Production Planning and Resource Allocation for Medical Instruments Manufacturing

Fang Yifan

Abstract

This project describes the medical instrument manufacturing factory develops the production scheduling and resource allocation with multiple jobs and multiple machines. The company was a multinational medical devices and health care company with headquarters in the United States. Singapore branch is one of the medical diagnostics devices production lines to fulfill the orders worldwide. In this research, the following Job Shop Scheduling problems with three algorithms have been studied: (1) Minimize Makespan Disjunctive Model (2) Minimize the Weighted sum of Earliness and Tardiness Disjunctive Model (3) Minimize Makespan Disjunctive Model with Assembly Problem These three scheduling models are based on multiple jobs with different machines, which could be applied in different order scenarios for the company. Each job is not required to process at all machines. The three mathematical models based on scheduling requirements were developed in an effort to obtain the optimal solutions. Heuristic algorithms have been developed to solve the problems. The performances of the heuristic algorithms were demonstrated on some desensitized data to test the problems. The solver Gurobi was used to find optimal solutions with python code. The test results displayed with Gantt Charts could be directly given the image of the scheduling processes. Besides, there are meaningful and sorted text outputs with different models to identify every job and machine start time with process duration. The quality and CPU time of solutions were the factors of interest. The sizes of data metrics could become another element to consider in actual production planning in a manufacturing factory.