Thesis Archive
Development of a Mathematical Model for Optimal Operational Adjustments in Process Industries in the case of Sugar Manufacturing
Jude Bautista
Ruth Gatmaitan
Reinhart Perez
Abstract:
Disruptions and delays in schedule are common problems in chemical process industries. Despite being a common occurrence, these problems can be unpredictable and can cause financial implications to the process plant. Hence, it is crucial to develop strategies for managing different cases of delays and to reduce the economic impact to the plant. This is especially applicable to the sugar manufacturing due to the limited operation period of 4 to 6 months every year. The meager operating time is mainly due to the seasonal nature of its raw materials such as sugarcane and sugar beets. Thus, implementing strategies and optimal schedules would ensure that the limited operation time is being fully maximized for the profit while, mitigating the losses due to unexpected inoperability. This paper formulates an optimal scheduling model for sugar plant adapted from Kondili et al. (1993) using Mixed Integer Linear Programming (MILP). The approach uses scenario analysis in case of evaporator maintenance and delayed deliveries or mill breakdown; the result is a schedule optimization model which is demonstrated in the case of the sugar manufacturing industry. In the case of mill breakdown and evaporator maintenance, the profit is decreased by 1.37% and 8.54%, respectively. The decrease in profit caused by evaporator maintenance is due to the product being produced one period earlier, which increases the storage cost. On the other hand, the decrease in profit caused by the mill breakdown is due to the reduced value of products. For the future studies, the alternative solutions of adding an additional crusher, evaporator, or clarifying unit and the outsourcing of the juice feed should be considered to determine the time it takes to breakeven the extra costs due to outsourcing and extra equipment.
Adviser:
Aviso, Kathleen