LEADER 03727nam 2200457 450 001 9910810060103321 005 20230627034101.0 010 $a1-119-67172-8 010 $a1-119-67171-X 010 $a1-119-67170-1 035 $a(CKB)4100000011990674 035 $a(MiAaPQ)EBC6683936 035 $a(Au-PeEL)EBL6683936 035 $a(OCoLC)1262371205 035 $a(EXLCZ)994100000011990674 100 $a20220412d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistical quality control using Minitab, R, JMP, and Python /$fBhisham C. Gupta 210 1$aHoboken, New Jersey :$cJohn Wiley & Sons, Inc.,$d[2021] 210 4$d??2021 215 $a1 online resource (393 pages) 311 $a1-119-67163-9 320 $aIncludes bibliographical references and index. 330 0 $aThis book introduces Statistical Quality Control and elements of Six Sigma Methodology, both of which have widespread application. Chapter 1 of this book begins with a brief discussion of the different types of data encountered in various fields of statistical applications. Some terminology is also defined. Then, the authors introduce certain graphical and numerical tools needed to do some preliminary analysis of these data. In Chapter 2 the basic concept of statistical quality control (SQC) is discussed. The basic concept of Six Sigma Methodology is also introduced. In Chapter 3, the author briefly covers different types of sampling methods, which are encountered whenever we use sampling schemes to study certain populations. Chapter 4 discusses the Phase 1 Control Charts for variables. Phase 1 Control Charts for attributes is covered in Chapter 5. Next, the Phase II Control Charts to detect small shifts is discussed in Chapter 6. In Chapter 7, the author discusses the various types of Process Capability Indices (CPI). Next, in Chapter 8, the book covers certain aspects of Measurement System Analysis (MSA). The book continues with a discussion of various aspects of PRE-control in Chapter 9, which is an important tool of SQC. Chapter 10 covers various kinds of acceptance sampling schemes which are still used at certain places in the world. Finally, Chapter 11 discusses the latest version 19 of MINITAB and R. Using these software packages, the author covers various SQC techniques. After going through the material presented in this chapter, the reader will be able to analyze, using R and/or MINITAB, all the SQC techniques discussed in this book and implement them in various sectors whenever and wherever high-quality products are desired. Statistical quality control refers to the use of statistical methods in the monitoring and maintaining of the quality of products and services. One method, referred to as acceptance sampling, can be used when a decision must be made to accept or reject a group of parts or items based on the quality found in a sample. A second method, referred to as statistical process control, uses graphical displays known as control charts to determine whether a process should be continued or should be adjusted to achieve the desired quality. 606 $aQuality control$xStatistical methods 606 $aSix sigma (Quality control standard) 615 0$aQuality control$xStatistical methods. 615 0$aSix sigma (Quality control standard) 676 $a658.5620218 700 $aGupta$b Bhisham C.$f1942-$01611178 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910810060103321 996 $aStatistical quality control using Minitab, R, JMP, and Python$94097852 997 $aUNINA