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.     

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.     

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.     

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.     

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.     

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.     

An uncertain multidisciplinary design optimization method using interval convex models

This article proposes an uncertain multi-objective multidisciplinary design optimization methodology, which employs the interval model to represent the uncertainties of uncertain-but-bounded parameters. The interval number programming method is applied to transform each uncertain objective function into two deterministic objective functions, and a satisfaction degree of intervals is used to convert both the uncertain inequality and equality constraints to deterministic inequality constraints. In doing so, an unconstrained deterministic optimization problem will be constructed in association with the penalty function method. The design will be finally formulated as a nested three-loop optimization, a class of highly challenging problems in the area of engineering design optimization. An advanced hierarchical optimization scheme is developed to solve the proposed optimization problem based on the multidisciplinary feasible strategy, which is a well-studied method able to reduce the dimensions of multidisciplinary design optimization problems by using the design variables as independent optimization variables. In the hierarchical optimization system, the non-dominated sorting genetic algorithm II, sequential quadratic programming method and Gauss–Seidel iterative approach are applied to the outer, middle and inner loops of the optimization problem, respectively. Typical numerical examples are used to demonstrate the effectiveness of the proposed methodology.     

Designing scalable product families by the radial basis function–high-dimensional model representation metamodelling technique

Product family design is cost-efficient for achieving the best trade-off between commonalization and diversification. However, for computationally intensive design functions which are viewed as black boxes, the family design would be challenging. A two-stage platform configuration method with generalized commonality is proposed for a scale-based family with unknown platform configuration. Unconventional sensitivity analysis and information on variation in the individual variants’ optimal design are used for platform configuration design. Metamodelling is employed to provide the sensitivity and variable correlation information, leading to significant savings in function calls. A family of universal electric motors is designed for product performance and the efficiency of this method is studied. The impact of the employed parameters is also analysed. Then, the proposed method is modified for obtaining higher commonality. The proposed method is shown to yield design solutions with better objective function values, allowable performance loss and higher commonality than the previously developed methods in the literature.     

Modularity analysis and commonality design: a framework for the top-down platform and product family design

With a highly fragmented market and increased competition, platform-based product family design is recognised as an effective method for constructing a product line that satisfies diverse customer demand while keeping design and production cost- and time-effective. Recognising the need for modularity and commonality in platform development, this paper presents a systematic framework to assist in implementing top-down platform and product family design, which aims to achieve system-level modularity for variety generation, and rationalise the commonality configuration for module instantiation. In the first phase of platform development, a robust and flexible product family architecture is constructed to accommodate variations by analysing the external varieties of the generic product architecture, and provide a modularity design space, wherein the design tasks are further decomposed into module instantiation. The second phase of detailed platform development aims to enhance commonality in terms of engineering efficiency by coordinating with the back-end product realisation stage. A tractable optimisation method is used to capture and resolve the trade-off between commonality configuration and individual product performance. A family of power tool designs is used to demonstrate the potential and feasibility of the proposed framework at the system level and detailed design stages.     

Radial basis functional model for multi-objective sheet metal forming optimization

Fracture and wrinkling are two major defects in sheet metal forming and can be eliminated via an appropriate drawbead design. This article proposes to adopt a multi-objective particle swarm optimization (MOPSO) approach, which differs from traditional multi-objective optimization with construction of a single cost function. MOPSO shows a certain advantage over other single cost function or population-based algorithms. While radial basis function (RBF) has shown considerable promise in highly non-linear problems, there has been no report in sheet metal forming design. Here RBF is attempted to establish the metamodels for fracture and wrinkling criteria in sheet metal forming design. In this article, a sophisticated automobile inner stamping case is exemplified, which demonstrated that RBF provides a better surrogate accuracy and MOPSO is more effective than the other methods studied. The use of RBF driven MOPSO procedure significantly improved the formability and can be recommended for sheet metal process design.     

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.     

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.     

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     

Improving cost effectiveness in an existing product line using component product platforms1

Previously, we introduced a new method for improving commonality in a highly customised, low volume product line using component product platforms. The method provides a bottom-up platform approach to redesign family members originally developed one-at-a-time to meet specific customer requirements. In this paper, we extend the method with an activity-based costing (ABC) model to specifically capture the manufacturing costs in the product line, including the cost associated with implementing a platform strategy. The valve yoke example is revisited in this paper, the customised ABC model is defined, two design strategy alternatives are addressed, and the new method is used to determine which alternative is better at resolving the trade-off between commonality, total cost, and product performance. The proposed method shows promise for creating a product platform portfolio from a set of candidate component platforms that is most cost-effective within an existing product line. The proposed method allows for arbitrary leveraging as it does not rely solely on the traditional vertical, horizontal, or beachhead strategies advocated for the market segmentation grid, and this is especially beneficial when applied to an existing product line that was developed one-at-a-time time such that artefact designs are inconsistent from one to another.     

基于游客感知服务质量的多目标旅游产品优化设计

旅游产品的优化设计问题是当今旅游企业运营管理中最重要的内容之一。从游客感知服务质量的角度针对旅游服务的六大要素以及实现要素的备选方案进行研究。通过引入期望服务质量和实际感知服务质量概念,提出了游客满意度最大、优化设计成本最小和旅游景区生态环境最优的单目标旅游产品优化设计模型,并且分析目标之间的权重,最终确定多目标的旅游产品优化设计模型。最后,通过一个亲子游产品优化设计的实际案例,对多目标模型的有效性进行了验证,为旅游服务企业在旅游产品设计方面提供更加可行的决策。     

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.     

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.     

The comparison of multi-objective particle swarm optimization and NSGA II algorithm: applications in centrifugal pumps

In the present study, multi-objective optimization of centrifugal pumps is performed in three steps. In the first step, efficiency (η) and the required net positive suction head (NPSHr) in a set of centrifugal pumps are numerically investigated using commercial software. Two meta-models based on the evolved group method of data handling (GMDH) type neural networks are obtained in the second step for modeling of η and NPSHr with respect to geometrical design variables. Finally, using the obtained polynomial neural networks, a multi-objective particle swarm optimization method (MOPSO) is used for Pareto-based optimization of centrifugal pumps considering two conflicting objectives, η and NPSHr. The Pareto results of the MOPSO method are also compared with those of a multi-objective genetic algorithm (NSGA II). It is shown that some interesting and important relationships as useful optimal design principles involved in the performance of centrifugal pumps can be discovered by Pareto-based multi-objective optimization of the obtained polynomial metamodels representing η and NPSHr characteristics.     

Web-based configuration design system for product customization

In mass customization, web-centric knowledge-based configuration systems have become an important tool to help customers configure products that satisfy their different needs and the complex configuration constraints of a product family (PF). An effective knowledge representation scheme and the associated reasoning mechanisms are essential for the success of these systems. This paper presents an object-oriented approach that integrates the functional and structural models of a PF with design process knowledge. Invasion-based search algorithms are proposed to deal with different situations in product customization and heuristic knowledge is introduced in these algorithms to improve the search efficiency. Optimization models have been constructed in terms of customers’ preferences to provide them with the highest satisfaction in product customization. Based on the representation scheme and reasoning algorithms, a web-based configuration system prototype is developed to support product customization. An example of a bicycle family is used as a study case and described in details.     

Topology optimization of structures under multiple loading cases with a new compliance–volume product

This article proposes a new topology optimization method for the design of structures under multiple loading cases. The design is formulated as a multi-objective optimization problem by minimizing a new compliance–volume product, which optimizes the overall stiffness and volume simultaneously to avoid the empirical decision on design constraints and obtain an even lower structural volume. A normalized exponential weighted criterion (NEWC) method is included in the multi-objective optimization problem for the capture of the entire Pareto frontier. A weight evaluation method, in terms of the fuzzy multiple-attribute group decision-making (FMAGDM) theory, is incorporated in the problem to evaluate the weights of the objectives and guarantee the optimal design in an acceptable level. The solid isotropic material with penalty (SIMP) method is used to represent the dependence of elemental densities on material properties. Three typical numerical examples are employed to show the effectiveness of the proposed method.