Aditya Gandhi

Abstract

In workforce allocation, gaps between workers available and workers needed at various operations result in production delays and a loss of profitability for the manufacturer. These gaps can be reduced by overtime assignments of workers from other shifts. However, for a multiple shift planning horizon, a mix of cross-training of workers over different tasks along with overtime assignments may be a good strategy. This work develops an industry-motivated cross-training framework that identifies workers and operations for normal, overtime, and training assignments. A mixed integer programming model that integrates all three assignment tasks is formulated and solved. The production scenario consists of skill level based qualifications for workers that need to be assigned to operations in every shift. Factory floor conditions such as limits on worker levels at specific operations, scheduling restrictions and worker training protocols are also considered. The data taken into account includes parameters such as man-machine ratio, tool count, and limits on skill qualifications for workers. The output of the model provides a cross-training schedule and an assignment schedule that can be used by floor managers on a shift-by-shift basis. The MIP model is implemented in C# using the .NET framework and the IBM ILOG CPLEX Optimizer.

Library of Congress Subject Headings

Manpower planning--Data processing; Employees--Training of--Mathematical models; Mathematical optimization

Publication Date

12-11-2014

Document Type

Thesis

Student Type

Graduate

Degree Name

Industrial and Systems Engineering (MS)

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)

Advisor

Scott E. Grasman

Advisor/Committee Member

Michael R. Hewitt

Comments

Physical copy available from RIT's Wallace Library at HF5549.5.M3 G36 2014

Campus

RIT – Main Campus

Plan Codes

ISEE-MS

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