Design candidate identification using neural network-based fuzzy reasoning

Conceptual design has profound impact on success of a product design. Identification of the best conceptual design candidate is a crucial step as design information is not complete and design knowledge is minimal at conceptual design stage. This paper presents a method for design candidate evaluation and identification using neural network-based fuzzy reasoning. The method consists of the following steps: (1) acquisition of customer needs and ranking of their importance, (2) establishment of measurable metrics and their relations with customer needs, (3) development of design specifications and initial evaluation of design candidates, and (4) evaluation and identification of design candidates based on design specifications and customer needs using neural network-based fuzzy reasoning. A case study is given to show the effectiveness of the proposed method and associated algorithms.     

Perceived feature utility-based product family design: a mobile phone case study

To assure profit maximization through mass customization and personalization, effectively eliciting consumer needs across different market segments is critical. Although functional performance specifications and adequacy of various design forms can be measured directly and objectively, many designers and engineers struggle with clearly evaluating product criteria requiring subjective consumer input; the fact that these inputs change over time further complicates the process. To appropriately evaluate product criteria, an effective design decision-making analysis is required. In this study, we propose a methodology to assure effective elicitation of needs and their inclusion in design decision making and illustrate it using a mobile phone product family design scenario. First, consumer perceived utility of design features is gathered using a questionnaire (500+ responses) and then modeled using multi- attribute utility theory to facilitate the evaluation of a product family while responding to needs across customer clusters shaped by demographics. The methodology goal is to determine the relative goodness of a product family in comparison to its competition. We also compare and evaluate the application of the proposed method to conjoint analysis.     

Product portfolio identification with data mining based on multi-objective GA

In the initial stage of product design, it is essential to define product specifications according to various market niches. An important issue in this process is to provide designers with sufficient design knowledge to find out what customers really want. This paper proposes a data mining method to facilitate this task. The method focuses on mining association rules that reflect the mapping relationship between customer needs and product specifications. Four objectives, support, confidence, interestingness and comprehensibility, are used for evaluating the extracted rules. To solve such a multi-objective problem, a Pareto-based GA is utilized to perform the rule extraction. Through computational experiments on an electrical bicycle case, it is shown that our approach is capable of extracting useful and interesting knowledge from a design database.     

Deriving engineering software from requirements

With the advent of intelligent computer aided design systems, companies such as Boeing are embarking on an era in which core competitive engineering knowledge and design rationale is being encoded in software systems. The promise of this technology is that this knowledge can be leveraged across many different designs, product families, and even different uses (e.g., generative process planning for manufacturing). The current state of the practice attempts to achieve this goal through the reuse of software components. A fundamental problem with this approach to knowledge sharing and reuse is that what we are trying to reuse is software—the end artifact in a long and complicated process that goes from requirement specifications, through a process of design, to implementations. Knowledge sharing and reuse can not easily and uniformly occur at the software level. So what can be done as an alternative? This paper describes a theory, methodology, language, and tool for the semi-automatic development and maintenance of engineering software from requirement specifications. In essence, this paradigm for software development and maintenance is one that explicitly captures requirement specifications, designs, implementations, and the refinement processes that lead from requirements all the way down to software. By recording this entire refinement history, we stand a better chance of leveraging knowledge for different uses.     

Design by customer: concept and applications

Customer satisfaction can be increased by reducing the gap between what customer really needs (customer requirements) and what manufacturer can provide (product specifications). The approach of Design for Customer where products are generated by translating customer needs into product specifications (in mass production system) or into product variety (in mass customization system) is not able to give optimum satisfaction to all customers. Some customers are still forced to relax their requirements and to accept predefined product in the assortment. This study proposes a new concept of Design by Customer to increase customer satisfaction by opening maximum possible channel for customers to involve in value creation so that they are no longer only searching for goods but they can also, when necessary, involve in production cycle to specify their own design. In order to ensure the viability of the proposed concept, the integration of multi customer involvement decoupling point, product attribute analysis, crowdscreening and new manufacturing strategy are introduced in this paper. Real products of resin-based table clocks are used as practical example to verify the concept applicability and to demonstrate its merit.     

Empirical assessment of two approaches for specifying software product line use case scenarios

Modularity benefits, including the independent maintenance and comprehension of individual modules, have been widely advocated. However, empirical assessments to investigate those benefits have mostly focused on source code, and thus, the relevance of modularity to earlier artifacts is still not so clear (such as requirements and design models). In this paper, we use a multimethod technique, including designed experiments, to empirically evaluate the benefits of modularity in the context of two approaches for specifying product line use case scenarios: PLUSS and MSVCM. The first uses an annotative approach for specifying variability, whereas the second relies on aspect-oriented constructs for separating common and variant scenario specifications. After evaluating these approaches through the specifications of several systems, we find out that MSVCM reduces feature scattering and improves scenario cohesion. These results suggest that evolving a product line specification using MSVCM requires only localized changes. On the other hand, the results of six experiments reveal that MSVCM requires more time to derive the product line specifications and, contrasting with the modularity results, reduces the time to evolve a product line specification only when the subjects have been well trained and are used to the task of evolving product line specifications.     

Integrated product line design and supplier selection: A multi-objective optimization paradigm

Product line design is commonly used to provide higher product variety for satisfying diversified customer needs. To reduce the cost and development time and improve quality of products, companies quite often consider sourcing. Conventionally, product line design and supplier selection are dealt with separately. Some previous studies have been attempted to consider product line design and supplier selection simultaneously but two shortcomings were noted. First, the previous studies considered several objectives as a single objective function in the formulation of optimization models for the integrated problem. Second, positions of product variants to be offered in a product line in competitive markets are not clearly defined that would affect the formulation of marketing strategies for the product line. In this paper, a methodology for integrated product line design and supplier selection is proposed to address the shortcomings in which a multi-objective optimization model is formulated to determine their specifications and select suppliers for maximizing the profit, quality and performance as well as minimizing the cost of the product line. In addition, joint-spacing mapping is introduced to help estimate market share of products and indicate positions of product variants. The proposed methodology can provide decision makers with a better tradeoff among various objectives of product line design, and define market positions of product variants explicitly. The results generated based on the methodology could help companies develop product lines with higher profits, better product quality and larger market share to be obtained. A case study of a product line design of notebook computers was performed to illustrate the effectiveness of the proposed methodology. The results have shown that Pareto optimal product line designs and the specifications of product variants can be determined. Suppliers of components and modules can be selected with considerations of minimum sourcing cost, and maximum performance and quality of product variants. Prices and positions of the product variants can also be determined.     

ICADS: Intelligent Car Audio Design System for product planning

This paper describes the development of a system, ICADS (Intelligent Car Audio Design System), that can be used to effectively support product development engineers in car audio product design. We have demonstrated the use of expert system technology and the technique of quality function deployment (QFD) in supporting car audio design planning. QFD is applied as a knowledge acquisition method in this study to support car audio design teams in the development of products in a structured way that relates market demand via engineering specifications to parts specifications. We believe that other industries can use a similar approach for developing an expert system that can support product design planning.     

A framework for integrating manufacturing process design and analysis

Product design and evaluation requires a broad and varied set of information and analysis tools. Yet effective design and evaluation of a product during its design phase is critical if production costs are to be minimized. A system is described that integrates product design specifications with material and process databases, and a simulation-based analysis module. The system allows product designs to be evaluated in terms of economic and technical criteria, and to identify the best production environment.     

Design of flexible static program analyzers with PQL

Static program analyzers (SPA) are interactive tools that enhance program understanding during maintenance by answering queries about programs. Depending on the maintenance task in hand, SPAs must process different source programs and answer different types of program queries. Flexibility is, therefore, a desirable property of SPAs. The author describes a program query language, called PQL, that facilitates the design of flexible SPAs. PQL is a conceptual level, source language-independent notation to specify program queries and program views. In PQL, one can query global program design as well as search for detail code patterns. PQL queries are answered automatically by a query evaluation mechanism built into an SPA. Program design models and POL form the core of an SPA conceptual model. He based the SPA's architecture on this conceptual model. By separating the conceptual model from the implementation decisions, one can design SPAs that are customizable to the needs of the maintenance project at hand. Depending on criteria such as efficiency of query evaluation or simplicity of the SPA design, one can implement the same functional specifications of an SPA on a variety of program representations to meet the required criteria. Apart from its role in the design of SPAs, the conceptual model also allows one to rigorously study SPA functionality in the context of the underlying maintenance process and programmer behavior models, in isolation from tool implementation details     

Supporting management and maintenance of manufacturing knowledge in design automation systems

Many companies base their business strategy on customized products. To enable a high level of product adaptation in an engineer-to-order approach companies invest time and resources to develop design automation systems. Initially, when implementing a design automation system, the focus is on successfully developing a system that generates design variants based on different customer specifications (i.e. the execution of system embedded knowledge and system output). However, in the long run, two important aspects are the management and maintenance of the knowledge that governs the designs. Further, the increasing emphasis on deploying a holistic view of a product’s properties and functions implies an increasing number of life-cycle requirements. The knowledge to adapt the product to fulfil these requirements should also be used and consequently incorporated into the knowledge-base, allowing for correct decisions to be made. In a system for automated variant design, the implications on the product of these life-cycle requirements have to be expressed as algorithms, production rules and/or computational statements to be intertwined with the design calculations. The number of requirements can be significantly large, and the knowledge scattered over different application systems used for the realisation of the design automation system. This makes it difficult to manage and maintain the system as the product life-cycle environment changes and evolves.In this article, the focus is on the requirements related to manufacturing. For that, an approach for the modelling of manufacturing requirements, supporting both knowledge execution and information management, in systems for automated variant design is introduced. The approach has been applied and refined when developing a design automation system in cooperation with a company to demonstrate and verify the approach’s usability.     

Safety-based availability assessment at design stage

The availability of a system or equipment is one of the crucial characteristics that measures the customer satisfaction and strongly influences his final choice decision between concurrent products. The aim of this work is to provide an approach to improve the products availability assessment by taking into account the safety criteria by considering the use situations at design stage. Our work focuses on the routine design of complex products. The availability is often simply estimated considering reliability and maintainability. Basically, the intrinsic availability is the probability that it is operating satisfactorily at any point in time when used under conditions stated by design specifications. The time considered includes operating time and active repair time. Thus, intrinsic availability excludes from consideration all other times in the product lifecycle such as: accident management time, storage time, administrative time or logistic time. But many studies show that the loss of availability performance is also due to accidents that occur in different unforeseeable utilization situations. This engenders stops of the system to ensure the users safety according to standards recommendations. In this purpose, we consider the structural product architecture and the different use cases that correspond to the operational states and downtimes due to stop events that may happen during the utilization like failures, maintenance tasks and accidents. Then, we propose a product behavioral analysis including the use cases to describe interactions between the product and users or maintenance operators. We use Markov chains to model the use cases corresponding to operating time (OT), maintenance time (MT) and preparing time after accidents (RT). Then these three parameters are considered to specify a generic approach to improve the availability assessment. Such an approach provides the traceability of the product behavior along its lifecycle. In this way, the main causes of stop can be identified and this may guide the designer for improving the availability of the product future versions. To validate our approach, an application is presented considering a printing line. The comparison of our simulation considering an industrial case study shows a good agreement about the influence of safety on the availability.     

User satisfaction modeling framework for automotive audio interfaces

Currently the research on product satisfaction is evolving to integrate pleasure and delight alongside other, more traditional needs. Pleasure and delight are emotional and hedonic benefits experienced by the user when interacting with the product. Thus, user satisfaction models have to deal with high complexity of product properties that collectively contribute to satisfaction. The formulation of these models has to include not only a proper taxonomy, but also the organization of such properties in categories and their relation to well defined satisfaction dimensions. Successful models would help to find out the most effective technical and design specifications (engineering parameters) that give shape to specific attributes of design, sometimes called “brand feelings”, defined in accordance with the business strategy. The objective of this paper is to present a user satisfaction modeling framework that deals with the complexity of an in-car user interface, namely the audio one. The proposed framework defines three distinct types of product properties: engineering parameters (P), perceived product attributes (A) and satisfaction dimensions (D) and presents a methodology to link the perceived product attributes (A) to satisfaction dimension (D).     

试论基于家电产品维护便利性的设计方法

在家电产品的使用中,维护是一项重要的内容,维护便利性符合当前产品人性化设计的主导思想。本文从产品设计的角度出发,探讨了家电产品维护便利性设计中可以采取的一些技巧以及禁忌。提出家电产品维护便利性设计应纳入产品系统设计范畴,成为产品设计新的突破口。     

A systematic framework for evaluating design concepts of a new product

This study aims to suggest a systematic framework to evaluate design concepts for a new product at the concept‐development phase. It focuses especially on evaluating design concepts based on user requirements and implicit tasks, defining trends in technology alternatives, and relating users' perceived value to product functionality. The potential user needs and functional requirements were identified through scenario‐based analysis and hierarchical task analysis. Technology alternatives were also investigated to support users in performing the required tasks effectively and efficiently. For a quantifiable evaluation measure, customer‐perceived value (CPV) attributes were used to evaluate the benefits and costs of the current design concept as compared to perceived alternatives. A case study was conducted to evaluate the design concepts of a new computer‐supported cooperative work (CSCW)‐based system with a tangible user interface, which was designed to support group decision‐making activities, such as business meetings. At the concept‐development phase, engineering specifications are not determined, and cost cannot be precisely estimated. Thus, while we dealt with design‐concept evaluation, we had no choice but to exclude cost attributes, such as monetary expenditure. It is still expected that our framework would be effective in incorporating user‐centered design perspectives early in the process of new product development. © 2010 Wiley Periodicals, Inc.     

A non-dominated sorting genetic algorithm based approach for optimal machines selection in reconfigurable manufacturing environment

This paper deals with a problem of reconfigurable manufacturing systems (RMSs) design based on products specifications and reconfigurable machines capabilities. A reconfigurable manufacturing environment includes machines, tools, system layout, etc. Moreover, the machine can be reconfigured to meet the changing needs in terms of capacity and functionality, which means that the same machine can be modified in order to perform different tasks depending on the offered axes of motion in each configuration and the availability of tools. This problem is related to the selection of candidate reconfigurable machines among an available set, which will be then used to carry out a certain product based on the product characteristics. The selection of the machines considers two main objectives respectively the minimization of the total cost (production cost, reconfiguration cost, tool changing cost and tool using cost) and the total completion time. An adapted version of the non- dominated sorting genetic algorithm (NSGA-II) is proposed to solve the problem. To demonstrate the effectiveness of the proposed approach on RMS design problem, a numerical example is presented and the obtained results are discussed with suggested future research.     

Vague knowledge search in the design for outsourcing using fuzzy decision tree

One of the most popular strategies in business today is global outsourcing. The information which needs to be provided for outsourcing and obtained from outsourced maintenance during the R&D processes is very important for the successful development of a product. Although DFX plays a key role in the R&D processes by considering the important X item constraints simultaneously in the design stage, the vague outsourced maintenance data and knowledge are seldom properly analyzed and used. In this study, fuzzy decision tree is used to form a search mechanism for vague knowledge in design for outsourcing (DFO) with index for classifying vague knowledge. Computational experiments were conducted to demonstrate the performance of the proposed search mechanism and knowledge classification.     

决策规则获取算法及规则表示

提出了一种基于粗糙集理论的决策规则获取算法及实用的决策规则表示方法。产品智能设计系统中,在概念设计阶段需要决定产品的类型。一般的产品设计过程,是从分析用户给定的技术参数、设计要求开始。规则获取算法就是从设计参数中挖掘设计知识,从而确定哪种类型的产品最适合用户的要求。该算法不需要任何先验知识。为了将算法应用到实际系统中,必须解决规则表示问题。本文将关系数据库成功地应用于设计规则的表示,使设计出的专家系统推理方便,运行效率高。通过继电器智能设计实例,说明了本方法的应用。     

Model-Based Prognostic Techniques Applied to a Suspension System

Conventional maintenance strategies, such as corrective and preventive maintenance, are not adequate to fulfill the needs of expensive and high availability transportation and industrial systems. A new strategy based on forecasting system degradation through a prognostic process is required. The recent advances in model-based design technology have realized significant time savings in product development cycle. These advances facilitate the integration of model-based diagnosis and prognosis of systems, leading to condition-based maintenance and increased availability of systems. With an accurate simulation model of a system, diagnostics and prognostics can be synthesized concurrently with system design. In this paper, we develop an integrated prognostic process based on data collected from model-based simulations under nominal and degraded conditions. Prognostic models are constructed based on different random load conditions (modes). An Interacting Multiple Model (IMM) is used to track the hidden damage. Remaining-life prediction is performed by mixing mode-based life predictions via time-averaged mode probabilities. The solution has the potential to be applicable to a variety of systems, ranging from automobiles to aerospace systems.