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Michael Kay

MK
A headshot of Michael Kay standing in front of some bookshelves.

Industrial and Systems Engineering

Associate Professor

IMSE Director

Industrial and Systems Engineering

Fitts-Woolard Hall 4161

919.515.2008

Bio

Michael Kay has been an associate professor of Industrial Engineering at NC State University since 1992. He is the Director of Integrated Manufacturing Systems Engineering Program. He is past-President and Liaison to the MHI Roundtable Advisory Committee of the College-Industry Council on Material Handling Education.

Teaching:
ISE 453: Design of Production, Logistics, and Service Systems
OR/ISE 501: Introduction to Operations Research
ISE 754: Logistics Engineering

Research:
Home Delivery Logistics Networks using Driverless Delivery Vehicles
Public Logistics Networks
Multimedia Sensor Fusion for Intelligent Camera Control

Software:
Matlog: Logistics Engineering Matlab Toolbox
Lgpy: Logistics Engineering Python Package
Julog: Logistics Engineering Julia Toolbox
GAOT: Genetic Algorithm Optimization Toolbox (zip)

Documents:
Basic Concepts in Matlab (pdf)
Lecture Notes for Production System Design (pdf)
Material Handling Equipment (pdf)
Material Handling Equipment Taxonomy
Warehousing (pdf)

Education

Ph.D. Industrial Engineering NC State University 1922

M.S. Industrial Engineering University of Florida 1954

B.A. Economics University of Florida 1981

Area(s) of Expertise

Kay's research focuses is on the design of public logistics networks. Areas of research interest include logistics network design. metaheuristics, freight transportation, material handling, warehousing, facilities design, and genetic algorithms.

Publications

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Grants

Date: 08/16/21 - 12/31/22
Amount: $109,106.00
Funding Agencies: Ricoh USA, Inc.

This proposal is aimed developing models and providing analysis to aid Ricoh in the development of spare parts supply chain networks with additive manufacturing (AM) capability. The goal is to design and exercise a decision-support model that helps Ricoh evaluate the answers to the following questions: When should I consider adding AM capability into my spare parts logistics network? If I should use AM, where do I locate AM capability in the network? Do the statistical characteristics of my spare parts demand impact the design of my supply network? How can I quantitatively measure the efficiency, resilience and security of the network? After establishing it, how do I best resource, manage, and employ the AM capability? Due to the fast-changing environment and capabilities of AM equipment, the model must be flexible enough to adjust to new evolutions of AM technology as new materials, processes, and capabilities continue to emerge over time. The model will provide optimization of supply chain configurations given the production capabilities, both traditional and AM, available to the supply chain under forecast demand scenarios.

Date: 11/01/16 - 5/15/22
Amount: $500,000.00
Funding Agencies: John Deere Turf Care, Inc.

John Deere Turf Care would like to undertake projects in process improvement, quality, systems integration and other manufacturing related areas. The Integrated Manufacturing Systems Engineering (IMSE) Institute engages in manufacturing system projects and research. IMSE student interns will work with John Deere personnel on these projects.

Date: 07/01/17 - 6/30/18
Amount: $36,815.00
Funding Agencies: Center for Additive Manufacturing and Logistics - (CAMAL)

Additive manufacturing (AM) offers a potentially game changing approach for manufacturing products. Together, industry and academia are working towards identifying the opportunities and tackling the associated challenges of employing AM technology for final-use part production. Notable AM operational challenges include: (i) integrating the technology into the industry; (ii) optimizing the productivity within the build chamber; and (iii) utilizing resources more effectively (e.g. existing manufacturing capacity, additive manufacturing capacity, labor). The research proposed aims to contribute clarity towards the third operational challenge listed, utilizing the collection of resources most effectively within a production environment consisting of both AM and traditional manufacturing (TM) technologies. The primary aim of the research focuses on scheduling and dispatch policies for an AM-TM resourced facility through cost modelling analysis. A secondary aim of research investigates the associated inventory policies for all types of the associated system entity flow (i.e. raw materials, work-in-progress, and finished goods).

Date: 07/01/05 - 6/30/11
Amount: $165,867.00
Funding Agencies: NCSU Furniture Manufacturing & Management Center

Globalization in the manufacture of furniture has resulted in an almost daily erosion in the number and scale of domestic furniture producers. Casegoods manufacturers have been the most severely impacted, although import competition in upholstered goods is now accelerating. Possible explanations for the development of this situation abound. These include the high cost of labor and regulation in the U.S., government subsidies of foreign producers, failure to invest in manufacturing and information technology, poor asset utilization (single shift operation), failure to advertise and ?connect? with consumers, stagnant product innovation, and a retailing system that emphasizes price and destroys margins, as well as many others. The rapid movement of furniture production to off-shore sources has significantly increased the need for efficient, reliable supply chains. In addition, because of the relatively longer supply leadtimes, inventory control policies have become more critical for balancing customer service levels and inventory costs. The purpose of this project is: ? provide analysis of potential supply chain configurations; ? provide analysis of inventory control policies of potential supply chain configurations; and ? provide training to industry personnel on supply chain issues.


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