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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
This book focuses on industrial constraints such as subcontracting, warranty, and quality in manufacturing and logistic fields and gives new integrated maintenance strategies. It presents new production and maintenance Control Policies compared to the Hedging Point theory Strategy and different integrated strategies of maintenance are developed under industrial constraints in order to propose a robustness production and maintenance plan.
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Seitenzahl: 194
Veröffentlichungsjahr: 2016
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Table of Contents
Cover
Title
Copyright
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
Landmarks
Cover
Table of Contents
Begin Reading
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Series Editor
Hisham Abou-Kandil
Production and Maintenance Optimization Problems
Logistic Constraints and Leasing Warranty Services
Nidhal Rezg
Zied Hajej
Valerio Boschian-Campaner
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:
ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK
www.iste.co.uk
John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA
www.wiley.com
© ISTE Ltd 2016
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.
1Forecasting and Maintenance under Subcontracting Constraint with Delay in Transportation
This chapter presents a forecasting problem relating to production and maintenance optimization to meet random demand with a single machine M1 on a finite horizon. The function rate of M1 depends on the production rate for each period within the forecasting horizon. In order to satisfy customer demand, subcontracting assures the remaining production through machine M2 with a delay in transportation. An analytical formulation of the problem is proposed using sequential computation of the optimal production plan, for which an optimal preventive maintenance policy has been calculated based on minimal repair.
First, we find, the optimal production plans of the principal (M1) and subcontracting (M2) machines. Such plans minimize the total production and inventory cost for situations with and without returned products at an agreed service level and with a delay in subcontracting transportation.
Second, we determine a joint effective maintenance policy with the optimal production plan, which integrates the various constraints for production rates, transportation delay and returned production deadline.
Numerical results are presented to highlight the application of the approach we develop and sensitivity analysis shows the robustness of the model.
1.1. Introduction
Industry improvement requires a reduction in costs and maximization of customer satisfaction. These two goals can be achieved with good management and decision-making. The importance of subcontracting has grown both from economic and production points of view. The new manufacturing paradigm, which emphasizes outsourcing, cooperation, networking and agility, is regularly discussed at a general level but very little empirical research has been done on these issues.
Amesse et al. [AME 01] introduced the importance of subcontracting as an industrial strategy across all domains. Subcontracting requires collaboration, logic, coordination and management between the manufacturing companies in order to meet customer requires in terms of quantity and delay [AND 99, BER 01].
Recently, more work relating to production and maintenance coupling has been published that integrates new constraints corresponding to the concept of subcontracting. There are a number of different works that deal with subcontracting under constraints, for example [DEL 07] and [DAH 10]. Dellagi et al. [DEL 07] have contributed to the development of integrated maintenance policies while coupling maintenance and production under the constraint of subcontracting. In an industrial model, they assumed that production consisted of only one machine and, in order to satisfy customer demand, it was necessary to collaborate with another subcontracting machine. Dahane et al. [DAH 10] aims to determine maintenance policies that consider the concept of subcontracting, but concerning the provider of a subcontracting service. The optimal time for maintenance and the optimal stock level, considering the relationship between production and maintenance, is determined. The demand, in several works that take the subcontracting approach, is assumed to be constant and known across an infinite horizon. This type of problem is more difficult in the case of random demand over a finite horizon. In this situation, variations in production rates are necessary to meet demand.
Regarding a production/inventory problem without maintenance, Holt et al. [HOL 60] proposed a model defining a quadratic cost minimization program that approximates the cost functions for hiring and laying off labor, overtime, inventory and product shortage through the use of suitable quadratic functions. As a result, and considering some constraints, this model provides an optimal smoothing solution for aggregating inventory, production and the workforce. In this context, Silva and Cezarino [SIL 04] have analyzed a production–planning optimization problem that uses both imperfect information from decision inventory variables and computes the expected cost.
Several works have dealt with the interdependent relationship between production and maintenance planning. There are different attempts to study the problem of conflict in management decisions and the necessity of combining objectives in order to enhance the global benefits of industry, and mainly to minimize global costs, in the literature. Research has been carried out to analyze the problem of joint production and maintenance optimization. In this context, Aghazzaf et al. [AGH 08] have developed models dealing with integrated maintenance based on aggregated production planning, where decision variables related to preventive and corrective maintenance are used. Recently, Hajej et al. [HAJ 11] have dealt with combined production and maintenance plans for a manufacturing system satisfying random demand over a finite horizon. In their model, they consider the influence of production on the degradation of a machine, and consequently consider maintenance planning.
In our study, we build on models presented in Hajej et al. [HAJ 09] and Ayed et al. [AYE 12] where the given manufacturing systems cannot ensure the total demand over the given time horizon and subcontracting is called for.
Ayed et al. [AYE 12] dealt with a randomly failing manufacturing system M1 which has to satisfy random demand across a finite horizon at a required service level. To help meet demand, subcontracting through another production system M2 is used. M1 operates with a variable production rate and its failure rate depends on both time and production rate.
Hajej et al. and Ayed et al. [AYE 12 HAJ 09, HAJ 11, HAJ 12] have, however, ignored several significant characteristics and terms of manufacturing systems, such as transportation, terms of delay, quantity and subcontracting transport, in their work. Many pieces of research analyze transportation delays, such as the delay in delivery between a manufacturing plant and the warehouse that has purchased the manufactured goods, and the impact of such delays on the manufacturing system. For example Richard and Chen [RIC 05], which considered a multi-agent architecture of supply chain integration, proposed heuristics and programming models in order to devise demand-driven supply chains via two types of bidding approaches: customization and webbing. Recently, based on the works by Hajej etal. [HA 11, HAJ 12], Turki et al. [TUR 12] studied a simple manufacturing model composed of one machine with a transport delay between production (at the manufacturing plant) and receipt by the customer (at the warehouse) by treating the impact of delivery time and withdrawal on production/maintenance planning and quantity transported per time period in order to satisfy a random demand.
Motivated by the work in Turki et al. [TUR 12], we treat the aspect of transportation in another more complex and realistic industrial system composed of two machines (a principal and a subcontractor machine), by integrating a subcontractor with its related characteristics, such as transportation delay. This study has novelty and originality in the development of a production and maintenance optimization plan to address this type of problem. It shows that a subcontractor machine can be used to help guarantee the desired service level by distributing production so that the principal machine is not used at its maximum rate, since its degradation rate is correlated with production level.
The primary objective of this chapter is to determine economical production planning over the finite horizon based on forecasting demand, taking into account the transportation delay relating to subcontracting. The impact of transportation delay on optimal production planning will be studied thereafter. Our secondary objective is to establish economical production plans for the principal and subcontractor machines, taking into account the influence of products returned to the production system. The last objective is to determine a joint effective maintenance policy using the optimal production plan, which integrates the various constraints for production rates, transportation delay and the deadline for product return.
This remainder of this chapter is organized as follows:
–
section 1.2
