Preface

In manufacturing companies the cost of quality can be around 20% of the total turnover. The largest proportion of this is associated with costs due to failure of the product during production or when the product is in service with the customer. Typically, such failure costs are due to rework, scrap, warranty claims, product recall and product liability claims, representing lost profit to the company. A lack of understanding of variability in manufacture, assembly and service conditions at the design stage is a major contributor to poor product quality and reliability. Variability is often detected too late in the design and development process, if at all. This can lead to design changes prior to product release, which extend the time to bring the product to market or mean the incursion of high costs due to failure with the customer.

To improve customer satisfaction and business competitiveness, companies need to reduce the levels of non-conformance and attendant failure costs associated with poor product design and development. Attention needs to be focused on the quality and reliability of the design as early as possible in the product development process. This can be achieved by understanding the potential for variability in design parameters and the likely failure consequences in order to reduce the overall risk. The effective use of tools and techniques for designing for quality and reliability can provide this necessary understanding to reduce failure costs.

Various well-known tools and techniques for analysing and communicating potential quality and reliability problems exist, for example Quality Function Deployment (QFD), Failure Mode and Effects Analysis (FMEA) and Design of Experiments (DOE). Product manufacturing costs can be estimated using techniques in Design for Assembly (DFA) and Design for Manufacture (DFM). For effective use, these techniques can be arranged in a pattern of concurrent product development, but do not specifically question whether component parts and assemblies of a design can be processed capably, or connect design decisions with the likely costs of failure. Quality assurance registration with BS EN ISO 9000 does not necessarily ensure product quality, but gives guidance on the implementation of the systems needed to trace and control quality problems, both within a business and with its suppliers.

Chapter 1 of this book starts with a detailed statement of the problem, as outlined above, focusing on the opportunities that exist in product design in order to reduce failure costs. This is followed by a review of the costs of quality in manufacturing companies, and in particular how failure costs can be related to design decisions and the way products later fail in service. An introduction to risk and risk assessment provides the reader with the underlying concepts of the approaches for designing capable and reliable products. The chapter ends with a review of the key principles in designing for quality and reliability, from both engineering design research and industrial viewpoints.

Capable design is part of the Design for Quality (DFQ) concept relating to quality of conformance. Chapter 2 presents a knowledge-based DFQ technique, called Conformability Analysis (CA), for the prediction of process capability measures in component manufacture and assembly. It introduces the concepts of component manufacturing capability and the relationships between tolerance, variability and cost. It then presents the Component Manufacturing Variability Risks Analysis, the first stage of the CA methodology from which process capability estimates can be determined at the design stage. The development of the knowledge and indices used in an analysis is discussed within the concept of an 'ideal design'. The need for assembly variability determination and the inadequacy of the DFA techniques in this respect is argued, followed by an introduction to assembly sequence diagrams and their use in facilitating an assembly analysis. The Component Assembly Variability Risks Analysis is then presented, which is the second stage of the CA methodology. Finally explored in this chapter is a method for linking the variability measures in manufacturing and assembly with design acceptability and the likely costs of failure in service through linkage with FMEA.

The use of CA has proved to be beneficial for companies introducing a new product, when an opportunity exists to use new processes/technologies or when design rules are not widely known. Design conformance problems can be systematically addressed, with potential benefits, including reduced failure costs, shorter product development times and improved supplier dialogue. A number of detailed case studies are used to demonstrate its application at many different levels.

Chapter 3 reports on a methodology for the allocation of capable component tolerances within assembly stack problems. There is probably no other design effort that can yield greater benefits for less cost than the careful analysis and assignment of tolerances. However, the proper assignment of tolerances is one of the least understood activities in product engineering. The complex nature of the problem is addressed, with background information on the various tolerance models commonly used, optimization routines and capability implications, at both component manufacturing and assembly level. Here we introduce a knowledge-based statistical approach to tolerance allocation, where a systematic analysis for estimating process capability levels at the design stage is used in conjunction with methods for the optimization of tolerances in assembly stacks. The method takes into account failure severity through linkage with FMEA for the setting of realistic capability targets. The application of the method is fully illustrated using a case study from the automotive industry.

Product life-time prediction, cost and weight optimization have enormous implications on the business of engineering manufacture. Using large Factors of Safety in a deterministic design approach fails to provide the necessary understanding of the nature of manufacture, material properties, in-service loading and their variability. Probabilistic approaches offer much potential in this connection, but have yet to be taken up widely by manufacturing industry. In Chapter 4, a probabilistic design methodology is presented providing reliability estimates for product designs with knowledge of the important product variables. Emphasis will be placed on an analysis for static loading conditions. Methods for the prediction of process capability indices for given design geometry, material and processing route, and for estimating material property and loading stress variation are presented to augment probabilistic design formulations. The techniques are used in conjunction with FMEA to facilitate the setting of reliability targets and sensitivity analysis for redesign purposes. Finally, a number of fully worked case studies are included to demonstrate the application of the methods and the benefits that can accrue from their usage.

Chapter 5 discusses the important role of the product development process in driving the creation of capable and reliable products. Guidance on the implementation problems and integrated use of the main tools and techniques seen as beneficial is a key consideration. The connection of the techniques presented in the book with those mentioned earlier will be explored, together with their effective positioning within the product development process. Also touched on are issues such as design reviews, supplier development and Total Quality Management (TQM) within the context of producing capable and reliable products.

The book provides effective methods for analysing mechanical designs with respect to their capability and reliability for the novice or expert practitioner. The methods use physically significant data to quantify the engineering risks at the design stage to obtain more realistic measures of design performance to reduce failure costs. All core topics such as process capability indices and statistical modelling are covered in separate sections for easy reference making it a self-contained work, and detailed case studies and examples are used to augment the approaches. The book is primarily aimed at use by design staff for 'building-in' quality and reliability into products with application of the methods in a wide range of engineering businesses. However, the text covers many aspects of quality, reliability and product development of relevance to those studying, or with an interest in, engineering design, manufacturing or management. Further, it is hoped that the text will be useful to researchers in the field of designing for quality and reliability.

The authors are very grateful to Mr Stan Field (formerly Quality Director at British Aerospace Military Aircraft & Aerostructures Ltd) and to Mr Richard Batchelor of TRW for their invaluable support and collaboration on this work. Thanks are also extended to Mr Bob Swain of the School of Engineering for his help with the preparation of many drawings. The Engineering & Physical Sciences Research Council, UK (Grant Nos GR/J97922 and GR/L62313), has funded the work presented in this book.

J.D. Booker, M. Raines, K.G. Swift School of Engineering, University of Hull, UK

May 2000

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