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Enhancing Lean-Kaizen practices through IoT and automation: A comprehensive analysis with simulation modeling in the Thai food industry |
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| รหัสดีโอไอ | |
| Creator | 1. Siwasit Pitjamit 2. Parida Jewpanya 3. Pinit Nuangpirom |
| Title | Enhancing Lean-Kaizen practices through IoT and automation: A comprehensive analysis with simulation modeling in the Thai food industry |
| Publisher | Faculty of Engineering, Khon Kaen University |
| Publication Year | 2567 |
| Journal Title | Engineering and Applied Science Research |
| Journal Vol. | 51 |
| Journal No. | 3 |
| Page no. | 286-299 |
| Keyword | Simulation modeling, Noodle production process, Lean-Kaizen, Internet of Things, Automation |
| URL Website | https://ph01.tci-thaijo.org/index.php/easr/index |
| Website title | Engineering and Applied Science Research |
| ISSN | 2539-6161 |
| Abstract | This research delves into a comprehensive examination of the noodle production process within the Thai food industry, focusing on pivotal challenges related to quality control during steaming, weighing, sealing, and vacuum packaging. In response to these challenges, our study investigates the strategic integration of Internet of Things (IoT) and automation solutions to amplify production efficiency. Employing advanced plant simulation tools, including lean manufacturing and Kaizen principles, coupled with methodologies like value stream mapping and flow process charts, we explore four distinct improvement scenarios. Scenario 1 targets enhancements in the dough-baking system during the steaming process, while Scenario 2 concentrates on optimizing the boiler control system. Scenario 3 addresses the weighing and packing process, and Scenario 4 aims at automating the packing process. These scenarios collectively showcase substantial reductions in cycle time, labor costs, and improvements in production capacity. The research design spans a 30-day data collection period, capturing critical metrics related to cycle time, changeover time, workforce, lead time, value-added time, and inventory levels. The gathered data unveils inefficiencies and challenges within the noodle production process, offering a foundation for identifying bottlenecks and areas for enhancement. The study's outcomes underscore the efficacy of technology-driven solutions in addressing production challenges and boosting operational efficiency. Specifically, Scenario 1 and Scenario 4, integrating IoT technology and automation, exhibit a remarkable 7.8% increase in productivity with a one-year payback period. Meanwhile, Scenario 3 significantly reduces labor costs and enhances overall efficiency. These findings contribute to the broader industry discourse, emphasizing the transformative potential of technology-driven solutions in addressing key production challenges and advancing operational excellence. The research provides valuable insights for practitioners seeking innovative approaches to enhance their processes and embrace Industry 4.0 advancements. |
