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.     

On the valuation of goods and selection of the best design alternative

A platform is the set of elements and interfaces that are common to a family of products. In this paper, the design of a platform-based product family is formulated as an optimization problem. This optimization is then transformed into a two-step process amenable to industrial product design processes. The first step involves designing the technical aspects of the product family, optimizing an objective (or a set of objectives) subject to technical constraints, with external uncertain factors fixed. We have previously presented such a method for designing product families based on platforms that optimizes performance and cost metrics, using variables and a system model. That approach allows a team of engineers to design and evaluate candidate platforms, given perfect understanding of the designs and requirements. The second step is to quantify the value to the firm for each identified design alternative, while here accounting for external uncertain factors of the product family development. In this paper we present a model to perform this second step of the overall approach. Real options concepts are introduced to model the risks and delayed decision benefits present during product development due to uncertainty in technologies, funding, etc. We develop a quantitative measure of the value to the company for different family designs, and apply it to select the most appropriate design from the possible alternatives. An application to the design of platform-based families of spacecraft is shown. Electronic Publication     

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 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.     

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.     

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.     

Platform design variable identification for a product family using multi-objective particle swarm optimization

The variability of products affects customers’ satisfaction by increasing flexibility in decision-making for choosing a product based on their preferences in competitive market environments. In product family design, decision-making for determining a platform design strategy or the degree of commonality in a platform can be considered as a multidisciplinary optimization problem with respect to design variables, production cost, company’s revenue, and customers’ satisfaction. In this paper, we investigate evolutionary algorithms and module-based design approaches to identify an optimal platform strategy in a product family. The objective of this paper is to apply a multi-objective particle swarm optimization (MOPSO) approach to determine design variables for the best platform design strategy based on commonality and design variation within the product family. We describe modifications to apply the proposed MOPSO to the multi-objective problem of product family design and allow designers to evaluate varying levels of platform strategies. To demonstrate the effectiveness of the proposed approach, we use a case study involving a family of General Aviation Aircraft. We show that the proposed optimization algorithm can provide a proper solution in product family design process through experiments. The limitations of the approach and future work are also discussed.     

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.     

基于仿真的制冷产品质量预测与优化

产品质量的预测与优化是产品设计的关键。提出了基于仿真的制冷产品质量预测与优化方法,将现实中存在的不确定因素和设计参数的波动以概率分布的形式输入制冷系统仿真模型,并结合随机模型方法实现了在设计阶段对产品质量进行预测。同时提出了一种获取产品质量损失函数的新方法,即采用中心复合试验设计与蒙特卡洛模拟结合,获得设计能力指数随部件容差变化的响应面模型,将该模型作为约束条件,以成本最低为目标,对部件容差进行优化后显著提高了产品的质量与经济性。     

Development of a production cost estimation framework to support product family design

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), which 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.     

基于优化的产品平台参数规划方法

 为满足客户化和全球竞争的需求,企业要实现大规模定制(mass customization,MC).基于公共产品平台的产品族设计是实现大规模定制的一种有效方式,而平台规划是面向产品族设计方法学的核心内容,也是目前研究中的一个热点问题.基于模型参数的平台设计是其方法之一.针对基于一系列标准可变参数的产品平台,用优化方法对产品平台参数进行规划,以满足各种客户需求.该规划方法无需事先人为指定,而是在满足客户需求的前提下,尽可能提高产品族中设计变量的共性,从而确定最好的产品平台的公共参数及其最优值,以及个性参数及其变化值,并以带式输送机为例验证了该方法.     

Modular product family design: Agent-based Pareto-optimization and quality loss function-based post-optimal analysis

The advent of mass customization and increased manufacturing competition has necessitated that many companies offer platform-oriented multiple product variants. Various design strategies such as Design for Variety and product family design have become critical in this respect. This paper provides a two-step approach to tackle the modular product family design problem. The first step performs a multi-objective optimization using a multi-agent framework to determine the Pareto-design solutions for a given module set. The proposed multi-agent framework is new and has built in flexibility to handle various constraints such as module compatibility during the optimization process. The second step performs post-optimization analysis that includes a novel application of the quality loss function to determine the optimal platform level for a related set of product families and their variants. The proposed method is applied to a product family design example to demonstrate its validity and effectiveness.     

An integrated approach to product family redesign using commonality and variety metrics

Redesigning a product family entails carefully balancing the trade-offs between commonality and differentiation that are governed by the underlying platform architecture. Numerous metrics for commonality and variety exist to support product family and product platform design; however, rarely are they used in concert to help redesign platforms and families of products effectively. In this paper, we introduce an integrated approach that uses multiple product family metrics to establish an effective platform redesign strategy. Specifically, we present a detailed procedure to integrate the generational variety index, product line commonality index, and design structure matrix to prioritize components for redesign based on variety and commonality needs in a family of products. While all three of these tools exist in the literature and have been used extensively to support product family design, the novelty in our work lies in their integration to establish a redesign strategy for platform architectures that achieves a better balance between the commonality and variety within a product family. To demonstrate the proposed approach, case studies involving two generations of wireless computer mice and two families of dishwashers are presented. Ongoing and future work is also discussed.     

Module-scale-based product platform planning

Planning product platform by taking full advantage of existing product resources is an effective tactic for mass customization, which can help not only keep market share, improve production batch, but also enhance customization. In this paper, we investigate a methodology for achieving the goal. As a basis, product platform is defined as a set of modules, platform parameters and individual parameters. Then, the steps of product platform planning are given. First, product modules are identified; second, a strategy of choosing platform parameters is investigated based on considering the influence of customizing individual parameters upon the activities, such as design, die, machining, assembly, service and management, in all product life cycle; third, an optimization model is employed to determine the value of platform parameters whose carriers are the modules. Finally, the proposed methodology is effectively demonstrated in an instance of motorcycle-hydraulic-disk brake platform planning.     

Product family platform selection using a Pareto front of maximum commonality and strategic modularity

Product family design offers a cost-effective solution for providing a variety of products to meet the needs of diverse markets. At the beginning of product family design, designers must decide what can be shared among the product variants in a family. Optimal design formulations have been developed by researchers to find one optimal component sharing solution based on commonality, cost or technical performance of a product family. However, these optimization methods may not be able to apply in consumer product design because some metrics (e.g., visual appeal and ergonomics) of a consumer product cannot be formulized. In this paper, we suggest a tradeoff between commonality and the quality of the modular architecture in product family platform selection. We introduce a method for designers to identify multiple component sharing options that lie along a Pareto front of maximum commonality and strategic modularity. The component sharing options along the Pareto front can be evaluated, compared, and further modified. We demonstrate the method using a case study of product family platform selection of high-end and low-end impact drivers and electric drills. In the case study, the quality of the modular architecture is evaluated using a design structure matrix (DSM) for each of product variants. Three architectures along the Pareto front with maximum commonality, optimal modularity, and a balanced solution of the two metrics are highlighted and further examined to validate the effectiveness of our method.     

From user requirements to commonality specifications: an integrated approach to product family design

Many companies design families of products based on product platforms that enable economies of scale and scope while satisfying a variety of market applications. Product family design is a difficult and challenging task, and a variety of methods and tools have been created to support this platform-based product development. Unfortunately, many of these methods and tools have been developed—and consequently exist—in isolation from one other. In this paper, we introduce an approach to integrate several of these disparate tools into a framework to translate user needs and requirements into commonality specifications during product family design. The novelty of the approach lies in how we integrate the market segmentation grid, Generational Variety Index (GVI), Design Structure Matrix (DSM), commonality indices, mathematical modeling and optimization, and multi-dimensional data visualization tools to identify what to make common, what to make unique, and what parameter settings are best for each component and/or subsystem in the product family. The design of a family of unmanned ground vehicles (UGVs) demonstrates the proposed approach and highlights its benefits and limitations.     

Assessing and improving commonality and diversity within a product family

At a time when product differentiation is a major indicator of success in the global market, each company is looking to offer competitive and highly differentiated products. This differentiation issue is restricted by the design of platform-based products that share modules and/or components. It is not easy to differentiate products in a market that is often overwhelmed by numerous options. A platform-based approach can be risky because competition in the global market can become an internal competition among similar products within the family if there is not enough differentiation in the family. Thus, the goal for the product platform is to share elements for common functions and to differentiate each product in the family by satisfying different targeted needs. To assess commonality in the family, numerous indices have been proposed in the literature. Nevertheless, existing indices focus on commonality and reflect an increase in value when commonality increases but do not positively reflect an increase in the value as a result of diversity; hence, the commonality versus diversity index (CDI) is introduced in this paper to assess the commonality and diversity within a family of products or across families. The CDI has variable levels of depth analysis to help designers design or improve the product family. Two case studies using single-use cameras and power tool families highlight the usefulness of this new index.     

Tolerance synthesis by a new method for system reliability-based optimization

The performance–cost ratio of a product may be significantly improved by a better tolerance assignment. Current practice guided by experience usually leads to a conservative and costly design. Because yield in mechanical engineering is analogous to system reliability in structural engineering, this article applies a system reliability-based optimization formulation to tolerance synthesis and presents a sequential approximate programming method. This method is an extension of the approach for the optimization with component reliability constraints. Two often-quoted examples are analyzed in detail to illustrate its effectiveness and a strategy for tolerance assignment is recommended.     

INTEGRATING PRODUCT DESIGN AND MANUFACTURING: A GAME THEORETIC APPROACH

One approach for increasing the quality of a product and the efficiency of its realization is to pay attention to the integration of product design and manufacturing. An integrated product realization process must be able to accommodate sequential stages of activity along a product realization time-line, independent information flow between stages, and trade-offs between various activities and factors. In this paper, a decision-based approach that is consistent with such characteristics is explored. This approach is anchored in game theory and a decision construct, namely, the Compromise Decision Support Problem. The merging of these two elements provides a mathematical and systematic basis for coordinating product design and manufacturing. This approach is illustrated via an example, namely, the redesign of a common component platform for a family of absorber-evaporator modules for absorption refrigeration, in order to reduce their costs and production times. The focus is on the method rather than the results per se.     

The Design and Analysis of 2 k—P × s Prototype Experiments

Israel Prototype testing and experimentation play a key role in the development of new products. It is common practice to build a single prototype product and then test it at specified operating conditions. It is often beneficial, however, to make several variants of a prototype according to a fractional factorial design. The information obtained can be important in comparing design options and improving product performance and quality. In such experiments the response of interest is often not a single number but a performance curve over the test conditions. In this article we develop a general method for the design and analysis of prototype experiments that combines orthogonal polynomials with two-level fractional factorials. The proposed method is simple to use and has wide applicability. We explain our ideas by reference to an experiment reported by Taguchi on carbon monoxide exhaust of combustion engines. We then apply them to an experiment on a prototype fluid-flow controller.