A module generation algorithm for product architecture based on component interactions and strategic drivers

Benefits of modularity are often achieved from module independence that allows for independent development to reduce overall lead time and economies of scale due to sharing similar modules across products in a product family. Current modularity methods tend to describe only one of these views, either the module–module independence or the product–product shared module similarity. This paper proposes a new hybrid module generation algorithm that balances both module independence and product similarity, allowing product similarity strategy to influence the coupling-driven architecture considerations. The proposed method builds on two popular matrix-based methods: the design structure matrix approach and modular function deployment that each has been developed to support these two different aspects of the module generation. This paper presents a novel algorithm that integrates both views and allows a balanced clustering that takes both interactions and company portfolio strategy into account. Usefulness of the algorithm is presented using a cordless handheld vacuum cleaner as a case study and by comparing it to alternative approaches.     

A multi-objective fuzzy graph approach for modular formulation considering end-of-life issues

Increased awareness of the negative environmental impact caused by electronic waste has driven electronics manufacturers to re-engineer their product design process and include product end-of-life considerations into their design criteria. Design for the Environment (DfE), as a possible solution, lacks an implementation framework. To address this problem, a fuzzy graph based modular product design methodology is developed to implement DfE strategies in product modular formulation considering multiple product life cycle objectives guided by DfE. A fuzzy connected graph approach is used to present the product structure, whereby fuzzy relationship values are determined by applying Analytic Hierarchy Process (AHP) to life cycle environmental objectives along with other functional and production concerns. Based on the fuzzy connected graph, an optimal modular formulation is searched using the graph-based clustering algorithm to identify the best module configuration. An example is provided to illustrate the methodology and the algorithm presented in this paper.     

机电产品模块划分与综合评价集成设计方法

目的 为了满足机电产品日益多样化、个性化的市场需求,提高产品模块划分的稳定性与模块化方案评价的可靠性,提出产品模块划分与评价集成方法。方法 对产品的功能结构进行分析,构建产品的量化信息模型,合理分配各量化指标的权重,构建描述组件间关系的综合矩阵。采用基于原子理论的聚类算法进行模块划分,通过改变模块粒度,稳定地得出产品模块划分的多个可行方案。通过考虑产品的模块化程度和基于信息熵的模块复杂度,构建模块化方案的综合评价模型,以确定最优的模块划分结果。结论 采用模块划分与综合评价集成设计方法对某小型雕刻机进行模块化设计,并通过对比原子聚类算法与其他模块划分方法所得的模块化结果,验证了所提出设计方法的可行性和高效性。     

An evolutionary algorithm for a new multi-objective location-inventory model in a distribution network with transportation modes and third-party logistics providers

This paper proposes a multi-objective optimisation algorithm for solving the new multi-objective location-inventory problem (MOLIP) in a distribution centre (DC) network with the presence of different transportation modes and third-party logistics (3PL) providers. 3PL is an external company that performs all or part of a company’s logistics functions. In order to increase the efficiency and responsiveness in a supply chain, it is assumed that 3PL is responsible to manage inventory in DCs and deliver products to customers according to the provided plan. DCs are determined so as to simultaneously minimise three conflicting objectives; namely, total costs, earliness and tardiness, and deterioration rate. In this paper, a non-dominated sorting genetic algorithm (NSGA-II) is proposed to perform high-quality search using two-parallel neighbourhood search procedures for creating initial solutions. The potential of this algorithm is evaluated by its application to the numerical example. Then, the obtained results are analysed and compared with multi-objective simulated annealing (MOSA). It is concluded that this algorithm is capable of generating a set of alternative DCs considering the optimisation of multiple objectives, significantly improving the decision-making process involved in the distribution network design.     

Attribute selection for product configurator design based on Gini index

Customer needs play a critical role in product design. Matching diversified customer needs with a company’s product offerings has been a challenge for academia and industry. To this end, product configurator systems have been accepted as important tools to elicit customer needs to meet the challenge. However for complex products with many product possibilities and intricate inter-product relationships, current product configuration systems may become tedious and time consuming for customers’ choice navigation process. They cannot adapt to each individual customer’s preferences by leveraging on the attribute specification information captured in previous configuration steps. This paper presents a Gini index-based attribute selection approach for configurator design. Product configuring is modelled as a sequential query–answer process. In each configuring step, the Gini index is deployed to quantify the clarity of the designer’s beliefs about the customer’s needs. The attribute which contributes most to the clarity will be selected for the customer to configure. A product recommendation module is also integrated with the configurator to further improve the efficiency. As a result, designers obtain clarification on the customer’s needs and preferences in an accelerated manner. An example is presented to test the viability of the method.     

乡村振兴下秸秆家具绿色模块化设计研究

目的 实施乡村振兴战略必须要优先考虑生态文明,以绿色发展引领美丽乡村的振兴。农村废弃秸秆焚烧产生的大量烟雾会对大气造成污染,从绿色模块化设计角度出发,分析秸秆材料的特点以及设计的多种可能性,对废弃秸秆进行有效利用以减少焚烧污染,将乡土材料转换为可利用的资源。方法 运用绿色模块化设计理念以功能与结构的相关性进行聚类划分,在此基础上对划分的模块进行零件变型设计,形成产品族的扩展设计,以增加产品的绿色属性及个性化需求。结论 明确了模块划分在秸秆材料家具设计中的实现方法,使其符合现代家具产品的使用功能、绿色属性及美学特征,拓展了自然材料在现代家具产品设计中的应用范围,优化了秸秆材料设计在家具领域的方法,传达了乡村振兴下的绿色生态发展理念。     

面向大规模定制的产品模块化设计

介绍了面向大规模定制的产品模块化设计的基本思想及模块创建过程和模块配置过程的研究现状,在此基础上进一步指出了面向MC的模块化设计面临的新课题.     

Proactive environmental strategies and performance: role of green supply chain processes and green product design in the Chinese high-tech industry

Though many firms still believe that passive environmental strategies are sufficient, it is pertinent that they move beyond this belief and take a proactive supply chain-wide environmental stance so as to create a sustainable environment. In this paper, we seek to extend current work within green supply chain management by considering multiple green supply chain capabilities and performance measures. We hypothesise the linkage between environmental orientation, green supply chain capabilities and performance by drawing upon stakeholder theory and natural resource-based view. More importantly, our study is the first to distinguish between product and process-related capabilities in the green supply chain area and study their direct and mediating role with respect to environmental and financial performance measures. Using survey data collected from 256 Chinese-based high-tech firms, we analyse several hypothesised relationships. Our results provide strong support for the significant role that green product design and green supply chain processes can play in improving firms’ environmental and financial performance. Interestingly, our results also suggest that green product design may not have a direct impact on financial performance.     

包装机械模块化设计的研究

以制袋成型－充填－封口机为例，介绍一种新的设计方法；分析了模块化设计的特点，在对制袋成型－充填－封口机进行功能分析的基础上建立模块，并分解各主要模块，最后对各模块的优化组合和模块的计算机管理系统的建立进行了讨论。     

Modular simulation tool for modelling JIT manufacturing

Since quantitative information is very helpful in implementing JIT production techniques, computer simulation can be a valuable tool in designing, implementing or changing JIT practices in a production system. Nowadays, existing simulation software incorporates modular programming and enhanced graphic systems for output representation. It enables users to generate modules that represent partial aspects of a JIT system. These modules, adequately modified and integrated, give researchers and practitioners the possibility to create complex models that can be applied to a variety of JIT systems or JIT production environments. A modular simulation tool, based on the modular capabilities of Witness, is introduced in this paper. As a module example, the feeder double-kanban line module is presented, which represents one of the core aspects of a JIT manufacturing system. Finally, module integration is illustrated by modelling a U-Shaped line. The experimentation and evaluation of the U-line allow one to appreciate how modular simulation can be a powerful tool in decision making, by enabling users to analyse systems configurations and operation rules before implementing them.     

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.     

Designing a cellular manufacturing system considering decision style,skill and job security by NSGA-II and response surface methodology

Cell formation is a traditional problem in cellular manufacturing systems that concerns the allocation of parts, operators and machines to the cells. This paper presents a new mathematical programming model for cell formation in which operators’ personality and decision-making styles, skill in working with machines, and also job security are incorporated simultaneously. The model involves the following five objectives: (1) minimising costs of adding new machines to and removing machines from the cells at the beginning of each period, (2) minimising total cost of material handling, (3) maximising job security, (4) minimising inconsistency of operators’ decision styles in cells and (5) minimising cost of suitable skill. On account of the NP-hard nature of the proposed model, NSGA-II as a powerful meta-heuristic approach is used for solving large-sized problems. Furthermore, response surface methodology (RSM) is used for tuning the parameters. Lastly, MOPSO and two scalarization methods are employed for validation of the results obtained. To the best of our knowledge, this is the first study that presents a multi-objective mathematical model for cell formation problem considering operators’ personality and skill, addition and removal of machines and job security.     

A Review of:“Ergonomics in Computerized Offices”. By ETIENNE GRANDJEAN (Taylor & Francis, 1986.) [Pp. viii + 227.] Price: cloth, £25·00; paperback, £11·50.

The use of precedence diagrams and estimates of task times, as the only source of engineering information for assembly line balancing (ALB), is common to most ALB techniques developed to date. This paper presents a model which incorporates the information carried by an assembly chart (or a Gozinto chart) into the ALB problem in an attempt to consider engineering objectives such as improving work methods and work enrichment in the design of assembly lines. A multi-objective approach is developed which integrates the traditional objective of minimizing the idle time of the line with the objective that a minimum number of subassemblies should be handled at each workstation.     

基于模糊Kano模型的模块化办公收纳产品设计

目的 通过对办公空间中模块化办公收纳产品设计的研究,从使用人群的需求出发,对用户需求进行有效分析,为使用人群创造出兼具实用性和趣味性的办公收纳产品,为模块化办公收纳产品的设计提供针对性的建议,让模块化办公收纳产品更符合用户预期和市场需求。方法 在前期调研的基础上建立模糊Kano模型,按照5种不同属性对用户需求进行分类,通过计算Better-Worse系数对不同类型的需求属性进行排序,随后将有效数据引入模块化设计方法中,为模块化办公收纳产品设计的功能模块划分与构建提出相应的解决方案。结果 发现用户对模块化办公收纳产品的灵活性、趣味性具有强烈需求,同时希望增加实用性功能。结论 将模糊Kano模型应用于模块化办公收纳产品设计中能有效提高用户满意度,提高模块化办公收纳产品的市场竞争力。     

A decentralised multi-objective scheduling methodology for semiconductor manufacturing

This paper presents a decentralised multi-objective scheduling methodology for semiconductor manufacturing. In this methodology, a new classification method is designed based on utilisations and entropies in order to decentralise global objectives into local ones of work stations. Then, a decentralised multi-objective scheduling policy is proposed to control virtual production lines (VPLs) and machine workload. Results of numerical experiments show that the proposed methodology outperforms common rule-based scheduling policies and a compound scheduling strategy.     

最小偏差法在机械多目标优化设计中的应用

提出了处理多目标问题的最小偏差法,并将其应用于机械多目标优化设计。以流体动压滑动轴承多目标优化设计为例,建立了以摩擦系数最小、发热量最小和承载能力最大为目标函数的多目标优化设计数学模型,根据最小偏差法原理构造统一目标函数,利用改进遗传算法对该问题进行了优化设计。算例整个求解过程和结果表明,该方法既可以避免人为因素的影响,又能够获得比常规设计更佳的设计参数,同时也验证了所提方法对于解决机械多目标优化设计问题的有效性和可行性。     

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.     

Incorporation of high recyclability material selection in computer aided design

Manufacturing are now under increasing pressure of tighten environmental legislation to preserve natural resources. Product design, as a part of manufacturing activities, has to be more concern to deliver product specification with reduced environmental impact. Design for Recycling (DFR) is one of the promising approaches in prolonging material utilization of a product in the early stage of design. DFR focus on harmonizing product design with the recycling practices in order to minimize the loss of valuable materials and preventing unnecessary waste streams at the end of product’s life. In turn, it limits the usage of natural resources.To implement DFR, designers are faced with the challenge of compromising different design objectives such as cost, functional or technical requirements and product’s recyclability performance. This paper attempts to propose an intelligent approach that could facilitate designers to make an easy and quick recyclability assessment as well as selecting recyclable materials integrated with computer aided design. In this paper, the use of fuzzy inference system and genetic algorithm is proposed to optimize the multi-objective problem in the selection of recyclable materials. Case study on the actual conceptual design using computer aided design environment is demonstrated and showing that the proposed method successfully can be applied concurrently during product design. Comparison of proposed method with Sustainability Express Solid Work is also presented. The proposed method can assist product designers to design a high recyclability product without ignoring technical perspectives.     

基于模块化设计思想的镀膜机快速设计研究

以大规模定制思想为背景,提出了一种镀膜机快速设计方法,阐述了镀膜机模块化设计的方法,研究了镀膜机的模块划分方法、知识工程的应用、实例的推理技术,通过镀膜机的设计流程分析,说明了模块化设计形成的特点。证明了运用模块化设计思想能很好地解决客户的个性化定制需求与产品开发周期较长的矛盾。     

Development of a multidisciplinary–multiresponse robust design optimization model

Robust design is an efficient process improvement methodology that combines experimentation with optimization to create systems that are tolerant to uncontrollable variation. Most traditional robust design models, however, consider only a single quality characteristic, yet customers judge products simultaneously on a variety of scales. Additionally, it is often the case that these quality characteristics are not of the same type. To addresses these issues, a new robust design optimization model is proposed to solve design problems involving multiple responses of several different types. In this new approach, noise factors are incorporated into the robust design model using a combined array design, and the results of the experiment are optimized using a new approach that is formulated as a nonlinear goal programming problem. The results obtained from the proposed methodology are compared with those of other robust design methods in order to examine the trade-offs between meeting the objectives associated with different optimization approaches.