| 摘要(英) |
Technological advancements and the rapid pace of progress have resulted in shorter product cycles and faster changes in customer demands. This poses a significant challenge for manufacturing factories in terms of customization and handling small orders, necessitating their transition into the era of Industry 4.0 to achieve automation and highly personalized production. However, the transition from Industry 3.0 to 4.0 presents considerable difficulties and barriers. As a solution, companies can first transition into Industry 3.5 before entering 4.0.
Factory production planning traditionally relies on manual calculations of materials, labor hours, and manpower to determine scheduling and provide order delivery estimates. When various factors such as human resources, machinery, materials, and regulations change, scheduling needs to be re-planned, and discussions regarding production sequences and delivery times arise. The real-time nature and accuracy of such planning pose risks and concerns. To expedite scheduling and minimize the risk of judgment errors, companies are developing intelligent manufacturing systems and implementing them in their factories to enhance planning and production efficiency. This, in turn, reduces personnel working hours and improves the overall effectiveness of each department.
In this research, the case study focuses on the Electronic Component Business Group of Company D to examine the benefits of the upcoming smart manufacturing system and analyze its advantages and challenges in terms of user operations. The findings will provide the case company with future improvement directions and recommendations. |
| 參考文獻 |
中文參考文獻
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英文參考文獻
1. Kagermann, H., J. Helbig, A. Hellinger, and W. Wahlster ,Recommendations for Implementing the Strategic Initiative Industrie 4.0: Final Report of the Industrie 4.0 Working Group, Berlin, Germany: Federal Ministry of Education and Research. (2013a)
2. Adhesive tapes market: global industry trends, share, size, growth, opportunity and forecast 2022-2027 , Research & Markets,2022
3. Kuo, T. C., Chen, K. J., Shiang, W. J., Huang, P. B., Otieno, W., & Chiu, M. C.. A collaborative data-driven analytics of material resource management in smart supply chain by using a hybrid Industry 3.5 strategy. Resources, Conservation and Recycling, 164, 105160. 2021
4. Chien, C. F., Hong, T. Y., & Guo, H. Z.. A conceptual framework for “Industry 3.5” to empower intelligent manufacturing and case studies. Procedia Manufacturing, 11, 2009-2017. 2017
5. Chien, C. F., Hsu, C. Y., & Chang, K. H. (2013). Overall wafer effectiveness (OWE): A novel industry standard for semiconductor ecosystem as a whole. Computers & Industrial Engineering, 65(1), 117-127. |
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