{"product_id":"introduction-to-statistical-process-control-isbn-9781119528456","title":"Introduction to Statistical Process Control","description":"\u003cp\u003e\u003cb\u003eAn Introduction to the Fundamentals and History of Control Charts, Applications, and Guidelines for Implementation\u003c\/b\u003e \u003c\/p\u003e \u003cp\u003e\u003ci\u003eIntroduction to Statistical Process Control \u003c\/i\u003eexamines various types of control charts that are typically used by engineering students and practitioners. This book helps readers develop a better understanding of the history, implementation, and use-cases. Students are presented with varying control chart techniques, information, and roadmaps to ensure their control charts are operating efficiently and producing specification-confirming products. This is the essential text on the theories and applications behind statistical methods and control procedures.\u003c\/p\u003e \u003cp\u003eThis eight-chapter reference breaks information down into digestible sections and covers topics including:\u003c\/p\u003e \u003cp\u003e●      An introduction to the basics as well as a background of control charts\u003c\/p\u003e \u003cp\u003e●      Widely used and newly researched attributes of control charts, including guidelines for implementation\u003c\/p\u003e \u003cp\u003e●      The process capability index for both normal and non-normal distribution via the sampling of multiple dependent states\u003c\/p\u003e \u003cp\u003e●      An overview of attribute control charts based on memory statistics\u003c\/p\u003e \u003cp\u003e●      The development of control charts using EQMA statistics \u003c\/p\u003e \u003cp\u003eFor a solid understanding of control methodologies and the basics of quality assurance, \u003ci\u003eIntroduction to Statistical Process Control\u003c\/i\u003e is a definitive reference designed to be read by practitioners and students alike. It is an essential textbook for those who want to explore quality control and systems design.\u003c\/p\u003e \u003cp\u003eAbout the Authors xi\u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction and Genesis \u003c\/b\u003e\u003cb\u003e1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 History and Background of Control Charts 3\u003c\/p\u003e \u003cp\u003e1.3 What is Quality and Quality Improvement? 5\u003c\/p\u003e \u003cp\u003eTypes of Quality-Related Costs 7\u003c\/p\u003e \u003cp\u003e1.4 Basic Concepts 9\u003c\/p\u003e \u003cp\u003e1.4.1 Descriptive Statistics 9\u003c\/p\u003e \u003cp\u003e1.4.2 Probability Distributions 14\u003c\/p\u003e \u003cp\u003eContinuous Probability Distributions 14\u003c\/p\u003e \u003cp\u003eDiscrete Probability Distributions 18\u003c\/p\u003e \u003cp\u003e1.5 Types of Control Charts 19\u003c\/p\u003e \u003cp\u003e1.5.1 Attribute Control Charts 19\u003c\/p\u003e \u003cp\u003e1.5.2 Variable Control Charts 20\u003c\/p\u003e \u003cp\u003e1.6 Meaning of Process Control 21\u003c\/p\u003e \u003cp\u003eReferences 22\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Shewhart Type Control Charts for Attributes \u003c\/b\u003e\u003cb\u003e23\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Proportion and Number of Nonconforming Charts 24\u003c\/p\u003e \u003cp\u003e2.1.1 Proportion of Nonconforming Chart (\u003ci\u003ep\u003c\/i\u003e-Chart) 25\u003c\/p\u003e \u003cp\u003eVariable Sample Size 28\u003c\/p\u003e \u003cp\u003eImproved \u003ci\u003ep\u003c\/i\u003e-Chart 29\u003c\/p\u003e \u003cp\u003e2.1.2 Number of Nonconforming Chart (\u003ci\u003enp\u003c\/i\u003e-Chart) 30\u003c\/p\u003e \u003cp\u003e2.1.3 Performance Evaluation Measures 30\u003c\/p\u003e \u003cp\u003e2.2 Number of Nonconformities and Average Nonconformity Charts 32\u003c\/p\u003e \u003cp\u003e2.2.1 Number of Nonconformities (\u003ci\u003ec\u003c\/i\u003e\u003ci\u003e-\u003c\/i\u003e) Chart 33\u003c\/p\u003e \u003cp\u003e2.2.2 Average Nonconformities (\u003ci\u003eu\u003c\/i\u003e\u003ci\u003e-\u003c\/i\u003e) Chart 34\u003c\/p\u003e \u003cp\u003e2.2.3 The Performance Evaluation Measure 38\u003c\/p\u003e \u003cp\u003eDealing with Low Defect Levels 39\u003c\/p\u003e \u003cp\u003e2.3 Control Charts for Over-Dispersed Data 40\u003c\/p\u003e \u003cp\u003e2.3.1 Dispersion of Counts Data 40\u003c\/p\u003e \u003cp\u003e2.3.2 \u003ci\u003eg\u003c\/i\u003e-Chart and \u003ci\u003eh\u003c\/i\u003e-Chart 40\u003c\/p\u003e \u003cp\u003e2.4 Generalized and Flexible Control Charts for Dispersed Data 44\u003c\/p\u003e \u003cp\u003e2.4.1 The \u003ci\u003egc\u003c\/i\u003e- and the \u003ci\u003egu\u003c\/i\u003e-Charts 45\u003c\/p\u003e \u003cp\u003e2.4.2 Control Chart Based on Generalized Poisson Distribution 46\u003c\/p\u003e \u003cp\u003eProcess Monitoring 47\u003c\/p\u003e \u003cp\u003eA Geometric Chart to Monitor Parameter θ 48\u003c\/p\u003e \u003cp\u003e2.4.3 The \u003ci\u003eQ\u003c\/i\u003e- and the \u003ci\u003eT\u003c\/i\u003e-Charts 49\u003c\/p\u003e \u003cp\u003eThe OC Curve 52\u003c\/p\u003e \u003cp\u003e2.5 Other Recent Developments 52\u003c\/p\u003e \u003cp\u003eReferences 54\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Variable Control Charts \u003c\/b\u003e\u003cb\u003e57\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 57\u003c\/p\u003e \u003cp\u003e3.2 \u003ci\u003ex̅\u003c\/i\u003e Control Charts 58\u003c\/p\u003e \u003cp\u003e3.2.1 Construction of \u003ci\u003ex̅\u003c\/i\u003e and \u003ci\u003eR\u003c\/i\u003e Charts 59\u003c\/p\u003e \u003cp\u003e3.2.2 Phase II Control Limits 62\u003c\/p\u003e \u003cp\u003e3.2.3 Construction of \u003ci\u003ex̅\u003c\/i\u003e Chart for Burr Distribution Under the Repetitive Sampling Scheme 63\u003c\/p\u003e \u003cp\u003e3.3 Range Charts 72\u003c\/p\u003e \u003cp\u003e3.4 Construction of \u003ci\u003eS\u003c\/i\u003e-Chart 72\u003c\/p\u003e \u003cp\u003e3.4.1 Construction of \u003ci\u003ex̅\u003c\/i\u003e Chart 74\u003c\/p\u003e \u003cp\u003e3.4.2 Normal and Non-normal Distributions for \u003ci\u003ex̅\u003c\/i\u003e and S-Charts 75\u003c\/p\u003e \u003cp\u003e3.5 Variance \u003ci\u003eS\u003c\/i\u003e\u003ci\u003e\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e-Charts 75\u003c\/p\u003e \u003cp\u003e3.5.1 Construction of \u003ci\u003eS\u003c\/i\u003e\u003ci\u003e\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e-Chart 76\u003c\/p\u003e \u003cp\u003e3.5.2 The Construction of Variance Chart for Neutrosophic Statistics 77\u003c\/p\u003e \u003cp\u003e3.5.3 The Construction of Variance Chart for Repetitive Sampling 81\u003c\/p\u003e \u003cp\u003eReferences 87\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Control Chart for Multiple Dependent State Sampling \u003c\/b\u003e\u003cb\u003e91\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 91\u003c\/p\u003e \u003cp\u003e4.2 Attribute Charts Using MDS Sampling 91\u003c\/p\u003e \u003cp\u003e4.2.1 The \u003ci\u003enp\u003c\/i\u003e-Control Chart 92\u003c\/p\u003e \u003cp\u003e4.3 Conway–Maxwell–Poisson (COM–Poisson) Distribution 98\u003c\/p\u003e \u003cp\u003e4.4 Variable Charts 106\u003c\/p\u003e \u003cp\u003e4.5 Control Charts for Non-normal Distributions 107\u003c\/p\u003e \u003cp\u003e4.6 Control Charts for Exponential Distribution 109\u003c\/p\u003e \u003cp\u003e4.7 Control Charts for Gamma Distribution 111\u003c\/p\u003e \u003cp\u003eReferences 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 EWMA Control Charts Using Repetitive Group Sampling Scheme \u003c\/b\u003e\u003cb\u003e121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Concept of Exponentially Weighted Moving Average (EWMA) Methodology 121\u003c\/p\u003e \u003cp\u003e5.2 Attraction of EWMA Methodology in Manufacturing Scenario 126\u003c\/p\u003e \u003cp\u003e5.3 Development of EWMA Control Chart for Monitoring Averages 127\u003c\/p\u003e \u003cp\u003e5.4 Development of EWMA Control Chart for Repetitive Sampling Scheme 127\u003c\/p\u003e \u003cp\u003e5.5 EWMA Control Chart for Repetitive Sampling Using Mean Deviation 128\u003c\/p\u003e \u003cp\u003e5.6 EWMA Control Chart for Sign Statistic Using the Repetitive Sampling Scheme 139\u003c\/p\u003e \u003cp\u003e5.7 Designing of a Hybrid EWMA (HEWMA) Control Chart Using Repetitive Sampling 147\u003c\/p\u003e \u003cp\u003eReferences 154\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Sampling Schemes for Developing Control Charts \u003c\/b\u003e\u003cb\u003e161\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Single Sampling Scheme 161\u003c\/p\u003e \u003cp\u003e6.2 Double Sampling Scheme 162\u003c\/p\u003e \u003cp\u003e6.3 Repetitive Sampling Scheme 165\u003c\/p\u003e \u003cp\u003e6.3.1 When a Shift of \u003ci\u003eμ\u003c\/i\u003e\u003csub\u003e\u003ci\u003e1\u003c\/i\u003e\u003c\/sub\u003e = \u003ci\u003eμ\u003c\/i\u003e + kσ Occurs in the Process 169\u003c\/p\u003e \u003cp\u003e6.4 Mixed Sampling Scheme 176\u003c\/p\u003e \u003cp\u003e6.4.1 Mixed Control Chart Using Exponentially Weighted Moving Average (EWMA) Statistics 179\u003c\/p\u003e \u003cp\u003e6.5 Mixed Control Chart Using Process Capability Index 180\u003c\/p\u003e \u003cp\u003e6.5.1 Analysis Through Simulation Approach 187\u003c\/p\u003e \u003cp\u003eReferences 187\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Memory-Type Control Charts for Attributes \u003c\/b\u003e\u003cb\u003e191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Exponentially Weighted Moving Average (EWMA) Control Charts for Attributes 191\u003c\/p\u003e \u003cp\u003e7.1.1 Binomial EWMA Charts 192\u003c\/p\u003e \u003cp\u003e7.1.2 Poisson EWMA (PEWMA) Chart 194\u003c\/p\u003e \u003cp\u003ePerformance Evaluation Measure 196\u003c\/p\u003e \u003cp\u003eCalculation of ARLs Using the Markov Chain Approach 196\u003c\/p\u003e \u003cp\u003e7.1.3 Other EWMA Charts 202\u003c\/p\u003e \u003cp\u003eGeometric EWMA Chart 202\u003c\/p\u003e \u003cp\u003eConway–Maxwell–Poisson (COM–Poisson) EWMA Chart 204\u003c\/p\u003e \u003cp\u003e7.2 CUSUM Control Charts for Attributes 209\u003c\/p\u003e \u003cp\u003e7.2.1 Binomial CUSUM Chart 210\u003c\/p\u003e \u003cp\u003e7.2.2 Poisson CUSUM Chart 215\u003c\/p\u003e \u003cp\u003e7.2.3 Geometric CUSUM Chart 217\u003c\/p\u003e \u003cp\u003e7.2.4 COM–Poisson CUSUM Chart 219\u003c\/p\u003e \u003cp\u003ePerformance Measure 219\u003c\/p\u003e \u003cp\u003e7.3 Moving Average (MA) Control Charts for Attributes 220\u003c\/p\u003e \u003cp\u003e7.3.1 Binomial MA Chart 221\u003c\/p\u003e \u003cp\u003e7.3.2 Poisson MA Chart 223\u003c\/p\u003e \u003cp\u003e7.3.3 Other MA Charts 225\u003c\/p\u003e \u003cp\u003eReferences 226\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Multivariate Control Charts for Attributes \u003c\/b\u003e\u003cb\u003e231\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Multivariate Shewhart-Type Charts 231\u003c\/p\u003e \u003cp\u003e8.1.1 Multivariate Binomial Chart 231\u003c\/p\u003e \u003cp\u003eChoice of Sample Size 233\u003c\/p\u003e \u003cp\u003e8.1.2 Multivariate Poisson (MP) Chart 234\u003c\/p\u003e \u003cp\u003e8.1.3 Multivariate Conway–Maxwell–Poisson (COM–Poisson) Chart 239\u003c\/p\u003e \u003cp\u003e8.2 Multivariate Memory-Type Control Charts 243\u003c\/p\u003e \u003cp\u003e8.2.1 Multivariate EWMA Charts for Binomial Process 243\u003c\/p\u003e \u003cp\u003eDesign of MEWMA Chart 244\u003c\/p\u003e \u003cp\u003e8.2.2 Multivariate EWMA Charts for Poisson Process 245\u003c\/p\u003e \u003cp\u003e8.3 Multivariate Cumulative Sum (CUSUM) Schemes 246\u003c\/p\u003e \u003cp\u003e8.3.1 Multivariate CUSUM Chart for Poisson Data 247\u003c\/p\u003e \u003cp\u003eReferences 248\u003c\/p\u003e \u003cp\u003eAppendix A: Areas of the Cumulative Standard Normal Distribution 251\u003c\/p\u003e \u003cp\u003eAppendix B: Factors for Constructing Variable Control Charts 253\u003c\/p\u003e \u003cp\u003eIndex 255\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eMUHAMMAD ASLAM\u003c\/b\u003e, Ph.D., is a Professor in the Department of Statistics at King Abdulaziz University at Jeddah, Saudi Arabia. He was awarded the \"Research Productivity Award for the year\" in 2012 by Pakistan Council for Science and Technology. He is the founder of neutrosophic statistical quality control and neutrosophic inferential statistics. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAAMIR SAGHIR\u003c\/b\u003e, Ph.D., is a Professor in the Department of Mathematics at Mirpur University of Science and Technology. He received his Ph.D. in Statistics from Zhejiang University in China. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eLIAQUAT AHMAD\u003c\/b\u003e, Ph.D., is an Associate Professor in the Department of Statistics and Computer Science at the University of Veterinary and Animal Sciences, Lahore, Pakistan. He's taught Statistics for over 24 years at the Ph.D. and M. Phil levels.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAN INTRODUCTION TO THE FUNDAMENTALS AND HISTORY OF CONTROL CHARTS, APPLICATIONS, AND GUIDELINES FOR IMPLEMENTATION\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003ci\u003eIntroduction to Statistical Process Control\u003c\/i\u003e examines various types of control charts that are typically used by engineering students and practitioners. This book helps readers develop a better understanding of the history, implementation, and use-cases. Students are presented with varying control chart techniques, information, and roadmaps to ensure their control charts are operating efficiently and producing specification-confirming products. This is the essential text on the theories and applications behind statistical methods and control procedures. \u003c\/p\u003e\u003cp\u003eThis eight-chapter reference breaks information down into digestible sections and covers topics including: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eAn introduction to the basics as well as a background of control charts\u003c\/li\u003e \u003cli\u003eWidely used and newly researched attributes of control charts, including guidelines for implementation\u003c\/li\u003e \u003cli\u003eThe process capability index for both normal and non-normal distribution via the sampling of multiple dependent states\u003c\/li\u003e \u003cli\u003eAn overview of attribute control charts based on memory statistics\u003c\/li\u003e \u003cli\u003eThe development of control charts using EQMA statistics\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eFor a solid understanding of control methodologies and the basics of quality assurance, \u003ci\u003eIntroduction to Statistical Process Control\u003c\/i\u003e is a definitive reference designed to be read by practitioners and students alike. It is an essential textbook for those who want to explore quality control and systems design.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989466956005,"sku":"NP9781119528456","price":123.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119528456.jpg?v=1761784215","url":"https:\/\/k12savings.com\/products\/introduction-to-statistical-process-control-isbn-9781119528456","provider":"K12savings","version":"1.0","type":"link"}