Date of Graduation

5-2014

Document Type

Thesis

Degree Name

Master of Science in Industrial Engineering (MSIE)

Degree Level

Graduate

Department

Industrial Engineering

Advisor

Justin R. Chimka

Committee Member

Richard Cassady

Second Committee Member

Chase Rainwater

Abstract

The conventional method used in attribute control charts is the Shewhart three sigma limits. The implicit assumption of the Normal distribution in this approach is not appropriate for skewed distributions such as Poisson, Geometric and Negative Binomial. Normal approximations perform poorly in the tail area of the these distributions. In this research, a type of attribute control chart is introduced to monitor the processes that provide count data. The economic objective of this chart is to minimize the cost of its errors which is determined by the designer. This objective is a linear function of type I and II errors. The proposed control chart can be applied to Poisson, Geometric and Negative Binomial as the underlying distribution of count data. Control limits in this chart is calculated optimally since it is based on the probability distribution of the data and can detect a directional shift in the process rate. Some numerical results for the optimal design of the proposed control chart are provided. The expected cost of the control chart is compared to that of a one sided c chart. The effects of changing the available parameters on the cost, errors and the optimal limits of the proposed control chart are shown graphically.

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