Application of Traditional and Fuzzy Quality Function Deployment in the Product Development Process

It is the nature of problems in quality management to contain elements of uncertainty. The uncertainty of input data is the result of a subjective approach to the interpretation of imprecise information. The aim of this article is to present the application of an effective fuzzification instrument in dealing with different kinds of uncertainty and also the application of natural language to model decision making in quality management. The article shows how the integration of fuzzy logic can assist with the planning of a particular product. First, the traditional Quality Function Deployment (QFD) method was used for the purpose of achieving quality improvement in a boiler (house electric water heater). Second, the QFD method combined with fuzzy logic was used for the same purpose. The preferred quality characteristics were defined using both traditional and fuzzy QFD methods, and results obtained were compared and discussed. The implications of the research for practice and future research are outlined.     

A Mini-Review on Metal Recycling from Spent Lithium Ion Batteries

The rapid growth of lithium ion batteries (LIBs) for portable electronic devices and electric vehicles has resulted in an increased number of spent LIBs. Spent LIBs contain not only dangerous heavy metals but also toxic chemicals that pose a serious threat to ecosystems and human health. Therefore, a great deal of attention has been paid to the development of an efficient process to recycle spent LIBs for both economic aspects and environmental protection. In this paper, we review the state-of-the-art processes for metal recycling from spent LIBs, introduce the structure of a LIB, and summarize all available technologies that are used in different recovery processes. It is notable that metal extraction and pretreatment play important roles in the whole recovery process, based on one or more of the principles of pyrometallurgy, hydrometallurgy, biometallurgy, and so forth. By further comparing different recycling methods, existing challenges are identified and suggestions for improving the recycling effectiveness can be proposed.     

再生剂碳含量与FCC产品分布的数学关联研究

利用催化裂化试验数据,通过模型方程推导和参数估计,分别建立了再生剂碳含量对转化率、焦炭产率,裂化气体产率和汽油产率影响的数学模型,并用所建模型对催化裂化产品分布进行预测分析。模型预测结果表明,随再生剂碳含量提高,转化率、焦炭和裂化气体产率和选择性均不断降低,汽油选择性逐渐提高,汽油产率存在一个极大值。     

面向物能资源优化利用的机械产品设计

本文分析了机械产品设计中影响制造系统物能资源消耗的主要因素,并在此基础上提出了一种面向物能资源优化利用的机械产品设计模型,对提高物能资源利用率的产品设计的方法和途径进行了讨论。     

基于产品数据管理的系统集成

本文通过对企业实际需求和产品数据管理（PDM）技术的研究分析，提出基于PDM的系统集成思想及体系结构，并对相关技术进行了探讨     

Elements in a new sustainable industrial culture Environmental assessment in product development

In the last few years the environmental focus in the manufacturing industry has shifted from the manufacturing processes to the products themselves, as these are accountable for the environmental impacts in all life cycle phases. The paper describes for three industrial cases how a newly developed LCA methodology can assist the product developer in development of more environmentally friendly products. Finally, common experience gained will be discussed.     

Product platform two-stage quality optimization design based on multiobjective genetic algorithm

Product platform design (PFD) has been recognized as an effective means to satisfy diverse market niches while maintaining the economies of scale and scope. Numerous optimization-based approaches have been proposed to help resolve the tradeoff between platform commonality and the ability to achieve distinct performance targets for each variant. In this study, we propose a two-stage multiobjective optimization-based platform design methodology (TMOPDM) for solving the product family problem using a multiobjective genetic algorithm. In the first stage, the common product platform is identified using a nondominated sorting genetic algorithm II (NSGA-II); In the second stage, each individual product is designed around the common platform such that the functional requirements of the product are best satisfied. The design of a family of traction machine is used as an example to benchmark the effectiveness of the proposed approach against previous approachs.     

Regression models for estimating product life cycle cost

Product life cycle cost (LCC) is defined as the cost that is incurred in all stages of the life cycle of a product, including product creation, use and disposal. In recent years, LCC has become as crucial as product quality and functionality in deciding the success of a product in the market. In order to estimate LCC of new products, researchers have employed several (parametric) regression analysis models and artificial neural networks (ANN) on historical life cycle data with known costs. In this article, we conduct an empirical study on performance of five popular non-parametric regression models for estimating LCC under different simulated environments. These environments are set by varying the number of cost drivers (independent variables), the size of sample data, the noise degree of sample data, and the bias degree of sample data. Statistical analysis of the results recommend best LCC estimation models for variable environments in stages of the product life cycle. These findings are validated with real-world data from previous work.     

Human experience and product usability: principles to assist the design of user-product interactions

This paper introduces research that investigates how human experience influences people's understandings of product usability. It describes an experiment that employs visual representation of concepts to elicit participants' ideas of a product's use. Results from the experiment lead to the identification of relationships between human experience, knowledge, and context-of-use - relationships that influence designers' and users' concepts of product usability. These relationships are translated into design principles that inform the design activity with respect to the aspects of experience that trigger people's understanding of a product's use. A design tool (ECEDT) is devised to aid designers in the application of these principles. This tool is then trialled in the context of a design task in order to verify applicability of the findings.     

Economical green product design based on simplified computer-aided product structure variation

Environmental issues have become an imperative concern for most companies in relation to modern product development. Special procedures have to be taken during the product development process to comply with recent green directives. Product structure is recognized as a critical factor that provides effective means for reducing environmental impact in product end-of-life. However, most previous studies failed to leverage the vast latitude at the design stage due to the assumption of a fixed product structure. To overcome this deficiency, we propose a CAD-based approach that allows automatic variation of 3D product structure by means of changing the combination of parts, selecting the assembly method, and rearranging the assembly sequence. A computing scheme uses Genetic Algorithm (GA) techniques to produce an optimal product structure from the design alternatives generated by the approach. This corresponds to lower assembly/disassembly costs, while complying with specified recycling and recovering rates. The scheme also chooses a smaller set of parts that needs to be disassembled and determines an economical disassembly process. Implemented in a commercial CAD system, the test results demonstrated the effectiveness of this scheme in green product design in a cost-effective manner.