An Application of Simulation Modeling for Scheduling in a Manufacturing Environment

Open Access
Imel, Kaitlyn Sirois
Area of Honors:
Industrial Engineering
Bachelor of Science
Document Type:
Thesis Supervisors:
  • M Jeya Chandra, Thesis Supervisor
  • Harriet Black Nembhard, Honors Advisor
  • Simulation
  • Linear Programming
  • Simio
  • Gams
  • Manufacturing
  • Scheduling
Production scheduling is a complex problem that many manufacturing facilities face. Due to this complexity, there are many methods available for optimizing the production schedule according to facility specifications; however, many plant managers still utilize fairly simple methods to schedule production, thus leading to wasted resources and costly inefficiencies. This thesis looks at one such scenario in which a facility currently utilizes a set of rules to schedule a complex production across four lines with thousands of products. The company has continually failed to meet demand requirements. The experimentation for this thesis compares two methods of scheduling in order to choose the most adequate one to implement and replace the current methods and to serve as a best in practice for similar situations. The two methods to be analyzed are linear programming through excel and Gams and simulation modeling utilizing Simio. The results from the analysis show that although both methods created viable solutions to the problem, the Simio model was much easier to create and contains a more practical user interface for monthly scheduling purposes. The Simio model also allows other aspects of the facility to easily be added onto the scheduler model.