Problem-solving based, as much as possible, on real data, expert knowledge, and on-field observation are quite desired objectives. However, it creates several difficulties on deployment in real situations. In this work, a data-driven version of the well-known PDCA cycle is proposed for continuous improvement within a general class of problems represented by key performance indicators (KPI). Such class is wide enough to accommodate several real problems but still has a controlled level of complexity that allows defining a general data-driven protocol that covers all the (sub)steps of the cycle. New approaches and alternatives in the literature are discussed. A brief example of one of the steps of the protocol is given with real data from a company that adopts many of the new Industry 4.0 technologies.
Track: Continuous Improvement
Published in: 12th Annual International Conference on Industrial Engineering and Operations Management, Istanbul, Turkey
Publisher: IEOM Society International
Date of Conference: March 7
-10
, 2022
ISBN: 978-1-7923-6131-9
ISSN/E-ISSN: 2169-8767