Interweaving genetic programming and genetic algorithm for structural and parametric optimization in adaptive platform product customization

An adaptive product platform offers high customizability for generating feasible product variants for customer requirements. Customization takes place not only to product platform structure but also to its relevant parameters. Structural and parametric optimization processes are interwoven with each other to achieve the total optimality. This paper presents an evolutionary method dealing with interwoven structural and parametric optimization of adaptive platform product customization. The method combines genetic programming and genetic algorithm for handling structural and parametric optimization, respectively. Efficient genetic representation and operation schemes are carefully adapted. While designing these schemes, features specific to structural and parameter customization are considered for the simplification of platform product management. The experimental results show that the performance of the proposed algorithm outperforms that of the tandem evolutionary algorithm in which a genetic algorithm for parametric optimization is totally nested in a genetic programming for structural optimization.     

Mapping Product Design Specification for Mass Customization

Mass customization is an emerging field in manufacturing research community where customer satisfaction is achieved by complying with exact customer requirements at mass production efficiencies. Product varieties have mostly failed in the aspect of satisfying customer requirements, since knowing beforehand exactly what customer needs is beyond the scope of any manufacturing or marketing paradigm. So design to order and build to order is widely talked in the industry to capture heterogeneous market segments. In order to achieve the challenging task of customization at mass production efficiencies, a tight integration of the various entities involved is necessary. Gathering customer requirements, finalizing product design and eventual manufacturing need to be seamlessly integrated to achieve mass production efficiencies. Product designs are classified into customizable product platform families, and then searched based on customer requirements to identify the most conformal design family. Finally the design parameter transport is carried out from customer domain to product domain. Eventually a valid and realizable product specification is generated. The paper will address these issues of classification, selection and ultimately the mapping of parameters. A methodology to classify the product design information, which can easily accommodate design variations based on product platform architecture is proposed. Further, adaptive design customization, which relates most design parameters with the scalable platform design parameters using matrix formulation, is discussed. The proposed design parameter classification and adaptive synthesis of design parameters is applied to a spring design example.     

Applying fuzzy multiple attributes decision making for product configuration

Mass customization (MC) is an emergent concept in industry intended to provide customized products through flexible processes in high volumes and at reasonably low costs. The method of configuration is one of important ways to realize quickly product customization. But, in business, particularly through the Internet, a customer normally develops in his mind some sort of ambiguity, given the choice of similar alternative products. This paper proposes a new approach to product configuration by applying the theory of fuzzy multiple attribute decision making (FMADM), which focus on uncertain and fuzzy requirements the customer submits to the product supplier. The proposed method can be used either in the product data management system or e-commerce websites, with which it is easy for customers to get his preferred product according to the utility value with respect to all attributes. Finally, the digital camera is taken as an example to further verify the validity and the feasibility of the proposed method.     

面向MC的客户群体倾向模型

面向大规模定制生产，建立了客户倾向模型，通过关联分析法量化市场调研和客户需求，采用最大树模糊聚类法进行基于属性重要度的客户群体划分和市场细分，获取客户群体消费倾向，为客户需求的工程特征转换、进行产品簇规划提供数学准备和数据支持。     

Concurrent product configuration and process planning: Some optimization experimental results

In nowadays industrial competition, optimizing concurrently the configured product and the planning of its production process becomes a key issue in order to achieve mass customization development. However, if many studies have addressed these two problems separately, very few have considered them concurrently. We therefore consider in this article a multi-criteria optimization problem that follows an interactive configuration and planning process. The configuration and planning problems are considered as constraint satisfaction problems (CSPs). After some recalls about this two-step approach, we propose to evaluate a recent evolutionary optimization algorithm called CFB-EA (for constraint filtering based evolutionary algorithm). CFB-EA, specially designed to handle constrained problems, is compared with an exact branch and bound approach on small problem instances and with another evolutionary approach carefully selected for larger instances. Various experiments, with solutions spaces up to 10¹⁷, permit us to conclude that CFB-EA sounds very promising for the concurrent optimization of a configured product and its production process.     

Mass production of tooling product families via modular feature-based design to manufacturing collaboration in PLM

Product Lifecycle Management (PLM) is recognized as one of the most effective approaches for better, fast and cheaper product development and management. Mass customization is one of the key technologies in PLM to provide tailored product to end customers with the cost of mass production. Characterized by short production lead-time and dynamic customer requirements with low batch size and high variety, tooling product families are facing the challenge of high production cost. New technology with modular feature-based design to manufacturing collaboration to satisfy the needs of mass production with low cost in tooling industry is developed in this study. A corresponding prototype system is demonstrated to show the efficiency of the technology developed.     

Responsive consistency restoration in interactive product configuration by content-addressable memory

With the context of individualized product design in mass customization, the practice of product configuration is transformed from traditional unidirectional process into bidirectional design interactions. In this interactive configuration manner, maintaining the consistency of configuration assignments, often referred to as consistency restoration, is one of the primary issues which should be addressed. The task of consistency restoration faces two great challenges: the uncertainty and individualized flexibility of customer requirements. The uncertainty turns problem dynamic and deteriorates the computational complexity of existing consistency restoration methods. The individualized flexibility turns the task of consistency restoration ill-structured. Consequently, these two characteristics increase the response time in interactive configuration and make companies face the challenge of ‘customization-responsiveness squeeze’. To leverage this problem, this paper proposes a responsive approach to facilitate the task of consistency restoration. A methodology based on content-addressable memory (CAM) is established, which compiles a CSP-based consistency restoration into a memory recalling process and automatically corrects the incompleteness and inconsistency within the memory. Specific orientation mechanism based on customer preference is proposed to introduce customer flexibility into CAM model. The resulting oriented-CAM method is demonstrated by a case study and the performance and responsiveness are analyzed.     

支持大批量定制的产品配置设计系统的研究

针对大批量定制生产的特点，提出基于产品功能结构单元的产品配置模板来完成对客户配置需求的快速响应，给出了产品配置模板的信息模型和配置求解策略．由于机械产品结构的复杂性，引入配置设计知识的混合表达方法以适应不同产品设计类型的要求．最后给出基于产品配置模板信息模型的配置设计系统的实例．     

基于OCL的配置工具研究与实现

大规模定制是现代工业发展的趋势。它不但具有大规模生产的低成本优势,而且能够满足用户的个性化需求。产品配置是实现大规模定制的重要方法,实现产品配置的核心是配置工具。GPCT（Generic Product Configuration Tool）是河北工业大学创新设计研究所开发的领域无关的配置工具。它以UML表示产品配置模型,以OCL文法表达产品部件间的约束。给出了GPCT的约束维护和验证方法,并以数控立式磨床为例,介绍了GPCT的实际应用。     

Integrated Vehicle Configuration System—Connecting the domains of mass customization

Configuration design for mass customized vehicles necessitates the coordination of customer requirements, product characteristics, production processes, and logistics networks, in order to achieve rapid response to customer orders. Existing product configurators are mainly used as sales tools, and fail to account for the requirements of the entire customer order fulfillment process. In this regard, this paper proposes an Integrated Vehicle Configuration System (IVCS) to facilitate customer order processing based on information from multiple domains in a mass customization environment. An IVCS business model is proposed to incorporate the decision factors for configuration design related to different planning stages. The business model is supported by a comprehensive ontology framework, which enhances communications between different stakeholders involved in the order fulfillment process. The configuration approach is based on combinations of selective and generative rules and can be integrated with existing ERP systems. It also provides mechanisms to handle configuration rules that allow users to convert soft preferences into product specifications, bill-of-materials, and, furthermore, into logistics configurations. An example of a computerized configuration system showcases the process from customer engineering to design and production.     

A methodology of developing product family architecture for mass customization

Mass customization, aiming at delivering an increasing product variety that best serves customer needs while keeping mass production efficiency, has recently received numerous attention and popularity in industry and academia alike. This paper presents a methodology of developing product family architecture (PFA) to rationalize product development for mass customization. Systematic steps are developed to formulate a PFA in terms of functional, technical and physical views. The diverse needs of customers are matched with the capabilities of a firm through systematic planning of modularity in three consecutive views. The development of a PFA provides a unifying integration platform to synchronize market positioning, commonality employment and manufacturing scale of economy across the entire product realization process. A case study in an electronics company is reported to illustrate the potential and the feasibility of PFA methodology.     

大规模定制下基于本体的服务产品配置研究*

为了研究服务产品大规模定制的实现,探讨了服务产品大规模定制的实现机理和关键技术,指出模块化设计对服务产品族及服务产品平台的重要性。在服务产品模块化设计的基础上,为了提高服务产品配置知识的共享性和重用性,提出了一般服务产品配置的模型和概念,结构化了服务产品配置的构件和模块,建立了服务产品配置本体。采用网络本体语言OWL形式化服务产品配置的结构知识,采用语义网规则语言SWRL编码服务产品配置的约束知识,并分别映射到JESS推理系统的知识库和规则库中,使用JESS推理机执行推理过程,产生配置结果。为说明该方法的     

Progressive sharing of modules among product variants

Recent market transition from mass production to mass customization forces manufacturers to design products that meet individual requirements. In order to address the high cost of this practice, manufacturers develop product families with a common platform, whose variants are designed to meet different customer demands. Parallel to this transition, the dynamics of the market forces designers to develop products composed of modules that are standardized as much as possible across products, thus can be more resilient than complete designs in a changing world.Starting from an original set of different components, our method designs a modular common platform and additional modules, shared by subsets of the designs, from which variants are composed.We applied the method to the layout design of a set of products. Consequently, the geometric aspect of the product family optimization is emphasized, but functional aspects related to the product features and to customer needs are also addressed due to their manifestation in the layout. The design search space is explored using shape grammar rules that alter component geometry and therefore, functionality. The search for optimal design is performed using simulated annealing. Given different objective formulations or parameter settings, the method can be used to explore the solution space. A simple example problem demonstrates the feasibility of the method.     

面向绿色设计的产品族规划

以实现大规模定制模式下的绿色设计为目标,将环境影响因素纳入产品族规划的考虑范畴,从拆卸性能、回收性能、环境影响以及经济性能4个方面对产品族内部结构单元的绿色性能进行量化分析.在对量化结果进行相关性分析的基础上,运用模糊聚类的方法对产品族结构单元实例进行归类处理,筛选出满足客户绿色性能需求的实例参与配置设计,给出一种面向绿色设计的产品族规划方法.最后以自动豆浆机产品族的规划为例,对文中方法进行了验证与分析.     

基于产品感性定制模型的顾客协同设计系统

为使产品定制模型更加适合缺少相关领域专业知识的大众消费者,建立了基于感性工学的产品感性定制模型.引入配件感性性能指数、产品感性性能矩阵对产品感性性能进行量化.使用层次分析法实现了求解与顾客对产品感性性能需求对应的产品工程配置的方法.并应用产品感性定制模型,构建了基于Web和虚拟现实技术的顾客协同设计系统.     

Mass customization design of engineer-to-order products using Benders’ decomposition and bi-level stochastic programming

Leveraging product differentiation and mass production efficiency in mass customization basically entails a configure-to-order paradigm. In the engineer-to-order (ETO) business, however, companies build unique products in response to ‘foreseeable’ customer specifications. The key challenge of ETO mass customization lies in the complexity of accommodating future design changes when customers are involved in customizing design specifications. This paper proposes a two-stage, bi-level stochastic programming framework to tackle ETO mass customization. At the first stage, product platform configuration is integrated with production reconfiguration, which is formulated as a shortest path problem with resource constraints (SPPRC) to optimize production delays within the capabilities of the process platform. Benders’ decomposition algorithm is applied to solve this optimal configuration problem owing to its high computational efficiency. The second stage scrutinizes the optimal configuration resulting from the first stage for scaling optimization of design parameters (DPs) for each module. All DPs are differentiated by standard or customizable DPs. A bi-level stochastic program is implemented to leverage conflicting goals between the producer (leader) and consumer (follower) surpluses. As a result, ETO customization design is anchored with optimal values of standard DPs and optimal value ranges of customizable DPs. A case study of ship engine and power generator ETO design is presented, demonstrating the feasibility and potential of the ETO mass customization framework.     

客户驱动的大批量定制模型研究

针对具有模块化特性的产品大批量定制问题，提出了一种以客户驱动为基础的大批量定制模型．通过客户驱动参数描述、参数映射、模块特性参数编码规则的建立，得出定量描述的数学模型，从而使产品定制问题转变为模块的组合优化问题．该模型正在汽车产品的客户定制中进行实验研究．     

Multiple platforms design and product family process planning for combined additive and subtractive manufacturing

Industry 4.0 promotes the utilization of new exponential technologies such as additive manufacturing in responding to different manufacturing challenges. Among these, the integration of additive and subtractive manufacturing technologies can play an important role and be a game changer in manufacturing products. In addition, using product platforms improves the efficiency and responsiveness of manufacturing systems and is considered an enabler of mass customization. In this paper, a model to design multiple platforms that can be customized using additive and subtractive manufacturing to manufacture a product family cost-effectively is proposed. The developed model is used to determine the optimal number of product platforms, each platform design (i.e. its features set), the assignment of each platform to various product variants, and the macro process plans for customizing the platforms while minimizing the overall product family manufacturing cost.The multiple additive/subtractive platforms and their process plans are determined by considering not only the commonality between the product variants but also their various manufacturing cost elements and the customer demand of each variant. The design of multiple product family platforms and their process plans is NP-hard problem. A genetic algorithm-based model is developed to reduce the computational complexity and find optimal or near optimal solution. Two case studies are used to illustrate the developed multiple platform model. The model results were compared with a single platform model in literature and the results demonstrate the multiple platform model superiority in manufacturing product families in lower cost. The use of the developed model enables manufacturing product families cost efficiently and allows manufacturers to manage diversity in products and market demands.     

基于产品感性定制模型的顾客协同设计系统

为使产品定制模型更加适合缺少相关领域专业知识的大众消费者,建立了基于感性工学的产品感性定制模型。引入配件感性性能指数、产品感性性能矩阵对产品感性性能进行量化。使用层次分析法实现了求解与顾客对产品感性性能需求对应的产品工程配置的方法。并应用产品感性定制模型,构建了基于Web和虚拟现实技术的顾客协同设计系统。