Artificial Neural Networks in Manufacturing: Scheduling

Artificial Neural Networks in Manufacturing: Scheduling

George A. Rovithakis (Aristotle University of Thessaloniki, Greece), Stelios E. Perrakis (Technical University of Crete, Greece) and Manolis A. Christodoulou (Technical University of Crete, Greece)
Copyright: © 2006 |Pages: 26
DOI: 10.4018/978-1-59140-670-9.ch014
OnDemand PDF Download:
$37.50

Abstract

In this chapter, a neuroadaptive scheduling methodology, approaching machine scheduling as a control-regulation problem, is presented and evaluated by comparing its performance with conventional schedulers. Initially, after a brief reference to the context of existing solutions, the evaluated controller is thoroughly described. Namely, the employed dynamic neural network model, the subsequently derived continuous time neural network controller and the control input discretization that yield the actual dispatching times are presented. Next, the algorithm guaranteeing system stability and controller-signal boundedness and robustness are evaluated on an existing industrial test case that constitutes a highly nonacyclic deterministic job shop with extremely heterogeneous part-processing times. The major simulation study, employing the idealistic deterministic job-shop abstraction, provides extensive comparison with conventional schedulers, over a broad range of raw-material arrival rates, and through the extraction of several performance indices verifies its superb performance in terms of manufacturing-system stability and low makespan, low average lead times, WIP, inventory, and backlogging costs. Eventually, these extensive experiments highlight the practical value and the potential of the mathematical properties of the proposed neuroadaptive controller algorithm and its suitability for the control of nontrivial manufacturing cells.

Complete Chapter List

Search this Book:
Reset
Table of Contents
Preface
Joarder Kamruzzaman, Rezaul Begg, Ruhul Sarker
Acknowledgments
Joarder Kamruzzaman, Rezaul Begg, Ruhul Sarker
Chapter 1
Joarder Kamruzzaman, Ruhul A. Sarker
The primary aim of this chapter is to present an overview of the artificial neural network basics and operation, architectures, and the major... Sample PDF
Artificial Neural Networks: Applications in Finance and Manufacturing
$37.50
Chapter 2
Ruhul A. Sarker, Hussein A. Abbass
Artificial Neural Networks (ANNs) have become popular among researchers and practitioners for modeling complex real-world problems. One of the... Sample PDF
Simultaneous Evolution of Network Architectures and Connection Weights in Artificial Neural Networks
$37.50
Chapter 3
David Encke
Researchers have known for some time that nonlinearity exists in the financial markets and that neural networks can be used to forecast market... Sample PDF
Neural Network-Based Stock Market Return Forecasting Using Data Mining for Variable Reduction
$37.50
Chapter 4
Yuehui Chen, Ajith Abraham
The use of intelligent systems for stock market prediction has been widely established. In this paper, we investigate how the seemingly chaotic... Sample PDF
Hybrid-Learning Methods for Stock Index Modeling
$37.50
Chapter 5
John Fulcher, Ming Zhang, Shuxiang Xu
Financial time-series data is characterized by nonlinearities, discontinuities, and high-frequency multipolynomial components. Not surprisingly... Sample PDF
Application of Higher-Order Neural Networks to Financial Time-Series Prediction
$37.50
Chapter 6
Masoud Mohammadian, Mark Kingham
In this chapter, an intelligent hierarchical neural network system for prediction and modelling of interest rates in Australia is developed. A... Sample PDF
Hierarchical Neural Networks for Modelling Adaptive Financial Systems
$37.50
Chapter 7
Sumit Kumar Bose, Janardhanan Sethuraman, Sadhalaxmi Raipet
The term structure of interest rates holds a place of prominence in the financial and economic world. Though there is a vast array of literature on... Sample PDF
Forecasting the Term Structure of Interest Rates Using Neural Networks
$37.50
Chapter 8
Joarder Kamruzzaman, Ruhul A. Sarker, Rezaul K. Begg
In today’s global market economy, currency exchange rates play a vital role in national economy of the trading nations. In this chapter, we present... Sample PDF
Modeling and Prediction of Foreign Currency Exchange Markets
$37.50
Chapter 9
Tong-Seng Quah
Artificial neural networks’ (ANNs’) generalization powers have in recent years received admiration of finance researchers and practitioners. Their... Sample PDF
Improving Returns on Stock Investment through Neural Network Selection
$37.50
Chapter 10
Eldon Gunn, Corinne MacDonald
This chapter provides some examples from the literature of how feed-forward neural networks are used in three different contexts in manufacturing... Sample PDF
Neural Networks in Manufacturing Operations
$37.50
Chapter 11
M. Imad Khan, Saeid Nahavandi, Yakov Frayman
This chapter presents the application of a neural network to the industrial process modeling of high-pressure die casting (HPDC). The large number... Sample PDF
High-Pressure Die-Casting Process Modelling Using Neural Networks
$37.50
Chapter 12
Sergio Cavalieri, Paolo Maccarrone, Roberto Pinto
The estimation of the production cost per unit of a product during its design phase can be extremely difficult, especially if information about... Sample PDF
Neural Network Models for the Estimation of Product Costs: An Application in the Automotive Industry
$37.50
Chapter 13
Tapabrata Ray
Surrogate-assisted optimization frameworks are of great use in solving practical computationally expensive process-design-optimization problems. In... Sample PDF
A Neural-Network-Assisted Optimization Framework and Its Use for Optimum-Parameter Identification
$37.50
Chapter 14
George A. Rovithakis, Stelios E. Perrakis, Manolis A. Christodoulou
In this chapter, a neuroadaptive scheduling methodology, approaching machine scheduling as a control-regulation problem, is presented and evaluated... Sample PDF
Artificial Neural Networks in Manufacturing: Scheduling
$37.50
Chapter 15
Bernard F. Rolfe, Yakov Frayman, Georgina L. Kelly, Saeid Nahavandi
This chapter describes the application of neural networks to recognition of lubrication defects typical to industrial cold forging process. The... Sample PDF
Recognition of Lubrication Defects in Cold Forging Process with a Neural Network
$37.50
About the Authors