| Summary: | 碩士 === 國立臺灣海洋大學 === 食品科學系 === 101 === The aim of the study was to develop a quality prediction model under the continuous temperature information in 18 degree ready-to-eat food during logistics flows, and the parameters of the model was converted to decay parameter for profits analysed. Further, we discuss how to improve inventory decision by the temperature monitoring. Base on the continuous temperature information, the growth of Pseudomonas spp. was chosen and developed by mathematical model with Gompertz model. The 18 degree ready- to- eat sandwiches were chosen and stopover in the five processes (temporary, storage, tally, shipping and transportation) before reaching retailer. Temperature logging data was imported to the model, and exponential regression was uesd to construct growth rate (B) and time at which maximum growth rate (M) from the second-hand data of sandwich. In addition, the prediction model is an over prediction based on the sensitivity analysis. On the other hand, the profit was analyzed with the decay parameters which were obtained from the quality prediction model. Subsequently, two different types of situation, including quality inspection cost (Scenario 1) and price discount (Scenario 2), were set up. Based on the profit model of inventory, the scenario 2 shows that the quality of the products influenced by the value of products and it maked the price decision of the products and to get the maximum profit for the company. Therefore, the model was an effective tool which combining with continuous temperature application. It could improve the quality management by considering analysis of shelf life and profit analysed.
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