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The paper presents a new approach to texture analysis. The need for a more formal definition of the term surface texture is first identified, and an appropriate texture taxonomy proposed. A method of analysis is described, synthesising innovative elements of machine vision and computer graphics to achieve an object‐centred inspection technique, which is both robust and flexible in application. A selection of experimental results is presented in the paper.

In this paper, a review of materials selection methods is presented. It initially discusses the importance of materials selection in various fields of scientific study particularly in engineering design. Various tools and methods for the selection of materials are reviewed. These include materials handbook, materials data‐bases, materials selection charts, artificial intelligence systems, and other computeraided materials selection systems.

CAD, CAM, CAE and CIM systems with their ability to quickly generate and change product data have strained the conventional systems used to manage data. As a result, the time spent by an engineer in looking for the right information far exceeds the time spent on the actual design work. A product data management system is a tool that helps engineers and others manage both data and the product development process, and hence support a concurrent engineering framework in a company. Although PDM systems provide numerous benefits to a company, there are problems associated with firstly identifying an appropriate system for a company and then in its implementation. For a successful implementation of a PDM system it is important for a company to first evaluate its requirements. This paper proposes a QFD (quality function deployment) based methodology for evaluating a company’s current status vis‐à‐vis PDM implementation.

This paper proposes an expert system that incorporates QFD (quality function deployment) methodology for the identification of the strategic components of a company for a PDM (product data management) system. A PDM system helps a company in carrying out its collaborative product development activities by providing a platform, through which information can be shared. It also helps in managing the different activities involved in the product development process. The use of QFD methodology in an expert system rationalises the process of identifying the strategic components of a PDM system for a successful collaborative product development strategy. In the proposed approach the PDM requirements are directly correlated with the PDM functions. This helps in prioritising the PDM components/functions and in providing a transparent way of understanding the correlation between the PDM requirements and the PDM components/functions. The use of expert system overcomes the complexities associated with QFD methodology.

The purpose of this paper is to describe the construction of a key model for knowledge management (KM) systems using AHP‐QFD for the semiconductor industry in Taiwan.

The performance evaluation matrix was modified to set up a standard performance matrix for system introduction. The importance weights of models related to KM via the analytic hierarchy process (AHP) and after consulting experts' opinions. The method of quality function deployment (QFD) was integrated for the system models of a KM system and correlation weights of key objectives to be improved.

Seven key objectives need to be improved. Correlations between the key objectives to be improved and the KM system models are located via QFD for eight critically important models to be improved.

In this study, the questionnaires were e‐mailed to respondents sampled from the list of the Taiwan Semiconductor Industry Association (TSIA).

Actual cases are investigated and a KM system prototype is established in this research to provide reference for the semiconductor industry when introducing a KM system.

Companies can evaluate the performance of system introduction rapidly and regulate their investments in resources efficiently using the measurement, analysis and improvement methods provided here so that the performance of introducing the KM system will be increased effectively at the lowest cost.

The purpose of this paper is to argue that the quality function deployment (QFD) matrix that has been successfully used for developing products from customer needs can also be applied to improve the service quality of telecommunication companies.

The paper presents a case study of the two big telecom companies (Ufone and Mobilink) of Pakistan. Data have been collected by a cross‐sectional field study of users, frontline employees and management of telecom companies. The QFD matrix has been applied to identify customer needs, to do comparative analysis of the prepaid services of these companies and to recommend the suitable measure for incorporating these requirements into their services.

It has been found that through emphasizing two technical descriptors (Antennas and Base Station Controller System), a company will not only be in a competitive position to meet the customer's demand but will also gain an advantage over its competitor.

Research findings are limited to telecom companies. Further research can be carried out in other service providing companies.

Research outcomes also imply that if managers want to listen to the voice of their customers and update their products and services accordingly, the proposed methodology of QFD is much more effective than the traditional approaches, in which decisions regarding the product or services are prioritized based on the manager's point of view.

Most of the previous research has applied QFD for developing products from customer needs. This is one of the few studies which have successfully applied the QFD Matrix in service providing companies.

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence (AI) will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of AI techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different AI techniques to be considered and then shows how these AI techniques are used for the components of IMS.

To provide the reader with an appreciation of the present trends in the UK automotive supply industry as they affect the first and second tier supply chain and aims to give researchers an insight into the complex interaction between suppliers and their customers.

Literature review which is divided into the sub‐sections of strategy, structure, processes and co‐ordination required within the manufacturing environment, to identify the influence of synchronous supply as it affects these main areas of operations management.

Through the use of examples from previous papers written on automotive and related supply industry operating methods, and to date Grounded Theory forming a pilot study to empirical research for this research, it concludes that synchronous supply can provide the lead for an efficient automotive supply chain.

The concept of synchronous supply presents a challenging research framework for supplier operating strategy, structuring processes and co‐ordination between the vehicle manufacturer (VM) and the whole supply chain.

A useful source of information for VMs and their first tier suppliers to understand more about synchronous supply and its affect on the supply chain.

This paper presents the concept of synchronous supply as a challenging framework for supplier operating strategy, structuring processes and co‐ordination between the VM and the whole supply chain.

The purpose of this paper is to provide tangible examples of product data management (PDM) practices in large high‐tech companies, and to highlight current challenges.

This paper is a qualitative interview study. First, a PDM system frame was defined to aid analyses. Second, an interview study was carried out in four companies to clarify the practical realisation of PDM, and the current challenges. The interviewees are experts in the field of PDM, currently holding significant related posts in their companies.

Overall, PDM activities are similar in all companies, however, there is some diversity in the realisation of these practices. PDM related challenges identified in this study are various, strongly influenced by company background and current organisational state.

This paper includes interviews in four companies with different backgrounds, and a workshop, providing a good view on topical issues in the field of PDM. The obtained results could vary to some degree, should the sample size be larger, or especially should the products of the studied companies be less complex.

This paper provides managers and PDM system developers' with a better understanding over the issues that are affecting PDM solution development and on major system requirements, together with relevant insight on current challenges.

The existing literature is relatively scarce in describing the practicalities of PDM. The obtained results highlight the significance of company background influencing the selection of PDM solutions.

Machine design and manufacture is the key to the advancement of manufacturing industry. Before any machine can be designed, it is important to establish requirements of the machine. Identifies quality function deployment (QFD) as one of the tools that can be used to identify customer needs and link the needs to product design. By bringing forward customers’ requirements into the design process, design rework and unnecessary iteration between design and manufacture can be reduced. In this project, QFD for a pultrusion machine design has been chosen as a case study. QFD was applied at the front end of the design process. The QFD process started with identifying the customers and determining their needs. These needs were translated into engineering requirements which were then used to formulate general specifications of the machine. A step by step approach was introduced to make the QFD process more manageable. Reports on the first phase of a research project in which QFD was used to capture all vital information from the customers and translated that into engineering requirements.