HIERARCHICAL PRODUCTION PLANNING AND ENERGY MODELING FOR FOOD PROCESSING PLANTS
Abstract
The food processing industry has experienced a dramatic change in recent years. Food processors have become increasingly concerned with the productivity improvement and energy utilization. Furthermore their product demands are subject to uncertainity, seasonality and rapid fluctuations. At any time, a manager is confronted with requirements leaving him with considerable over-or-under capacity. Effective production planning is a major need of all highly complex, multi-product food processing plants. Hierarchical production planning offers a unique opportunity to solve such problems. The development of a generalized user-oriented multi-period, multi-resource production planning system for food processing plants is presented. The practical and computational aspects of the model for implementation are considered and some associated problems are solved. A distinguishing feature of this study is that the emphasis is given to the development of an operational and easy to implement framework as a managerial aid to production planning and scheduling. The procedure starts with an inter-active user-oriented program used to formulate the LP model and control food rocessing plant input data. This program is a link between the model formulation and plant data. Then the model is solved using a semi-commercial LP package "MINOS". At this level, an optimal production plan is determined at an aggregate level. The production planning problem solution is very important and a necessary pre-requisite to the consideration of scheduling, design and/or energy modeling procedures. Examples are given in this study, using a fully integrated meat processing plant. Finally, the development of an energy utilization model for a food processing plant is described. The model is used to predict the time-of-day energy utilization of major processes in a meat processing plant. The modest case study results provided encouraging results which lead to believe that this methodology has interesting potential yet to be fully exploited. The model results would allow the user (decision maker) to evaluate a wide variety of alternative production plans, system designs and operating policies. This model would further be used for the ranking of various alternatives according to improvements in throughput and allied costs.
Degree
Ph.D.
Subject Area
Agricultural engineering
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