Production planning mechanisms in demand-driven wood remanufacturing industry

L'objectif principal de cette thèse est d'étudier le problème de planification de la production dans le contexte d'une demande incertaine, d’un niveau de service variable et d’approvisionnements incontrôlables dans une usine de seconde transformation du bois. Les activités de planification et de contrôle de production sont des tâches intrinsèquement complexes et difficiles pour les entreprises de seconde transformation du bois. La complexité vient de certaines caractéristiques intrinsèques de cette industrie, comme la co-production, les procédés alternatifs divergents, les systèmes de production sur commande (make-to-order), des temps de setup variables et une offre incontrôlable. La première partie de cette thèse propose une plate-forme d'optimisation/simulation permettant de prendre des décisions concernant le choix d'une politique de planification de la production, pour traiter rapidement les demandes incertaines, tout en tenant compte des caractéristiques complexes de l'industrie de la seconde transformation du bois. À cet effet, une stratégie de re-planification périodique basée sur un horizon roulant est utilisée et validée par un modèle de simulation utilisant des données réelles provenant d'un partenaire industriel. Dans la deuxième partie de cette thèse, une méthode de gestion des stocks de sécurité dynamique est proposée afin de mieux gérer le niveau de service, qui est contraint par une capacité de production limitée et à la complexité de la gestion des temps de mise en course. Nous avons ainsi développé une approche de re-planification périodique à deux phases, dans laquelle des capacités non-utilisées (dans la première phase) sont attribuées (dans la seconde phase) afin de produire certains produits jugés importants, augmentant ainsi la capacité du système à atteindre le niveau de stock de sécurité. Enfin, dans la troisième partie de la thèse, nous étudions l’impact d’un approvisionnement incontrôlable sur la planification de la production. Différents scénarios d'approvisionnement servent à identifier les seuils critiques dans les variations de l’offre. Le cadre proposé permet aux gestionnaires de comprendre l'impact de politiques d'approvisionnement proposées pour faire face aux incertitudes. Les résultats obtenus à travers les études de cas considérés montrent que les nouvelles approches proposées dans cette thèse constituent des outils pratiques et efficaces pour la planification de production du bois.The main objective of this thesis is to investigate the production planning problem in the context of uncertain demand, variable service level, and uncontrollable supply in a wood remanufacturing mill. Production planning and control activities are complex and represent difficult tasks for wood remanufacturers. The complexity comes from inherent characteristics of the industry such as divergent co-production, alternative processes, make-to-order, short customer lead times, variable setup time, and uncontrollable supply. The first part of this thesis proposes an optimization/simulation platform to make decisions about the selection of a production planning policy to deal swiftly with uncertain demands, under the complex characteristics of the wood remanufacturing industry. For this purpose, a periodic re-planning strategy based on a rolling horizon was used and validated through a simulation model using real data from an industrial partner. The computational results highlighted the significance of using the re-planning model as a practical tool for production planning under unstable demands. In the second part, a dynamic safety stock method was proposed to better manage service level, which was threatened by issues related to limited production capacity and the complexity of setup time. We developed a two-phase periodic re-planning approach whereby idle capacities were allocated to produce more important products thus increasing the realization of safety stock level. Numerical results indicated that the solution of the two-phase method was superior to the initial method in terms of backorder level as well as inventory level. Finally, we studied the impact of uncontrollable supply on demand-driven wood remanufacturing production planning through an optimization and simulation framework. Different supply scenarios were used to identify the safety threshold of supply changes. The proposed framework provided managers with a novel advanced planning approach that allowed understanding the impact of supply policies to deal with uncertainties. In general, the wood products industry offers a rich environment for dealing with uncertainties for which the literature fails to provide efficient solutions. Regarding the results that were obtained through the case studies, we believe that approaches proposed in this thesis can be considered as novel and practical tools for wood remanufacturing production planning

Resolving forward-reverse logistics multi-period model using evolutionary algorithms

© 2016 Elsevier Ltd In the changing competitive landscape and with growing environmental awareness, reverse logistics issues have become prominent in manufacturing organizations. As a result there is an increasing focus on green aspects of the supply chain to reduce environmental impacts and ensure environmental efficiency. This is largely driven by changes made in government rules and regulations with which organizations must comply in order to successfully operate in different regions of the world. Therefore, manufacturing organizations are striving hard to implement environmentally efficient supply chains while simultaneously maximizing their profit to compete in the market. To address the issue, this research studies a forward-reverse logistics model. This paper puts forward a model of a multi-period, multi-echelon, vehicle routing, forward-reverse logistics system. The network considered in the model assumes a fixed number of suppliers, facilities, distributors, customer zones, disassembly locations, re-distributors and second customer zones. The demand levels at customer zones are assumed to be deterministic. The objective of the paper is to maximize the total expected profit and also to obtain an efficient route for the vehicle corresponding to an optimal/near optimal solution. The proposed model is resolved using Artificial Immune System (AIS) and Particle Swarm Optimization (PSO) algorithms. The findings show that for the considered model, AIS works better than the PSO. This information is important for a manufacturing organization engaged in reverse logistics programs and in running units efficiently. This paper also contributes to the limited literature on reverse logistics that considers costs and profit as well as vehicle route management

Selection of return channels and recovery options for used products

Due to legal, economic and socio-environmental factors, reverse logistics practices and extended producer responsibility have developed into a necessity in many countries. The end results and expectations may differ, but the motivation remains the same. Two significant components in a reverse logistics system -product recovery options and return channels - are the focus of this thesis. The two main issues examined are allocation of the returned products to recovery options, and selection of the collection methods for product returns. The initial segment of this thesis involves the formulation of a linear programming model to determine the optimal allocation of returned products differing in quality to specific recovery options. This model paves the way for a study on the effects of flexibility on product recovery allocation. A computational example utilising experimental data was presented to demonstrate the viability of the proposed model. The results revealed that in comparison to a fixed match between product qualities and recovery options, the product recovery operation appeared to be more profitable with a flexible allocation. The second segment of this thesis addresses the methods employed for the initial collection of returned products. A mixed integer nonlinear programming model was developed to facilitate the selection of optimal collection methods for these products. This integrated model takes three different initial collection methods into consideration. The model is used to solve an illustrative example optimally. However, as the complexity of the issue renders this process ineffective in the face of larger problems, the Lagrangian relaxation method was proposed to generate feasible solutions within reasonable computational times. This method was put to the test and the results were found to be encouraging

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies

An Examination of the Relationship Between Environmental Practices and Firm Performance

Recently, there has been a great deal of interest in the research literature regarding how environmental practices (EPs) can improve firm performance. According to Rondinelli and Vastag (1995), firms may have been reacting to an increasingly difficult regulatory environment or responding to market pressure. Either way, the responses of firms to environmental pressures has led to practices that impact profitability. Currently, more firms are trying to understand the benefits of a proactive approach to environmental policies. Some firms may be motivated to become environmentally proactive since it could lead to more efficient use of resources and improve corporate image. Despite this intuitive argument, many firms are reluctant to take a more aggressive and proactive approach to EPs, due to a dearth of evidence that benefits exceed the costs of pursuing these initiatives. This attitude is attested to by the relatively low number of ISO 14000 certifications that have been issued to U.S. firms (NIST 1998, ISO 2001)

Material Planning for Remanufacturing Defense Assets

This paper develops a planning system for depots remanufacturing components of defense assets, such as helicopters, armored cars, and so forth. These depots take in used assets, disassemble them, repair, upgrade and reassemble them to supply US troops and, occasionally, foreign military services of allied nations. Uncertainty in the supply of used components, the yield of good parts, and the demand for remanufactured products makes this a difficult process to manage. This article describes a multi-period material planning system for the process. It covers everything from collection to final delivery. The system is based on material requirements planning, a method familiar to many managers. It uses linear programming to develop purchase recommendations and to schedule the disassembly of the used components. The researcher held meetings with remanufacturing practitioners to set the system parameters and to evaluate the approach

Design of Closed Loop Supply Chains

Increased concern for the environment has lead to new techniques to design products and supply chains that are both economically and ecologically feasible. This paper deals with the product - and corresponding supply chain design for a refrigerator. Literature study shows that there are many models to support product design and logistics separately, but not in an integrated way. In our research we develop quantitative modelling to support an optimal design structure of a product, i.e. modularity, repairability, recyclability, as well as the optimal locations and goods flows allocation in the logistics system. Environmental impacts are measured by energy and waste. Economic costs are modelled as linear functions of volumes with a fixed set-up component for facilities. We apply this model using real life R&D data of a Japanese consumer electronics company. The model is run for different scenarios using different parameter settings such as centralised versus decentralised logistics, alternative product designs, varying return quality and quantity, and potential environmental legislation based on producer responsibility.supply chain management;reverse logistics;facility location;network design;product design

Optimization modeling for the operation of closed-loop supply chains.

Environmentally conscious manufacturing and remanufacturing/recycling of endof- life products are steadily growing in importance. The problem of managing the waste generated due to the disposal of many types of products has many aspects. The main driving forces for solving this growing problem are the rapid diminishment of raw material resources, decreasing space in landfills and increasing levels of pollution. The drivers associated with these forces are governmental regulations which require that the manufacturers take back the end-of-life products and customer perspectives on environmental issues. This research considers the problem of increasing levels of electronic and electrical equipments waste. The implementation of closed-loop supply chains can be beneficial both economically and ecologically for these problems. Relevant literature to understand various issues involved in the operation of reverse logistics systems and closed-loop supply chains is reviewed. Upon reviewing the issues involved in closed-loop supply chains, the problem is considered as an ill-structured problem. A problem structuring technique called Why-What\u27s Stopping Analysis is used to analyze the problem from various perspectives. Also, since a closed-loop supply chain involves multiple objectives, two techniques for categorizing the objectives into fundamental and means objectives are presented: Fundamental Objective Hierarchy and Means Objective Network techniques, respectively. A Goal Program (GP) modeling approach is used to handle many of the objectives identified by the previously mentioned techniques. In this research a consolidated objective function is defined which includes all of the deviational variables considered in various goals defined in the model. The consolidated goal is to minimize the weighted sum of all deviational variables. A non preemptive goal programming approach has been used with goals being assigned different weights according to their priorities. The values of the deviational variables help the decision maker to see which of the different goals are satisfied with the existing values of parameters and which of the goals aren\u27t. The goal program has been run with both uniform and variable demand values in all the periods. In the absence of real data, all the parameter values considered for this research have been assumed. The major contributions of the research are as follows: each member of the supply chain has its own individual objective and the related constraints which is a more realistic approach, the model considers multiple products, and the model considers operations at the product, subassembly, part, and material levels. All the above contributions make this research as the first approach of its kind which has never been attempted (based on literature reviewed) and the goal programming methodology used is also a well accepted approach among all the multi-objective programming approaches. Results show the effect of varying the priority/weight associated with a goal. Results also show that values of the deviational variables (positive or negative) help a decision maker to analyze the model. The goal programming approach is considered to be the most effective approach in terms of defining the mathematical model, analyzing the output, and modifying the model (if needed)