Production performance measurement is the most important activity to achieve the higher productivity in food industries. The Overall Equipment Effectiveness (OEE) is a standard for measuring production productivity. However, the uncertainty of OEE components could mask the true production performance estimation in food processing lines. In this study, the production speed and stoppage duration measurements as major uncertainties to estimate the OEE and its components were investigated. In order to handle the uncertainties, two methods based on fuzzy arithmetic and interval arithmetic were conducted to supplement the classical-OEE. To survey the classical-OEE, the operational data field of edible oil purification process over a period of two years were examined. The comparison results of filed data revealed that the new OEE index has been increased around 4% by maintenance improvements. In such index, the total availability, performance efficiency and quality rate were improved by 3%, 2% and 5%, respectively. The research results showed that the spread values of Fuzzy-OEE are more explicit to show the worst and best values, while the interval arithmetic of OEE reflects the results by tighter limits. The proposed methods are more convenient to quantify uncertainty with limits to understand the OEE variations helping to make better decisions on uncertainties in food production lines.

生产绩效评估是实现食品工业更高生产率的最重要活动。总体设备效率（OEE）是衡量生产生产率的标准。但是，OEE组件的不确定性可能会掩盖食品加工生产线中真实的生产性能估算。在这项研究中，对生产速度和停止时间的测量作为估计OEE及其组成部分的主要不确定因素进行了调查。为了处理不确定性，采用了基于模糊算法和区间算法的两种方法对经典OEE进行了补充。为了调查经典OEE，对食用油提纯过程两年的操作数据字段进行了检查。归档数据的比较结果表明，通过维护改进，新的OEE索引已增加了约4％。在该指数中，总可用性，性能效率和质量率分别提高了3％，2％和5％。研究结果表明，Fuzzy-OEE的扩展值更明确地显示了最差值和最佳值，而OEE的区间算法通过更严格的限制反映了结果。所提出的方法更方便地对不确定性进行定量，以了解OEE的变化，从而有助于对食品生产线中的不确定性做出更好的决策。研究结果表明，Fuzzy-OEE的扩展值更明确地显示了最差值和最佳值，而OEE的区间算法通过更严格的限制反映了结果。所提出的方法更方便地对不确定性进行定量，以了解OEE的变化，从而有助于对食品生产线中的不确定性做出更好的决策。研究结果表明，Fuzzy-OEE的扩展值更明确地显示了最差值和最佳值，而OEE的区间算法通过更严格的限制反映了结果。所提出的方法更方便地对不确定性进行定量，以了解OEE的变化，从而有助于对食品生产线中的不确定性做出更好的决策。