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"In the early 1990s, the process industries recognized that they would face a major staffing shortage because of the large number of "baby boomer" employees who would be retiring. Industry partnered with community colleges, technical colleges, and universities to remedy this situation. These collaborators in education and industry recognized that pre-training for process technicians would benefit industry by reducing the costs associated with training and traditional hiring methods. They recognized that teachers needed consistent curriculum content and exit competencies in order to produce process technology graduates who would be knowledgeable, competent, and able to take over the demands of the field. This was how the NAPTA series on Process Technology was born"--
Using actual examples of software process improvement from the private sector and government, this work demonstrates how quality systems, measurement techniques and performance evaluations work. It presents a methodology for analyzing an ongoing software development process and establishing a rational plan for process improvement.
Using actual examples of software process improvement from the private sector and government, this work demonstrates how quality systems, measurement techniques and performance evaluations work. It presents a methodology for analyzing an ongoing software development process and establishing a rational plan for process improvement.
Ellis Ott taught generations of quality practitioners to be explorers of the truth through the collection and graphical portrayal of data. From a simple plea to "plot the data" to devising a graphical analytical tool called the analysis of means (ANOM), Ott demonstrated that process knowledge is to be gained by seeking the information contained within the data.In this newest version of Ott's classic text, the authors have strived to continue down the path that he created for others to follow. Additions to this revised edition include: the use of dot plots as an alternative to histograms; digidot plots; adding events to charts; emphasis on the role that acceptance control charts play in controlling risks and the computation of average run length (ARL); a new chapter devoted to process capability, process performance, and process improvement, including the use of confidence intervals for process capability metrics; narrow-limit gauging as another means of assessing the capability of a process; Six Sigma methodology; design resolution; scatter plot matrices as applied to datasets of higher dimensions; and a new chapter on measurement studies.
Introduction -- Hardware Integration -- Software Integration -- Integration of Statistical Methods -- Facility Integration -- Summary -- References -- CHAPTER 11: Factory of the Future -- Introduction -- Manufacturing Cells -- Flexible Manufacturing Systems -- Material Handling -- Fault Tolerance -- References -- Index
This book provides a common sense computer-oriented, determinstic manufacturing approach, which employs statistics but does not require a background in this area, theoretical mathematics or computer science to understand and apply. In a clear, easy-to-read style, this reference text highlights critical parameters that have a major impact upon process quality and identifies sensors for parameter monitoring; discusses appropriate applications of deterministic techniques to many manifacturing situations ranging from simple to complex; includes chapter summaries, helpful illustrations and numerous citations to ehnance comprehension and facilitate further research. Written from the perspective of a practioner who 'knows how to make parts'; presenting practical solutions to manufacturing problems it is essential reading for industrial, quality control, electrical and electronics, mechancial, manufacturing and systems engineers/managers and undergraduate and graduate-level students in the above areas.
- over 100 illustrations amplify the text, adding clarity to the discussion of the techniques of quality- examples depict challenges typically encountered in the world of quality and process improvement- chapter-end problems allow readers to set up experiments, giving them confidence in their newly acquired abilities- CD-ROM with Excel examples is included with text
The financial markets industry is at the same crossroads as the automotive industry in the late 1970s. Margins are collapsing and customization is rapidly increasing. The automotive industry turned to quality and its no coincidence that in the money management industry many of the spectacular failures have been due largely to problems in quality control. The financial industry in on the verge of a quality revolution. New and old firms alike are creating new investment vehicles and new strategies that are radically changing the nature of the industry. To compete, mutual funds, hedge fund industries, banks and proprietary trading firms are being forced to quicklyy research, test and implement trade selection and execution systems. And, just as in the early stages of factory automation, quality suffers and leads to defects. Many financial firms fall short of quality, lacking processes and methodologies for proper development and evaluation of trading and investment systems. Authors Kumiega and Van Vliet present a new step-by-step methodology for such development. Their methodology (called K - Presents a robust process engineering framework for developing and evaluating trading and investment systems - Best practices along the step-by-step process will mitigate project risk, model risk, and ensure data quality - Includes a quality model for backtesting and managing market risk of working systems
This handbook is designed as a reference for ASQ's Certified Quality Process Analyst (CQPA) Body of Knowledge (BoK), providing the essential information needed to prepare for the CQPA examination. The handbook is aimed at quality professionals who, in support of and under the direction of quality engineers or supervisors, analyze and solve quality problems and are involved in quality improvement projects. It's ideal for recent graduates and experienced professionals who want to expand their knowledge of quality tools and processes. There are five main sections in the CQPA Body of Knowledge, further subdivided into related subsections. These sections are: Quality Concepts and Team Dynamics Quality Tools and Process Improvement Techniques Data Analysis Customer-Supplier Relations Corrective and Preventive Action (CAPA) This updated edition has been revised and expanded to match the 2020 BoK with enhancements to: tools for assessing training effectiveness best practices on the Six Sigma DMAIC methodology and process maps with a focus on process architecture examples of lean and value analysis, Theory of Constraints risk management, business process management and lifecycle phases the importance of data collection and analysis, data integrity, validity, and reliability examples of gage R&;R and attribute agreement analysis Sandra L. Furtererspan, BS, MS, MBA, PhD, is an associate professor at the University of Dayton in the Department of Engineering Management, Systems and Technology. She is an ASQ Certified Six Sigma Black Belt, Certified Manager of Quality/ Organizational Excellence, Certified Quality Engineer, an ASQ fellow, and a certified Six Sigma Master Black Belt. She is also a contributor to ASQ's certification handbooks (CMQ/OE and CQIA) and a prolific speaker.