Michael Kay

About

Michael Kay is the Director of IMSEI and an Associate Professor at NC State University. His research focus is in the field of industrial and systems engineering, contributing to areas related to operations research, system analytics, and optimization. As a key faculty member, he is involved in advancing the understanding and application of engineering principles to improve complex systems. His role encompasses leadership in research initiatives and academic programs within the department, supporting the development of innovative solutions in industrial engineering. His work is integral to the department's mission of fostering research and education that support the engineering community and industry partners.

Research topics

• Computer Science
• Engineering
• Computer Security
• Economics
• Operations research
• Business
• Marketing
• Systems engineering
• Microeconomics
• Mathematical optimization

Selected publications

• Challenges and opportunities to integrate the oldest and newest manufacturing processes: metal casting and additive manufacturing

  Rapid Prototyping Journal · 2020 · 60 citations

  Purpose This paper aims to investigate the current state, technological challenges, economic opportunities and future directions in the growing “indirect” hybrid manufacturing ecosystem, which integrates traditional metal casting with the production of tooling via additive manufacturing (AM) process including three-dimensional sand printing (3DSP) and printed wax patterns. Design/methodology/approach A survey was conducted among 100 participants from foundries and AM service providers across the…

  DOI

• Digital Facility Layout Planning

  Sustainability · 2020 · 53 citations

  Senior authorCorresponding

  In recent years, companies have increased their focus on sustainability to achieve environmental-friendly improvements, to manage pressures from society and regulations, and to attract customers that appreciate sustainability efforts. While companies have mainly aimed short-term/operational improvements, long-term improvements are difficult to reach. One of the fundamental, strategical decision-making processes for a company is facility layout planning. The layout of a facility can have a signif…

  DOI

• Designing a manufacturing network with additive manufacturing using stochastic optimisation

  International Journal of Production Research · 2022 · 22 citations

  Senior authorCorresponding

  Two of the major problems Traditional Manufacturing (TM) supply chains face are setting requisite reactive strategies to address the uncertainties in demand and the optimal placement of these buffering capacities in order to be both responsive and cost-effective. With Additive Manufacturing (AM) stepping into large-scale production at different firms, we address the aforementioned supply chain dilemmas by considering the potential role of AM in a TM supply chain network where AM facilities can a…

  PublisherDOI

• Performance tradeoffs for spare parts supply chains with additive manufacturing capability servicing intermittent demand

  Journal of Defense Analytics and Logistics · 2021 · 10 citations

  Purpose The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns. Design/methodology/approach This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies…

  DOI

• Modeling and transportation planning for US noncombatant evacuation operations in South Korea

  Journal of Defense Analytics and Logistics · 2020 · 5 citations

  Purpose The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions. Design/methodology/approach It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity a…

  DOI

Frequent coauthors

• Brandon M. McConnell

  North Carolina State University

  28 shared

• Russell E. King

  North Central State College

  27 shared

• Kristin Thoney-Barletta

  18 shared

• Thom J. Hodgson

  North Carolina State University

  16 shared

• Jeffrey A. Joines

  North Carolina State University

  8 shared

• Ryan D. Winz

  U.S. Air Force Institute of Technology

  8 shared

• Kenan Karagül

  Pamukkale University

  8 shared

• J.A. Janet

  7 shared

Similar researchers at North Carolina State University

• Reha Uzsoyh-56
• Jingyan Dongh-37
• S. Sebnem Ahiska Kingh-35