Industry X.0 takes an insightful look at the business impact of the Internet of Things movement on the industrial sphere. Eric Schaeffer combines deep analysis with practical strategic guidance, and offers tangible and actionable recommendations on how to realise value in the current digital age. Based on extensive research and insights into the six core competencies that have been identified by Accenture, Industry X.0 explores critical aspects of the Industrial Internet of Things (IIoT), discussing and defining them in an engaging and accessible manner. These include managing smart data, handling digital product development, skilling up the workforce, mastering innovation, making the most of platforms and ecosystems, and much more. Meticulously researched and clearly explained, Industry X.0 makes a stringent case for companies to actively shift mind-sets away from products, towards services, value and outcomes. Complemented by a wealth of case studies and real world examples, this book provides invaluable, practical 'how-to' advice for business organizations as they embark on their journeys into the era of the IIoT.

Create the personalized and compelling experiences that today's customers expect by harnessing AI and digital technologies to create smart connected products, with this cutting-edge guide from senior leaders at Accenture. Digital technology is both friend and foe: highly disruptive, yet it cannot be ignored. As traditional products transform into smart connected products faster than ever before, companies that fail to make use of it now put themselves in the firing line for disintermediation or even eradication. However, digital technology is also the biggest opportunity for product-making businesses to create the next generation of goods in the marketplace. In Reinventing the Product, Eric Schaeffer and David Sovie, both Senior Managing Directors at Accenture, show how this reinvention is made possible, to deliver truly intelligent, and often even autonomous, products. Reinventing the Product makes the case for companies to rethink their product strategy, innovation and engineering processes, including: - How to harness the opportunities of AI and digital technologies, such as IoT sensors, blockchain, advanced analytics, cloud and edge computing - Practical advice on transforming their entire culture to build the future of successful 'living products' - Features case studies from global organizations such as Faurecia, Signify, Symmons and Haier and interviews with thought leaders from top companies including Amazon, ABB, Tesla, Samsung and Google This book provides the only advice any product-making company needs as it embarks on, or accelerates, its digitization journey.

Modern Industrial Statistics The new edition of the prime reference on the tools of statistics used in industry and services, integrating theoretical, practical, and computer-based approaches Modern Industrial Statistics is a leading reference and guide to the statistics tools widely used in industry and services. Designed to help professionals and students easily access relevant theoretical and practical information in a single volume, this standard resource employs a computer-intensive approach to industrial statistics and provides numerous examples and procedures in the popular R language and for MINITAB and JMP statistical analysis software. Divided into two parts, the text covers the principles of statistical thinking and analysis, bootstrapping, predictive analytics, Bayesian inference, time series analysis, acceptance sampling, statistical process control, design and analysis of experiments, simulation and computer experiments, and reliability and survival analysis. Part A, on computer age statistical analysis, can be used in general courses on analytics and statistics. Part B is focused on industrial statistics applications. The fully revised third edition covers the latest techniques in R, MINITAB and JMP, and features brand-new coverage of time series analysis, predictive analytics and Bayesian inference. New and expanded simulation activities, examples, and case studies—drawn from the electronics, metal work, pharmaceutical, and financial industries—are complemented by additional computer and modeling methods. Helping readers develop skills for modeling data and designing experiments, this comprehensive volume: Explains the use of computer-based methods such as bootstrapping and data visualization Covers nonstandard techniques and applications of industrial statistical process control (SPC) charts Contains numerous problems, exercises, and data sets representing real-life case studies of statistical work in various business and industry settings Includes access to a companion website that contains an introduction to R, sample R code, csv files of all data sets, JMP add-ins, and downloadable appendices Provides an author-created R package, mistat, that includes all data sets and statistical analysis applications used in the book Part of the acclaimed Statistics in Practice series, Modern Industrial Statistics with Applications in R, MINITAB, and JMP, Third Edition, is the perfect textbook for advanced undergraduate and postgraduate courses in the areas of industrial statistics, quality and reliability engineering, and an important reference for industrial statisticians, researchers, and practitioners in related fields. The mistat R-package is available from the R CRAN repository.