%0 Conference Proceedings
%T Study of the Predictive Mechanism with Big Data-Driven Lean Manufacturing and Six Sigma Methodology
%+ College of Electrical Engineering [Zhejiang]
%A Chen, Hong
%A Wu, Jiande
%A Zhang, Wei
%A Guo, Qing
%A Lu, Huifeng
%Z Part 14: The New Digital Lean Manufacturing Paradigm
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B IFIP International Conference on Advances in Production Management Systems (APMS)
%C Nantes, France
%Y Alexandre Dolgui
%Y Alain Bernard
%Y David Lemoine
%Y Gregor von Cieminski
%Y David Romero
%I Springer International Publishing
%3 Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems
%V AICT-633
%N Part IV
%P 662-672
%8 2021-09-05
%D 2021
%R 10.1007/978-3-030-85910-7_70
%K Predictive mechanism
%K Lean manufacturing
%K Six sigma
%K DMAIC
%K Statistical process control
%K Hypothesis testing
%Z Computer Science [cs]Conference papers
%X In order to achieve the sustainable development, the predictive mechanism with big data-driven Lean Manufacturing and Six Sigma methodology is proposed in this paper. The sustainable development for serious competition is often studied, however, the predictive mechanism with big data-driven Lean Manufacturing and Six Sigma methodology is seldom mentioned in publications. This paper reports the predictive mechanism from the perspective of big data-driven Lean Manufacturing. The key techniques including PLC communication, DMAIC roadmap, SPC technique and Hypothesis Testing are utilized to eliminate the waste and obtain continuous improvement. The demonstration of calculator production indicates the predictive mechanism can effectively eliminate the waste and improve the output by 60% with the sufficient capability of Cp > 1.33 and Cpk > 1.
%G English
%Z TC 5
%Z WG 5.7
%2 https://inria.hal.science/hal-03806514/document
%2 https://inria.hal.science/hal-03806514/file/520761_1_En_70_Chapter.pdf
%L hal-03806514
%U https://inria.hal.science/hal-03806514
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-APMS
%~ IFIP-WG5-7
%~ IFIP-AICT-633