Mixed Integer Programming Formulations for the Production Planning Problems in Additive Manufacturing and 3D Printing
Sabancı School of Management, Sabancı University
Advances in material science as well as manufacturing technologies have given rise to the use of additive manufacturing (AM) and 3D printing in not only production of prototypes but also for production of final parts or products in industries such as aerospace, defense and automotive. This paper deals with the production planning problem in such direct digital manufacturing environments where powder-based AM machines are utilized to manufacture the parts on a job (build) basis.
We are given the physical parameters of each part, i.e. the height, area and volume, and parameters associated with the AM machines such as the build chamber’s height and area, set-up time, per unit volume production speed and cost. Moreover, the labor cost and the per unit volume material costs are given. The corresponding production planning problem involves the assignment of parts to jobs and jobs to AM machines. We consider, separately and simultaneously, the cost and the makespan minimization objectives. For each of these problems, a mixed-integer programming (MIP) formulation is presented. The results of our extensive experimentation for solving the MIP formulations using a commercial solver is provided. For the multi-objective version of the problem, consisting of the cost and makespan objective, we construct and analyze the efficient frontier by adopting the diversity maximization (DMA) approach. The DMA approach enables generating a diverse set of efficient solutions, by multiple solutions of a MIP formulation. In each iteration, considering the current set of efficient solutions, the formulation yields the most diverse new efficient solution, and then the formulation is modified accordingly for the subsequent iteration. This is joint work with Yossi Bukchin (Department of Industrial Engineering, Faculty of Engineering, Tel Aviv University).
F. Tevhide Altekin is an Assistant Professor of Operations Management at Sabancı School of Management, Sabancı University. She received her B.S., M.S. and Ph.D. degrees in Industrial Engineering from Middle East Technical University. Her main research focuses on production planning problems in additive manufacturing, disassembly line design, assembly line design, design of reverse logistics networks and design of after-sales networks. She teaches Ph.D., PMBA, MBA and undergraduate level courses in operations management, business process analysis and design, introduction to management, business simulation and data analysis, operations and decision systems, and advanced Excel for managers. She is the recipient of the second place of the Sabancı University 2011 graduating class teaching awards.
Friday, October 25, 2019 at 4.00 pm in IE 03