Table of Contents

Cover

Title

Introduction

I.1. Motivation and literature review
I.2. Overview of the topic

1 Forecasting and Maintenance under Subcontracting Constraint with Delay in Transportation

1.1. Introduction
1.2. Production without retuned products
1.3. Production with retuned products
1.4. Joint maintenance policy
1.5. Conclusion

2 Sequentially Optimizing Production, Maintenance and Delivery Activities Taking into Account Product Returns

2.1. Introduction
2.2. Planning of production, delivery and maintenance
2.3. Transformation of the stochastic production, maintenance and delivery planning model to a deterministic equivalent
2.4. Numerical example and numerical optimization procedure
2.5. Conclusion

3 A Decision Optimization Model for Leased Manufacturing Equipment with Warranty for a Production–Maintenance Forecasting Problem

3.1. Introduction
3.2. Description of the problem
3.3. Mathematical model
3.4. Numerical example
3.5. Conclusion

4 Global Control Policy Taking into Account Maintenance and Product Non-conformity

4.1. Introduction
4.2. Control strategy for stochastic multi-machine multi-product systems: analytical approach
4.3. Description of the production system and the control strategy
4.4. Simulation model
4.5. Experimental analysis
4.6. Finding the best compromise between cost, availability and quality: multi-criteria analysis
4.7. Conclusion

Appendices

Appendix 1
Appendix 2
Appendix 3

Bibliography

Index

End User License Agreement

List of Tables

1 Forecasting and Maintenance under Subcontracting Constraint with Delay in Transportation

Table 1.1. Numerical data
Table 1.2. Mean demand
Table 1.3. Principal machine: U*_1,K
Table 1.4. Subcontractor machine: U*_2,k
Table 1.5. Principal machine: U*_1,k
Table 1.6. Subcontractor machine: U*_2,k
Table 1.7. Total cost variation as a function of service level α with τ = 2
Table 1.8. Total cost variation as a function of standard deviation σ with τ = 2
Table 1.9. Numerical data
Table 1.10. Mean demand
Table 1.11. Principal machine: U*_1,k
Table 1.12. Subcontractor machine: U*_2,k
Table 1.13. Principal machine: U*_1,k
Table 1.14. Subcontractor machine: U*_2,k
Table 1.15. Principal machine: U*_1,k
Table 1.16. Subcontractor machine: U*_2,k

2 Sequentially Optimizing Production, Maintenance and Delivery Activities Taking into Account Product Returns

Table 2.1. Numerical data
Table 2.2. Average demand for the numerical example
Table 2.3. Optimal production plan
Table 2.4. Optimal delivery plan
Table 2.5. Average demand
Table 2.6. Optimal production plan
Table 2.7. Optimal delivery plan
Table 2.8. Delivery time τ and number of preventive maintenance actions N for each value of σ
Table 2.9. Number of preventive maintenance actions N for each value of Ccm
Table 2.10. Numerical data
Table 2.11. Principal machine u*(k)
Table 2.12. Transported quantity: Q*(k)
Table 2.13. Principal machine u*(k)
Table 2.14. Transported quantity: Q*(k)
Table 2.15. Principal machine u*(k)
Table 2.16. Transported quantity: Q*(k)

3 A Decision Optimization Model for Leased Manufacturing Equipment with Warranty for a Production–Maintenance Forecasting Problem

Table 3.1. Average forecasted demand
Table 3.2. Plan to meet the forecast production requirements
Table 3.3. Compromise intervals for the extended warranty cost (in mu) for Cpm = 200 and Ccm = 1,500
Table 3.4. Variation in Cpm cost when Ccm = 1,500
Table 3.5. Variation in Ccm cost when Cpm = 200
Table 3.6. Compromise intervals for the extended warranty cost at Cpm = 200 and Ccm = 1,500 and Δt = 2

4 Global Control Policy Taking into Account Maintenance and Product Non-conformity

Table 4.1. The correspondence between states and events
Table 4.2. Relations between real variables and standardized variables
Table 4.3. Results of the analysis of variance
Table 4.4. Comparative analysis for different Cp/Cs ratios
Table 4.5. Comparative analysis for different MC/MP ratios
Table 4.6. Results of the analysis of variance
Table 4.7. The compromise reached
Table 4.8. Summary of results

List of Figures

1 Forecasting and Maintenance under Subcontracting Constraint with Delay in Transportation

Figure 1.1. Initial production problem without any returned products
Figure 1.2. Production rate variation as a function of T for the principal machine
Figure 1.3. Production rate variation as a function of T for subcontractor machine
Figure 1.4. Total cost variation as a function of τ
Figure 1.5. Production rate variation as a function of service level for principal machine with τ = 2
Figure 1.6. Production rate variation as a function of standard deviation σ with τ = 2
Figure 1.7. Production problem with returned products
Figure 1.8. Production rates of principal machine variation as a function of percentage of products returned δ with τ = 1.Δt
Figure 1.9. Production rates of the subcontractor machine variation as a function of percentage of products returned δ with τ = 1.Δt
Figure 1.10. Total cost variation as a function of the transportation delay τ and percentage of products returned δ
Figure 1.11. Variability of returned production deadline with τ = 3, and x = 3
Figure 1.12. Variability of returned production deadline
Figure 1.13. Maintenance optimization
Figure 1.14. Total cost variation as a function of N with τ = 0
Figure 1.15. Total cost variation as a function of N with τ = 1
Figure 1.16. Total cost variation as a function of N with τ = 4
Figure 1.17. MP number variation as a function of τ
Figure 1.18. Total cost variation as a function of N with τ = 1

2 Sequentially Optimizing Production, Maintenance and Delivery Activities Taking into Account Product Returns

Figure 2.1. Description of the problem
Figure 2.2. Maintenance and production periods
Figure 2.3. Evolution of the rate of failure over time. For a color version of this figure, see www.iste.co.uk/rezg/services.zip
Figure 2.4. The total cost as a function of the delivery time τ and number of preventive maintenance actions N
Figure 2.5. The total cost as a function of the delivery time τ and number of preventive maintenance actions N
Figure 2.6. Economical production plan
Figure 2.7. Delivery quantity plan
Figure 2.8. Number of products produced by machine M variation as a function of product returned δ
Figure 2.9. Transported quantity variation as a function of product returned δ
Figure 2.10. Total cost and delivery time are function of product returned δ
Figure 2.11. Total cost and delivery time are function of service level α

3 A Decision Optimization Model for Leased Manufacturing Equipment with Warranty for a Production–Maintenance Forecasting Problem

Figure 3.1. Lifecycle of a leased machine with warranty and extended warranty periods
Figure 3.2. Evolution of the rate of failure for policy I.1
Figure 3.3. Average number of failures when the lessee does not extend the warranty period
Figure 3.4. Average number of failures if the lessee does extend the warranty period
Figure 3.5. The win–win interval for the extended warranty for Policy II-2
Figure 3.6. There is no win–win interval for the extended warranty cost for Policy I.1

4 Global Control Policy Taking into Account Maintenance and Product Non-conformity

Figure 4.1. The considered production system
Figure 4.2. The different states of the system
Figure 4.3. Iso-response of the cost function in plane (m₂, h₂). For a color version of this figure, see www.iste.co.uk/rezg/services.zip
Figure 4.4. Variation of the cost function in space (h₁, m₂, h2). For a color version of this figure, see www.iste.co.uk/rezg/services.zip
Figure 4.5. Iso-responses of the availability function in plane (m₁, m₂). For a color version of this figure, see www.iste.co.uk/rezg/services.zip
Figure 4.6. Variation of the availability function in plane (m₁, m₂). For a color version of this figure, see www.iste.co.uk/rezg/services.zip
Figure 4.7. Variation of function N(t)
Figure 4.8. Representation of desirability. For a color version of this figure, see www.iste.co.uk/rezg/services.zip
Figure 4.9. Desirable cost
Figure 4.10. Desirable level of availability
Figure 4.11. Desirable level of loss

First published 2016 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

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John Wiley & Sons, Inc.
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The rights of Nidhal Rezg, Zied Hajej and Valerio Boschian-Campaner to be identified as the author of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2016949449

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN 978-1-78630-095-9

Introduction

I.1. Motivation and literature review

The improvement of industry involves the reduction of costs and maximization of customer satisfaction. Satisfying customer demands in a timely fashion has become difficult due to the random nature of such demands, a problem compounded by machine failures and low system availability. High system availability, minimal machine failure and customer satisfaction cannot be achieved without good management and a good knowledge of how to address problems while making decisions. These decisions are generally associated with three levels of hierarchical planning: strategic, tactical and operational planning.

The allocation of resources can become necessary over long periods of time, as purchase costs can become prohibitive. Subcontracting and leasing have become very important for many manufacturing enterprises because of the advantages that these solutions can bring. Such industrial solutions are becoming increasingly popular, for example subcontracting the workforce to perform certain tasks (maintenance, supervision, audit, etc.) or leasing workstations in order to produce the required quantities of products.

Several industrial constraints imposed on companies have led to the revision of integrated maintenance production strategies. Such strategies are adopted in order to develop and optimize new, integrated maintenance-based production strategies, taking into account certain industrial constraints, such as logistics, quality, warranties, and subcontracting. Through the development of such maintenance/production strategies produced under constraints, we can gain an overview of the maintenance strategies and production decisions required to balance industrial system availability, productivity and customer satisfaction.

I.2. Overview of the topic

This book explores several maintenance and production optimization problems, taking into account certain industrial constraints.

Chapter 1 covers an integrated production and maintenance optimization strategy for a forecasting production and maintenance problems. The production system is composed of a single machine M₁ subjected to random failure. In order to satisfy the random demand, under given service level, subcontracting assures the rest of the production through machine M₂ with transportation delay. An analytic study of the problem has been proposed using a sequential determination of the economical production plan for which an optimal preventive maintenance strategy has been calculated based on minimal repair. Firstly, an economic production plan of principal and subcontracting machines was obtained, which minimizes the total cost of production and inventory for the cases with and without returned products under service level and subcontracting transportation delay. Secondly, a joint maintenance strategy is determined according to the optimal production plan, under various constraints for production rates, transportation delay and returned production deadlines. Numerical results are presented to highlight the application of the developed approach and sensitivity analyses show the robustness of the model.

Chapter 2 presents a stochastic production, maintenance and delivery problem for a deteriorating manufacturing system. Under stochastic demand, in terms of service level, product return and delivery time, this book proposes a mathematical formulation based on quadratic modeling. Production and maintenance policies are developed in order to study the influence of delivery time on the planning of production, maintenance and delivery activities. Simulation results are presented to illustrate the exploitation of the proposed approach.

In Chapter 3 we develop a mathematical model based on the forecasting production/maintenance optimization problem, to study lease contracts with basic and extended warranties based on win-win relationship between the lessee and the lessor. The influence of production rates in equipment degradation and consequently on the total cost by each side during the finite leasing period is stated in order to determine a theoretical condition under which a compromise-pricing zone exists under different possibilities of maintenance policies.

Chapter 4 presents presents a control policy of a manufacturing system under cost, availability and quality constraints. The production system consists of a two machines and two buffers and produces conforming and non-conforming products. A preventive maintenance strategy is developed in order to determine the instants at which preventive maintenance has to be performed on each machine, and both buffer inventory levels. A simulation, experimental design and multi-criteria analysis are presented to prove the adopted approach.

Production and Maintenance Optimization Problems

Logistic Constraints and Leasing Warranty Services

Introduction

I.1. Motivation and literature review

I.2. Overview of the topic