Optimal Production Scheduling for the Sausage Industry

The increased consumption of processed foods, as well as a greater variety of products offered by the food industry has required for greater flexibility and the most efficient coordination in the allocation of existing resources. The sausage industry in particular in recent years had an increase in consumption, and this has led to a search for a more efficient use of available resources to achieve increased productivity, cost reduction, reliability in attendance and reduction of lead times. These aspects of production and management can be achieved more easily through tools of programming production. The sausage production is a batch process. The process can be divided into two main stages, the first refers to the preparation, the mixture of raw materials and stuffing; the second stage refers to the cooking of products that were stuffed in the first stage. A variety of types of products are obtained in the sausage industry. Most of these products do not have an exclusive line and therefore, there is a dispute between equipment and intermediate states. The products are classified as perishable, and it is recommended that production should not exceed the demand under the risk of keeping products in stock and overcome the shelf life validity of the product. The objective of this paper was to optimize the production for the sausage industry using values of demands for each product. The proposed approach states the problem as a model of mixed integer linear programming (MILP) to represent the decisions involved and was solved using the GAMS (General Algebraic Modelling System) language. The model was applied to the problem of production scheduling with real-world operational data from an industry and was able to generate better results than those used by industry. Thus, the model proved to be appropriate to support the decisions of production scheduling in the sausage industry.