Stochastic Modeling and Analysis of Manufacturing Systems

Stochastic Modeling and Analysis of Manufacturing Systems edited by David D. Yao.

Manufacturing systems have become increasingly complex over recent years. This volume presents a collection of chapters which reflect the recent developments of probabilistic models and methodologies that have either been motivated by manufacturing systems research or been demonstrated to have signi...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Yao, David D. (Editor)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 1994.
Edition:1st ed. 1994.
Series:Springer Series in Operations Research and Financial Engineering,
Springer eBook Collection.
Subjects:
Business.
Management science.
Operations research.
Decision making.
Production management.
Economic theory.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 1 Jackson Network Models of Manufacturing Systems
  • 1.1 Introduction
  • 1.2 Jackson Networks
  • 1.3 The Throughput Function and Computation
  • 1.4 Monotonicity of the Throughput Function
  • 1.5 Concavity and Convexity
  • 1.6 Multiple Servers
  • 1.7 Resource Sharing
  • 1.8 Arrangement and Majorization
  • 1.9 Conclusions
  • 1.10 Notes
  • 1.11 References
  • 2 Hierarchical Modeling of Stochastic Networks, Part I: Fluid Models
  • 2.1 Introduction
  • 2.2 A Flow Network in Discrete Time
  • 2.3 Flow Networks in Continuous Time
  • 2.4 Linear Fluid Network and Bottleneck Analysis
  • 2.5 Functional Strong Law of Large Numbers
  • 2.6 Applications and Hints at Prospects of Fluid Models
  • 2.7 References and Comments
  • 2.8 References
  • 3 Hierarchical Modeling of Stochastic Networks, Part II: Strong Approximations
  • 3.1 Introduction
  • 3.2 The Model
  • 3.3 Preliminaries
  • 3.4 The Main Results
  • 3.5 Fitting Parametes
  • 3.6 Proof of the Main Results
  • 3.7 References, Possible Extensions and Future Research
  • 3.8 References
  • 4 A GSMP Framework for the Analysis of Production Lines
  • 4.1 Introduction
  • 4.2 GSMP and Its Scheme
  • 4.3 Structural Properties of the Scheme
  • 4.4 The (a, 6, k) Tandem Queue
  • 4.5 Properties with Respect to (a, b, k)
  • 4.6 Line Reversal
  • 4.7 Subadditivity and Ergodicity
  • 4.8 Cycle Time Limits
  • 4.9 Notes
  • 4.10 References
  • 5 Stochastic Convexity and Stochastic Majorization
  • 5.1 Introduction
  • 5.2 Stochastic Order Relations: Functional Characterizations
  • 5.3 Second-Order Stochastic Properties
  • 5.4 Arrangement and Likelihood Ratio Orderings
  • 5.5 Stochastic Rearrangement and Majorization
  • 5.6 Notes
  • 5.7 References
  • 6 Perturbation Analysis of Production Networks
  • 6.1 Introduction
  • 6.2 Overview Through the Single-Machine Model
  • 6.3 Differentiation
  • 6.4 Analysis of the Single-Machine Model
  • 6.5 Production Networks
  • 6.6 Steady-State Derivative Estimation
  • 6.7 Concluding Remarks
  • 6.8 Notes
  • 6.9 References
  • 7 Scheduling Networks of Queues: Heavy Traffic Analysis of a Bi-Criteria Problem
  • 7.1 Introduction
  • 7.2 A Single Server Queue
  • 7.3 A Closed Network
  • 7.4 A Network with Controllable Inputs
  • 7.5 An Example
  • 7.6 A Review of Related Results
  • 7.7 References
  • 8 Scheduling Manufacturing Systems of Re-Entrant Lines
  • 8.1 Introduction
  • 8.2 Re-Entrant Lines: The Models
  • 8.3 Fluctuation Smoothing Scheduling Policies to Reduce Variance of Lateness, Variance of Cycle-Time, and Mean Cycle-Time
  • 8.4 Stability of LBFS, SRPTS, EA, EDD and All Least Slack Scheduling Policies
  • 8.5 Dynamic Scheduling of a Single Machine with Set-Up Times: A Push Model
  • 8.6 Clear-A-Praction Policies
  • 8.7 A Lower Bound on Optimal Cost
  • 8.8 A Good CAF Policy
  • 8.9 Non-Acyclic Manufacturing Systems with Set-Up Times
  • 8.10 Concluding Remarks
  • 8.11 Notes
  • 8.12 References.

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