Professor Mingzhou Jin
Department of Industrial and Systems Engineering
University of Tennessee
Date: Friday, March 6, 2020
Time: 1 - 1:50 pm
Location: D3 W122
Abstract: Considering the proliferation of the additive manufacturing (AM) technology, we study the economic feasibility of adopting AM for low-volume stochastic demand products in single-facility operating enterprises. Industrial level AM machines are quite expensive causing small and medium enterprises contemplate about its adoption. A numerical analysis aiding enterprises to decide on the magnitude of optimal AM investment has not yet found its place in the literature. Although some studies answered which products are economically better to occupy the AM capacity, they lacked some key aspects of AM, e.g., long production lead times. We use the procurement lead time of a product as a cost driver and create cost functions to estimate the long-term average costs of using AM and conventional manufacturing (CM) with stocking. Since AM technology has a limited capacity to build all products, we select the most economically suitable ones and determine the optimal number of AM machines to be invested in. For modeling purposes, we use M/G/k queueing theory due to the shared capacity in AM use and (S-1, S ) inventory policy with backorders for the conventional stocking because of the low and stochastic features of the demand. In this light, we create a mixed integer non-linear program and present three solution algorithms one of which promises the global optimum. To aid enterprises with strategic-decision of AM adoption, our study answers: 1) Should we adopt AM for low-volume demand? 2) How many AM machines would be optimal? 3) Which products are suitable for AM? To provide a useful guide for practitioners, a detailed analysis is presented while distinguishing the focus areas of AM end-users and original equipment manufacturers. Conclusively, several extension opportunities were shared to shed light on the path of other researchers, including a network design for AM adoption.
Biography: Dr. Mingzhou Jin is a Professor and Associate Head of the Department of Industrial and Systems Engineering and Director of the Institute for a Secure and Sustainable Environment at the University of Tennessee, Knoxville (UTK). He is also directing the Logistics, Transportation, and Supply Chain Engineering (LTS) lab, the Business and Engineering for Additive Manufacturing (BEAM) Center, and the Reliability and Maintainability Engineering (RME) program for the Tickle College of Engineering. Dr. Jin has done more than 50 funded projects in the areas of transportation, logistics and supply chain management, optimization, data analytics and advanced manufacturing with funding of more than $7M from federal and state agencies and industry, including NSF, US Department of Transportation (DOT), US Department of Energy, Oak Ridge National Lab, Argon National Lab, Y-12 Facility, US Department of Homeland Security, three state DOTs, and two University Transportation Centers. He has conducted multiple projects for major companies such as FedEx, Nissan, Lockheed Martin,and Boeing, and foundations such as Material Handling Industry. He has been actively involved in Institute of Industrial and Systems Engineers (IISE), being the president of the Logistics and Supply Chain division of in 2016, the president of the Engineering Economy division in 2015, and currently a regional Vice President. He now serves as the associate editor for the Journal of Cleaner Production and is on the editorial boards of the Engineering Economists and the International Journal of Production Economics. He has published almost 70 journal papers. Dr. Jin is an IISE fellow.