APPLICATION OF THE AGGREGATED DMAIC-PDCA METHOD – CASE STUDY
The turbulent environment in which production companies operate today forces them to constantly improve processes. Among the methods supporting the improvement of the efficiency of production processes, we can distinguish PDCA method derived from Japanese experience (Toyota Production System) and DMAIC related to the Six Sigma concept. Implementation of changes with the use of both methods has a positive effect. Literature can identify the factors determining the choice of one of them for implementation under specific production conditions. The authors of the article make considerations regarding the use of aggregated DMAIC and PDCA methods to create a sustainable environment of continuous improvement in a short time. Based on the company's study, the authors distinguish key elements that determine the effective combination of these methods. This connection is presented on the basis of the practical implementation of the production process efficiency improvement project at a workstation.
Rahman, A., Shaju, S.U.C., Sarkar, S.K., Hashem, M.Z., Hasan, S.M.K., Mandal, R., A case study of six sigma define-measure-analyze-improve-control (DMAIC) methodology in garment sector, Independent Journal of Management & Production (IJM&P), Vol.8, No.4, (2017).
Ghosh, S., Maiti, J., Data mining driven DMAIC framework for improving foundry quality - a case study, Production Planning & Control, Vol.25, No.6, pp. 478-493, (2014).
Improta, G. Balato, G., Romano, M., Ponsiglione, A.M., Raiola, E., Russo, M.A., Cuccaro, P., Santillo, L.C., Cesarelli, M., Improving performances of the knee replacement surgery process by applying DMAIC principles, Journal of Evaluation in Clinical Practice, (2017).
Karout, R., Awasthi, A., Improving software quality using Six Sigma DMAIC-based approach: a case study", Business Process Management Journal, Vol.23, No.4, pp. 842-856, (2017).
Jaworski, J., Kluz, R., Trzepieciński, T., Investigation of Stability of Fabrication System of Casting Parts, Archives of Foundry Engineering, Vol.14, No.1, pp. 5-8, (2014).
ThanhDat, N., Claudiu, K.V., Zobia, R., Lobont, L., Knowledge portal for Six Sigma DMAIC process, IOP Conference Series: Materials Science and Engineering, (2016).
Kuwaiti, A., Subbarayalu, A.V., Reducing patients' falls rate in an Academic Medical Center (AMC) using Six Sigma "DMAIC" approach, International Journal of Health Care Quality Assurance, Vol.30, No.4, pp. 373-384, (2017).
Zasadzien, M., Optimization of the soldering process by DMAIC technology, Production Engineering Archives, Vol.11, No.2, pp. 6-10, (2016).
Mast, J., Lokkerbol, J., An analysis of the Six Sigma DMAIC method from the perspective of problem solving, Int. J. Production Economics, Vol.139, pp. 604-614, (2012).
Wojakowski, P., Warzolek, D., Application of lean tools to measure and improve work in assembly cell: a case study, Research in Logistics & Production, Vol.7, No.1, pp. 41-51, (2017).
Parkash, S., Dr. Veerender Kumar Kaushik. Supplier Performance Monitoring and Improvement (SPMI) through SIPOC Analysis and PDCA Model to the ISO 9001 QMS in Sports Goods Manufacturing Industry. Logforum 7.4 (2011).
Sokov, M., Pavletic, D., Kern Pipan, K., Quality Improvement Methodologies - PDCA Cycle, RADAR Matrix, DMIAC and DFSS, Journal of Achievements in Materials and Manufacturing Engineering, Vol.43, (2010).
Paris J.F., State of Readiness: operational excellence as precursor to becoming a high-performance organization, 1st edition, Greenleaf Book Goup Press, Austin, Texas, (2017).
Agmoni, E., The role of Kaizen in creating radical performance results in a logistics service provider, LogForum, Vol.12, pp. 225-245, (2016).
Pisz, I., Łapunka, I., Fuzzy logic-decision-making system dedicated to evaluation of logistics project effectiveness, LogForum, Vol.12, pp. 199-213, (2016).
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