inspection strategies.     

Optimal accelerated life tests under a cost constraint with non-uniform stress durations

ABSTRACT

To collect the information about the lifetime distribution of a product, a standard life testing method at normal working conditions is impractical when the product has a substantially long lifespan. Accelerated life testing solves this problem by subjecting the test units at higher stress levels for quicker and more failure data. Due to constrained resources in practice, several decision variables such as the allocation proportions and stress durations must be determined carefully at the design stage in order to run an accelerated life test efficiently. These decision variables directly affect the experimental cost as well as the estimate precision of the parameters of interest. This article investigates these optimal decision variables based on several well-known optimality criteria under the constraint that the total experimental cost does not exceed a pre-specified budget. A general scale family of distributions is considered for the underlying lifetimes to accommodate different lifetime models at different stress levels for flexible modeling. The constant-stress and step-stress accelerated life tests are then studied in detail with linearly decreasing stress durations as the stress level progresses. Under the identical budget constraint, the efficiencies of these two stress loading schemes are compared using two case studies.     

A Method for Architecting Product Platforms

Consider a group of products sharing common parts and assemblies. The products in question we call a product family, and the common elements, the platform. In this paper, we present a method for designing product platforms and the derived family that takes into consideration both the technical performance requirements as well as the cost of the product family. The design of a platform-based product family is formulated as a general optimization problem in which the advantages of designing a common platform must be balanced against the constraints of the individual product variants and constraints of the family as a whole. This optimization approach forms the basis for a practical implementation as an interactive, team-based negotiation model for designing a family of interplanetary spacecraft based on a common platform. The approach is used to consider and specify different subsystems that could be made common to all the missions. It is also used to evaluate the impact of those platform design decisions on the performance of the product family, and thus be able to select from among feasible platform designs.     

云环境下大规模定制中资源配置研究

针对传统大规模定制生产模式无法满足日益个性化的产品市场变化,导致产品无法形成生产批量,在生产过程中增加成本和时间的问题,结合云制造的背景环境,提出云环境下大规模定制产品的生产模式,并通过建立包含生产总时间、生产总成本和产品总质量的多目标优化函数模型,使用NSGA-Ⅱ算法对所建模型进行求解,对模式运行中的资源配置问题进行研究。最后通过航模发动机进行算例验证,证明所建模型可以得到解决云环境下大规模定制产品生产过程中资源优化配置问题的最优生产方案。     

Flexible product platforms: framework and case study

Customization and market uncertainty require increased functional and physical bandwidth in product platforms. This paper presents a platform design process in response to such future uncertainty. The process consists of seven iterative steps and is applied to an automotive body-in-white where 10 out of 21 components are identified as potential candidates for embedding flexibility. The paper shows how to systematically pinpoint and value flexible elements in platforms. This allows increased product family profit despite uncertain variant demand, and specification changes. We show how embedding flexibility suppresses change propagation and lowers switching costs, despite an increase of 34% in initial investment for equipment and tooling. Monte Carlo simulation results of 12 future scenarios reveal the value of embedding flexibility.

Optimal platform design using non-dominated sorting genetic algorithm II and technique for order of preference by similarity to ideal solution; application to automotive suspension system

Unlike conventional approaches where optimization is performed on a unique component of a specific product, optimum design of a set of components for employing in a product family can cause significant reduction in costs. Increasing commonality and performance of the product platform simultaneously is a multi-objective optimization problem (MOP). Several optimization methods are reported to solve these MOPs. However, what is less discussed is how to find the trade-off points among the obtained non-dominated optimum points. This article investigates the optimal design of a product family using non-dominated sorting genetic algorithm II (NSGA-II) and proposes the employment of technique for order of preference by similarity to ideal solution (TOPSIS) method to find the trade-off points among the obtained non-dominated results while compromising all objective functions together. A case study for a family of suspension systems is presented, considering performance and commonality. The results indicate the effectiveness of the proposed method to obtain the trade-off points with the best possible performance while maximizing the common parts.     

A framework for designing balanced product platforms by estimating the versatility of components

Mass customisation is a common trend in many industries, and the platform-based product family strategy is a widely used method for this purpose. While the platform strategy can reduce the cost of variety by sharing common assets such as components and production processes, it has the risk of losing market share owing to its limitation on diversity. A balance between commonality and variety needs to be achieved when designing platforms that are both efficient and effective. In this paper, we focus on developing a platform that is versatile for highly effective differentiation to increase market share, incorporating the preferences of customers for different kinds of diversity. By distinguishing preferred and non-preferred diversity and ignoring the unnecessary need for differentiation, a platform designer can increase commonality without loss of market share. Under the assumption that a versatile platform is composed of versatile components, we estimate the versatility of components to identify the versatile ones. The estimation method consists of two phases: the market analysis phase, for identifying which specifications are preferred to be differentiated, and the product analysis phase, for assessing how much impact the differentiation may have on the component. A high versatility score indicates that the corresponding component is suitable for being platformed since it is not likely to be changed to increase market share. At the same time, a low versatility score provides a clue for improving the product architecture. The proposed method was applied to computer mouse design and yielded a reasonable platform plan.     

Activity-Based Costing: A Manufacturing Management Decision-Making Aid

ABSTRACT

Serious distortion can occur in manufacturing product costing systems that use a single volume-related base (like direct labor hours) to assign overhead costs to products. Activity-based costing (ABC) assumes that activities consume resources, and products consume activities; hence, ABC makes activities its focus. Costs are traced from activities to products based on demand for the focus activity (or activities). Conventional cost systems are imprecise due to the lack of detail in the allocation of overhead. In contrast, ABC provides more accurate product cost because it captures many dynamic variables while assigning overhead costs through defined activities.