Towards Industry 4.0 Utilizing Data-Mining Techniques: a Case Study on Quality Improvement

The use of data-mining as an analytical tool has been increasing in recent years; and the emergence of new manufacturing paradigms such as the Industry 4.0 initiative have led many smaller manufacturers to look at utilizing these powerful techniques; however, practical applications are still in their infancy, and remain out of reach for many of these small manufacturing enterprises (SME's). This paper focuses on methods to integrate these emerging paradigms into existing manufacturing processes, specifically, how data-mining principles may be used to begin to explore the concept of Intelligent Manufacturing under Industry 4.0; with a focus on improving product and process quality. In collaboration with an industrial partner; a respected manufacturer of household electronic appliances, techniques were developed using open-source and freely-available software, running on readily available hardware and using only existing data-collection points, that were able to provide actionable feedback which could be used to make improvements to the manufacturing operations; and to increase product quality. This paper serves as evidence that the ability to utilise these techniques is now within reach of numerous smaller manufacturing operations, and provides a further understanding of how moves towards fully Industry 4.0 ready factories may be made in the years to come. (c) 2017 The Authors. Published by Elsevier B.V.