مدل برنامه ریزی تولید به منظور کاهش ریسک و بهبود مدیریت عملیات
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7898||2010||12 صفحه PDF||سفارش دهید||11500 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 124, Issue 2, April 2010, Pages 463–474
Traceability has become an essential business function to consistently supply quality and safe food products to consumers. However, it has been not rare that the efforts in traceability are separately made from routine operations management decisions. In this paper, an integrated optimisation model is developed in which the product safety related traceability factor is incorporated with operations factors to develop an optimal production plan. The model aims to improve traceability and manufacturing performance by simultaneously optimising the production batch size and batch dispersion with risk factors. Two industrial cases are used to support numerical analyses to investigate the benefit under various business situations and product features.
With frequently reported food quality and safety incidents and new legislations, traceability has become an essential business function to consistently supply quality and safe food products to consumers in food industry (EU Regulation, 2002). Many efforts are being undertaken to rebuild the consumer confidence by implementing production protocols, information technology and supply chain management processes to improve quality and safety control through supply chains. Food traceability does not only deliver an extra guarantee for food safety but also provides transparency of the value chain towards consumers (Fritz and Schiefer, 2009). The existing research mainly focuses on applying sophisticated technologies and information systems to enhance the traceability management. However, the cost required for the investment on those technologies and systems certainly impede the enthusiasm of organisations in pursuit of efficient traceability systems. This research investigates a new approach to integrating food traceability management with operations management processes. An integrated production planning model is proposed where the risk related traceability factor is incorporated with operations factors to optimise the overall performance of a manufacturing system. The research quantitatively investigates the benefits from the seamless integration of operations planning with strategic considerations on food traceability and risk issues through the proposed production planning model. Two industrial case studies are presented to help understanding of the proposed integration strategy.
نتیجه گیری انگلیسی
An integrated production planning model is developed in this study. The proposed model, based on a cost analysis, simultaneously optimises the production batch quantity and batch dispersion in the food manufacturing context. The model incorporates production set-up cost, inventory holding cost, raw material cost, traceability cost, product perish cost and food risk assessment. To analyse the effect of product recall coefficient, price and risk rating of raw material batches, and product shelf-life features on the model performance, industrial case based numerical analysis was provided. In addition to illustrating the proposed model, case studies suggest that the integrated approach is an effective way to improve operations and traceability performance. The major contribution of the research is the proposed innovation of operations management in the food supply chain, where food safety and quality issues are seamlessly integrated with operations factors in the production planning process. The research demonstrates benefits of such an approach through the case examples, which could also make impact on other industries with a similar situation. The integrated model provides enterprises with a practical approach to quantitatively evaluate operations performance from both risk management and operations management perspectives. It can support business decision making at both operational and strategic levels. Finally, it should be underlined that the integrated model presented in this paper is deterministic. Using deterministic models alone does not take the cost associated with supply and demand uncertainty into consideration. It will be useful to investigate further research problem using stochastic models. Moreover, the model did not consider the potential benefits food manufacturers could gain by providing for a longer product shelf-life. Food manufacturers may benefit from increased sales as product freshness has become an important criterion when consumers make their purchasing decisions. It will be an important and challenging topic for future research as under this circumstance the model actually considers the problem from the whole supply chain perspective.