13Analytics as an Enabler of Advanced Manufacturing
Ron S. Kenett Inbal Yahav and Avigdor Zonnenshain
Synopsis
Knowledge and information are critical assets for any manufacturing enterprise. They enable businesses to differentiate themselves from competitors and compete efficiently and effectively to the best of their abilities. At present, information technology, telecommunications, and manufacturing are merging as the means of production are becoming increasingly autonomous. Advanced manufacturing, or Industry 4.0, is based on three interconnected pillars: (i) Computerized Product Design and Smart Technology; (ii) Smart Sensors, Internet of Things, and Data Collectors integrated in Manufacturing Lines; and (iii) Analytics, Control Theory and Data Science.
This chapter consists of a critical review of the third pillar of data analytics, and how it is related to the two other pillars. Our objective is to present a context for a range of analytic challenges in the Industry 4.0 context. We first provide a general introduction to advanced manufacturing elements followed by a listing of trends in modern analytic tools and technology. We then list challenges in analytics supporting Industry 4.0. The information quality (InfoQ) framework serves here as a backbone for evaluating the analytics technology required for Industry 4.0. The eight InfoQ dimensions are: (i) Data Resolution; (ii) Data Structure; (iii) Data Integration; (iv) Temporal Relevance; (v) Chronology of Data and Goal; ...
Get Systems Engineering in the Fourth Industrial Revolution now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.