Cadre de planification intégrée de la chaîne logistique pour la gestion et l'évaluation de stratégies de bioraffinage forestier

Le bioraffinage est maintenant reconnu comme une solution prometteuse pour la transformation de l’industrie forestière. Ce concept offre l’opportunité aux entreprises forestières de diversifier leurs revenus par la production de nouveaux bioproduits à valeur ajoutée. La transition vers le bioraffinage implique toutefois plusieurs changements stratégiques importants, notamment dans le modèle d’affaires des entreprises. En effet, celles-ci devront à la fois se questionner sur la pertinence de rester ou non dans le domaine plus traditionnel des pâtes et papiers, faire la sélection d’un portefeuille de procédés et produits de bioraffinage, pénétrer de nouveaux marchés, et effectuer une gestion de la production permettant de minimiser le risque de volatilité du marché. Au cours des dernières années, les principes de gestion de la chaîne logistique ont été au cœur des recherches du milieu universitaire et de l’industrie afin d’accroître la rentabilité de l’ensemble des opérations. L’application des concepts de gestion de la chaîne logistique pourrait donc grandement aider les entreprises forestières à être plus compétitives globalement. Dans cette optique, l’objectif principal de cette thèse était de concevoir une approche systématique pour la gestion et l’évaluation de stratégies de bioraffinage intégrées à une usine forestière. À cet effet, une approche de gestion de la chaîne logistique dite axée sur les marges de profit a été développée. Celle-ci intègre des concepts inspirés de la gestion des recettes, de la flexibilité manufacturière et de la comptabilité par activité. Les concepts sont incorporés dans un modèle de planification tactique dont l’objectif est de maximiser la rentabilité de l’entreprise. La structure du modèle mathématique et du modèle de coût associé permettent de représenter le plus fidèlement possible les activités de l’entreprise, de l’approvisionnement, jusqu’aux ventes. Il est ainsi possible de modéliser les différentes configurations de procédés présentes dans une usine et menant à la flexibilité manufacturière. Le modèle peut alors être utilisé comme plateforme pour évaluer différentes stratégies d’opération de l’entreprise, aux niveaux de la production et de la chaîne logistique. L’approche axée sur les marges de profit a été illustrée par l’étude du cas d’une usine de production de papier journal envisageant l’implantation d’un procédé de fractionnement de la biomasse pour fabriquer différents bioproduits. Diverses analyses tactiques et stratégiques ont été effectuées pour montrer la pertinence de l’approche comme outil d’aide à la prise de décision pour des problèmes de gestion propres au bioraffinage forestier. Le modèle a été utilisé pour évaluer la rentabilité d’une entreprise lors de sa transformation vers le bioraffinage, en considérant simultanément l’investissement dans de nouveaux procédés de bioraffinage et la fermeture d’actifs papetiers. En offrant une meilleure visualisation et une meilleure compréhension de la dynamique des coûts et de la chaîne logistique sous divers scénarios, l’outil permet d’éclairer le processus de prise de décision. Couplé à une analyse de scénarios, il offre aussi la possibilité de développer une stratégie d’implantation par phase qui stabiliserait les revenus lors de la transformation vers le bioraffinage. L’outil de planification a aussi été employé pour étudier la gestion de la production du portefeuille de produits permettant d’atténuer les risques causés par la volatilité du marché. Une des analyses reliées à la gestion du portefeuille porte sur l’exploitation de la flexibilité au niveau de la production de pâtes thermomécanique et désencrée afin de minimiser le coût d’approvisionnement en matières premières selon les conditions du marché. Une autre analyse étudie l’impact de la flexibilité de l’approvisionnement et de la production d’un procédé de fractionnement de la biomasse sur les ventes et la rentabilité. Les résultats de l’étude montrent que les processus d’approvisionnement et de production doivent être considérablement modifiés selon les conditions de marché pour produire un portefeuille de produits avec des marges optimales. La dynamique des coûts de production et le nombre d’interrelations présentes dans une bioraffinerie forestière complexifient l’identification des meilleures conditions d’opération. Ils corroborent ainsi la pertinence d’utiliser un tel modèle de planification pour identifier les meilleures opportunités. De plus, les résultats montrent que, dans un contexte où les ventes peuvent être variées jusqu’à un certain niveau, il peut être souhaitable de payer davantage pour certains types de biomasse si ces derniers offrent un portefeuille de produits avec de meilleurs revenus. ---------- Biorefining is now recognized as a promising solution to transform the struggling forestry industry and to generate value-added pathways. The implementation of new products and processes will help companies to diversify revenues, but implies several strategic changes in the business model. Companies will face the dilemma of exiting or not traditional pulp and paper operations, while selecting their biorefinery product and process portfolio. As well, they will have to enter new markets and manage production to minimize the risk of market volatility. Over the past decades, both industry and academia paid a lot of attention to supply-chain management in order to increase the cost effectiveness of overall operations. The application of supply-chain management concepts could therefore greatly help the transforming North American forestry industry to compete globally. The objective of this Ph.D. project was to propose and illustrate an integrated supply-chain planning framework for the management and the evaluation of forest biorefinery strategies. This framework, named margins-based, integrates principles from revenue management, activity-based cost accounting, and manufacturing flexibility in a tactical planning model that maximizes profit of a company. The structure of the mathematical model and its associated cost model aims to represent as closely as possible the activities of a company, from procurement to sales. It enables the modeling of different process configurations leading to manufacturing flexibility. The model can thus be used as a platform for evaluating various operating strategies of a company, at both production and supply-chain levels. A case study of a newsprint mill implementing a parallel biomass fractionation line producing several bioproducts was used to illustrate this margins-based approach. Various strategic and tactical analyses were conducted to show the relevance of the approach as a decision-making tool for management problems related to the forest biorefinery. The model was used to evaluate the profitability of a company during its transformation to the biorefinery, by considering the gradual divestment in pulp and paper activities, while implementing a new biorefinery process. Results show that the tool can enhance decision-making activities by providing a better visualization and better comprehension of supply-chain and cost- related dynamics under different scenarios. Coupled with a scenario analysis, it offers the opportunity to develop a phased implementation strategy that would stabilize profitability during the transformation to the biorefinery. The planning tool was also used to study the management of a product portfolio to mitigate the risk of market volatility. One analysis focused on the exploitation of thermomechanical and deinked pulping flexibility in order to minimize the cost of raw material procurement in different to market conditions. Another analysis examined the impact of feedstock and production flexibility of a fractionation process on sales and profitability. Results show that the procurement and production needed to manufacture the product mix that provides the optimum margins vary significantly. Biorefinery processes can have complex interrelations that make dynamics and trade-offs between manufacturing options not easy to identify and understand. Results thus highlight the relevance of using such planning tools to identify the best opportunities. In a context where sales can be varied to a certain level, results also show that it may be beneficial to pay more for certain types of biomass if they offer a product portfolio mix with higher revenues

Feeding Ourselves Thirsty: How the Food Sector is Managing Global Water Risks

The global food sector faces extraordinary risks from the twin challenges of water scarcity and water pollution. Growing competition for water, combined with weak regulations, failing infrastructure, pollution and climate change impacts threaten the sector's water security and contribute to a water availability emergency that was recently ranked the world's "top global risk" by the World Economic Forum.This report examines how water risks affect the profitability and competitive positioning of 37 major food sector companies in four industries: packaged food, beverage, meat and agricultural products. It evaluates and ranks these companies -- the majority of which are U.S. domiciled and publicly-traded -- on how well they are positioned to anticipate and mitigate these risks, as well as contribute to improved water resource management.The report provides recommendations for how analysts and investors can effectively evaluate food sector companies on their water risk exposure and management practices. It also provides recommendations for how food companies can improve water efficiency and water quality across their operations and supply chains to reduce risks and protect water resources

Models for Flexible Supply Chain Network Design

Arguably Supply Chain Management (SCM) is one of the central problems in Operations Research and Management Science (OR/MS). Supply Chain Network Design (SCND) is one of the most crucial strategic problems in the context of SCM. SCND involves decisions on the number, location, and capacity, of production/distribution facilities of a manufacturing company and/or its suppliers operating in an uncertain environment. Specifically, in the automotive industry, manufacturing companies constantly need to examine and improve their supply chain strategies due to uncertainty in the parameters that impact the design of supply chains. The rise of the Asian markets, introduction of new technologies (hybrid and electric cars), fluctuations in exchange rates, and volatile fuel costs are a few examples of these uncertainties. Therefore, our goal in this dissertation is to investigate the need for accurate quantitative decision support methods for decision makers and to show different applications of OR/MS models in the SCND realm. In the first technical chapter of the dissertation, we proposed a framework that enables the decision makers to systematically incorporate uncertainty in their designs, plan for many plausible future scenarios, and assess the quality of service and robustness of their decisions. Further, we discuss the details of the implementation of our framework for a case study in the automotive industry. Our analysis related to the uncertainty quantification, and network's design performance illustrates the benefits of using our framework in different settings of uncertainty. Although this chapter is focused on our case study in the automotive industry, it can be generalized to the SCND problem in any industry. We have outline the shortcomings of the current literature in incorporating the correlation among design parameters of the supply chains in the second technical chapter. In this chapter, we relax the traditional assumption of knowing the distribution of the uncertain parameters. We develop a methodology based on Distributionally Robust Optimization (DRO) with marginal uncertainty sets to incorporate the correlation among uncertain parameters into the designing process. Further, we propose a delayed generation constraint algorithm to solve the NP-hard correlated model in significantly less time than that required by commercial solvers. Further, we show that the price of ignoring this correlation in the parameters increases when we have less information about the uncertain parameters and that the correlated model gives higher profit when exchange rates are high compared to the stochastic model (with the independence assumption). We extended our models in previous chapters by presenting capacity options as a mechanism to hedge against uncertainty in the input parameters. The concept of capacity options similar to financial options constitute the right, but not the obligation, to buy more commodities from suppliers with a predetermined price, if necessary. In capital-intensive industries like the automotive industry, the lost capital investment for excess capacity and the opportunity costs of underutilized capacity have been important drivers for improving flexibility in supply contracts. Our proposed mechanism for high tooling cost parts decreases the total costs of the SCND and creates flexibility within the structure of the designed SCNs. Moreover, we draw several insights from our numerical analyses and discuss the possibility of price negotiations between suppliers and manufacturers over the hedging fixed costs and variable costs. Overall, the findings from this dissertation contribute to improve the flexibility, reliability, and robustness of the SCNs for a wide-ranging set of industries.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145819/1/nsalehi_1.pd

Analysis of the Dynamical Behavior of Firms in a Three Layered Modular Assembly Model

This paper formulate an option model considers supplier's reaction as the profit sharing in module production, and analyses it by the agent theory. A dynamic environment in the model of the system of the production of modules of three layers is assumed, and the maker and the supplier are modeled by the technique of Genetic Programming (GP) as an agent who takes the action of selfoptimization. As result, the condition that the agent can exist continuously in the market is requested. In conclusion, violent competition and the selection of the similar agent are found even in the model of the option to consider the profit sharing and the reaction

An optimization model for a monopolistic firm serving an environmentally conscious market: Use of Chemical Reaction Optimization Algorithm

This work considers a monopolist firm which faces the following twin challenges of serving an environmentally sensitive market. The first challenge is the demand׳s elasticity to emissions and price. To entice its emission conscious customers and generate higher demand, the firm incrementally invests in cleaner production technologies. It also adopts a voluntary limit on its emissions from transportation. However, such investments and penalty lead to the second challenge of reduced net profit. To address above trade-off, a Non-Linear Programming (NLP) model with a maximization quadratic profit function has been formulated. Recently developed, Chemical Reaction Optimization algorithm, with superior computational performance, has been adopted to solve the NLP. The output of the model provides near optimal monopolistic price, best attainable reduction in manufacturing emissions through proportional investment and makes a choice of suitable mode of transportation for each type of product offered by the firm. Three types of sensitivity analyses were performed by varying contextual parameters: customers׳ emission elasticity, penalty charged per unit emission and investment coefficient. The results, underpin the importance of investments in cleaner technologies and the need of financial aids for profit maximizing firms operating in cleaner markets. This work provides a decision making tool to determine the near optimal degree of each of the above dimension in multiple business fronts

Sustainable Supply Chain Management of Cocoa Beans in Indonesia: A Review

This review describes the sustainable supply chain management of cocoa beans in Indonesia. Cocoa beans are produced in some areas in Indonesia such as Central Sulawesi Province, Southeast Sulawesi, South Sulawesi, West Sulawesi, Lampung and other provinces. Indonesian cocoa beans performing special characteristic that is having higher melting point therefore it does not easily melt in higher temperature. So, Indonesian cocoa are commonly used for blending materials. In order to support the strength value of Indonesian cocoa beans, the sustainable supply chain management should also be considered. The sustainable supply chain management of cocoa beans will support the management system prioritizing balance and sustainability so that the business system is maintained. In addition, this will support increased effectiveness, efficiency and competitiveness of Indonesian cocoa beans globally

ALIGNMENT OF BUSINESS STRATEGY AND SUPPLY CHAIN MANAGEMENT: a study of medium-to-large-sized internationalized German companies from an international business student perspective

In an increasingly globalized world, effective supply chain management and its alignment with a company’s business strategy is seen as a firm’s competitive advantage. Existing studies, which were conducted in internationally known companies, suggest three main strategies: Lean, agile and leagile supply chain strategies. Lean supply chain strategies in markets with a stable demand follow a cost-minimizing approach. Agile supply chain strategies in markets with an unpredictable demand focus on differentiation, innovation and flexibility in order to fulfill customer-specific demand. Finally, leagile supply chain strategies try to combine lean aspects for a base demand and agile aspects for more customer specification. This study researches internationalized medium-to-large-sized German companies with the purpose of understanding how companies can improve their supply chain management from an international business perspective. Results are based on the analysis of qualitative data collected through 14 semi-structured interviews with employees from the SC or business department. Findings suggest that lean, agile and leagile supply chains exist as described in the literature. Furthermore, the supply chain strategies called ‘project’ SC and ‘capable’ SC were found. Project SCs are used for a fixed period of time in order to conduct customer-specific ventures. They are a specialized version of agile SCs with the difference that they are constructed from scratch. Capable SCs are characterized by delivery reliability and speed and customer closeness in markets with predictable demand. They can be considered an advancement of leagile SCs. Furthermore risk- hedging SC management was researched. Moreover, the changes in strategies over the years were examined and the meaning of increased automation and usage of computerized systems in the context of industry 4.0 were questioned. The results show that changes and technology play different roles according to industry. In conclusion the findings cannot be generalized due to the small sample size. However, the results give an insight into current supply chain management strategies that can lead to the practical implication of integrating the customer more in the SC. In the future SCs could have increased transparency, flexibility, and simultaneity. Further quantitative research is recommended.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Real-time optimization of an integrated production-inventory-distribution problem.

In today\u27s competitive business environment, companies face enormous pressure and must continuously search for ways to design new products, manufacture and distribute them in an efficient and effective fashion. After years of focusing on reduction in production and operation costs, companies are beginning to look into distribution activities as the last frontier for cost reduction. In addition, an increasing number of companies, large and small, are focusing their efforts on their core competencies which are critical to survive. This results in a widespread practice in industry that companies outsource one or more than one logistics functions to third party logistics providers. By using such logistics expertise, they can obtain a competitive advantage both in cost and time efficiency, because the third party logistics companies already have the equipment, system and experience and are ready to help to their best efforts. In this dissertation, we developed an integrated optimization model of production, inventory and distribution with the goal to coordinate important and interrelated decisions related to production schedules, inventory policy and truckload allocation. Because outsourcing logistics functions to third party logistics providers is becoming critical for a company to remain competitive in the market place; we also included an important decision of selecting carriers with finite truckload and drivers for both inbound and outbound shipments in the model. The integrated model is solved by modified Benders decomposition which solves the master problem by a genetic algorithm. Computational results on test problems of various sizes are provided to show the effectiveness of the proposed solution methodology. We also apply this proposed algorithm on a real distribution problem faced by a large national manufacturer and distributor. It shows that such a complex distribution network with 22 plants, 7 distribution centers, 8 customer zones, 9 products, 16 inbound and 16 outbound shipment carriers in a 12-month planning period can be redesigned within 33 hours. In recent years, multi-agent simulation has been a preferred approach to solve logistics and distribution problems, since these problems are autonomous, distributive, complex, heterogeneous and decentralized in nature and they require extensive intelligent decision making. Another important part in this dissertation involved a development of an agent-based simulation model to cooperate with the optimal solution given by the optimization model. More specifically, the solution given by the optimization model can be inputted as the initial condition of the agent-based simulation model. The agent-based simulation model can incorporate many other factors to be considered in the real world, but optimization cannot handle these as needed. The agent-based simulation model can also incorporate some dynamics we may encounter in the real operations, and it can react to these dynamics in real time. Various types of entities in the entire distribution system can be modeled as intelligent agents, such as suppliers, carriers and customers. In order to build the simulation model more realistic, a sealed bid multiunit auction with an introduction of three parameters a, ß and y is well designed. With the help of these three parameters, each agent makes a better decision in a simple and fast manner, which is the key to realizing real-time decision making. After building such a multi-agent system with agent-based simulation approach, it supports more flexible and comprehensive modeling capabilities which are difficult to realize in a general optimization model. The simulation model is tested and validated on an industrial-sized problem. Numerical results of the agent-based simulation model suggest that with appropriate setting of three parameters the model can precisely represent the preference and interest of different decision makers

Traceability system for capturing, processing and providing consumer-relevant information about wood products: System solution and its economic feasibility

Current research and practice reports indicate the existence of purchase barriers concerning eco-friendly products, e.g. wood products. These can be ascribed to consumers' mistrust regarding the non-observable environmental impact of wood products. To counter the mistrust, wood products are commonly endowed with eco-labels, which may be perceived mostly as a marketing tool, therefore not fulfilling their intended purpose. Current studies have shown that providing consumers with wood product information based on traceability systems increases product trust and purchase intentions, with those information items most valued by consumers being identified as well. Based on this, the paper proposes a traceability information system for the capturing, processing, and provision of product information using examples of wood furniture. Furthermore, a cost-benefit model for the proposed solution is developed. The calculations indicate the possibility of implementing traceability at the item level based on a four-layer system architecture enabling the capture and delivery of all information valued by consumers at acceptable costs. The proposed system helps to overcome purchase barriers of eco-friendly products, increasing consumers' product trust and purchase intentions

Exploring Cloud Adoption Possibilities for the Manufacturing Sector: A Role of Third-Party Service Providers

As the manufacturing sector strides towards digitalization under the influence of Industry 4.0, cloud services have emerged as the new norm, driving change and innovation in this rapidly transforming landscape. This study investigates the possibilities of cloud adoption in the manufacturing sector by developing a conceptual model to identify suitable cloud-based solutions and explores the role of third-party service providers in aiding manufacturers throughout their cloud adoption journey. The research methods consist of a comprehensive literature review of the manufacturing industry, digital transformation, cloud computing, etc., followed by qualitative analyses of industrial benchmarks case studies and an investigation into an application of the developed model to a hypothetical food manufacturing company as an example. This study indicates that cloud adoption can yield substantial benefits in the manufacturing sector, including operational efficiency, cost reduction, and innovation, etc. The study concludes that the developed conceptual model provides a practical framework to identify the most suitable cloud-based solutions during the cloud adoption process in the manufacturing context. In addition, third-party service providers like Capgemini are capable of not only filling the technical gaps but also consulting strategic directions and innovations for their client organizations, hence playing a vital role in driving the industrial digital transformation process. With an extensive mapping of their capabilities, a set of recommendations intended to assist Capgemini in enhancing capabilities and improving competitive performance in the market has been offered