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Availability management is a major factor in successful supply chain management since it influences key supply chain performance metrics such as customer service level and inventory. The availability management process involves generating availability outlook, scheduling customer orders against the availability outlook, and fulfilling the orders. The process is also associated with many uncertainties such as customer demand, customer preference of product configuration, and changes in supply constraints and various supply chain policies, which also affect the supply chain performance. As e-commerce is becoming a major part of business transactions it is much easier for customers to compare availability and services from many different sellers. Therefore, it is important for sellers to process customer orders in real-time, promise ship dates, fulfill the orders as promised, and to have availability of resources to be able to promise customers desirable ship dates. In today's competitive and dynamic business environment, companies need to continually evaluate the effectiveness of the availability management process and supporting IT system and look for ways to transform the process to achieve better customer service and profitability. To do that, there is a need for an easy-to-use modeling tool that can accurately assess the effectiveness of the existing availability management process, evaluate the impact of potential changes in the process and identify opportunities for improvement. In this chapter, we describe an availability management simulation tool that was developed at IBM to support the continuous effort to improve the availability management process. The simulation model has become a critical tool in making strategic business decisions that impact customer service and profitability at IBM. [ABSTRACT FROM AUTHOR]

In this chapter, we show that reducing supply chain uncertainty increases responsiveness and thereby benefits bottom line performance as assessed via total cycle time reduction. This positive effect we term the uncertainty reduction principle. As the key enabler, we use the uncertainty circle to focus on the sources to be eliminated. We also show that these sources of uncertainty can react and magnify in a flywheel effect caused by poor value stream management. A supply chain audit methodology is described for identifying and codifying uncertainty. Our proposition is that smooth material flow leads to and statistically correlates with uncertainty reduction. Examples are given of good real-world supply chain practices thereby identified. Transferability of the uncertainty reduction principle is assured by establishing readily assimilated "best practice" guidelines via the study of "exemplar" operating characteristics. [ABSTRACT FROM AUTHOR]

As an event-driven system, a supply chain network will face uncertainties inside the supply chain and also unexpected events outside the supply chain network such as contingency, disruption, and disaster. These uncertainties and unexpected events have negative impacts on the survival and performance of supply chain networks. As a dynamic system, a supply chain network will evolve over time. Nodes and links may be added and deleted, or part of networks can be disconnected. The functional performance of nodes and links of supply chain networks may deteriorate quickly under unexpected events. Providing resilient capability against failures is a critical issue for supply chain networks since a single failure may propagate along the chain and cause a series of severe losses in network performance and structure. Robustness of a supply chain network is an important research issue, a vulnerable supply chain network may not be able to operate at all. The goal of this chapter is to investigate the relationship between robustness metrics and basic network parameters. A systemwide approach is presented to quantifying the robustness of supply chain networks. This approach considers both network structural and network functional parameters. Metagraphs are employed to calculate the structural robustness of nodes, and a topological index is used to capture the robustness of the overall network structure. Finally, the integrated systemwide network robustness index can be obtained by the proposed algorithm. Several hypothetical supply chain networks are employed to demonstrate the proposed approach. [ABSTRACT FROM AUTHOR]

We review inventory models that use multiple sourcing (diversification) to deal with upstream (supply) uncertainty. To provide a structured review, we identify three sources of supply uncertainty as follows: supply timing, supply quantity (or quality), and purchase price. Then, we summarize the main results that exist in the literature. Finally, based on our observations, we provide directions for future research. [ABSTRACT FROM AUTHOR]

Despite the importance of transport within the supply chain, it has traditionally been treated as a separate functional silo within businesses. More recently, there has been increased recognition that transport needs to be integrated into the supply chain. This chapter considers the role of vendor managed inventory and demonstrates how it can be used to improve both transport and supply chain performance. With VMI control, inventory across the supplier/customer interface (including transport) is managed holistically. Scenario analysis is carried out via simulation and through a case study from the U.K. grocery sector. Among the benefits identified are control of the bullwhip effect, improved customer service, lower transport costs, and improved vehicle fill. In addition, it is found that VMI is particularly effective during times of pressure within the supply chain. [ABSTRACT FROM AUTHOR]

Supply chains are distributed systems and hence multiagent based systems are considered the best approach to manage supply chains. In multiagent systems for supply chain management, each agent is assigned to model a facility and the interaction protocol to connect the agents is defined. The intelligent agents interact with each other to dynamically access, transfer, and evaluate the information of the supply chain. We introduce a specific multiagent system for dynamic lot-sizing in supply chains. The dynamic lotsizing problem over a planning horizon makes a plan that minimizes cost while satisfying forecasted external demands. The common drawbacks of the majority of dynamic lot-sizing algorithms are that they offer centralized solutions with a monolithic view of the problem. On the other hand, supply chains are struggling with expensive inefficiencies due to the lack of information sharing. Therefore, there is a need to design coordination mechanisms that are capable of motivating information sharing. Supply chain entities will be willing to share information when they are guaranteed to get the right benefits in return for information sharing. Such trustworthy mechanisms may not produce the global optimum of monolithic models, but they would be more reasonable, considering the reality of supply chains. [ABSTRACT FROM AUTHOR]

In this chapter, we introduce two types of supply chains that consist of an independent manufacturer and an independent distributor and decentralized supply chain planning models for them. Those supply chains are based on a decentralized planning environment where the manufacturer and the distributor collaborate with each other without disclosing their private information. Although collaboration with other supply chain participants is indispensable for survival in the supply chain, available information for sharing tends to be limited to preserve independent competitive power. In line with this changing environment, two types of supply chains are defined and investigated with focus on their frameworks. Also, decentralized supply chain planning models for two proposed supply chains are discussed. A brief numerical example is employed to illustrate the potential use of the proposed models. Finally, some issues concerning implementation of the proposed decentralized supply chain planning models are discussed. [ABSTRACT FROM AUTHOR]

The semiconductor industry has a supply chain network that is distributed all over the world, and its manufacturing process has the particular characteristics that should be considered in supply chain modeling. In this chapter, we suggest integrated mathematical models for the semiconductor industry supply chain consisting of production and distribution chains, where manufacturing reentry, binning, and substitution are considered. Four models, push-production, balance-production, target-production, and pullproduction model for the production chain and two models, push-distribution and pull-distribution for the distribution chain are suggested with mathematical formulations. [ABSTRACT FROM AUTHOR]

Managing an integrated supply chain has become a necessary capability for competing in the global market. Cooperating with business partners prevents duplicating efforts and allows a company to focus on its core competencies. Hence, collaborating companies together have the potential to form a strong supply chain. At the individual company level, practitioners of lean concepts have demonstrated dramatic improvements in productivity within their manufacturing facilities. However, the potential benefits of lean implementation are limited to four walls of companies when business partners are excluded from integrating into a leaner overall value stream. The flow from a lean supplier to a lean customer may not be lean if the two parties are not synchronized. As a result, the supply chain formed within lean companies may not be lean after all, due to lack of cooperation and synchronization among participating companies. Extending the value stream from a lean company to its partners allows the company to widen the pursuit for perfection to the whole supply network. Furthermore, applying lean concepts to a supply chain opens new windows of opportunity for supply chain participants to collectively achieve higher levels of competitiveness. Thus, the integration of supply chain management and lean thinking covers both local and overall leanness, which leads to a truly lean supply chain. This chapter provides an overview of the lean supply chain, the including concepts, approaches, challenges, and future development. In the first part of the chapter, basic concepts and impacts of lean thinking will be introduced, followed by the issues of applying lean thinking in supply chain management. Then, an integrated framework of a lean supply chain will be presented. The second part of the chapter covers the building blocks of lean supply chains, including lean logistics, information technology, performance measurement and improvement, and collaboration beyond partnerships. Subsequently, the challenges for building or maintaining a sustainable lean supply chain will be discussed. Finally, discussions of potential developments that can further improve lean supply chains will be summarized in the concluding section. [ABSTRACT FROM AUTHOR]

The aim of this chapter is to present a structured study of the e-government phenomenon by implementing a holistic research approach which starts by identifying and declaring the importance of strategic issues such as vision and mission statements, followed by the determination of the e-government strategic value chain and the presentation of traditional e-business models and their application in the e-government context. Next, a detailed examination of the available information and communication technologies (ICT) frameworks to support the government supply chain, as found in the literature, is executed and an IT framework is proposed followed by a series of discussions related to the most important technology oriented issues that are found in the literature. Finally, based on an extended literature review of e-government projects around the globe, a series of selected case studies categorized by stage of government transformation is presented. [ABSTRACT FROM AUTHOR]

This chapter proposes a modeling methodology for designing reverse logistics networks. The model aims at determining the location and missions of sites for the recovery of unused products from ultimate consumers, valorization or clean disposal of recovered products, redistribution of reusable materials, and attribution of new or reusable (valorized) products. Valorization activities refer to repair, refurbishing, reassembling, product disassembly for reusable material recovery (cannibalization), and recycling. The proportion of recovered product volumes to orient to valorization and clean disposal activities is not known a priori but is determined according to demand and return volumes, site capacities, and the general anticipated state of recovered product volumes. This model may be used to evaluate the impact of reintegrating valorized products (finished products and spare parts) into current supply chains initially designed only for distribution and maintenance of new products. The chapter discusses key parameters such as the localization and estimation of potential returns and demands for new and reusable (valorized) products, as well as the probability that a returned product be in a specific state, which could lead to one or many processing alternatives (repair, disassembly, clean disposal, etc.). This mathematical model is inspired by the recent healthcare allocation and valorization of the wheelchair policy of the Province of Quebec (Canada), governed and managed by a governmental agency. [ABSTRACT FROM AUTHOR]

Businesses are undergoing a major paradigm shift, moving from traditional management into a world of agile organizations and processes. An agile enterprise should be able to respond rapidly to market changes. For this reason, enterprises have been seeking to develop numerous information technology (IT) systems to assist with their business processes. However, by their very nature, information/knowledge in the systems is disparate and heterogeneous and can be represented in various ways (text, pdf, html, etc.) and can be either structured or unstructured. It is, therefore, difficult to acquire, organize, or distribute information/knowledge using only traditional information technology methods such as e-mail or file servers. Because of the autonomous and collaborative aspects inherent in agent-based technology, this may be a possible solution to the problem of heterogeneity. Agent technology radically alters not only the way in which computers interact, but also the way complex processes, e.g., supply chains are conceptualized and built. This chapter proposes an agent-based system and formulates agile interaction for the collaboration of supply chain entities in a heterogeneous environment. The agent-based system enhances supply chain agility through the approach in which the agents autonomously plan and pursue their objectives and subgoals to cooperate, coordinate, and negotiate with others and to respond flexibly and intelligently to dynamic and unpredictable situations. Annotation and articulation mechanisms are developed to address and solve the heterogeneity problem of information/knowledge resources. [ABSTRACT FROM AUTHOR]

Information is said to be the glue that holds supply chains together. As a key infrastructure, Web-based technologies continue to have significant impact on supply chain strategies. On the coordination side, the Web provides a virtually free platform for enhancing transparency, eliminating information delays and distortions, and significantly reducing transaction costs. One should note, however, that, although information flow has accelerated considerably, material flow has not gained much speed. This phenomenon makes the coordination of material, information, and cash flows even more crucial for effective supply chain coordination. On the design side, current technology does not yet permit dynamic supply chain design in response to changing business environment. The adoption of Web Services represents a significant step in that direction. [ABSTRACT FROM AUTHOR]

The goal of mobile supply chain event management (SCEM) is to monitor supply networks by observing specific events, disruptions, and exceptions in real-time, alerting decision-makers if problems have occurred and offering them good solutions. This chapter presents a framework for mobile SCEM based on software agents, auto-ID, sensor, and mobile computing technologies. Such technologies can be used together to proactively anticipate unexpected events, disruptions, and delays in the supply network before they lead to major problems and to provide useful alerts. Local human or artificial decision-handling agents can be proactively notified via mobile devices before delays arise or events fail to take place at all. A special focus is placed on a simulation approach. Herein, simulation is used to support agents by offering them good solutions for handling events. The authors of this chapter will show how to combine the above-mentioned technologies in mobile SCEM with simulation systems and open enterprise resource planning (ERP) systems to realize adaptive supply networks. Potentials and challenges in realizing adaptive supply networks by such technologies are also discussed. [ABSTRACT FROM AUTHOR]

Our thesis is that the evolution of information technology (IT) facilitates the flow of information, which in turn may reduce the variance of an inventory system, and hence its cost. We use radio-frequency identification (RFID) as a paradigm. RFID is the latest application of IT to tracking goods and services or anything for that matter, including human beings. It is an evolution from bar code and palette technology, and, in this chapter, we present the argument that RFID is superior in reducing the mean and variance of inventory cycle times. As inventory cost is a function of these (among other variables, such as unit holding and shortage costs), we show that RFID reduces this cost. Also, because RFID leads to rapid transmission of data, it would help avoid excessive inventories and shortages, further reducing total inventory cost. We argue that RFID is superior to existing identification technologies according to mean-variance stochastic dominance. We discuss the ethical implications and the societal trade-offs inherent in RFID, as society must decide how much of its privacy it is willing to curtail in the pursuit of lower prices versus physical security. [ABSTRACT FROM AUTHOR]

In recent years, radio-frequency identification (RFID) has emerged as an important technology to facilitate the management of a supply chain. Because the technology is expensive and time-consuming to implement on a large scale, most enterprises require a relatively rigorous business case to support the decision whether or when to adopt the technology. To enable the development of such business cases, a tool set has been developed to quantify the business value of RFID for different participants in a manufacturing-retail supply chain. The tool set consists of two tools which are linked: A business value model, implemented as an in-house developed application using commercial spreadsheet software, and a business process model, implemented using a commercial discrete-event simulation package. The business process model computes and provides certain supply chain performance metrics to the business value model, which are otherwise difficult to obtain. Because it is not trivial to capture the full range of potential benefits of RFID, it is necessary to coordinate two different types of decision support tools (spreadsheets and computer simulation). [ABSTRACT FROM AUTHOR]

In this chapter, we first give an introduction to radio-frequency identification (RFID) technology. We discuss capabilities and limitations of this technology in a supply chain setting. We then present several current applications of this technology to supply chains to demonstrate best practices and important implementation considerations. Subsequently, we discuss several issues that may hinder widespread RFID implementation in supply chains. We close by deriving several consequences for successful implementation of RFID, and we give guidance on how a company might best benefit from this technology. [ABSTRACT FROM AUTHOR]

This article presents a systems approach to RFID deployment in a supply chain from two perspectives: (1) RFID data-based decision-making at all levels of supply chain and (2) communications infrastructure necessary to provide seamless data and information flow. The main contribution of this article is highlighting the interconnection between these two perspectives and the fact that without tackling these issues simultaneously, no viable solution can be developed. Unlike typical articles in the literature, which solely highlight the potential advantages of RFID technologies, this article aims to provide an overview of the basic challenges of deploying RFID systems in supply networks. By providing visibility, effective RFID implementation in a supply chain can bridge the gap between the shop floor and higher level operations. Such a revolutionary concept changes the traditional "linear" structured supply chains into network-centric supply chains. Based on this concept, this article presents a wide range of RFID applications, ranging from shop floor control to inventory management, and discusses technical and research challenges. [ABSTRACT FROM AUTHOR]