Multi-behavior agent model for planning in supply chains: An application to the lumber industry

Recent economic and international threats to western industries have encouraged companies to increase their performance in all ways possible. Many look to deal quickly with disturbances, reduce inventory, and exchange information promptly throughout the supply chain. In other words they want to become more agile. To reach this objective it is critical for planning systems to present planning strategies adapted to the different contexts, to attain better performances. Due to consolidation, the development of integrated supply chains and the use of inter-organizational information systems have increased business interdependencies and in turn the need for increased collaboration to deal with disturbance in a synchronized way. Thus, agility and synchronization in supply chains are critical to maintain overall performance. In order to develop tools to increase the agility of the supply chain and to promote the collaborative management of such disturbances, agent-based technology takes advantage of the ability of agents to make autonomous decisions in a distributed network through the use of advanced collaboration mechanisms. Moreover, because of the highly instable and dynamic environment of today's supply chains, planning agents must handle multiple problem solving approaches. This paper proposes a Multi-behavior planning agent model using different planning strategies when decisions are supported by a distributed planning system. The implementation of this solution is realized through the FOR@C experimental agent-based platform, dedicated to supply chain planning for the lumber industry.     

Systems dynamics modelling of a manufacturing supply chain system

Supply chains are multifaceted structures focusing on the integration of all the factors involved in the overall process of production and distribution of end products to the customers. Growing interest in supply chain systems has highlighted the need to adopt appropriate approaches that can ensure the efficient management of their complexity, enormity and broadness of scope. With the main aim of supply chain management being to optimise the performance of supply chains, attention is mainly drawn to the development of modelling frameworks that can be utilised to analyse and comprehend the dynamic behaviour of supply chains. While there have been only a few supply chain modelling attempts reported in the literature, this paper proposes a modelling framework that is used to simulate the operation of a supply chain network of moderate complexity. The proposed model comprises four echelons and is build around a central medium-sized manufacturing company operating as a typical Make-to-Order (MTO) system. The developed model was built using a systems dynamics (SD) approach. The operations performed within a supply chain are a function of a great number of key variables which often seem to have strong interrelationships. The ability of understanding the network as a whole, analysing the interactions between the various components of the integrated system and eventually supplying feedback without de-composing it make systems dynamics an ideal methodology for modelling supply chain networks. The objective of the paper is to model the operation of the supply chain network under study and obtain a true reflection of its behaviour. The modelling framework is also used to study the performance of the system under the initial conditions considered and compare it with that obtained by running the system under eight different scenarios concerning commonly addressed real-life operational conditions. The modelling effort has focused on measuring the supply chain system performance in terms of key metrics such as inventory, WIP levels, backlogged orders and customer satisfaction at all four echelons. The study concludes with the analysis of the obtained results and the conclusions drawn from contrasting the system’s performance under each investigated scenario to that of the benchmark model.     

A framework for measuring the performance of service supply chain management

Despite the increasing attention to the service supply chain management by both practitioners and academics, the performance measurement of service supply chains still remains unexplored. Most service firms realize that, in order to evolve an efficient and effective service supply chain, service supply chain management needs to be assessed for its performance. A literature review was conducted on performance measurement issues of service supply chains. This paper develops a framework of service supply chain performance measurement. Based on the strategic, tactical and operational level performance in a service supply chain, measures and metrics are discussed. The emphasis is on performance measures dealing with service supply chain processes such as demand management, customer relationship management, supplier relationship management, capacity and resource management, service performance, information and technology management and service supply chain finance. And to prioritize service supply chain performance measurement indicators to improve service supply chain performance, a methodology based on the extent fuzzy analytic hierarchy process is stressed. The developed framework of service supply chain performance measurement is applied to the hotel supply chain. The results of this study are useful both to practitioners in the service supply chain and to researchers carrying out further studies in the field.     

SUPPLY SYSTEM DYNAMICS: DISTRIBUTED CONTROL IN SUPPLY CHAINS AND NETWORKS

The purpose of this article is to make a contribution to a more effective management for supply chains and networks, which we are subsuming under the title supply systems. We conceive of supply systems management as the design, control, and development of logistics along the value chain or in value networks. In this article, we concentrate on control, i.e., the regulation and steering of supply systems from production to customer and vice versa, with the help of system dynamics modeling and simulation. Traditionally, supply chain management has been heavily supported by discrete event simulation and optimization models on very detailed levels. Established tools, e.g., Manufacturing Resources Planning, Enterprise Resources Planning, and Production Planning Systems, have emphasized highly specialized functions, such as the planning for optimal capacity use and achievement of delivery goals, via the sequencing, scheduling, and dispatching of individual orders, or the global allocation of resources but without the possibility to evaluate different outcomes of the allocation process. In the quest for efficiency and effectiveness, new approaches to control, which lead beyond these functions of disposition, are needed. We present a model that combines two systemic methodologies that operate on higher levels of aggregation and complement each other: system dynamics to model and simulate the supply chain and cybernetic control to apply control-theoretical concepts, namely proportional, derivative, and integral control, in a combined mode as well as according to a recursive logic of distributed control. This way, substantial improvements in both efficiency and effectiveness can be achieved, and ultimately organizational viability can be enhanced.     

Toward a methodological framework for agent-based modelling and simulation of supply chains in a mass customization context

In a dynamic customer-centric supply chain context, classic forecasting models turn out to have a limited applicability. In order to estimate the key performance indices of these Supply Chains and to facilitate their management, it is necessary to use more elaborate tools such as a simulation. However building simulation of customer-centric supply chains is no trivial matter. It requires the elaboration of a representative model and the execution of this model according to a set of hypotheses associated to scenarios. Due to their properties, Multi-Agent Systems seem particularly well suited for the modelling and the simulation of Supply Chains and more especially in a mass customization context. In this paper we propose an agent modelling framework for the modelling and simulation of such Supply Chains to facilitate their management. We show how this framework can be applied to a case of customer-centric Supply Chain from the golf club industry and we present an experiment plan associated.     

Enterprise systems and demand chain management: a cross-sectional field study

Increased product variety, compressed cycle times, supply chain network based competition and the uncertainty in business environment are forcing organizations to shift their emphasis towards demand chain management. Though enterprise systems and supply chain management software solutions are well in place in most of the large enterprises in Australia, their ability to support demand chain management approach is not yet known. This paper investigates the adoption of demand chain management in Australian organizations using cross-sectional qualitative field study. It found that the adoption is limited despite the organizational capabilities and sound digital platforms. Standardization, integration, visibility and control of processes and information, enabled by enterprise systems, are helping the organizations in improving their ability to sense and shape market demand and customer needs, and build agility into their decision making processes. Attempts to synchronise operating and finance cycles and collecting market intelligence and sharing of that across the supply chain are some of the initiatives that have started showing benefits. Adopting the demand chain management initiatives such as establishment of market intelligence mechanism, building agility into decision making processes, sophisticated usage of optimization tools embedded in software solutions, and process frameworks such as Supply Chain Operations Reference are helping organizations to achieve both agility and control simultaneously.     

A hierarchical framework for visualising and simulating supply chains in virtual environments

This paper presents research into applying virtual environment (VE) technology to supply chain management (SCM). Our research work has employed virtual manufacturing environments to represent supply chain nodes to simulate processes and activities in supply chain management. This will enable those who are involved in these processes and activities to gain an intuitive understanding of them, so as to design robust supply chains and make correct decisions at the right time. A framework system and its hierarchical structure for visualising and simulating supply chains in virtual environments are reported and detailed in this paper.     

Determination and exchange of supply information for co-operation in complex production networks

Today's manufacturing industry is characterised by strong interdependencies between companies operating in globally distributed production networks. The operation of such value-added chains has been enabled by recent developments in information and communication technologies (ICT) and computer networking. To gain competitive advantages and efficiency improvements such as reduced inventory and higher delivery reliability, companies are introducing information exchange systems that communicate demand to suppliers and production progress information to customers in the network. This article proposes a system that supports co-operation in complex production networks by enabling companies to determine and exchange supply information with their customers. The requirements for such a system are analysed and it is embedded in a framework of supply chain management business processes. The system facilitates the determination and exchange of meaningful, reliable and up-to-date order status information from the supplier to the customer. Based on comparing the progress of an internal production order with a pre-defined milestone model for each product, the status of the customer order is determined and—in case of lateness—communicated to the customer together with an early warning. To demonstrate the developed supply information concepts and processes, the business process is implemented as a pilot system and evaluated by the user companies participating in the 5th Framework IST project Co-OPERATE.     

Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

The Bass model is a very successful parametric approach to forecast the diffusion process of new products. In recent years, applications of the Bass model have been extended to other operational research fields such as managing customer demands, controlling inventory levels, optimizing advertisement strategies, and so forth. This study attempts to establish an application for optimizing manufacturers’ production plans in a three-stage supply chain under the Bass model’s effects on the market. The supply chain structure considered in this research is similar to other common supply chains comprised of three stages, namely retailer, distributor and manufacturer. The retailer stage has to handle customer demands following the Bass diffusion process. Market parameters and essential information are assumed to be available and ready for access. Each stage is expected to determine its inventory policy rationally. That is, each stage will attempt to maximize its own profits. These decisions will back-propagate their effects to upper stages. This study adopts a dynamic programming approach to determine the inventory policies of each stage so as to optimize manufacturers’ production plans.     

基于颜色Petri网的不确定库存模型性能仿真

供应链中由于信息传递过程中出现的信息膨胀引起牛鞭效应造成各种成本的急剧增长,为使目标函数费用最小,基于颜色Petri网建立了不同需求预测方法及库存策略的CPN模型。在订单数量等变量随机产生以及订货点等因素不确定的情况下,通过实验仿真数据确定了存储、订货及缺货费用与各种不确定变量的关系,从而确定了最优的库存策略。通过对比实验证明了该方法的有效性及正确性。     

A survey on control theory applications to operational systems,supply chain management,and Industry 4.0

Modern production and logistics systems, supply chains, and Industry 4.0 networks are challenged by increased uncertainty and risks, multiple feedback cycles, and dynamics. Control theory is an interesting research avenue which contributes to further insights concerning the management of the given challenges in operations and supply chain management. In this paper, the applicability of control theory to engineering and management problems in supply chain operations is investigated. Our analysis bridges the fundamentals of control and systems theory to supply chain and operations management. This study extends our previous survey in the Annual Reviews in Control (Ivanov et al. 2012) by including new literature published in 2012–2018, identifying two new directions of control theory applications (i.e., ripple effect analysis in the supply chains and scheduling in Industry 4.0) and analysis towards the digital technology use in control theoretic models. It describes important issues and perspectives that delineate dynamics in supply chains, operations, and Industry 4.0 networks and identifies and systemizes different streams in the application of control theory to operations and supply chain management and engineering in the period from 1960–2018. It updates the existing applications and classifications, performs a critical analysis, and discusses further research avenues. Further development of interdisciplinary approaches to supply chain optimization is argued. An extended cooperation between control engineers and supply chain experts may have the potential to introduce more realism to dynamic planning and models, and improve performance in production and logistics systems, supply chains, and Industry 4.0 networks. Finally, we analyze the trends towards the intellectualization of control and its development towards supply chain control analytics.     

Specifying information systems for business process integration – A management perspective*

Supply chain management and customer relationship management are concepts for optimizing the provision of goods to customers. Information sharing and information estimation are key tools used to implement these two concepts. The reduction of delivery times and stock levels can be seen as the main managerial objectives of an integrative supply chain and customer relationship management. To achieve this objective, business processes need to be integrated along the entire supply chain including the end consumer. Information systems form the backbone of any business process integration. The relevant information system architectures are generally well-understood, but the conceptual specification of information systems for business process integration from a management perspective, remains an open methodological problem. To address this problem, we will show how customer relationship management and supply chain management information can be integrated at the conceptual level in order to provide supply chain managers with relevant information. We will further outline how the conceptual management perspective of business process integration can be supported by deriving specifications for enabling information system from business objectives. This work has been funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung), record no. 01HW0196.     

Implementation of intelligent systems, enabling integration of SMEs to high-value supply chain networks

In the face of increasing competition from low-cost economies, European manufacturing companies are focusing on optimisation of operational activities to remain competitive. Previous work has identified how companies can optimise implementation of specialist technology to improve production capability; however increasing demands in service requirements such as customisability and flexibility are often negating the localised gains in capability.Supply chain management has become an increasingly important aspect of operations improvement to ensure support throughout the product realisation process. The key to creating a supply chain capable of this rapid response and high level of adaptability is integration of intelligent systems and management capabilities.A site-visit-based survey and characterisation of small and medium enterprises (SMEs), comprising actual or potential supply chain components, reveals that even those with well developed capabilities and attitudes to adopting production technologies are largely not proactive with technology adoption targeting these needs.A review of requirements for SMEs to achieve such competitive supply chain capabilities reveals a hierarchy of technical expertise to be developed. This is presented as an implementation strategy for staged introduction of these tools and techniques with a view to establishing high-value supply chains capable of withstanding business pressures from developing economies.     

The role of the customer order decoupling point in production and supply chain management

In order to compete successfully, operations in any type of firm need to be strategically aligned to the market requirements. This concerns both manufacturing and supply chain operations. The customer order decoupling point (CODP) is getting increasing attention as an important input to the design of manufacturing operations as well as supply chains. This paper investigates the impact of the position and role of the CODP on issues of concern for production and supply chain management. The focus is on the design and strategic planning aspects of the supply chain, and the design of manufacturing planning and control systems. The paper proposes a dual design approach for production and supply chain planning systems; one type of system for operations upstream the CODP and another type of system for downstream operations in order to fully support the characteristics and objectives of each respective part of the supply chain.     

Applicability of optimal control theory to adaptive supply chain planning and scheduling

Decisions in supply chain planning and control are interconnected and depend on tackling uncertainties and dynamics. From this perspective, control theory (CT) is an interesting research avenue for the supply chain management (SCM). In this paper, the applicability of optimal CT to SCM is investigated. Our analysis is based on the fundamentals of control and systems theory and experimental modeling. The paper describes important issues and perspectives that delineate dynamics in supply chains, identifies and systemizes different streams in application of CT to production, logistics, and SCM in the period from 1960 to 2011. It derives some classifications, performs a critical analysis, and discusses further researches. Some drawbacks and missing links in the literature are pointed out. Several crucial application areas of control theory to SCM are discussed. Subsequently, optimal program control, challenges and advantages of its application in the SCM are addressed. It is shown how optimal program control can be applied to adaptive supply chain planning. In addition, it is concluded that with the help of CT, robustness, adaptability, and resilience of supply chains can be investigated in their consistency with operations planning and execution control within a conceptually and mathematically integrated framework. However, although SCs resemble control systems, they have some peculiarities which do not allow a direct application of CT methods. In this setting, further development of interdisciplinary approaches to supply chain optimization is argued. An extended co-operation between control and supply chain experts may have the potential to introduce more realism to the dynamic planning and models and improve real-time supply chain control policies.     

Real-time supply chain control via multi-agent adjustable autonomy

Real-time supply chain management in a rapidly changing environment requires reactive and dynamic collaboration among participating entities. In this work, we model supply chain as a multi-agent system where agents are subject to an adjustable autonomy. The autonomy of an agent refers to its capability to make and influence decisions within a multi-agent system. Adjustable autonomy means changing the autonomy of the agents during runtime as a response to changes in the environment. In the context of a supply chain, different entities will have different autonomy levels and objective functions as the environment changes, and the goal is to design a real-time control technique to maintain global consistency and optimality. We propose a centralized fuzzy framework for sensing and translating environmental changes to the changes in autonomy levels and objectives of the agents. In response to the changes, a coalition-formation algorithm will be executed to allow agents to negotiate and re-establish global consistency and optimality. We apply our proposed framework to two supply chain control problems with drastic changes in the environment: one in controlling a military hazardous material storage facility under peace-to-war transition, and the other in supply management during a crisis (such as bird-flu or terrorist attacks). Experimental results show that by adjusting autonomy in response to environmental changes, the behavior of the supply chain system can be controlled accordingly.     

System dynamics of supply chain network organization structure

Information technology is providing manufacturers with additional flexibility with regard to their supply chain network choices. Our research studies supply chain network organization structures categorized by the organic and mechanistic management control structures. The structural impacts on cost and fill rate performance are studied in two-echelon and two-supply-chain network organization models under different market coordination conditions using system dynamic simulations. Our results show significant effects of demand and network structural factors, and their interactions, on these measures. As demand becomes dynamic, the cooperative interaction model, where supply chains cooperate to satisfy customer demand, is found to have better system performance than the competitive supply chain model. The analysis also suggests that increasing the responsiveness at the downstream plant is particularly important to the overall system performance improvement.     

SysML-based design chain information modeling for variety management in production reconfiguration

Satisfying diverse customer needs leads to proliferation of product variants. It is imperative to model the coherence of functional, product and process varieties throughout the design chain. Based on a model-based systems engineering approach, this paper applies the Systems Modeling Language (SysML) to model design chain information. To support variety management decisions, the SysML-based information models are further implemented as a variety coding information system. A case study of switchgear enclosure production reconfiguration system demonstrates that SysML-based information modeling excels in conducting requirements, structural, behavioral and constraints analysis and in performing trade-off study. In addition, it maintains semantic coherence along the design chain, keeps traceability across different levels of abstraction, thus improving interoperability among heterogeneous tools.     

A distributed architecture for reconfigurable control of continuous process operations

This paper considers a new distributed approach to reconfigurable control of continuous process operations such as in chemical plants. The research is set on a premise that emerging business pressures of product customization and industrial globalization will lead to increased need for reconfigurability in process plants. The ability of processes to support dynamic and smooth reorganization of process schemes in tandem with the changing requirements of supply chains will become important in future. Conventional control approaches based on hierarchical architectures are limited in dealing with such emerging requirements due to their inflexible structures and operating rules. Instead, more distributed approaches are required which can support increased level of reconfigurability in control systems, especially at the lower levels in hierarchy where the visibility to disturbances remains high. In this paper, one such distributed approach is considered based on the concepts of holonic manufacturing and supply chain management. The proposed approach distributes the functionality of process control into several reconfigurable process elements. These elements, while having a stand-alone capability for making their own control decisions, are also able to reconfigure themselves into alternative process schemes which evolve with the changing requirements of production. An analogy between process plants and so-called dynamic supply networks or virtual enterprises is used in this paper to define the composition of reconfigurable process elements and their operations. The proposed approach is shown to offer improved process control system reconfigurability and a control architecture which is compatible with the supply chain management needs at the next higher level. The purpose of this paper is qualitative and motivational. It is aimed to propose a new research direction in the field of reconfigurable process control.     

Guidelines for Collaborative Supply Chain System Design and Operation

Over the past decade, firms have adopted supply chain management as a critical element of their corporate strategies. Despite these efforts, it is our observation that many firms do not realize the anticipated benefits of constructing collaborative operating relationships with supply chain partners. Our purpose in this paper is to establish a set of guiding principles for the effective design and execution of supply chain systems. These principles suggest why, what, and how collaborative relationships should be constructed.While constructing and operating a competitive supply chain is the primary objective of supply chain management, we have observed several impediments to achieving this goal. First, demand uncertainty is so substantial in most supply chain environments that if it is not adequately addressed, it can severely degrade the anticipated performance of the supply chain as measured in terms of unit cost, speed, quality, and responsiveness to changing conditions. Second, supply chains with poor physical characteristics that operate with long and variable response times cannot take full advantage of collaborative relationships due to their inability to respond to changes in the environment. Third, firms with poor information infrastructures lack the capabilities necessary to acquire, store, manipulate, and transmit data effectively and quickly. Fourth, business processes are often not designed properly, both intra- and inter-organizationally, to adapt to evolving supply chain conditions. Finally, decision support systems and operating policies that guide day-to-day operating decisions may not be adequately designed to contend with supply chain uncertainty.We also suggest that the strategic and tactical modeling paradigms employed in supply chain decision support systems are inadequate in many operational environments because of the manner in which uncertainty is treated. Furthermore, collaborative relationships that focus on reducing the uncertainty in operating environments by employing improved information systems and business processes will result in more efficient allocation of key resources, faster response times to market forces, and more reliable supply chain performance; however, these collaborative arrangements by themselves cannot compensate for fundamentally flawed and operationally ineffective manufacturing and distribution environments.