Handbook of Multivariate Process Capability Indices PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Handbook of Multivariate Process Capability Indices PDF full book. Access full book title Handbook of Multivariate Process Capability Indices by Ashis Kumar Chakraborty. Download full books in PDF and EPUB format.
Author: Ashis Kumar Chakraborty Publisher: CRC Press ISBN: 1000222039 Category : Business & Economics Languages : en Pages : 334
Book Description
Providing a single-valued assessment of the performance of a process is often one of the greatest challenges for a quality professional. Process Capability Indices (PCIs) precisely do this job. For processes having a single measurable quality characteristic, there is an ample number of PCIs, defined in literature. The situation worsens for multivariate processes, i.e., where there is more than one correlated quality characteristic. Since in most situations quality professionals face multiple quality characteristics to be controlled through a process, Multivariate Process Capability Indices (MPCIs) become the order of the day. However, there is no book which addresses and explains different MPCIs and their properties. The literature of Multivariate Process Capability Indices (MPCIs) is not well organized, in the sense that a thorough and systematic discussion on the various MPCIs is hardly available in the literature. Handbook of Multivariate Process Capability Indices provides an extensive study of the MPCIs defined for various types of specification regions. This book is intended to help quality professionals to understand which MPCI should be used and in what situation. For researchers in this field, the book provides a thorough discussion about each of the MPCIs developed to date, along with their statistical and analytical properties. Also, real life examples are provided for almost all the MPCIs discussed in the book. This helps both the researchers and the quality professionals alike to have a better understanding of the MPCIs, which otherwise become difficult to understand, since there is more than one quality characteristic to be controlled at a time. Features: A complete guide for quality professionals on the usage of different MPCIs. A step by step discussion on multivariate process capability analysis, starting from a brief discussion on univariate indices. A single source for all kinds of MPCIs developed so far. Comprehensive analysis of the MPCIs, including analysis of real-life data. References provided at the end of each chapter encompass the entire literature available on the respective topic. Interpretation of the MPCIs and development of threshold values of many MPCIs are also included. This reference book is aimed at the post graduate students in Industrial Statistics. It will also serve researchers working in the field of Industrial Statistics, as well as practitioners requiring thorough guidance regarding selection of an appropriate MPCI suitable for the problem at hand.
Author: Ashis Kumar Chakraborty Publisher: CRC Press ISBN: 1000222039 Category : Business & Economics Languages : en Pages : 334
Book Description
Providing a single-valued assessment of the performance of a process is often one of the greatest challenges for a quality professional. Process Capability Indices (PCIs) precisely do this job. For processes having a single measurable quality characteristic, there is an ample number of PCIs, defined in literature. The situation worsens for multivariate processes, i.e., where there is more than one correlated quality characteristic. Since in most situations quality professionals face multiple quality characteristics to be controlled through a process, Multivariate Process Capability Indices (MPCIs) become the order of the day. However, there is no book which addresses and explains different MPCIs and their properties. The literature of Multivariate Process Capability Indices (MPCIs) is not well organized, in the sense that a thorough and systematic discussion on the various MPCIs is hardly available in the literature. Handbook of Multivariate Process Capability Indices provides an extensive study of the MPCIs defined for various types of specification regions. This book is intended to help quality professionals to understand which MPCI should be used and in what situation. For researchers in this field, the book provides a thorough discussion about each of the MPCIs developed to date, along with their statistical and analytical properties. Also, real life examples are provided for almost all the MPCIs discussed in the book. This helps both the researchers and the quality professionals alike to have a better understanding of the MPCIs, which otherwise become difficult to understand, since there is more than one quality characteristic to be controlled at a time. Features: A complete guide for quality professionals on the usage of different MPCIs. A step by step discussion on multivariate process capability analysis, starting from a brief discussion on univariate indices. A single source for all kinds of MPCIs developed so far. Comprehensive analysis of the MPCIs, including analysis of real-life data. References provided at the end of each chapter encompass the entire literature available on the respective topic. Interpretation of the MPCIs and development of threshold values of many MPCIs are also included. This reference book is aimed at the post graduate students in Industrial Statistics. It will also serve researchers working in the field of Industrial Statistics, as well as practitioners requiring thorough guidance regarding selection of an appropriate MPCI suitable for the problem at hand.
Author: Ashis Kumar Chakraborty Publisher: CRC Press ISBN: 1000222136 Category : Business & Economics Languages : en Pages : 250
Book Description
Providing a single-valued assessment of the performance of a process is often one of the greatest challenges for a quality professional. Process Capability Indices (PCIs) precisely do this job. For processes having a single measurable quality characteristic, there is an ample number of PCIs, defined in literature. The situation worsens for multivariate processes, i.e., where there is more than one correlated quality characteristic. Since in most situations quality professionals face multiple quality characteristics to be controlled through a process, Multivariate Process Capability Indices (MPCIs) become the order of the day. However, there is no book which addresses and explains different MPCIs and their properties. The literature of Multivariate Process Capability Indices (MPCIs) is not well organized, in the sense that a thorough and systematic discussion on the various MPCIs is hardly available in the literature. Handbook of Multivariate Process Capability Indices provides an extensive study of the MPCIs defined for various types of specification regions. This book is intended to help quality professionals to understand which MPCI should be used and in what situation. For researchers in this field, the book provides a thorough discussion about each of the MPCIs developed to date, along with their statistical and analytical properties. Also, real life examples are provided for almost all the MPCIs discussed in the book. This helps both the researchers and the quality professionals alike to have a better understanding of the MPCIs, which otherwise become difficult to understand, since there is more than one quality characteristic to be controlled at a time. Features: A complete guide for quality professionals on the usage of different MPCIs. A step by step discussion on multivariate process capability analysis, starting from a brief discussion on univariate indices. A single source for all kinds of MPCIs developed so far. Comprehensive analysis of the MPCIs, including analysis of real-life data. References provided at the end of each chapter encompass the entire literature available on the respective topic. Interpretation of the MPCIs and development of threshold values of many MPCIs are also included. This reference book is aimed at the post graduate students in Industrial Statistics. It will also serve researchers working in the field of Industrial Statistics, as well as practitioners requiring thorough guidance regarding selection of an appropriate MPCI suitable for the problem at hand.
Author: Samuel Kotz Publisher: CRC Press ISBN: 1351421409 Category : Business & Economics Languages : en Pages : 224
Book Description
A solid, rigorous, yet comprehensible analysis of process capability indices, this work bridges the gap between theoretical statisticians and quality control practitioners, showing how an understanding of these indices can lead to process improvement.
Author: Wen-lea Pearn Publisher: World Scientific ISBN: 9814478113 Category : Technology & Engineering Languages : en Pages : 391
Book Description
This unique volume provides an up-to-date and detailed description of the various process capability indices widely (and sometimes misleadingly) used in the applications at production sites. The authors, who are internationally recognized experts in this area with numerous contributions to the field, provide a lucid exposition, which covers all the main aspects, developments and advances.The concept of Process Capability Index (PCI) is barely 20 years old, but the multitude of available versions can overwhelm even the most seasoned practitioner. The organized and self-contained presentation of the material starting from 1980's primitive indices (Cp and Cpk) up to the newly proposed indices for the cases of multiple dependent characteristics results in an authoritative and indispensable reference.A proper balance between theoretical investigation and “rule-of-thumb” practical procedures is maintained in order to eliminate the tensions among various methodologies of assessing the capability of industrial processes.
Author: Neil W. Polhemus Publisher: CRC Press ISBN: 1315405725 Category : Business & Economics Languages : en Pages : 206
Book Description
Process Capability Analysis: Estimating Quality presents a systematic exploration of process capability analysis and how it may be used to estimate quality. The book is designed for practitioners who are tasked with insuring a high level of quality for the products and services offered by their organizations. Along with describing the necessary statistical theory, the book illustrates the practical application of the techniques to data that do not always satisfy the standard assumptions. The first two chapters deal with attribute data, where the estimation of quality is restricted to counts of nonconformities. Both classical and Bayesian methods are discussed. The rest of the book deals with variable data, including extensive discussions of both capability indices and statistical tolerance limits. Considerable emphasis is placed on methods for handling non-normal data. Also included are discussions of topics often omitted in discussions of process capability, including multivariate capability indices, multivariate tolerance limits, and capability control charts. A separate chapter deals with the problem of determining adequate sample sizes for estimating process capability. Features: Comprehensive treatment of the subject with consistent theme of estimating percent of nonconforming product or service. Includes Bayesian methods. Extension of univariate techniques to multivariate data. Demonstration of all techniques using Statgraphics data analysis software. Neil Polhemus is Chief Technology Officer at Statgraphics Technology and the original developer of the Statgraphics program for statistical analysis and data visualization. Dr. Polhemus spent 6 years on the faculty of the School of Engineering and Applied Science at Princeton University before moving full-time to software development and consulting. He has taught courses dealing with statistical process control, design of experiments and data analysis for more than 100 companies and government agencies.
Author: Rachel Goodwin Publisher: ISBN: Category : Mathematical statistics Languages : en Pages : 79
Book Description
Process capability indices (PCIs) play an important role in the field of Statistical Process Control. Prior to the last 25 years, PCIs had been formulated to assess the quality of a single product characteristic. Product quality, however, is typically dependent on several related variables. Therefore, there is a great need for multivariate process capability indices (MPCIs). The quality of a product is almost always determined from sample data. Thus, it is imperative that an MPCI has a corresponding confidence interval. In that way, conclusions may be drawn regarding the capability of the process that makes that product. Of the MPCIs proposed over the last 25 years, few have an accompanying confidence interval. Under the assumption of multivariate normality, we propose four new MPCIs, each having a corresponding confidence interval, as well as a decision rule for determining whether a process can be declared capable or not at a given level of significance. Two of the indices are based on principal component analysis (PCA) while the other two rely on non-PCA linear transformations. The indices we propose represent multivariate extensions of the popular univariate index, Cp. Current indices that extend Cp to the multivariate domain are referred to as MCps. From this group we select four indices that have accompanying confidence intervals to use in a comparative study with our own. The selected indices have been criticized in the past by other authors for different reasons. Upon investigation we find that our proposed indices do not suffer from the same limitations as the others and that they may serve as adequate tools for assessing multivariate capability in a manufacturing environment.
Author: Ashis Kumar Chakraborty
Author: Ashis Kumar Chakraborty
Author: Pak Fai Tang
Author: Ashis Kumar Chakraborty
Author: Samuel Kotz
Author: Allen Lynn Lewis
Author: Wen-lea Pearn
Author: Neil W. Polhemus
Author: Rachel Goodwin
Author: Steven J. Littig, C. Teresa Laro and Stephen M. Pollock
Author: 黃冠禎