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2010 | Buch

Adaptive Supply Chain Management

verfasst von: Dmitry Ivanov, Boris Sokolov

Verlag: Springer London

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

Adaptive Supply Chain Management develops new viewpoints on the SCM goal paradigm, problem semantics, and decision-making support.

Drawing upon years of research and practical experience, and using numerous examples, the authors unite conceptual considerations of supply chains with a constructive level of engineering and solutions to real-world problems. Adaptive Supply Chain Management provides advanced insights into dynamics, complexity, and uncertainty in supply chains from the perspectives of systems analysis, control theory, and operations research. It also considers supply chain adaptability, stability, and crisis-resistance.

Providing readers with a comprehensive view of advanced SCM concepts, constructive mathematical techniques and models, Adaptive Supply Chain Management is an invaluable text for practitioners and researchers who specialize in SCM and operations.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Evolution of Supply Chain Management (SCM)

Abstract

The chapter starts by describing the role of SCM in enterprise management. Subsequently, the predecessors and establishment of SCM are discussed. Particularly, market and enterprise management paradigm developments in 1960–2010, objective economic grounds of SCM development, and the development of SCM are presented. Finally, the issues of SCM and related disciplines are discussed. We analyse the interrelations of logistics and SCM as well as arguing the multidisciplinary nature of SCM. The chapter highlights the key role of SCM in modern enterprise management and concludes that this role will increase in the coming years due to further globalization, customer orientation and advancements in information technology (IT). Finally, the main research directions on SCM are discussed.

Chapter 2. Conceptual Frameworks for Supply Chain Management

Abstract

In this chapter, the issues in agile, flexible and responsive SCs and related categories of postponement, virtual enterprises (VE) and coordination are considered. Different interrelations of these categories are examined. We also present the state of the art of adaptive SCM (A-SCM). Subsequently, the basics of the conceptual vision of the A-SCM approach at the organizational level are considered. We start with the main definitions, and then we consider the A-SCM framework as composed of elements drawn from SCM, VE, agile/responsive SCs, and sustainable SCM. In the A-SCM framework, we do not set off different value-adding chain management strategies with each other, but consider them as an integrated framework. All three value chain drivers – products and their life cycles, customers and their orders, and suppliers/outsourcers – are enhanced by combining the elements from SCM, agility, and sustainability. Moreover, these drivers are interlinked within a unified information space.

Chapter 3. Decision-making Support for Supply Chain Management

Abstract

This chapter deals with decision-making support for the SCM domain. The first part of the chapter is devoted to basic approaches to modelling SCs. We consider the model-based decision-making support as being composed of mathematical and informational models as well as of different hybrid models. In the class of mathematical models, we distinguish the research paradigms of OR, control theory and agent-based approaches. We also consider the main solution techniques: optimization, simulation, statistics, heuristics and hybrid models. Subsequently, we consider the information modelling of SCs subject to business process reengineering models, IT-driven models, and the use of modern IT techniques and methods for the integration of SC decision-making models. In the second part of the chapter, we analyse the information systems-driven decision-making support. Basic IT with regard to different application areas within the SCM domain are presented. Finally, we consider possibilities to develop integrated modelling frameworks (IMF) from informational and mathematical perspectives.

Chapter 4. Challenges in Research on Modern and Future Supply Chains

Abstract

This chapter deals with modern developments and challenges in SCM from both the practical and theoretical points of view. We highlight the following main challenges for SCM: compromising potential SC economic performance and SC stability; capturing uncertainty and dynamics; handling the multi-structural nature of SCs; ensuring interrelations and optimality of decisions at different management levels; conducting multi-disciplinary research on SCM; establishing links to different stages of the product life cycle, related enterprise management functions and the environment. Finally, we consider challenges in the further development of IT and organizational aspects for SCM. We conclude by summarizing 12 main misunderstandings of SCM that we have experienced in our teaching and consulting work so far.

Chapter 5. Uncertainty, Risk and Complexity

Abstract

In the focus of this chapter are the issues of uncertainty, risk and complexity in SCs. We discuss the origins of uncertainty, risk and complexity and provide proper classifications. The uncertainty factors are divided into environmental uncertainty, human thinking and decision-making uncertainty. The distinguishing purposeful and non-purposeful perturbation influences also form the basis of the proposed classifications. Subsequently, issues in SC complexity are presented. We conclude this chapter by analysing the practical issues of uncertainty in SCs. This chapter shows the interrelations between uncertainty and complexity management. The interlinking of uncertainty, risk, disturbances and deviations are discussed. Finally, constructive arguments to consider SCs as complex systems are discussed.

Chapter 6. Handling Uncertainty in Supply Chains

Abstract

As indicated in the recent literature, there are two types of risk affecting SCs: (1) risks arising from the problems of coordinating supply and demand and (2) risks arising from disruptions to normal activities. According to this classification, we will continue to consider the issues of uncertainty and risk in this chapter. This chapter analyses purposeful perturbation influences from the point of view of SC security, and non-purposeful perturbation influences from the point of view of SC vulnerability. We describe different kinds of both purposeful and non-purposeful perturbation influences. Subsequently, managerial impacts to handle uncertainty in SCs are addressed. In particular, leverages of SC reliability and flexibility are analysed.

Chapter 7. STREAM: Stability-based Realization of Economic Performance and Management

Abstract

In this chapter we develop the conceptual basics of the approach to balancing SC economic performance and stability as the primary objective in SC planning and optimization. The developed concept is named STREAM (Stability-based Realization of Economic Performance and Management). The concept STREAM, as the name implies, is based on the idea that the SC’s potential economic performance will be realized through the SC’s stability. The conceptual model of STREAM is based on conceptualizing the subject domain from uniform SCM and system-cybernetic positions by means of the interconnected considerations of (1) control and perturbation influences in SCs and (2) verbally describable properties of an SC as a business process (for example, security and flexibility) and theoretically attributed properties of an SC as a complex system (for example, adaptability and resilience). Finally, general algorithms of SC (re)planning under uncertainty are presented.

Chapter 8. Quantitative Modelling of Supply Chains

Abstract

This chapter is devoted to the modelling approaches in the SCM domain. The chapter starts with an analysis of OR on SCM that can be divided into three primary approaches to conducting SC modelling. These are optimization, simulation and heuristics. Subsequently, control theory application in the SCM domain is discussed. Finally, the approaches of complex adaptive systems (CAS) and multiagent systems (MAS) are analysed. A critical analysis of the advantages and limitations of different modelling techniques concludes this chapter. The chapter highlights the main features and application areas of OR, control theory and agentbased models in the SCM domain.

Chapter 9. DIMA – Decentralized Integrated Modelling Approach

Abstract

In this chapter, the basics of the SC multi-disciplinary treatment in the DIMA (Decentralized Integrated Modelling Approach) methodology are presented. The main principles of the DIMA are SC elements’ activity, multiple modelling, integration and decentralization. We consider these principles in detail in the course of the chapter. We introduce the concept of an “active modelling object” (AMO) as part of the generic model constructions. Integration is considered from four perspectives: the integration of various modelling approaches and frameworks, the integration of planning and execution models, the integration of decision-making levels, and the implementation of integration throughout “conceptual model → mathematical model → computation”. The integration and combined application of various models is implemented by means of multi-model complexes and qualimetry of models.

Chapter 10. Structure Dynamics Control and Multi-model Analysis

Abstract

One of the main features of SCs is the multi-structural design and changeability of structural parameters because of objective and subjective factors at different stages of the SC life cycle. In other words, SC structure dynamics is constantly encountered in practice. In this chapter, we present the concept and the models of SC structure dynamics. The common conceptual basis facilitates the construction of a complex of unified dynamic models for SC control. The models describe the functioning SC along with the collaboration processes within them. The unified description of various control processes allows the simultaneous synthesis of different SC structures. The proposed approach allows us to establish a dependence relation between the control technology applied to SCs and the SCM goals. This statement is exemplified by an analysis of SC functional abilities and goal abilities. It is important that the presented approach extends new scientific and practical results obtained in the modern control theory for the SCM domain.

Chapter 11. Adaptive Planning of Supply Chains

Abstract

In this chapter, we discuss the kernel of planning and scheduling as an integrated management function and provide a classification of planning tasks. Then we consider the method of adaptive planning. Subsequently, we present a general conceptual framework of the adaptive planning and scheduling with the models’ adaptation. The main purpose of the adaptation framework is to ensure parameter tuning of the dynamic scheduling model with regard to changes in the execution environment. In the proposed framework, the plans’ adaptation is connected with the models’ adaptation. Within the framework, a special controller concept is presented. Finally, we consider SC planning levels and their reflections. We develop a framework of decision-making consistency in SCM on the basis of adaptive planning principles.

Chapter 12. Modelling Operations Dynamics, Planning and Scheduling

Abstract

In this chapter, we present mathematical models and algorithms for operations dynamics planning and scheduling. The basics of the research approach are discussed. A complex of dynamic models for integrated planning and scheduling is presented. This complex is composed of dynamic models for collaborative operations control, resource control and flow control. Subsequently, we consider algorithms for optimal SC operations control and develop our own one. The proposed approach is based on the fundamental scientific results of modern control theory and systems analysis in combination with the optimization methods of OR. We formulate the planning and scheduling as optimal control problems, taking into account the discreteness of decision-making and the continuity of flows with the use of special techniques, e.g., by transferring the non-linearity from the dynamic models into the left part of the differential equations in constraints. The modelling procedure is based on an essential reduction of a problem dimensionality that is under solution at each instant of time due to connectivity decreases. For the computations, the dynamic Lagrange relaxation, transformation of the optimal control problem to the boundary problem and maximization of Hamiltonians with the use of Pontryagin’s maximum principle are used.

Chapter 13. Supply Chain Reconfiguration and Models’ Adaptation

Abstract

In this chapter, we consider issues of SC reconfiguration and models’ adaptation. We classify different SC reconfiguration issues within the control loop. The considerations presented lead us from a narrow traditional interpretation of complex systems’ reconfiguration to a wide interpretation within a new applied theory of SDC. In the first phase of re-configuration, the forming (generation) of allowable multi-structural macro-states is performed. In other words, a structural-functional synthesis of a new SC should be fulfilled in accordance with an actual or forecasted situation. In the second phase, a single multi-structural macro-state is selected, and adaptive plans of SC transition to the selected macro-state are constructed. Subsequently, a mathematical model of the SC reconfiguration and algorithms of parametric and structure adaptation are presented.

Chapter 14. Models of Supply Chain Global Stability and Manageability

Abstract

In this chapter the mathematical model complex of SC stability analysis is presented. These formal models present at the mathematical level the conceptual model of the global stability. In its development, stability comes to be interpreted in different ways beginning with the classical BIBO stability up to the nonquantified “conceptual” stability concepts. We consider as stability the SC property to approach the real SC performance to the planned one under the interacting SC processes in the real perturbed execution environment with regard to the variety of execution and goal criteria. The SC stability analysis addresses the problem of the direct connection of SC stability and economic performance. The model is based on the dynamic interpretation of the SC functioning process and uses for the first time the method of attainable sets (AS) for the SCM domain.

Chapter 15. Experimental Environment

Abstract

In this chapter the concept of the integrated experimental environment developed and its partial components are considered. A vision of a special software environment, which contains a simulation and optimization “engine” of SC planning, a Web platform, an ERP system and an SC monitor, is presented. For experiments, we elaborated two software prototypes: (1) SNDC – Supply Network Dynamics Control and (2) SCPSA – Supply Chain Planning and Stability Analysis. We provide some case examples with experimental results that reflect the models of the previous chapters.

Backmatter

Titel: Adaptive Supply Chain Management
verfasst von: Dmitry Ivanov
Boris Sokolov
Verlag: Springer London
Electronic ISBN: 978-1-84882-952-7
Print ISBN: 978-1-84882-951-0
DOI: https://doi.org/10.1007/978-1-84882-952-7