Pragmatic Big Data and smart manufacturing

Abstract

Abstract. Smart manufacturing is usually associated with fancy cobots and automated production lines. But the Big Data ecosystem has a part to play, and is probably faster and cheaper to start with. The numerical revolution has dramatically accelerated these last years, with many implications in different industries. We propose in this article to present these new tools, and discuss some real use cases. We will also present the best practices and some of the inevitable challenges related to data projects.The upcoming Industry 4.0 movement is full of promises. However, many still think it is the vision of a distant future, implying heavy changes and new fancy but expensive machines and tools. But it is first and foremost a digital transformation, and as such, will generate its share of data. It will therefore be possible to leverage the Big Data technological ecosystem to: -harness and bring value out of the data, -improve quality and conformance, -automate controls on the production line, -have a tight control on industrial and manufacturing processes as well as on the machinery and tools.

An overview of big data analytics application in supply chain management published in 2010-2019

“…In each stage, a lot of data is generated, and by collecting this data for all products, we can have a dataset with big data characteristics. Five areas of big data application in manufacturing are (Benhenni, 2017): 1-using data to forecast a complex process's output; 2-using data to capture that which is difficult to measure under regular conditions, 3-developing algorithms which can more accurately control the quality and safety of the final product; 4-using image metrology to reduce the amount of human supervision required; and finally, 5-obtaining the optimal time for doing predictive maintenance.…”