Statistical Quality Control: Using Minitab, R, Jmp and Python

ISBN-13: 9781119671633 / Angielski / Twarda / 2021 / 400 str.

Bhisham C. Gupta

Spis treści

Chapter 1- QUALITY IMPROVEMENT AND MANAGEMENT11.1 Introduction 11.2 Statistical Quality Control 11.3 Implementing Quality Improvement 91.4 Managing Quality Improvement 15Chapter 2 - BASIC CONCEPTS OF THE SIX SIGMA METHODOLOGY202.1 Introduction 202.2 What is Six Sigma? 202.3 Is Six Sigma New? 292.4 Quality Tools Used in Six Sigma 302.5 Six Sigma Benefits and Criticism 40Review Practice Problems 42Chapter 3- DESCRIBING QUANTITATIVE AND QUALITATIVE DATA 443.1 Introduction 443.2 Classification of Various Types of Data 443.3 Analyzing Data Using Graphical Tools 473.4 Describing Data Graphically523.5 Analyzing Data Using Numerical Tools 713.6 Some Important Probability Distributions 87Review Practice Problems107Chapter 4 - SAMPLING METHODS 1184.1 Introduction 1184.2 Basic Concepts of Sampling 1184.3 Simple Random Sampling1234.4 Stratified Random Sampling 1324.5 Systematic Random Sampling1394.6 Cluster Random Sampling145Review Practice Problems 151Chapter 5 - Phase I Quality Control Charts for Variables 1575.1 Introduction 1575.2 Basic Definition of Quality and its Benefits1585.3 Statistical Process Control1595.4 Control Charts for Variables 1705.5 Shewhart and R Control Charts when Process Mean and Standard Deviation Known 1945.6 Process Capability211Review Practice Problems 213Chapter 6 - Phase I Control Charts for Attributes 2236.1 Introduction 2236.2 Control Charts for Attributes 2236.3 The p chart: Control Chart for Fraction Nonconforming with Constant Samples Sizes2256.4 The c-Control chart - Control chart for nonconformities per sample 2376.5 The U-Chart 242Review Practice Problems 249Chapter 7 - Phase II Control Charts for Detecting Small Shifts2567.1 Introduction 2567.2 Basic Concepts of CUSUM Control Chart2577.3 Designing a CUSUM Control Chart 2617.4 Moving Average Control Chart 2797.5 Exponentially Weighted Moving Average Control Chart 284Review Practice Problems292Chapter 8 - Process and Measurement System Capability Analysis 2988.1 Introduction 2988.2 Development of Process Capability Indices3008.3 Various Process Capability Indices 3028.4 The Pre-control 3268.5 Measurement System Capability Analysis 334Review Practice Problems 354Chapter 9 - ACCEPTANCE SAMPLING PLANS 3639.1 Introduction3639.2 The Intent of Acceptance of Sampling Plan 3639.3 Sampling Inspection Versus 100 Percent Inspection 3649.4 Classification of Sampling Plans 3649.5 Acceptance Sampling by Attributes 3719.6 Single Sampling Plans for Attributes 3759.7 Other Types of Sampling Plans for Attributes 3769.8 Sampling Standards and Plans 3869.9 Dodge-Romig Tables 3929.10 Acceptance Sampling Plans By variables 3929.11 Continuous Sampling Plans 399Review Practice Problems 401Chapter 10 - CPMPUTER RESOURCES TO SUPPORT SQC 42710.1 Introduction42710.2 Using MINITAB10.3 Using R10.4 Using JMP10.5 Using PYTHON

O autorze

Bhisham C. Gupta, PhD, is Professor Emeritus of Statistics at the University of Southern Maine, where he has taught for 31 years. Prior to coming to USM as a full professor in 1985, Dr. Gupta served for 21 years at various institutions in Canada, Brazil, and India. He is the co-author of Statistics and Probability with Applications for Engineers and Scientists, First Edition and Second Edition, as well as the accompanying solutions manuals, all published by Wiley. He is also co-author of three books published by American Society for Quality (ASQ).