Doctoral Dissertations


"We present a framework that integrates strategic and operational workforce planning models. Since these models provide decisions for planning horizons with different lengths, the formulation and solution strategy should ensure that the flow of information between these models is both appropriate and consistent.

The single-shift workforce planning problem is formulated as a two-phase goal program. In the first phase, the model allocates the workers to machine groups and identifies the shortage of workers (referred to as gap) followed by the second phase, in which certain constraints are relaxed and the workers are reallocated to the machine groups in order to minimize the gap. For multi-shift planning, we first present a monolithic integer programming formulation that assigns regular and overtime workers to multiple shifts considering the factory overtime policies along with other business rules. Next, based on the problem structure, we present a decomposition strategy so that it can seamlessly be integrated with the single-shift model, providing flexibility for real-world implementations. The formulation of these models makes them both scalable and adaptable to general manufacturing scenarios. Lastly, we present a control theoretic formulation and solution strategy for the strategic models. We provide the structural analysis and sufficiency conditions for optimality for these models.

These models been developed considering the real-world business rules and data provided by a leading semiconductor manufacturer. We provide sample numerical results for the single-shift and multi-shift models based on initial testing and validation in their factories. The benefits of the proposed framework include: increased operational efficiencies due to optimal worker-machine group allocation, effective design and implementation of cross-training programs leading to accurate estimation of the workforce requirements, and reduction in the overall manufacturing costs"--Abstract, page iv.


Grasman, Scott E. (Scott Erwin)

Committee Member(s)

Liu, Zhen
Cudney, Elizabeth A.
Landers, Robert G.
Singler, John
Keng, Naiping


Engineering Management and Systems Engineering

Degree Name

Ph. D. in Engineering Management


Intel Corporation


This work was completely funded by Intel Research Council and Intel Corporation.


Missouri University of Science and Technology

Publication Date

Summer 2011


xi, 105 pages

Note about bibliography

Includes bibliographical references (pages 100-104).


© 2011 Shrikant Jarugumilli, All rights reserved.

Document Type

Dissertation - Restricted Access

File Type




Subject Headings

Management science -- Computer simulation
Semiconductor production equipment industry
Management science -- Mathematical models
Manufacturing processes -- Computer simulation

Thesis Number

T 10266

Print OCLC #


Electronic OCLC #


Link to Catalog Record

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