การปรับปรุงกระบวนการผลิตอุตสาหกรรมอาหารโดยการประยุกต์ใช้ดีเอ็มเอไอซีและระบบอัตโนมัติแบบดิจิทัล: กรณีศึกษาการผลิตปูอัดในประเทศไทย
Keywords:
DMAIC, Lean Six Sigma, Digital Automation, Productivity, Food IndustryAbstract
This research aims to improve the efficiency of the production process in the food industry by applying Lean Six Sigma concepts along with digital systems and automation under the DMAIC framework. The research employed a single-case embedded action research design in the case study factory, analyzing the production process using Value Stream Mapping 4.0 to identify losses in the process and establish key performance indicators. The study found that improving the production process by incorporating automation increased productivity by 430.87%, reduced waiting time from 39.50 seconds to 10.80 seconds, decreased lead time by 56.25%, and significantly increased the production process capability (Cpk) from 0.40 to 1.55. The implementation of automation and digital data integration in operations also enhanced the continuity of the production process flow and reduced system losses. Additionally, an economic feasibility analysis of process improvement options using financial indicators such as net present value (NPV), internal rate of return (IRR), and payback period showed that the investment in process improvement was justified, yielding a worthwhile return with an NPV of 22.20 million baht, an IRR of 30.70%, and a payback period of 2.64 years. This research presents an integrated approach for developing production process efficiency, which can be applied as a model for industries with similar processes.
References
Frank AG, Dalenogare LS, Ayala NF. Industry 4.0 technologies: implementation patterns in manufacturing companies. International Journal of Production Economics 2019;210:15–26. doi: 10.1016/j.ijpe.2019.01.004.
Nunez-Merino M, Maqueira-Marin JM, Moyano-Fuentes J, Castano-Moraga CA. Industry 4.0 and Supply Chain: A Systematic Science Mapping Analysis. Technological Forecasting and Social Change 2022;181:121788. doi: 10.1016/j.techfore.2022.121788.
Kamble SS, Gunasekaran A, Gawankar SA. Sustainable Industry 4.0 framework: a systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection 2018;117:408-25. doi: 10.1016/j.psep.2018.05.009.
Monostori L, Kadar B, Bauernhansl T, Kondoh S, Kumara S, Reinhart G, et al. Cyber-Physical Systems in Manufacturing. CIRP Annals 2016;65(2): 621–641. doi: 10.1016/j.cirp.2016.06.005.
Alexander P, Antony J, Rodgers B. Lean Six Sigma for Small and Medium Sized Manufacturing Enterprises: A Systematic Review. International Journal of Quality & Reliability Management 2019;36(3):378–397. doi: 10.1108/IJQRM-03-2018-0074.
Arey D, Le C, Gao J. Lean Industry 4.0: A Digital Value Stream Approach to Process Improvement. Procedia Manufacturing 2021;54:19–24. doi: 10.1016/j.promfg.2021.07.004.
Sony M, Naik S. Key Ingredients for Evaluating Industry 4.0 Readiness for Organizations: a Literature Review. Benchmarking: An International Journal 2020;27(7):2213–2232. doi: 10.1108/BIJ-09-2018-0284.
Maheshwari P, Kamble S, Belhadi A, Venkatesh M, Abedin MZ. Digital Twin-Driven Real-Time Planning, Monitoring, and Controlling in Food Supply Chains. Technological Forecasting and Social Change 2023;195:122799. doi: 10.1016/j.techfore.2023.122799.
Wang FK, Rahardjo B, Rovira PR. Lean Six Sigma with Value Stream Mapping in Industry 4.0 for Human-Centered Workstation Design. Sustainability 2022;14(17): 11020. doi: 10.3390/su141711020.
Skalli D, Charkaoui A, Cherrafi A, Garza-Reyes JA, Antony J, Shokri A. Industry 4.0 and Lean Six Sigma integration in manufacturing: a literature review, an integrated framework and proposed research perspectives. Quality Management Journal 2023;30(1):16–40.doi: 10.1080/10686967.2022.2144784.
Ivanov D, Dolgui A. A digital supply chain twin for managing the disruption risks and resilience in the era of industry 4.0. Production Planning & Control 2021;32(9):775-88. doi: 10.1080/09537287.2020.1768450.
Wang W, Yang H, Zhang Y, Xu J. IoT-Enabled Real-Time Energy Efficiency Optimisation Method for Energy-Intensive Manufacturing Enterprises. International Journal of Computer Integrated Manufacturing 2018;31(4–5):362–379. doi: 10.1080/0951192X.2017.1337929.
Utama DM, Abirfatin M. Sustainable Lean Six-Sigma: A New Framework for Improve Sustainable Manufacturing Performance. Cleaner Engineering and Technology 2023;17:100700. doi:10.1016/j.clet.2023.100700.
Meudt T, Metternich J, Abele E. Value Stream Mapping 4.0: Holistic Examination of Value Stream and Information Logistics in Production. CIRP Annals 2017;66(1):413–416. doi: 10.1016/j.cirp.2017.04.005.
Sanders A, Elangeswaran C, Wulfsberg J. Industry 4.0 implies lean manufacturing: research activities in industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management 2016;9(3):811-33. doi: 10.3926/jiem.1940.
McDonald T, Van Aken EM, Rentes AF. Utilising simulation to enhance value stream mapping: a manufacturing case application. International Journal of Logistics Research and Applications 2002;5(2):213-32. doi: 10.1080/13675560210148696.
Kolberg D, Zuhlke D. Lean Automation Enabled by Industry 4.0 Technologies. IFAC-PapersOnLine 2015;48(3):1870–1875. doi: 10.1016/j.ifacol.2015.06.359.
Antony J, Snee R, Hoerl RW. Lean Six Sigma: Yesterday, Today and Tomorrow. International Journal of Quality & Reliability Management 2017;34(7):1073–1093. doi: 10.1108/IJQRM-03-2016-0035.
Yu CM, Huang TH, Chen KS, Huang TY. Construct Six Sigma DMAIC Improvement Model for Manufacturing Process Quality of Multi-Characteristic Products. Mathematics 2022;10(5):814. doi:10.3390/math10050814.
Chiarini A, Kumar M. Lean Six Sigma and Industry 4.0 integration for operational excellence: evidence from Italian manufacturing companies. Production Planning & Control 2021;32(13):1084-101. doi: 10.1080/09537287.2020.1784485.
Sahoo S, Yadav S. Lean production practices and bundles: a comparative analysis. International Journal of Lean Six Sigma 2018;9(3):374-98. doi: 10.1108/IJLSS-01-2017-0002.
Sreedharan VR, Raju R, Sunder MV, Antony J. Assessment of Lean Six Sigma Readiness (LESIRE) for Manufacturing Industries Using Fuzzy Logic. International Journal of Quality & Reliability Management 2019;36(2):137–161. doi: 10.1108/IJQRM-09-2017-0181.
Jones D, Snider C, Nassehi A, Yon J, Hicks B. Characterising the Digital Twin: A Systematic Literature Review. CIRP Journal of Manufacturing Science and Technology 2020;29(Pt A):36–52. doi: 10.1016/j.cirpj.2020.02.002.
Bevilacqua A, Speranza B, Campaniello D, Sinigaglia M, Corbo MR, Lamacchia C. A Preliminary Report on the Use of the Design of Experiments for the Production of a Synbiotic Yogurt Supplemented with Gluten FriendlyTM Flour and Bifidobacterium infantis. Frontiers in Microbiology 2019;10:226. doi: 10.3389/fmicb.2019.00226.
Wuest T, Weimer D, Irgens C, Thoben KD. Machine Learning in Manufacturing: Advantages, Challenges and Applications. Production & Manufacturing Research 2016;4(1):23–45. doi: 10.1080/21693277.2016.1192517.
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