{"product_id":"robust-design-methodology-for-reliability-isbn-9780470713945","title":"Robust Design Methodology for Reliability","description":"Based on deep theoretical as well as practical experience in Reliability and Quality Sciences, \u003ci\u003eRobust Design Methodology for Reliability\u003c\/i\u003e constructively addresses practical reliability problems. It offers a comprehensive design theory for reliability, utilizing robust design methodology and six sigma frameworks. In particular, the relation between un-reliability and variation and uncertainty is explored and reliability improvement measures in early product development stages are suggested.  \u003cp\u003eMany companies today utilise design for Six Sigma (DfSS) for strategic improvement of the design process, but often without explicitly describing the reliability perspective; this book explains how reliability design can relate to and work with DfSS and illustrates this with real–world problems. The contributors advocate designing for robustness, i.e. insensitivity to variation in the early stages of product design development. Methods for rational treatment of uncertainties in model assumptions are also presented.\u003c\/p\u003e \u003cp\u003eThis book\u003c\/p\u003e \u003cul type=\"disc\"\u003e \u003cli\u003epromotes a new approach to reliability thinking that addresses the design process and proneness to failure in the design phase via sensitivity to variation and uncertainty;\u003c\/li\u003e \u003cli\u003eincludes contributions from both academics and industry practitioners with a broad scope of expertise, including quality science, mathematical statistics and reliability engineering;\u003c\/li\u003e \u003cli\u003etakes the innovative approach of promoting the study of variation and uncertainty as a basis for reliability work;\u003c\/li\u003e \u003cli\u003eincludes case studies and illustrative examples that translate the theory into practice.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eRobust Design Methodology for Reliability\u003c\/i\u003e provides a starting point for new thinking in practical reliability improvement work that will appeal to advanced designers and reliability specialists in academia and industry including fatigue engineers, product development and process\/ quality professionals, especially those interested in and\/ or using the DfSS framework.\u003c\/p\u003e  \u003cb\u003ePreface\u003c\/b\u003e  \u003cp\u003e\u003cb\u003eAcknowledgements\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAbout the Editors\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eContributors\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003ePART One METHODOLOGY\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eBo Bergman and Martin Arvidsson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Background\u003c\/p\u003e \u003cp\u003e1.2 Failure Mode Avoidance\u003c\/p\u003e \u003cp\u003e1.3 Robust Design\u003c\/p\u003e \u003cp\u003e1.4 Comments and Suggestions for Further Reading\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Evolution of Reliability Thinking – Countermeasures for Some Technical Issues\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eÅ\u003c\/i\u003e\u003ci\u003eke L\u003c\/i\u003e\u003ci\u003eö\u003c\/i\u003e\u003ci\u003ennqvist\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction\u003c\/p\u003e \u003cp\u003e2.2 Method\u003c\/p\u003e \u003cp\u003e2.3 An Overview of the Initial Development of Reliability Engineering\u003c\/p\u003e \u003cp\u003e2.4 Examples of Technical Issues and Reliability Countermeasures\u003c\/p\u003e \u003cp\u003e2.5 Discussion and Future Research\u003c\/p\u003e \u003cp\u003e2.6 Summary and Conclusions\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Principles of Robust Design Methodology\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eMartin Arvidsson and Ida Gremyr\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction\u003c\/p\u003e \u003cp\u003e3.2 Method\u003c\/p\u003e \u003cp\u003e3.3 Results and Analysis\u003c\/p\u003e \u003cp\u003e3.4 Discussion\u003c\/p\u003e \u003cp\u003e3.5 Conclusions\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003ePART Two METHODS\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Including Noise Factors in Design Failure Mode and Effect Analysis (D-FMEA) – A\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCase Study at Volvo Car Corporation\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eÅ\u003c\/i\u003e\u003ci\u003eke L\u003c\/i\u003e\u003ci\u003eö\u003c\/i\u003e\u003ci\u003ennqvist\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction\u003c\/p\u003e \u003cp\u003e4.2 Background\u003c\/p\u003e \u003cp\u003e4.3 Method\u003c\/p\u003e \u003cp\u003e4.4 Result\u003c\/p\u003e \u003cp\u003e4.5 Discussion and Further Research\u003c\/p\u003e \u003cp\u003e4.6 Summary\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Robust Product Development Using Variation Mode and Effect Analysis\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAlexander Chakhunashvili, Stefano Barone, Per Johansson and Bo Bergman\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction\u003c\/p\u003e \u003cp\u003e5.2 Overview of the VMEA Method\u003c\/p\u003e \u003cp\u003e5.3 The Basic VMEA\u003c\/p\u003e \u003cp\u003e5.4 The Enhanced VMEA\u003c\/p\u003e \u003cp\u003e5.5 The Probabilistic VMEA\u003c\/p\u003e \u003cp\u003e5.6 An Illustrative Example\u003c\/p\u003e \u003cp\u003e5.7 Discussion and Concluding Remarks\u003c\/p\u003e \u003cp\u003eAppendix: Formal Justification of the VMEA Method\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Variation Mode and Effect Analysis: An Application to Fatigue Life Prediction\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eP\u003c\/i\u003e\u003ci\u003eä\u003c\/i\u003e\u003ci\u003er Johannesson, Thomas Svensson, Leif Samuelsson, Bo Bergman and Jacques de Maré\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction\u003c\/p\u003e \u003cp\u003e6.2 Scatter and Uncertainty\u003c\/p\u003e \u003cp\u003e6.3 A Simple Approach to Probabilistic VMEA\u003c\/p\u003e \u003cp\u003e6.4 Estimation of Prediction Uncertainty\u003c\/p\u003e \u003cp\u003e6.5 Reliability Assessment\u003c\/p\u003e \u003cp\u003e6.6 Updating the Reliability Calculation\u003c\/p\u003e \u003cp\u003e6.7 Conclusions and Discussion\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Predictive Safety Index for Variable Amplitude Fatigue Life\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eThomas Svensson, Jacques de Maré and P\u003c\/i\u003e\u003ci\u003eä\u003c\/i\u003e\u003ci\u003er Johannesson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction\u003c\/p\u003e \u003cp\u003e7.2 The Load–Strength Reliability Method\u003c\/p\u003e \u003cp\u003e7.3 The Equivalent Load and Strength Variables\u003c\/p\u003e \u003cp\u003e7.4 Reliability Indices\u003c\/p\u003e \u003cp\u003e7.5 The Gauss Approximation Formula\u003c\/p\u003e \u003cp\u003e7.6 The Uncertainty Due to the Estimated Exponent \u003ci\u003eβ\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.7 The Uncertainty Measure of Strength\u003c\/p\u003e \u003cp\u003e7.8 The Uncertainty Measure of Load\u003c\/p\u003e \u003cp\u003e7.9 The Predictive Safety Index\u003c\/p\u003e \u003cp\u003e7.10 Discussion\u003c\/p\u003e \u003cp\u003eAppendix\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Monte Carlo Simulation versus Sensitivity Analysis\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eSara Lorén, P\u003c\/i\u003e\u003ci\u003eä\u003c\/i\u003e\u003ci\u003er Johannesson and Jacques de Mar´e\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction\u003c\/p\u003e \u003cp\u003e8.2 Transfer Function\u003c\/p\u003e \u003cp\u003e8.3 Example from an Industrial Context\u003c\/p\u003e \u003cp\u003e8.4 Highly Nonlinear Transfer Function\u003c\/p\u003e \u003cp\u003e8.5 Total Variation for Logarithmic Life\u003c\/p\u003e \u003cp\u003e8.6 Conclusions\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003ePART Three MODELLING\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Model Complexity Versus Scatter in Fatigue\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eThomas Svensson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction\u003c\/p\u003e \u003cp\u003e9.2 A Statistical Model\u003c\/p\u003e \u003cp\u003e9.3 Design Concepts\u003c\/p\u003e \u003cp\u003e9.4 A Crack Growth Model\u003c\/p\u003e \u003cp\u003e9.5 Partly Measurable Variables\u003c\/p\u003e \u003cp\u003e9.6 Conclusions\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Choice of Complexity in Constitutive Modelling of Fatigue Mechanisms\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eErland Johnson and Thomas Svensson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Background\u003c\/p\u003e \u003cp\u003e10.2 Questions\u003c\/p\u003e \u003cp\u003e10.3 Method\u003c\/p\u003e \u003cp\u003e10.4 Empirical Modelling\u003c\/p\u003e \u003cp\u003e10.5 A Polynomial Example\u003c\/p\u003e \u003cp\u003e10.6 A General Linear Formulation\u003c\/p\u003e \u003cp\u003e10.7 A Fatigue Example\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Interpretation of Dispersion Effects in a Robust Design Context\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eMartin Arvidsson, Ida Gremyr and Bo Bergman\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction\u003c\/p\u003e \u003cp\u003e11.2 Dispersion Effects\u003c\/p\u003e \u003cp\u003e11.3 Discussion\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Fatigue Damage Uncertainty\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAnders Bengtsson, Klas Bogsj\u003c\/i\u003e\u003ci\u003eö\u003c\/i\u003e\u003ci\u003eand Igor Rychlik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction\u003c\/p\u003e \u003cp\u003e12.2 Fatigue Review\u003c\/p\u003e \u003cp\u003e12.3 Probability for Fatigue Failure – Safety Index\u003c\/p\u003e \u003cp\u003e12.4 Computation of E [\u003ci\u003eD\u003c\/i\u003e(\u003ci\u003eT\u003c\/i\u003e )|\u003ci\u003ek\u003c\/i\u003e] and V [\u003ci\u003eD\u003c\/i\u003e(\u003ci\u003eT\u003c\/i\u003e )|\u003ci\u003ek\u003c\/i\u003e]\u003c\/p\u003e \u003cp\u003e12.5 Non Gaussian Loads – Examples\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Widening the Perspectives\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eBo Bergman and Jacques de Maré\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Background\u003c\/p\u003e \u003cp\u003e13.2 Additional Engineering Perspectives on Reliability\u003c\/p\u003e \u003cp\u003e13.3 Organizational Perspectives on Reliability\u003c\/p\u003e \u003cp\u003e13.4 Industrialization of Robust Design Methodology\u003c\/p\u003e \u003cp\u003e13.5 Adoptions of Fatigue Reliability Methodology\u003c\/p\u003e \u003cp\u003e13.6 Learning for the Future\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003eList of Abbreviations\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex\u003c\/b\u003e\u003c\/p\u003e  \u003cp\u003e\u003cstrong\u003eBo Bergman\u003c\/strong\u003e has held the post of SKF professor at the Department of Quality Sciences at Chalmers University of Technology, Sweden since 1999. From 1983 to 1999 he was Professor of Quality Technology and Management at Linköping University, where he was responsible for the creation of education and research in the quality field, and previous to this he held varying engineering and managerial positions in the fields of reliability, quality and statistics at Saab Aerospace. His research interests cover wide areas of quality of both a quantitative and a qualitative nature. He has authored more than 50 papers in international scientific journals and has authored and co-authored a number of books — including new, completely revised English versions of \u003cem\u003eQuality from Customer Needs to Customer Satisfaction\u003c\/em\u003e and \u003cem\u003eSix Sigma; the Pragmatic Approach\u003c\/em\u003e. \u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eJacques Demaré\u003c\/strong\u003e has held the post of Professor of Mathematical Statistics at Chalmers University of Technology since 1999. The focus of his work has been on both chemical and mechanical applications and he is currently working with statistical methods for material fatigue in co-operation with the Swedish National Testing and Research Institute. At Chalmers he has also worked in different ways to bring the mathematical and engineering disciplines closer together. \u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eThomas Svensson\u003c\/strong\u003e is a research engineer at the Technical Research Institute of Sweden (SP). He obtained his PhD in Fatigue Life Prediction in Service — A Statistical Approach in 1996, and is a member of the editorial board of Fatigue and Fracture of Engineering Materials and Structures.   Based on deep theoretical as well as practical experience in Reliability and Quality Sciences, \u003ci\u003eRobust Design Methodology for Reliability\u003c\/i\u003e constructively addresses practical reliability problems. It offers a comprehensive design theory for reliability, utilizing robust design methodology and six sigma frameworks. In particular, the relation between un-reliability and variation and uncertainty is explored and reliability improvement measures in early product development stages are suggested.  \u003c\/p\u003e\u003cp\u003eMany companies today utilise design for Six Sigma (DfSS) for strategic improvement of the design process, but often without explicitly describing the reliability perspective; this book explains how reliability design can relate to and work with DfSS and illustrates this with real–world problems. The contributors advocate designing for robustness, i.e. insensitivity to variation in the early stages of product design development. Methods for rational treatment of uncertainties in model assumptions are also presented.\u003c\/p\u003e \u003cp\u003eThis book\u003c\/p\u003e \u003cul type=\"disc\"\u003e \u003cli\u003epromotes a new approach to reliability thinking that addresses the design process and proneness to failure in the design phase via sensitivity to variation and uncertainty;\u003c\/li\u003e \u003cli\u003eincludes contributions from both academics and industry practitioners with a broad scope of expertise, including quality science, mathematical statistics and reliability engineering;\u003c\/li\u003e \u003cli\u003etakes the innovative approach of promoting the study of variation and uncertainty as a basis for reliability work;\u003c\/li\u003e \u003cli\u003eincludes case studies and illustrative examples that translate the theory into practice.\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eRobust Design Methodology for Reliability\u003c\/i\u003e provides a starting point for new thinking in practical reliability improvement work that will appeal to advanced designers and reliability specialists in academia and industry including fatigue engineers, product development and process\/ quality professionals, especially those interested in and\/ or using the DfSS framework.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989970108645,"sku":"NP9780470713945","price":167.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470713945.jpg?v=1761786073","url":"https:\/\/k12savings.com\/es\/products\/robust-design-methodology-for-reliability-isbn-9780470713945","provider":"K12savings","version":"1.0","type":"link"}