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SEMINAR:Data-driven Energy-Aware Production Control of Production System

Speaker: Barış Tan, Koç University

Title: Data-driven Energy-Aware Production Control of Production Systems

Date/Time: Nov 8, 2023, 13:40-14:30

Place: FENS G035 (Physical Only)

Abstract: Increasing energy efficiency in manufacturing has significant environmental and cost benefits. Turning on or off a machine dynamically while considering the production rate requirements can offer significant energy savings. Motivated by a project that aims at controlling the paint oven of an automotive producer to save energy, we investigate the optimal energy mode and production control policies to turn on and off a machine that operates in Working, Off, Idle, and Warmup energy modes with stochastic inter-arrival, production, and warmup times. The solution of the optimal control problem that minimizes the expected costs associated with energy usage in different energy modes and the costs associated with producing early or late according to the desired production rate, in the long run, is determined by analyzing the underlying Markov Decision Process. We show that when the inter-arrival time distribution is exponential, the optimal policy depends on the inventory position, leading to a buffer-based policy. The optimality of this policy is proven under heavy traffic. However, when the interarrival time is not exponential, the optimal policy depends on the inventory position and the current phase of the inter-arrival time. The phase- dependent policy can be implemented by predicting the current phase using the time elapsed since the last arrival. We present a matrix- geometric method to evaluate the system's performance operating with the optimal control policy. We show that policies that only use the inventory position information can be effective if the control parameters are chosen appropriately. However, the control policies that use inventory and time information further improve the performance. The case of controlling multiple machines simultaneously and solving the resource scheduling problem at the paint shop in the finite horizon will also be discussed. In conclusion, data-driven energy mode control yields manufacturers significant environmental and cost benefits. 

Bio:Barış Tan is a Professor of Operations Management and Industrial Engineering at Koç University. He is currently a visiting professor at Politecnico di Milano - Manufacturing and Production Systems Laboratory. He previously served as Vice President for Academic Affairs, Dean of the College of Administrative Sciences and Economics, and the Director of the Graduate School of Business at Koç University. His areas of expertise are in the design and control of production systems, supply chain management, stochastic modeling, and business model innovation. He received a BS degree in Electrical & Electronics Engineering from Boğazici University, an ME in Industrial and Systems Engineering, an MSE in Manufacturing Systems, and a Ph.D. in Operations Research from the University of Florida. He also held visiting positions at Harvard University - Division of Engineering and Applied Sciences, MIT - Operations Research Center, MIT - Laboratory for Manufacturing and Productivity, University of Cambridge - Judge Business School, and University College London - School of Management.