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by Kenneth a. Shaw (Author)
Updated to integrate the management of associated information processes, expand some application discussions, and provide additional reference material, the intent of this monograph is to help business professionals use waiting line (queuing) analysis methods to improve both service and manufacturing business applications of queuing situations. Emphasis is given to discussing the caveats in applying waiting line theory and becoming aware of the assumptions used in developing that theory. The importance of accounting for variability in waiting line processes is discussed in some detail because the basic queuing equations provide only average performance data under steady-state conditions. Understanding how much variability can exist for a given waiting line scenario provides a manager with the insight required to reduce these effects and develop innovative solutions for improving service while reducing operating costs. In general the mathematical tone of the book is focused on applications, not the derivation of the formulas presented. The few derivation exceptions illustrate some approaches not commonly discussed in textbooks-for example, the use of state diagrams and random number approximations of the probability distributions for use in simple simulation models. To aid in understanding the material presented, some practical examples are given at appropriate points in the text and some simulation approaches using common spreadsheet software are described.
Author Biography
Kenneth (Ken) Shaw has a PhD and MS in electrical engineering from Arizona State University and a BSEE from Purdue University. His experience in industry was gained at a number of high-technology enterprises that include Naval Avionics Facility, Royal Melbourne Institute of Technology, General Electric, Motorola Semiconductor, Unisys, and four divisions of Hewlett-Packard. He shared the lessons learned from that experience as an adjunct professor teaching operations and process management for the College of Business at Oregon State University from 2003 to 2011.
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Description
by Kenneth a. Shaw (Author)
Updated to integrate the management of associated information processes, expand some application discussions, and provide additional reference material, the intent of this monograph is to help business professionals use waiting line (queuing) analysis methods to improve both service and manufacturing business applications of queuing situations. Emphasis is given to discussing the caveats in applying waiting line theory and becoming aware of the assumptions used in developing that theory. The importance of accounting for variability in waiting line processes is discussed in some detail because the basic queuing equations provide only average performance data under steady-state conditions. Understanding how much variability can exist for a given waiting line scenario provides a manager with the insight required to reduce these effects and develop innovative solutions for improving service while reducing operating costs. In general the mathematical tone of the book is focused on applications, not the derivation of the formulas presented. The few derivation exceptions illustrate some approaches not commonly discussed in textbooks-for example, the use of state diagrams and random number approximations of the probability distributions for use in simple simulation models. To aid in understanding the material presented, some practical examples are given at appropriate points in the text and some simulation approaches using common spreadsheet software are described.
Author Biography
Kenneth (Ken) Shaw has a PhD and MS in electrical engineering from Arizona State University and a BSEE from Purdue University. His experience in industry was gained at a number of high-technology enterprises that include Naval Avionics Facility, Royal Melbourne Institute of Technology, General Electric, Motorola Semiconductor, Unisys, and four divisions of Hewlett-Packard. He shared the lessons learned from that experience as an adjunct professor teaching operations and process management for the College of Business at Oregon State University from 2003 to 2011.
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