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A Model for Process Control in Agile Supply Chain Networks Using Artificial Neural Networks | ||
| Health Management & Information Science | ||
| دوره 12، شماره 4، دی 2025، صفحه 267-273 اصل مقاله (859.59 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.30476/jhmi.2025.108149.1306 | ||
| نویسندگان | ||
| Alireza Aliasgharzadeh؛ Mahmood Mohammadi* ؛ Hassan Mehrmanesh | ||
| Department of Industrial Management, Islamic Azad University, Tehran Central Branch, Tehran, Iran | ||
| چکیده | ||
| model to enhance agility in supply chain networks, focusing on optimizing decision-making under demand fluctuations and cost constraints. Methods: A quantitative descriptive design was employed, utilizing cluster sampling (n=384) from a manufacturing company’s customer base. The ANN model integrated key variables (e.g., raw material flow, production volume, storage capacity) and was tested via sensitivity analysis to evaluate the impacts of production cost, service level, and factory capacity changes on objective function values. Results: The model significantly improved supply chain agility, enabling a dynamic response to demand shifts. A 111% production cost variation altered costs by ±15.7%, while a 91% capacity reduction rendered the model infeasible. A 411% demand surge disrupted service levels (91%), highlighting capacity constraints. Flexibility indicators (e.g., production adaptability) emerged as critical agility drivers. Conclusion: The ANN-based model optimizes supply chain performance, particularly in healthcare contexts where responsiveness and cost efficiency are paramount. Practical recommendations include workforce skill development, just-in-time production systems, and enhanced supplier IT integration. | ||
تازه های تحقیق | ||
Alireza Aliasgharzadeh (Google Scholar) Mahmood Mohammadi (Google Scholar) | ||
| کلیدواژهها | ||
| Process Control؛ Agile Supply Chain؛ Artificial Neural Network | ||
| مراجع | ||
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