Service supply chain management : a hierarchical decision modeling approach

A Service Supply Chain (SSC) may be described as a network of service provider facilities (in-house or outsourced), each of which is able to process one or more service tasks on an as needed basis. Two key characteristics of a SSC are (i) the business service is decomposable into several sequential tasks that can be processed by different service providers, and (ii) the primary capacity resource is skilled labor. SSCs are increasingly being developed by companies that experience a high variability of demand for their services (e.g., loan processing, analytical consulting services, emergency repair crews, claims processing, etc.). Typically, the customer wait time penalty is very high, to the extent that if the service is not provided within a certain time, the customer service request will abort. As a result, the service provider needs to maintain sufficient processing capacity to meet peak levels of demand. The primary advantage of a SSC, relative to a traditional dedicated facility, is that the processing capacity (labor) can be economically adjusted (lower hiring and firing costs) to match changes in the current demand level. In this dissertation, a hierarchical framework for modeling the decision structure in SSCs is developed. This framework introduces and defines the key SSC entities: service products, service jobs, service providers, and the parameters for characterizing the demand behavior. As part of the framework two problems are formulated and solved. First, given that Service Supply Chains are intended to be dynamic delivery networks that efficiently respond to demand variations, a strategic problem is which candidate service providers are selected to form the SSC network, and how the service tasks are assigned within the provider network. The problem is formulated and solved as a binary program. Second, a consequent tactical problem is how the workforce level at each service provider is dynamically adjusted (hiring and firing) as the real time demand data comes in the problem is formulated and solved as a linear program that bounds a mixed integer program (MIP). The strategic model takes the demand parameters, the competing providers’ information, and the service and tasks parameters, to select the providers that are going to become part of the SSC and assign tasks to them. A method to quantify cumulative demand variation per seasonal cycle is presented to derive aggregate demand parameters from the forecast. The design objective of the strategic model is to minimize set up cost and projected operational cost. The objective is achieved by simultaneously minimizing capital cost, hiring cost, firing cost, service delay cost, excess capacity cost, labor cost, and quality cost while fulfilling the capacity, tasks assignment, facility installation, and task capability constraints. The tactical model is constrained by the providers and task assignment resulting from the strategic model. It uses a more accurate demand forecast, and minimizes actual operational costs represented by hiring cost, firing cost, backlog cost and labor cost, while fulfilling the production balance, routing, capacity, workforce balance and demand constraints. It is solved in two phases. A relaxed model is solved as an LP and its solution is used for bounding a MIP problem. Finally, the behavior of the two models is studied by performing numerical experiments changing key supply chain parameters such as hiring and firing cost, demand variability, labor cost, and backlog cost

A Representation of Tactical and Strategic Precursors of Supply Network Resilience Using Simulation Based Experiments

Modern supply chains are becoming increasingly complex and are exposed to higher levels of risk. Globalization, market uncertainty, mass customization, technological and innovation forces, among other factors, make supply networks more susceptible to disruptions (both those that are man-made and/or ones associated with natural events) that leave suppliers unavailable, shut-down facilities and entail lost capacity. Whereas several models for disruption management exist, there is a need for operational representations of concepts such as resilience that expand the practitioners’ understanding of the behavior of their supply chains. These representations must include not only specific characteristics of the firm’s supply network but also its tactical and strategic decisions (such as sourcing and product design). Furthermore, the representations should capture the impact those characteristics have on the performance of the network facing disruptions, thus providing operations managers with insights on what tactical and strategic decisions are most suitable for their specific supply networks (and product types) in the event of a disruption. This research uses Agent-Based Modeling and Simulation (ABMS) and an experimental set-up to develop a representation of the relationships between tactical and strategic decisions and their impact on the performance of multi-echelon networks under supply uncertainty. Two main questions are answered: 1) How do different tactical and strategic decisions give rise to resilience in a multi-echelon system?, and 2) What is the nature of the interactions between those factors, the network’s structure and its performance in the event of a disruption? Product design was found to have the most significant impact on the reliability (Perfect Order Fulfillment) for products with high degrees of componentization when dual sourcing is the chosen strategy. However, when it comes to network responsiveness (Order Fulfillment Cycle Time), this effect was attenuated. Generally, it was found that the expected individual impact these factors have on the network performance is affected by the interactions between them

Exploring wood procurement system agility to improve the forest products industry’s competitiveness

Les difficultés vécus par l'industrie canadienne des produits forestiers dans la dernière décennie l’ont amené vers une transformation importante. L'innovation dans les produits et les processus est encore nécessaire afin de maximiser la valeur économique des ressources forestières. Cette thèse se concentre sur le les systèmes d'approvisionnement en bois de l’industrie forestière qui est responsable de la récolte et de la livraison des matières premières de la forêt vers les usines. Les entreprises les plus compétitives sont celles qui peuvent fournir les bons produits aux bons clients au bon moment. L'agilité du système d'approvisionnement en bois devient ainsi une des caractéristiques nécessaires à la compétitivité. Les objectifs de la thèse sont d'identifier les possibilités d'améliorer l'agilité du système d'approvisionnement en bois, de quantifier les gains potentiels et de proposer un mécanisme dans le but d’anticiper son impact à long terme. L’agilité est la capacité des systèmes d'approvisionnement en bois à répondre rapidement et efficacement à des fluctuations inattendues de la demande. Premièrement, nous identifions les capacités requises par le système d'approvisionnement en bois qui permettent l'agilité; ensuite, nous examinons la littérature portant sur les systèmes d'approvisionnement en bois pour trouver des signes de ces capacités. Suite à cette étape, une opportunité d'améliorer l'agilité des systèmes d'approvisionnement a été identifiée. Celle-ci implique une plus grande flexibilité dans le choix des traitements sylvicoles au niveau opérationnel afin de mieux aligner l'offre avec la demande. Une expérimentation a été menée en utilisant des données industrielles pour quantifier les avantages potentiels associés à l'approche. Dans les scénarios avec flexibilité permise, des profits significativement plus élevés et des taux plus élevés de satisfaction de la demande ont été observés. Ensuite, un système de simulation-optimisation de la planification hiérarchique a été développé pour étudier l'influence de la flexibilité au niveau opérationnel sur l'approvisionnement en bois à long terme. Le système a été mis en œuvre en utilisant les données hypothétiques d'une forêt du domaine public québécois pour un horizon de 100 ans. Le système développé a permis de mesurer les impacts à courts et à long terme des décisions d'approvisionnement. Il devrait permettre de mieux intégrer les pratiques d’aménagements forestiers avec les besoins de la chaîne d’approvisionnement.The significant downfall experienced by the Canadian forest products industry in the past decade has catalyzed the industry into a process of transformation. A concerted effort to maximize economic value from forest resources through innovation in both products and processes is currently underway. This thesis focuses on process innovation of wood procurement systems (WPS). WPS includes upstream processes and actors in the forest products supply chain, responsible for procuring and delivering raw materials from forests to manufacturing mills. The competitiveness of the industry depends on the agility of WPS to deliver the right product to the right customer at the right time. The specific aims of the thesis are to identify opportunities to improve wood procurement system agility, quantify the potential improvement in performance and propose a mechanism to anticipate its long-term impact. Agility is the ability to respond promptly and effectively to unexpected short-term fluctuation in demand. We first identify the capabilities a WPS needs to possess in order to enable agility; we then review the literature in the WPS domain to search for evidence of these capabilities. An opportunity to improve agility of WPS was then identified. It entailed providing managers with flexibility in the choice of silvicultural treatments at the operational level to permit better alignment of supply with the prevailing demand. An experiment was conducted using industry data to quantify the potential benefits associated with the approach. In scenarios where flexibility was permitted, significantly higher profits and demand fulfillment rates were observed. Next, a simulation-optimization system for hierarchical forest management planning was developed to examine the influence of operational level silvicultural flexibility on long-term wood supply. The system was implemented to a forest management unit in Québec in a rolling planning horizon basis for a 100 year horizon. The system demonstrated a capability to measure short and long-term impacts of supply decisions. It will prove to be a useful tool to better integrate forest management practices and supply chain needs

Strategic Planning and Design of Supply Chains: a Literature Review

In this paper, a literature review of the mathematical models for supply chain design is proposed. The research is based on the study and analysis of publications of the last twelve years from the most widespread international journal about operations management and logistics. The aim of the work lies in identifying tendencies in the literature and related open issues about the strategic decisions, economic parameters, constraints and model features considered in the strategic planning and design of supply chains. After a description of the review methodology, comparison parameters and paper exhaustiveness, some guidelines are given in order to support future works in this field

Integrated Forest Biorefinery Network Design Under Uncertainty

The Canadian Pulp and Pulp (P&P) industry has been recently confronted by shrinking markets and tighter profit margins. Transforming P&P mills into Integrated Forest Biorefineries (IFBR) is a prominent solution to save the struggling industry and allow diversification towards the promising bioproducts markets. The implementation of such a strategy is a complex process that faces many sources of uncertainty. Therefore, the industry is in need for a planning tool that facilitates the IFBR network design by taking the uncertain market conditions into consideration. First, we propose a mixed integer programming model to optimize the investment plan in addition to other tactical decisions over a long term planning horizon. We test the model using a realistic case study for Canadian P&P companies, where we perform a set of sensitivity analysis tests in terms of bioproduct demand and energy prices. Our results showcase the potential of the IFBR to help the P&P industry and highlight the substantial impact of the bioproduct demand on its profitability. Second, we develop a Multi-stage Stochastic Programming model which explicitly incorporates the demand uncertainty. We also develop a simulation platform to validate the model and compare its performance with alternative decision models. We assess the value of incorporating demand uncertainty in the planning process and we also elaborate on the value of flexibility in terms of adjusting the investment plan in response to changes in market trends. Our results demonstrate the significant value of explicitly incorporating the uncertainty in IFBR network design as well as flexibility in the investment plan

Hybrid Simulation-based Planning Framework for Agri-Fresh Produce Supply Chain

The ever-increasing demand for fresh and healthy products raises the economic importance of managing Agri-Fresh Produce Supply Chain (AFPSC) effectively. However, the literature review has indicated that many challenges undermine efficient planning for AFPSCs. Stringent regulations on production and logistics activities, production seasonality and high yield variations (quantity and quality), and products vulnerability to multiple natural stresses, alongside with their critical shelf life, impact the planning process. This calls for developing smart planning and decision-support tools which provides higher efficiency for such challenges. Modelling and simulation (M&S) approaches for AFPSC planning problems have a proven record in offering safe and economical solutions. Increase in problem complexity has urged the use of hybrid solutions that integrate different approaches to provide better understanding of the system dynamism in an environment characterised by multi-firm and multi-dimensional relationships. The proposed hybrid simulation-based planning framework for AFPSCs has addressed internal decision-making mechanisms, rules and control procedures to support strategic, tactical and operational planning decisions. An exploratory study has been conducted using semi-structured interviews with twelve managers from different agri-fresh produce organisations. The aim of this study is to understand management practices regarding planning and to gain insights on current challenges. Discussions with managers on planning issues such as resources constraints, outsourcing, capacity, product sensitivity, quality, and lead times have formed the foundation of process mapping. As a result, conceptual modelling process is then used to model supply chain planning activities. These conceptual models are inclusive and reflective to system complexity and decision sensitivity. Verification of logic and accuracy of the conceptual models has been done by few directors in AFPSC before developing a hybrid simulation model. Hybridisation of Discrete Event Simulation (DES), System Dynamics (SD), and Agent-Based Modelling (ABM) has offered flexibility and precision in modelling this complex supply chain. DES provides operational models that include different entities of AFPSC, and SD minds investments decisions according to supply and demand implications, while ABM is concerned with modelling variations of human behaviour and experience. The proposed framework has been validated using Table Grapes Supply Chain (TGSC) case study. Decision makers have appreciated the level of details included in the solution at different planning levels (i.e., operational, tactical and strategic). Results show that around 58% of wasted products can be saved if correct hiring policy is adopted in the management of seasonal labourer recruitment. This would also factor in more than 25% improved profits at packing house entity. Moreover, an anticipation of different supply and demand scenarios demonstrated that inefficiency of internal business processes might undermine the whole business from gaining benefits of market growth opportunities

Network design and technology management for waste to energy production:An integrated optimization framework under the principles of circular economy

The design of waste to bioenergy supply chains (W-BESC) is critically important for meeting the circular economy (CE) goals, whilst also ensuring environmental sustainability in the planning and operation of energy systems. This study develops a novel optimization methodology to aid sustainable design and planning of W-BESC that comprise multiple technologies as well as multiple product and feedstock types. The methodology identifies the optimum supply chain configuration and plans the logistics operations in a given region to meet the energy demand of specified nodes. A scenario based fuzzy multi objective modelling approach is proposed and utilized to capture the economic and environmental sustainability aspects in the same framework. We test the proposed model using the entire West Midlands (WM) region from the United Kingdom (UK) as a case study. In this scope, a comprehensive regional supply chain is designed to meet the energy and biofertilizer demand of specific nodes considering available waste and crop type biomass in the region. Further analysis is conducted to reveal the impacts of main economic and technological parameters on the supply chain performance indicators