Institute of Business and Management
|關鍵字:||冷鏈物流;風險評估;食品安全;專家系統;失效模式與效應分析;Cold Chain Logistics;Risk Assessment;Food Safety;Expert System;Failure Mode and Effects Analysis|
|摘要:||隨著貿易全球化與消費者對於食品的安全與品質高度重視，複雜與長距離的物流過程，對於易腐保鮮商品的品質與安全，形成重大挑戰，促使冷鏈物流（cold chain logistics；CCL）受到學術界與產業界的重視。CCL中潛藏許多危害因子與風險，如何在物流過程中確保商品品質，事前的風險鑑別與管理，對冷鏈績效為一非常重要議題，而以往非常少研究針對此議題，進行探索研究。本研究整合失效模式與效應分析（dailure mode and effect analysis；FMEA）與專家系統，建立兩階段風險評估模式，第一階段為風險鑑別，運用FMEA分析工具，系統性鑑別冷鏈物流失效模式與其產生效應，進而應用特性要因圖解析失效原因；第二階段為風險推論，將所鑑別失效模式，依其發生的嚴重度、發生度與偵測度三項指標，透過本研究建立的風險推論專家系統，推論失效模式風險優先指數（risk priority number；RPN），以提供一個精確的風險評估模式。本研究以生鮮食品冷鏈，進行實際案例探討，研究結果共鑑別出35項風險失效模式，其中溫度失控、延遲配送與資訊整合不佳為最嚴重的失效模式；隨著國際環保趨勢要求，節能與碳排放議題亦被鑑別為潛在風險。相較於傳統以質性或量化的風險評估方法，本研究發展風險評估專家系統，可提供一個精確與主動的冷鏈物流風險評估，對於資源有限的組織，可以在有限的資源下，提供冷鏈物流風險，經濟有效的管理。|
With the rapid growth of global trade and increasingly high consumer expectations of food safety and quality, maintaining freshness during long-distance distribution of perishable goods is an important topic. In recent years, the key drivers of cold chain logistics (CCL) have received increasing attention from both academics and industry managers. The cold chain is a special type of supply chain that links parties with numerous embedded risks across the entire supply chain. Risk assessment plays a crucial role in improving the performance of cold chain logistics. However, very little literature has been devoted to exploring this vital issue. To address this research gap, the current study integrated failure mode and effects analysis (FMEA) and risk inference expert systems to develop a two stage risk assessment model. The first stage systematically identified potential risks in CCL, employing the FMEA method. Further applying Ishikawa cause-and-effect diagram analysis causes for every identified failure mode were documented. The second stage evaluated risk by using a risk inference expert system, developed in this study, to obtain the risk priority number (RPN). The RPN of a given failure mode was evaluated using three indexes: degree of severity, frequency of occurrence, and chance of detection. Finally, a fresh food supply chain was used to demonstrate the proposed model. Thirty-five failure modes were identified in the sample cold chain. The most serious failure modes included: temperature out of control, delivery delay, and poor integration of chain. Notably, the issue of environmental consciousness, related to energy saving and carbon emissions, was also identified in this study. In contrast to the traditional risk assessment model, the current study provides an accurate proactive method of assessing high-risk events in uncertain environments for CCL. This approach enables firms to expend resources focusing on high risk events, rather than across the spectrum of potential events, thus achieving increased economic efficiencies.
Journal of Management and Systems