Download or read book Solving Complex Industrial Problems without Statistics written by Ralph R. Pawlak and published by CRC Press. This book was released on 2017-12-19 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting: Problem Solving Sans Statistics Enhance your problem-solving skills, and improve your company’s profitability using the methods outlined in Solving Complex Industrial Problems without Statistics. Introducing a process that involves working through problems and solutions without relying on complicated statistical design or analysis, this book pulls away from data-driven thinking and provides the problem solver with a new way of solving problems. Utilizing techniques that have been applied in facilities throughout the U.S., Canada, Italy, China, and Hong Kong, it demonstrates the use of process and problem differences and similarities, and provides a better understanding of analogous comparisons. The book incorporates visual analysis tools and problem examples in a format that facilitates comprehension and learning, presents novel concepts that do not require numbers or statistics, and provides a better understanding of the solution system/process overall. Each chapter presents new information, as well as case studies that include: Different problem situations Short histories detailing the operation, condition, and circumstances that were present at the time of each study Photographs, sketches, or tables with simple explanations to describe the circumstances, conditions, and the actions taken Methods of solution in rudimentary form Chapter summaries to review important mechanisms and workings Final summaries to tie together the important methods and techniques that facilitate easy problem solutions Solving Complex Industrial Problems without Statistics provides valuable insight into the solution of complex quality and manufacturing problems, without the use of statistics, and is essential to anyone involved in quality, control, problem-solving activities, or total quality management.