Abstract
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.
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Chen, H., Wu, J., Zhang, W., Guo, Q., Lu, H. (2021). Study of the Predictive Mechanism with Big Data-Driven Lean Manufacturing and Six Sigma Methodology. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-030-85910-7_70
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DOI: https://doi.org/10.1007/978-3-030-85910-7_70
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