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

Li, L.; Huang, George Q.; Newman, Stephen T.

doi:10.1016/j.rcim.2007.02.014

Cited by 20 publications

(8 citation statements)

References 13 publications

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“…Kasarda et al [86] employed the adaptive control theory to explain the process of adaptable product design. Two examples, an engine mount with a self-tightening mechanism [87] developed an adaptive platform for product mass customization. Genetic programming was used in design optimization.…”

Section: Other Applicationsmentioning

confidence: 99%

Adaptable design: Concepts, methods, and applications

Xue

Nee

2009

Proceedings of the Institution of Mechanical Engineers, Part B:

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Increasing competition in the global marketplace demands products with better functionality, higher quality, lower cost, shorter delivery lead time, and increased environmental friendliness. Although advanced manufacturing technologies can partially address these challenges, advanced design technologies are considered critical, since most design and manufacturing properties of a product are influenced by the design decisions made in the early design stages. This paper provides a comprehensive review on a new design paradigm — adaptable design — that aims at developing adaptable products to satisfy the various requirements of customers. The topics discussed in this review include the fundamental concepts, objectives, methodologies, and applications. The paper also presents the differences between adaptable design and other design methods, such as modular design, platform design, and product customization. The focus is on mechanical product design; however, potential applications of adaptable design in other disciplines are also briefly mentioned.

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Section: Other Applicationsmentioning

confidence: 99%

Adaptable design: Concepts, methods, and applications

Xue

Nee

2009

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Siddique and Boddu (2005) presented a template approach to represent a CAD model for an entire family that considers both modularity and scaling. Li et al (2007) also presented an adaptive product platform based on parametric technology to generate feasible product variants to meet customer requirements. Similarly, Zhang et al (2008) developed parameter scaling and modular configuration to rapidly conduct the variant design of the tunnel boring machine main frame.…”

Section: Introductionmentioning

confidence: 99%

Research on the information transfer characteristics of dimensions in the product variant design process

Xü

Yan

Ding

2017

AIEDAM

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Product variant design, as one of the key enabling technologies of mass customization, is the transfer of variant information among mating parts from the perspective of informatics. A dimension constraint network (DCN) among mating parts carries on the task of transferring variant information. What are the information transfer characteristics of dimensions in a constraint network is a fundamental issue to plan the product variant design process reasonably. We begin by showing the natural dynamics of the DCN from two aspects: structure and uncertainty. The information efficiency of the DCN was proposed based on its simple path to specify the information transfer capability of the network. Based on this, the information centrality of the dimension was developed by measuring the efficiency loss of the DCN after the removal of a dimension from the network, which describes the information transfer capability of this dimension. Further, the information centrality of a part was derived. Using a spherical valve subassembly, we calculated the information centrality of the dimensions in a constraint network. We determined that the information centrality of dimension is highly correlated to its out-degree. An approach to plan the sequence of the part variant design according to its information centrality was proposed. We calculated the uncertainties of the DCN and its cumulative uncertainties under different sequences of the part variant design. Results indicate that part variant design under the descending information centrality of the parts minimizes the uncertainty of the DCN. This suggests a new method of planning the sequence of part variant design.

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“…Huang, Li, and Chen (2007) proposed a tandem evolutionary algorithm for platform product customisation based on an adaptive platform, which mainly focuses on reusing a product platform. Li, Huang, and Newman (2007) extended the tandem evolutionary algorithm and interwove genetic programming and genetic algorithm to customise an adaptive product platform into product variants. Zhen, Jiang, and Meng (2006) advanced a method of evolutionary product platform parameters planning, which determines values of platform parameters and individual parameters through improving as more commonalty of design variables in a product family as possible to cover most variety customer demands.…”

Section: Introductionmentioning

confidence: 99%

“…In scale-based product platform design, three questions should be answered as follows (Li et al 2008): (1) the design variables that should be made common (platform parameters) or individual within the product platform; (2) the values the platform parameters should take and (3) the values of individual parameters in every derivative product. Different methods, such as PPCEM (Simpson, Jonathan, and Mistree 2001;Messac, Martinez, and Simpson 2002;Simpson and D'Souza 2004), VBPDM (Nayak, Chen, and Simpson 2002), evolutionary algorithm (Huang, Li, and Chen 2007;Li et al 2008), genetic algorithm (Huang, Li, and Chen 2007;Li, Huang, and Newman 2007;Qu et al 2011;Liu, Wong, and Lee 2011) and so on, are almost mainly focused on questions (2) and (3). Some methods, such as information theory and clustering analysis (Chen and Wang 2008), sensitivity analysis (Dai and Scott 2007) and regression analysis (Zhu, Jiang, and Long 2003), are proposed to identify platform parameters mainly considering how they influence on product performance.…”

Section: Introductionmentioning

confidence: 99%

A methodology to support platform parameters determination through considering main factors in product life cycle

Gao

Zhang

Xiao

2013

International Journal of Computer Integrated Manufacturing

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How to determine platform parameters properly is a key technique in product platform design, which is an effective tactic for mass customisation. First, product platform was defined as a set of modules, platform parameters and individual parameters. Modules and platform parameters embody economy of scale and individual parameters embody economy of scope. Second, a methodology about determining platform parameters, which considers seven factors such as design, die, machining, assembly, management, service and performance because different platform parameters result in different product scheme and would lead production change in product life cycle, was proposed. Third, an improved fuzzy comprehensive evaluation was employed to formalise the problem and arithmetic of determining platform parameters was also developed. Finally, the strategy and method are demonstrated applicable and effective in an instance of determining platform parameters for motorcycle-hydraulic-disk brake platform planning.

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

Cited by 20 publications

References 13 publications

Adaptable design: Concepts, methods, and applications

Adaptable design: Concepts, methods, and applications

Research on the information transfer characteristics of dimensions in the product variant design process

A methodology to support platform parameters determination through considering main factors in product life cycle

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