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Interval alignment policies and thei...

Wang, Meimei.

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Interval alignment policies and their applications.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Interval alignment policies and their applications./
作者:	Wang, Meimei.
面頁冊數:	118 p.
附註:	Adviser: James R. Perkins.
Contained By:	Dissertation Abstracts International67-09B.
標題:	Engineering, Industrial. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3232932
ISBN:	9780542869488

Interval alignment policies and their applications.
Wang, Meimei.

Interval alignment policies and their applications. - 118 p.

Adviser: James R. Perkins.

Thesis (Ph.D.)--Boston University, 2007.

Dynamic scheduling of parts, or jobs, is an area of intense research interest. Commonly, dynamic scheduling is done either on a heuristic basis or using queueing network models. Minimization of the average lead time (the time spent in the system by a part) is one of the primary performance objectives for a scheduling policy. From Little's Law, this is equivalent to minimization of the average work-in-process (WIP).

ISBN: 9780542869488Subjects--Topical Terms:

626639
Engineering, Industrial.

Interval alignment policies and their applications.
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502 $a Thesis (Ph.D.)--Boston University, 2007.
520 $a Dynamic scheduling of parts, or jobs, is an area of intense research interest. Commonly, dynamic scheduling is done either on a heuristic basis or using queueing network models. Minimization of the average lead time (the time spent in the system by a part) is one of the primary performance objectives for a scheduling policy. From Little's Law, this is equivalent to minimization of the average work-in-process (WIP).
520 $a In this dissertation, a new class of detailed scheduling policies, called interval alignment (IA) policies, is introduced. IA policies are based on the idea that there is no benefit to have a part arrive to a machine before it will receive processing from that machine. By adding delays to the system, IA policies effectively synchronize part flows, reducing waiting times at the machines.
520 $a In the past decade, much effort has been put into removing variability from the flow of material in systems. Significant progress has been made on this front, demonstrating the advantages of near-periodic release policies and explicit modeling of bounded processing times. The proposed IA policies effectively utilize these smoothed part flows to improve performance by decreasing the average system WIP and the average lead time. For a range of systems, IA policies are shown to outperform best-practice policies that currently are used both in academia and in industry.
520 $a The performance of heuristic policies is heavily system-specific. For example, the commonly-used First-Come-First-Served (FCFS) policy can result in unbounded WIP. However, using the IA scheduling policies introduced in this dissertation, it is shown that, by adding intermediate delays to the system, FCFS scheduling will become stable and may become the optimal policy.
520 $a In addition, in order to obtain computationally feasible results, queueing network models typically either rely on asymptotic assumptions (e.g., heavy traffic or light traffic arrival processes) or are Markovian (i.e., utilize exponential probability distributions). However, many real-world systems do not operate under asymptotic conditions and do not naturally adhere to the Markovian structure. For example, in supply chain systems and project management, processing-time distributions are often bounded within specification levels (e.g., uniform or triangular distributions). Such systems are characterized by low variation. As will be shown, IA scheduling policies are effective for these systems.
520 $a The primary focus of this dissertation is on the utilization of IA policies in order to reduce the average WIP in a system, for systems with low-to-moderate variability in processing times, interarrival times, demand rates, machine reliability, etc. In addition to scheduling in manufacturing systems, other application areas discussed include the use of IA policies in supply chain management, kanban-controlled systems, facility layout and capacity design, and work cell design.
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