THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

The purpose of this paper is to conduct a state-of-the-art review of the ongoing research on the Industry 4.0 phenomenon, highlight its key design principles and technology trends, identify its architectural design and offer a strategic roadmap that can serve manufacturers as a simple guide for the process of Industry 4.0 transition.,The study performs a systematic and content-centric review of literature based on a six-stage approach to identify key design principles and technology trends of Industry 4.0. The study further benefits from a comprehensive content analysis of the 178 documents identified, both manually and via IBM Watson’s natural language processing for advanced text analysis.,Industry 4.0 is an integrative system of value creation that is comprised of 12 design principles and 14 technology trends. Industry 4.0 is no longer a hype and manufacturers need to get on board sooner rather than later.,The strategic roadmap presented in this study can serve academicians and practitioners as a stepping stone for development of a detailed strategic roadmap for successful transition from traditional manufacturing into the Industry 4.0. However, there is no one-size-fits-all strategy that suits all businesses or industries, meaning that the Industry 4.0 roadmap for each company is idiosyncratic, and should be devised based on company’s core competencies, motivations, capabilities, intent, goals, priorities and budgets.,The first step for transitioning into the Industry 4.0 is the development of a comprehensive strategic roadmap that carefully identifies and plans every single step a manufacturing company needs to take, as well as the timeline, and the costs and benefits associated with each step. The strategic roadmap presented in this study can offer as a holistic view of common steps that manufacturers need to undertake in their transition toward the Industry 4.0.,The study is among the first to identify, cluster and describe design principles and technology trends that are building blocks of the Industry 4.0. The strategic roadmap for Industry 4.0 transition presented in this study is expected to assist contemporary manufacturers to understand what implementing the Industry 4.0 really requires of them and what challenges they might face during the transition process.

https://www.emerald.com/insight/content/doi/10.1108/JMTM-02-2018-0057/full/pdf

The future of manufacturing industry: a strategic roadmap toward Industry 4.0

Industry 4.0, digitization, and opportunities for sustainability

Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0

Fundamentals Of Neural Networks Architectures Algorithms And Applications

Traditional job shop scheduling is concentrated on centralized scheduling or semi-distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and distributed manufacturing system supported by novel and emerging manufacturing technologies such as mass customization, Cyber-Physics Systems, Digital Twin, and SMAC (Social, Mobile, Analytics, Cloud). The scheduling research needs to shift its focus to smart distributed scheduling modeling and optimization. In order to transferring traditional scheduling into smart distributed scheduling (SDS), we aim to answer two questions: (1) what traditional scheduling methods and techniques can be combined and reused in SDS and (2) what are new methods and techniques required for SDS. In this paper, we first review existing researches from over 120 papers and answer the first question and then we explore a future research direction in SDS and discuss the new techniques for developing future new JSP scheduling models and constructing a framework on solving the JSP problem under Industry 4.0.

/pdf/review-of-job-shop-scheduling-research-and-its-new-2zwek53yez.pdf

Review of job shop scheduling research and its new perspectives under Industry 4.0

How to model and implement connections between physical and virtual models for digital twin application

The determination of AGV vehicle requirements in a manufacturing system has a great impact on the system performance. This paper first defines the AGV vehicle requirement determination as a general...

/pdf/determination-of-vehicle-requirements-of-agv-system-based-on-3gchakh0kw.pdf

Jianlin Fu

Papers

Review of job shop scheduling research and its new perspectives under Industry 4.0

How to model and implement connections between physical and virtual models for digital twin application

Determination of vehicle requirements of AGV system based on discrete event simulation and response surface methodology