Analysis and design of the flow shop scheduling system in sausage production to minimize Makespan

Scheduling is the process of allocating resources or machines to carry out a set of tasks for a certain period. Scheduling based on process flow can be divided into flow shop and job shop. Flow shop scheduling is sequencing several jobs that each job has the same operation, and the second job cannot be done before the first job is completed. Flow shop scheduling becomes the main topic related to fulfilling orders on time. This paper presents the design of the flow shop scheduling system in sausage production. The proposed formulations are to design the buffer stock prediction model to determine the quantity of sausage production and design the flow shop scheduling model to minimize makespan. Recognizing business processes that occur in the system is the first step before the system is modeled. Business processes are presented in BPMN. Then, system modeling is documented in the Unified Modelling Language (UML). Buffer stock prediction model is solved using Ordinary Least Square (OLS) or multiple linear regression, and flow shop scheduling model is solved using Mixed-integer Linear Programming (MILP). In the buffer stock model, the predictors can explain the expected target linearly, and the model provides the predictive value of production level with a small error and accuracy of more than 90%. Then, the flow shop scheduling model can give the sequence of sausage production jobs that results in the shortest makespan.