Designing Product Reliability based on Total Product Lifecycle Modelling

Due to the rapid progress of technology and severe competition in market, recent industrial products are required to exhibit high quality and functionality. At the same time products are required to be environmentally conscious. Therefore it is important to achieve appropriate product reliability with minimum resource consumption. In the total product lifecycle there exist various kinds of disturbances which may deteriorate product quality and functionality. A reliability design method is proposed based on prediction of product behaviour deterioration and its influence on product functional failure. Effectiveness of the proposed method is evaluated by mechatronics product design.     

Design Reuse Methodology for Product Family Design

This paper presents a design reuse methodology to facilitate product family design. Three major processes are defined, namely, information modelling, information processing, and solution synthesis and evaluation. The information content assessment (ICA) method is proposed for solution evaluation. This method defines logical steps to compute the information content that is used as a uniform, dimensionless metric of product performances. In a case study, product families of the cellular phone were developed using the design reuse methodology. It is demonstrated that the design reuse method proposed in this paper can effectively manage the product family design processes, and the ICA method provides a useful way for performance evaluation.     

The Use of Virtual Reality Techniques during the Design Process: from the Functional Definition of the Product to the Design of its Structure

During the design process, designers have to define the structure of their product while considering its functional definition. This design phase remains little assisted for designers. In addition, as numerous options can be considered for the end of life of a product (reuse, remanufacturing, recycling,…) it becomes more difficult to obtain a compromise concerning the final structure of the product. In this paper, we will show how the use of virtual reality helps designers to transform the functional definition of the product into the design of its structure, during the conceptual design phase. The developed example will concern the design of a bathroom scale.     

Generating design alternatives for increasing recyclability of products

This paper proposes a design support method for improving the recyclability of electronic and electrical products. The method estimates the recycling rate of a product based on its end-of-life scenario. The method supports a designer in generating design alternatives that increase the rate by conducting impact analysis with the change of material composition and end-of-life scenario. The method suggests design alternatives with the constraint of keeping the other performance factors (e.g., flexural strength and thermal conductivity) constant by adjusting the geometric parameters (e.g., thickness and volume) of the components.     

Integrated Design Analysis for Product Simplification

A systematic methodology is presented for product structure simplification through an integration of Design for Manufacture and Assembly (DFMA) with the Theory of Invention Problem Solving (TRIZ). A new functional model is combined with a selection of TRIZ problem solving tools that are identified as effective in product structure simplification. DFMA analysis is used to evaluate alternative concepts. Application of the combined approach is illustrated through a case study of a heavy duty stapler.     

Determining the Reuse Potential of Components Based on Life Cycle Data

Reuse of components is one of the most efficient strategies for product recovery, which requires reliable methods for assessing the quality and the remaining life of used components. A new methodology, presented in this paper, is based on the trend analysis of lifetime monitoring data. Data with similar trends were grouped and a number of analysis techniques such as Linear Multiple Regression, Dynamic Ordinary Kriging, Universal Kriging and Neural Networks were applied in order to find the most suitable methodology for each group. The methodology was validated by using lifetime monitoring data from a consumer product.     

PLM支持下的虚拟制造技术及其应用研究

本文总结阐述了虚拟制造的概念、范畴、关键技术、应用意义等内容,分析归纳了我公司业务流程的现状及其面临的挑战,据此提出了我公司业务对虚拟制造技术的需求以及相应的新流程,最后给出了达索系统和西门子PLM针对我公司业务需要制定的技术解决方案,希望对后续项目的开展起到积极的帮助作用。     

An Integrated Methodology to Estimate the External Environmental Costs of Products

Environmental costs of products are closely related to their environmental impacts. This paper presents a methodology to estimate the environmental costs of products during the concept design phase by integrating a Simplified Life Cycle Assessment (SLCA) methodology with Economic Valuation (EV) methods such as EPS2000d, EXMOD and Ecosense. The new methodology estimates the environmental performance indicators for each stage of the product life cycle by using the SLCA, and obtains the cost values from the most suitable EV method. A number of passive and active products were used to prove the concept and demonstrate the efficiency of the methodology.     

Design for Environment — Do We Get the Focus Right?

Sometimes, products resulting from design for environment (DFE) endeavours are sub-optimisations from an environmental perspective, because the tool determines the process and not vice versa. For a more systematic way of getting the focus right a hierarchy of focusing is introduced:1. What is the function provided and what is the optimal way of providing it while making a business out of it? Which product should the company then produce?2. Where are the “environmental hot spots” in the life cycle of this product?3. Which DFE tool supports optimisation of the product by reducing these hot spots?     

Incorporating probabilistic model of customers’ preferences in concurrent engineering

Concurrent engineering has been generally accepted as an important approach to reduce time to market. For years, the focus of concurrency has been design and manufacturing. With customers’ inputs becoming more crucial for product development, incorporating customers’ preferences into the design process has become significant in the continuing quest for reducing time to market. Because customers’ preferences involve intricate interdependency on factors such as product attributes, deterministic methods often fall short of representing and manipulating their probabilistic nature. This paper presents a probabilistic model that could continuously incorporate and adapt customers’ preferences into the concurrent engineering methodology.     

Knowledge Brokering for Assisting the Generation of Automotive Product Design

The aim of this paper is to present a pragmatic model for the systematic transfer of ideas and knowledge at the early stage of product design in a company environment. In using the model, the basic premise is not to build a new product ‘from scratch’ but to reuse existing ideas and knowledge from other objects and products developed previously. This new approach is called Knowledge Brokering (KB).The developed KB model consists of four sequential steps, which cover the collection and clustering of explicit design knowledge, the systematic learning process, retention and transfer of tacit design knowledge. The premises for using the KB model and case study results from the automotive industry on the advantages and limitations of the new approach are also described.     

Reuse of information in multi-layer sigma-pi neural networks

This new work is an extension of existing research into artificial neural networks (Neville and Stonham, Connection Sci.: J. Neural Comput. Artif. Intell. Cognitive Res., 7, pp. 29–60, 1995; Neville, Neural Net., 45, pp. 375–393, 2002b). These previous studies of the reuse of information (Neville, IEEE World Congress on Computational Intelligence, 1998b, pp. 1377–1382; Neville and Eldridge, Neural Net., pp. 375–393, 2002; Neville, IEEE World Congress on Computational Intelligence, 1998c, pp. 1095–1100; Neville, IEEE 2003 International Joint Conference on Neural Networks, 2003; Neville, IEEE IJCNN'04, 2004 International Joint Conference on Neural Networks, 2004) are associated with a methodology that prescribes the weights, as opposed to training them. In addition, they work with smaller networks. Here, this work is extended to include larger nets. This methodology is considered in the context of artificial neural networks: geometric reuse of information is described mathematically and then validated experimentally. The theory shows that the trained weights of a neural network can be used to prescribe the weights of other nets of the same architecture. Hence, the other nets have prescribed weights that enable them to map related geometric functions. This means the nets are a method of ‘reuse of information’. This work is significant in that it validates the statement that, ‘knowledge encapsulated in a trained multi-layer sigma-pi neural network (MLSNN) can be reused to prescribe the weights of other MLSNNs which perform similar tasks or functions’. The important point to note here is that the other MLSNNs weights are prescribed in order to represent related functions. This implies that the knowledge encapsulated in the initially trained MLSNN is of more use than may initially appear.     

Proposal of cause–effect pattern library for realizing sustainable businesses

Sustainable business design has gained growing interest in recent years. However, it is often difficult to clarify which business activities actually contribute to (or violate) the sustainability of the earth due to high complexity of environmental and economical system of our society. In order to help a business to generate sustainable business ideas handling this complexity in a systematic and comprehensive manner, this paper proposes a method to formulate a wide variety of causalities in our society into a cause–effect pattern library and illustrates how to use it for design and planning of sustainable businesses.     

Structured Method for Identifying Success Factors in New Product Development of Machine Tools

New product development of machine tools is always costly and risky for machine tools manufacturers; nevertheless, there have been few academic studies on the product development process of machine tools. Successful product developments were found to be related to perceived superior skills and resources within the objective of machine tools manufacturers. In this study, in order to establish the product development methodology for machine tools, the success factors in new product development have been identified based on the results of the interview and questionnaire investigations with experienced engineers in Japanese machine tools manufacturers. Based on the findings of this study, a structured method for identifying the success factors in new product development has been proposed.     

Geometrical reliability of overconstrained mechanisms with gaps

Reliability design relates generally to simulation of fatigue strength, thermal effects, etc. not to simulation of geometrical variations, i.e. tolerancing. The variables for geometrical reliability are manufacturing, gap and functional deviations. In case of isoconstrained mechanisms, the linear expression of dependencies between these variables allows to calculate failure probability. For overconstrained mechanisms, these linear expressions are not applicable for the whole behaviour of the mechanism; nevertheless, they are applicable for each particular configuration of contacts. The different configurations represent events taken into account in a numerical evaluation assumed by the Form-Sorm method. A case study, with numerical results, illustrates and validates the chosen process.     

Intelligent Kano classification of product features based on customer reviews

Product features can be classified into different categories based on customer opinions. The rapid development of artificial intelligence and machine learning paves the way toward computational analysis of customer reviews for opinion mining. This paper presents an Intelligent Kano framework to extract, quantify, and classify different product features based on customer reviews. The framework is enabled by a novel integration of multiple artificial intelligence and machine learning techniques such as sentiment analysis and anomaly detection. A case study is conducted to validate the framework’s effectiveness. Over 12,000 customer reviews on two coffee machines are analyzed for the classification.     

Early design verification of complex assembly variability using a Hybrid – Model Based and Physical Testing – Methodology

Design verification in the digital domain, using model-based principles, is a key research objective to address the industrial requirement for reduced physical testing and prototyping. For complex assemblies, the verification of design and the associated production methods is currently fragmented, prolonged and sub-optimal, as it uses digital and physical verification stages that are deployed in a sequential manner using multiple systems. This paper describes a novel, hybrid design verification methodology that integrates model-based variability analysis with measurement data of assemblies, in order to reduce simulation uncertainty and allow early design verification from the perspective of satisfying key assembly criteria.     

产品设计的相似性模型

首先分析了产品设计过程,将其分为原理设计、结构设计和工艺设计3个阶段。产品的相似性体现在产品原理的相似性、结构的相似性、工艺设计的相似性与设计手段的相似性,在此基础上提出了产品设计的相似性模型,用相似性分析可以丰富产品设计的方法,缩短产品设计周期,拓宽产品设计的思路。     

直流氢电弧蒸发法制备金属纳米Ni粉和Cu粉的研究

采用自行设计的直流氢电弧等离子体蒸发设备，通过正交试验，系统研究了H2／Ar、电流和压力对纳米Ni粉和Cu粉制备产率、结构及粒度的影响。发现：（1）该设备能够制备出纳米级的Ni粉和Cu粉，且产率有了很大的提高，Ni粉最大产率提高了24倍，Cu粉的最大产率提高了203．7倍；（2）各因素对两种粉体制备产率影响的显著性顺序为：φ（H2）／φ（Ar）-电流-压力；对Ni粉平均粒径影响的显著性顺序为：φ（H2）／φ（Ar）-压力-电流；对Cu粉平均粒径影响的显著性顺序则为：压力-φ（H2）/φ（Ar）-电流；（3）所制备的纳米Ni粉和Cu粉为多晶型；Ni粉的平均粒径在20-65nm范围内；Cu粉平均粒径为23-141nm；制备的Ni粉中不含杂质，纯净度很高，但是Cu粉中含有一定量的CuO杂质；（4）设备内腔的冷却环境对控制极大粒度粉体的生成和粉体粒度分布具有重要影响。