Hybrid Petri-nets for modelling and performance evaluation of supply chains

Modelling and analysis of complex and co-ordinated supply chains is a crucial task due to its inherent complexity and uncertainty. Therefore, the current research direction is to devise an efficient modelling technique that maps the dynamics of a real life supply chain and assists industrial practitioners in evaluating and comparing their network with other competing networks. Here an effective modelling technique, the hybrid Petri-net, is proposed to efficiently handle the dynamic behaviour of the supply chain. This modelling methodology embeds two enticing features, i.e. cost and batch sizes, in deterministic and stochastic Petri-net for the modelling and performance evaluation of supply chain networks. The model is subsequently used for risk management to investigate the issues of supply chain vulnerability and risk that has become a major research subject in recent years. In the test bed, a simple productive supply chain and an industrial supply chain are modelled with fundamental inventory replenishment policy. Subsequently, its performance is evaluated along with the identification and assessment of risk factors using analytical and simulation techniques respectively. Thus, this paper presents a complete package for industrial practitioners to model, evaluate performance and manage risky events in a supply chain.     

A fractal perspective-based methodological framework for supply chain modelling and distributed simulation with multi-agent system

With the development of global economy, supply chain, as a recognised complex system, is becoming more complex for analysis. In this context, it is worth introducing the perspective of complex system in perceiving and modelling of supply chain system to address its dynamic, stochastic and uncertain characteristics. Therefore, this paper proposes a methodological framework of supply chain modelling and simulation based on the fractal perspective, and presents an all-round and systematic exposition of concept modelling and distributed simulation by means of multi-agent technology. In this framework, different supply chain scenarios focusing on manufacturing, inventory and transportation can be easily modelled and simulated at different scales and levels. In addition, a prototype system which implements the methodological framework and the key implementation techniques are presented as well. Finally, a supply chain example, which supposes manufacturer as the core member, is modelled and simulated with the prototype system to illustrate the effectiveness of the proposed framework.     

A simulation approach for evaluation and improvement of organisational planning in collaborative product development projects

Human behaviour and organisational structure impact collaborative product development outcome on a large scale. Therefore, companies are continuously seeking new opportunities to increase the efficiency, effectiveness and predictability of their collaborative product development projects, and to develop innovative principles for organisational design and management such as multi-functional teams. However, there are many factors which have to be considered and assessed to systematically optimise organisational planning in respect of team configuration, structure organisation, and human behaviour. This paper proposes an agent-based simulation methodology to evaluate and improve the organisational planning in complex product development projects. An agent-based integrated simulation model is formulated which can explicitly represent human behaviour, organisational interactions, and tasks networks. Based on the model, the design agent structure and behaviour protocols are studied in detail, and a simulation platform is developed. Finally, the methodology is evaluated in a collaborative roadway design project, and several management insights are established, which are proven to be effective for the organisational optimisation. The results of the case study also show that the methodology can effectively support the evaluation and improvement of organisational planning.     

基于SCOR模型的供应链建模方法

SCOR模型被遍布世界各地的、各行各业的众多企业所采用,为这些企业带来了巨大的效益。SCOR模型被认为是为企业进行供应链评估和流程再造的最佳工具。本文系统介绍了SCOR模型的完整建模方法以及实施SCOR模型所采用的自上而下的步骤。     

Bid generation and evaluation for MANPro-based real time scheduling

This paper proposes a bid generation and evaluation scheme and an information model for real-time scheduling. It is well known that an agent-based control approach performs according to both the negotiation mechanism itself and the single agent internal strategic policies. Mobile agent-based negotiation process (MANPro), which has been proposed in our previous work, concerns the first issue of the negotiation mechanism. This paper concerns the second issue of the single agent internal strategic policies. It explains how bids are generated and evaluated and how agents obtain mutual agreement in MANPro. First, the generic bid generation and evaluation framework for MANPro-based negotiation is proposed. Then, the generic framework is applied to a real-time scheduling system for a distributed shop floor control system (SFCS).     

A simulation based approach for supply network control

We focus on the problem of strategic network design in the context of multi-site enterprises. We develop a simulation model for various supply network designs evaluation. The suggested model is generic in the sense that only input data modifications are needed to adapt the model to a given supply network structure, while the model's procedural logic stays unchanged. The model reproduces the dynamics of the totality of the supply chain activities. It takes into account control policies related to the inventory management and to the scheduling of production activities. It also carries out local optimisations by dynamically allocating the customers’ demands to the appropriate distribution site and the replenishment orders expressed by the distribution and production sites of the enterprise so as to minimise a global cost function. Simulation execution permits to compute various performance measures. These indicators inform the decision-maker about the profit of the enterprise and about its customer's service level. In this paper, we propose to detail the simulation model. Then, for a fictitious problem of supply network design based on two real life applications, we highlight the influence of the control policies on the performance of the studied enterprise.     

A multi-agent system for chemical supply chain simulation and management support

Modern chemical production is customer-driven and the desired delivery time for the products is often shorter than their campaign length. In addition, the raw materials supplying time is often long. These features make it desirable to provide tools to support collaborative supply chain decision making, preferably over the Internet, and where there are conflicts, compromise decisions can be quickly reached and the effects of the decisions can be quantitatively simulated. This paper des cribes such a multi-agent system (MAS) that can be used to simulate the dynamic behaviour and support the management of chemical supply chains over the Internet. Geographically distributed retailers, logistics, warehouses, plants and raw material suppliers are modelled as an open and re-configurable network of co-operative agents, each performing one or more supply chain functions. Communication between agents is made through the common agent communication language KQML (knowledge query message language). A t the simulation layer, the MAS allows distributed simulation of the chain behaviour dynamically, so that compromise decisions can be rapidly and quantitatively evaluated. Because in a chemical supply chain the scheduling of the plant often dominates the chain performance, an optimum scheduling system for batch plants is integrated into the MAS. The functions of the system are illustrated by reference to a case study for the supply and manufacture using a multi-purpose batch plant of paints and coatings.     

Distributed simulation of virtual workshops for the multi-site scheduling feasibility evaluation

In this article, a distributed simulation tool for the feasibility evaluation of multi-site scheduling is proposed. The application areas concern supply chains (SCs) or networks of distributed workshops. The distributed simulation of workshops, called virtual workshops, generates various problems of causality and of tasks execution coordination. These problems are addressed in the proposed distributed architecture by the use of High Level Architecture protocol guaranteeing the synchronisation and the chronology of events occurring in the distributed simulations. An application to a simple case of the SC organising the flow between three workshops shows the effectiveness of the distributed simulation tool.     

Information sharing and coordination mechanisms for managing uncertainty in supply chains: a simulation study

The study aims to investigate the effectiveness of information sharing and coordination mechanisms in reducing uncertainty. Supply chains are constantly subject to unpredictable events that can adversely influence its ability to achieve performance objectives. This paper primarily aims at managing uncertainties originating from unexpectedly large demand spikes. The supply chain literature is full of effective supply chain uncertainty management practices. This paper reviews the different practices for improving management of uncertainty and proposes several combinations of information sharing and coordination mechanism for reducing the uncertainty in supply chains. Next, the proposed combinations are tested on the make-to-stock supply chain of a paper tissue manufacturer using an agent-based simulation approach to show how the use of different levels of information sharing and coordination can be effective in managing uncertainty under daily operations facing a huge mismatch of actual and forecast demand. The findings of this research suggest that, a centralised information structure without widespread distribution of information and coordination is not effective in managing uncertainty of supply chain networks, even with increased frequency of information flow. Similarly, coordinating material flows without widespread information sharing does not improve supply chain uncertainty management. Central coordination of material flows with supply chain wide information sharing across different members is found to be essential in managing supply chains effectively under uncertainty.     

Simulation-based ripple effect modelling in the supply chain

In light of low-frequency/high-impact disruptions, the ripple effect has recently been introduced into academic literature on supply chain management. The ripple effect in the supply chain results from disruption propagation from the initial disruption point to the supply, production and distribution networks. While optimisation modelling dominates this research field, the potential of simulation modelling still remains under-explored. The objective of this study is to reveal research gaps that can be closed with the help of simulation modelling. First, recent literature on both optimisation and simulation modelling is analysed. Second, a simulation model for multi-stage supply chain design with consideration of capacity disruptions and experimental results is presented in order to depict major areas of simulation application to the ripple effect modelling. Based on both literature analysis and the modelling example, managerial insights and future research areas are identified in regard to simulation modelling application to the ripple effect analysis in the supply chain. The paper concludes by summarising the most important insights and outlining a future research agenda.     

Individuals and their interactions in demand planning processes: an agent-based,computational testbed

The demand planning process in semiconductor supply chains faces many challenges. In this process, individuals, their properties such as sensing capabilities and their interactions play a crucial role. This paper shows how agent-based modelling (ABM) can provide a computational testbed to investigate these aspects with respect to forecast accuracy. Based on the requirements of the demand planning context, we develop an empirically validated agent-based model of the demand planning process. In this model, we incorporate different concepts from behavioural science and the distributed cognition perspective. We show the usefulness of this agent-based computational testbed by using a case study from the semiconductor industry. Our model shows that demand planning accuracy does not depend on the planning capabilities of planners alone, but that the interactions of the individuals, emerging from the planning process design, may both positively and negatively affect accuracy.     

区块链系统分布式计算的ADMM算法及其在主动配电网中的应用

区块链作为一种新颖的计算机技术,由于具备诸多的优点,其在未来主动配电网中有较大的应用潜力。因此如何将配电网中的集中式优化任务融入区块链系统的分布式计算模块是亟待解决的问题。以配电网动态经济调度优化的分布式建模为例,借助二阶锥规划（second-order cone programming,SOCP）凸松弛理论,参考了IEC 61970标准中CIM的建模思想,将传统的配电网耦合模型转换为一种分散式的电气模型;并提出一种运行于区块链上的基于交替方向乘子法（alternating direction method of multipliers,ADMM）的分布式最优潮流求解方法,从而使传统集中式优化在未来主动配电网中所面临的诸多难题得以解决。该方法无需对配电网进行全局协调或分层分区,仅利用区块链相邻节点间少量的通信即可通过并行计算得出模型的全局最优解。     

An object-oriented simulation meta-model to analyse supply chain performance

This paper proposes a meta-model, which allows automatic building of simulation models of supply chains. The proposed meta-model is made up from a user interface (to define the characteristics of the supply chain), an ad hoc objects library and a software application, to build the simulation model. The meta-model can dramatically reduce to a few minutes or even seconds the time required to test a specific configuration of a supply chain and/or a specific management policy and, since the simulation model is automatically built, neither the personnel skills nor the time available to build the simulation model represent significant hurdles anymore. The meta-model has been applied to represent a simplified supply chain according to six different scenarios, where demand is deterministic. For each scenario a simulation campaign has been performed and the outputs of the model (built through the proposed meta-model) correspond to the predicted results.     

Optimal inventory control with sequential online auction in agriculture supply chain: an agent-based simulation optimisation approach

With the development of e-commerce, in agriculture supply chain, online auction is adopted as an inventory clearing tool. Comparing to mathematical models studying inventory control over online sequential auctions, our agent-based simulation model could systematically describe the complexities of bidders’ information interactions and behaviour preferences caused from financial and production perspectives, and by other supply chain members. In addition, we take into account the complex and dynamic market environment, which will impact the operation effect of auction policies. With identical auction items, the profit-maximising firm must decide auction lot-size, which is the number of units in each auction, minimum initial bid, and the time interval between auctions. To obtain the optimal solution, nested partitions framework and optimal expected opportunity cost algorithm are integrated to improve computation accuracy and efficiency. A case study based on real data is conducted to implement and validate the proposed approach. Furthermore, based on the model, the paper studies the sensitivities of the decision variables under different supply and demand scenarios.     

Impact evaluation of supply chain initiatives: a system simulation methodology

To maintain enterprise competitiveness, enterprises require appropriate initiatives to efficiently manage the product, information and cash flows among different supply chain (SC) partners. Co-operation, postponement, vendor managed inventory, transhipment, logistic consolidation etc., are some of the typical initiatives for performance improvement in SC. In an industrial scenario, two or more of these SC initiatives are undertaken simultaneously for superior enterprise performance on multiple performance dimensions. These factors render the analytical SC models inapt and simulation modelling becomes a suitable methodology to study SC performance that can accommodate the complexities present. The impact studies of these initiatives are difficult because these require exploitation of flexible and dynamic modelling elements which are analytically complex and mathematically intractable. We address these issues in the present research by developing a simulation platform to undertake studies with an industrial SC scenario. The challenges to explore SC performance under multiple initiatives are the major motivations for the present research. The novelty of this research lies in the development of a multi-product, multi-echelon SC simulation platform for realistic and industrial SC scenario encompassing the capability to accommodate multiple SC initiatives simultaneously. It is based on the building block approach using Arena®. We undertake SC performance studies under the application of several important SC initiatives. The results are encouraging and they underline interesting research areas to explore further.     

Agent-based simulation and analysis of demand-driven production strategies in the timber industry

This paper addresses the generic problem of production planning in a divergent timber production environment. It aims at analysing the performance of various demand-driven production strategies of a timber production system. This analysis is performed using a simulation platform built on an agent-based advanced planning system. Nine production strategies configurations are evaluated under six scenarios in order to carry out a complete mixed level design of 54 simulation runs. Each of these configurations is a combination of a decoupling point position and a level of capacity that is committed to contracts with customers. Accordingly, the six scenarios are designed as a combination of supply type (i.e. log diameter distribution) and timber market prices. Production processes and co-production yields are based on a real manufacturing system from eastern Canada. Performance is evaluated from the logistic and economic points of view. Results demonstrate that demand-driven planning approaches that propagate demand information upstream the supply chain have the potential to improve planned customer service and reduce planned inventories. Results also show that timber companies need to receive a premium from their customers in order to compensate from the loss of potential value resulting from a more constrained planning environment.     

Anarchic manufacturing

This paper introduces anarchic manufacturing, an extremely distributed planning and control philosophy, as the methodology for planning and controlling future smart factories. Anarchic manufacturing delegates decision-making authority and autonomy to the lowest level of entities in system elements with no centralised control or oversight. It is often postulated that traditional hierarchical structures may not be well suited to manage the state-of-the-art hyper-connected smart factories due to their reliance on communication between management layers. Distributed systems, on the other hand, are commonly perceived to be inherently more flexible, robust and adaptable than hierarchical systems due to their structure. This paper characterises distributed systems by evaluating the relative flexibility of a representative hierarchical system against an anarchic system in a job shop scenario. Multi-agent-based simulation is used to model both hierarchical and anarchic systems, which are tested for flexibility following the Taguchi method and compared against Taillard's benchmark job shop problems for overall performance. The results show that the anarchic system performs as well as the hierarchical system when subjected to unforeseen disruption, refuting the argument that hierarchical systems are too rigid and distributed systems are inherently more flexible. However, anarchic manufacturing systems, which show adaptability and self-optimising traits, provide a platform to potentially enable the emerging digital manufacturing paradigm through the free market structure especially when bandwidth for communications is limited.     

Analysis of the bullwhip effect in multi-product,multi-stage supply chain systems–a simulation approach

This research aims to develop a simulation approach based on system dynamics modelling (SDM) and adaptive network based fuzzy inference system (ANFIS) for quantifying and reducing the bullwhip effect in a multi-product, multi-stage supply chain. The proposed model is comprised of three groups of variables influencing the bullwhip effect, namely the structure of a supply chain network, supply chain contributions (ordering process in regular situation or when a supplier has a promotion or shortage gaming) and supply chain performances (the number of defects and ordering lead time). As a result, a two layer simulation model is developed with three generic models. The flexibility of this proposed approach is its ability to model various types of ordering policies which are basic inventory policies, material requirement planning (MRP) system and just in time (JIT) approach. The supply chain of a beverage company was selected to validate and demonstrate the flexibility of the proposed model. The findings of the proposed simulation model are consistent with the results obtained from the case study. The error magnitude of the bullwhip effect level varied between 0 and 9% resulting in bullwhip effect reductions of up to 92%. Accordingly, the bullwhip effect levels are significantly decreased by using the proposed simulation model.     

Effects of information transparency and cooperation on supply chain performance: a simulation study

This research explores the effect of information transparency and cooperation among the front nodes of supply chains. Although published works in the supply chain (SC) domain underline the need for information transparency and cooperation for competitiveness of firms, the majority among these are conceptual or empirical. As such, the domain requires fresh effort towards analytical and simulation based research for validation. In the present work, simulation is used as the research methodology. The simulation platform is developed in ARENA®, which is based on simulation language SIMAN. It has the capability to model multi-product, multi-echelon supply chains. Cooperation is depicted in the form of demand pooling and accelerated delivery of consignments from cooperating SC nodes, when stock-out contingency occurs at a particular node. The modelling also explores the effects of full, partial and zero level of information transparency on the SC performance. The simulation results suggest that these initiatives improve SC service time performance. It is also observed that more advantages from cooperation and information transparency are obtainable when the SC is leaner. The studies also highlight that such SC initiative that motivates local optimisation at the nodes is counter-productive to SC wide performance.