Abstract
In multisite production environments, the appropriate management of production resources is an activity of fundamental relevance to optimally respond to market demands. In particular, each production facility can operate with different policies according to its objectives, prioritizing the quality and standardization of the product, customer service, or the overall efficiency of the system; goals which must be taken into account when planning the production of the entire complex. At the operational level, in order to achieve an efficient operation of the production system, the integrated problem of batching and scheduling must be solved over all facilities, instead of doing it for each plant separately, as has been usual so far. Then, this paper proposes a mixed-integer linear programming model for the multisite batching and scheduling problems, where different operational policies are considered for multiple batch plants. Through two examples, the impact of policies on the decision-making process is shown.
Highlights
Today, many companies compete through the development of new products and providing new services to their customers
This paper proposes a mixed-integer linear programming model for the multisite batching and scheduling problems, where different operational policies are considered for multiple batch plants
Production scheduling becomes even more important in the case of multiproduct batch plants, because, as it has been previously mentioned, the same equipment is shared by batches of distinct sizes and products that require different processing times
Summary
Many companies compete through the development of new products and providing new services to their customers. In order to achieve the optimum operation in a productive installation composed by several multiproduct batch plants, it is required to optimize over the entire complex simultaneously On this environment, several authors have dealt with planning and scheduling problems. Different types of facilities are addressed: Terrazas-Moreno and Grossmann (2011) and Shah and Ierapetritou (2012) consider multisite continuous multiproduct plants; Behnamian and Fatemi Ghomi (2013), plants with different geographical locations and parallel identical machines in each plant; Kopanos and Puigjaner (2009) and Ackermann et al (2018) have solved the simultaneous batching and scheduling of multisite production environments composed by batch plants, where the plants have one and several stages, respectively, and units operating in parallel. The model must decide simultaneously, while complying with the selected operational policy, in which plant to process each order, in how many batches is divided each order, the sizing of the batches, the allocation of the batches to specific units of the plant where they will be processed, and their initial and final processing times, in such a way that the total time required to complete and send orders to the customers is minimized
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