Graduate Thesis Or Dissertation
 

Resource planning of a high technology company under risk and uncertainty

Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/wm117s36q

Descriptions

Attribute NameValues
Creator
Abstract
  • A multi-phase methodology is proposed as an aid to resource planning and management activities in a high technology company faced with an uncertain marketing future. An attempt is made to incorporate both quantifiable and non-quantifiable factors. The problem analysis phase of the proposed methodology employs Resource Planning and Management (RPM) network as a graphical representation of quantifiable relationships within the physical process operated by the company. Simple linear relationships between 100 resources and 92 processes lead to a linear programming (LP) model which was solved on a CDC-3300 computer. The results were compared against the actual production schedule for the period from which the original data were obtained. The decision analysis phase adapts the LP model to incorporate forecasted demands for the next production period. Information generated from the LP model is used to identify the potential resource bottlenecks. The potential problem analysis phase considers the problem under uncertainty. A game theory payoff matrix is developed to estimate the effects of bottlenecks under a set of scenarios describing possible future conditions and for a given set of management alternatives. Hurwicz, Savage, and Wald criteria from game theory and nine choice rules advocated by Easton are described. These techniques aid the management in bridging the gap between the quantified values in the payoff matrices and the subjective preferences imposed by the decision maker. The proposed methodology is applied to the operation of a plant manufacturing accessories to precision doctrine instruments. Profitability, labor stabilization, and rate of return were used as three objectives evaluated under three marketing scenarios.
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Publisher
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome) using ScandAll PRO 1.8.1 on a Fi-6770A in PDF format. CVista PdfCompressor 5.0 was used for pdf compression and textual OCR.
Replaces

Relationships

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details JainPravinJ1976.pdf 2017-08-17 Public Download