{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T07:40:02Z","timestamp":1756712402453,"version":"3.44.0"},"reference-count":18,"publisher":"SAGE Publications","issue":"9","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>The steel industry plays a crucial role in global economic development, involving complex production and logistics processes. Effective transportation management, particularly crane utilization, is essential to maintaining smooth operations. However, inadequate planning regarding crane scheduling can lead to bottlenecks, reducing production efficiency. Despite its importance, the role of transportation in enhancing production flow remains underexplored. This study employs simulation modeling using Simio to analyze the production and transportation system of a steel company in Taiwan. Real-world data on production stages, transportation routes, and operational constraints are integrated into the model. Through various what-if scenarios, the impact of crane availability on production performance is evaluated. Key performance indicators such as throughput, station occupancy, and crane utilization rates highlight significant overuse of specific cranes, leading to inefficiencies. To address these bottlenecks, the model is iteratively adjusted by increasing the number of cranes. The results indicate that deploying six cranes, ensuring none exceeds 70% utilization, enhances throughput and balances production flow. This configuration reduces operational risks, minimizes downtime, and enhances overall efficiency. The study underscores the importance of integrating transportation planning into production management, providing valuable insights for improving operational decision-making in the steel industry.<\/jats:p>","DOI":"10.1177\/00375497251326918","type":"journal-article","created":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T13:52:45Z","timestamp":1743515565000},"page":"891-908","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Applying simulation technique to enhance the steel manufacturing process considering transportation"],"prefix":"10.1177","volume":"101","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1762-7163","authenticated-orcid":false,"given":"Shih-Hsien","family":"Tseng","sequence":"first","affiliation":[{"name":"Department of Industrial Management, National Taiwan University of Science and Technology, Taiwan"}]},{"given":"Oey","family":"Aldi Winata","sequence":"additional","affiliation":[{"name":"Department of Industrial Management, National Taiwan University of Science and Technology, Taiwan"}]}],"member":"179","published-online":{"date-parts":[[2025,4]]},"reference":[{"key":"e_1_3_3_2_2","first-page":"150","volume-title":"Proceedings of the 2013 IEEE international conference on automation science and engineering (CASE)","author":"Fanti MP","unstructured":"Fanti MP, Iacobellis G, Rotunno G, et al. A simulation based analysis of production scheduling in a steelmaking and continuous casting plant. In: Proceedings of the 2013 IEEE international conference on automation science and engineering (CASE), Madison, WI, 17\u201320 August 2013, pp. 150\u2013155. New York: IEEE."},{"key":"e_1_3_3_3_2","first-page":"1","article-title":"Applying HBMO-based SOM in predicting the Taiwan steel price fluctuation","volume":"12","author":"Chiu C-Y","year":"2014","unstructured":"Chiu C-Y, Fan S-KS, Shih P-C, et al. Applying HBMO-based SOM in predicting the Taiwan steel price fluctuation. 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