Nested coloured timed Petri nets for production configuration of product families

Production configuration is as an effective technique to deal with product variety while maintaining production stability and efficiency. It involves a diverse set of process elements (e.g., machines, operations), a high variety of component parts and assemblies and many constraints arising from product and process variety. Production configuration entails the selection and subsequent arrangement of process elements into complete production processes and the final evaluation of configured multiple alternatives. To better understand production configuration and its implementation, we study the underlying logic for configuring production processes using a dynamic modelling and visualisation approach. This is accomplished by developing a new formalism of nested coloured timed Petri nets (PNs). In view of the inherent modelling difficulties, in the formalism three types of nets–process nets, assembly nets and manufacturing nets–together with a nested net system are defined. Using an industrial example of vibration motors, we show how the proposed formalism can be applied to specify production processes at different levels of abstraction to achieve production configuration.     

Supply chain modelling and managing,using timed coloured Petri nets: a case study

This paper aims at developing a new methodology for designing and managing a supply chain (SC) and, at the same time, for evaluating the performance of every stakeholder involved in a production chain. The methodology proposed has been applied to a footwear supply chain and is based on coloured Petri nets (CPNs). The supply chain analysed in this paper is a complex production system consisting of a network of manufacturers and service suppliers related to logistics systems that provide transportation and storage. The model developed uses coloured, timed Petri nets to represent a supply chain and it is such that resources are the Petri Net (PN) places, the tokens are jobs, orders and/or products, while the colours represent job attributes. These colours are used to encode different data types and values that are attached to tokens. A “coloured token” represents a specific production order or a certain amount of a particular material supplied. Thus, it can be processed in different ways and it can be easily localised within the CPN model. The use of coloured Petri nets allows companies to create a compact representation of states, actions and events of the modelled system. The particular structure of this network allows the designers the easy realisation of a simulator using an “object-oriented”, dedicated programming, which is a useful tool for developing what-if analyses.     

Petri-net based applications for supply chain management: an overview

Supply networks are discrete event dynamic systems consisting of suppliers, manufacturers, distributors, and customers. It is a difficult and challenging task to model such a complex system. Recently, characterised as being capable of model parallelism and synchronisation, Petri nets (PNs) have attracted great attention for modelling and studying a supply network. Since each type of Petri net has its unique properties to model specific applications, this paper reviews and classifies Petri net applications for supply chain management (SCM). According to the decision problems facing SCM, we have the Petri net applications classified into three areas: competitive strategy, firm focused tactics, and operational efficiency. Categorising the Petri net applications will provide a guideline to industry practitioners and research academics to choose the appropriate Petri net for the problem. In addition, the paper attempts to offer future directions in applying the Petri net to SCM including: (1) modelling with uncertainty elements; (2) addressing the scalability issue of Petri nets; (3) integrating Petri nets with other tools; and (4) extending Petri nets to emerging applications.     

New flexibility drivers for manufacturing,supply chain and service operations

Increasing product proliferation, customisation, competition and customer expectations, as well as supply side disruptions, pose significant challenges to firm operations. Such challenges require improved efficiency and resilience in manufacturing, service and supply chain systems. New and innovative flexibility concepts and models offer a prospective route to such operational improvements. Several emerging issues in flexibility, such as risk and uncertainty management, environmental sustainability, optimal strategies under competition, optimal operations with strategic consumer behaviours are being examined in this regard. This overview provides a concise review of these critical research issues, and discusses related papers featured in this special issue. Four major flexibility drivers are classified: disruption risks, resilience and the ripple effect in the supply chain; digitalisation, smart operations and e-supply chains; sustainability and closed-loop supply chains; and supplier integration and behavioural flexibility.     

Structure dynamics control approach to supply chain planning and adaptation

Many of the existing methods and models of supply chain planning and control consider only one supply chain structure and assume it's more or less static in nature. In practice, supply chains have a multi-structural semantics and those multiple interrelated structures (organisational, functional, informational, financial, topological, technological, product, and energy structures) are dynamic and subject to many planned and disturbance-based changes. These changes are tackled by control activities which make planning an adaptive process. Although the supply chain optimal planning domain for static structures has been extensively investigated, the domain of planning and control of supply chains with structure dynamics merits more systematic and critical attention. In this study, an original form of supply chain representation as a dynamic system with changing multi-structural characteristics is developed. The structure dynamics control is a dynamic interpretation of the supply chain (re)synthesis process and aims at both advancing the supply chain (re)planning domain and enlarging the scope of the supply chain analysis domain that is currently rather limited. The developed approach is based on an optimal program control theory, active modelling objects, and structural–mathematical concept blended with mathematical programming. In this paper, we describe its basic features and exemplify possible applications and extensions regarding real planning and control problems faced by international supply chains in recent years.     

Distributed supply chain network modelling and simulation: integration of agent-based distributed simulation and improved SCOR model

Agent-based distributed simulation is an efficient methodology for modelling and analysing such complex adaptive systems as dynamic supply chain networks. However, it lacks an acceptable generic standard. Supply chain operations reference (SCOR) model is a cross-functional framework widely accepted as an industry standard. It provides the standard processes, performance metrics, best practices and associated software functionalities for modelling, evaluating and improving supply chain networks. However, it is a static tool. Integration of agent-based distributed simulation and SCOR model can exploit their advantages to form a generic methodology for modelling and simulation of a wide range of supply chain networks. Therefore, this paper proposes a methodology for distributed supply chain network modelling and simulation by means of integration of agent-based distributed simulation and an improved SCOR model. The methodology contains two components: a hierarchical framework for modelling supply chain network based on the improved SCOR model and agent building blocks integrating the standard processes from the SCOR model. The hierarchical framework provides an approach for structure modelling in any level with different granularities based on the improved SCOR model, and allows rapidly mapping a supply chain network into the structure model of a multi-agent system; while agent building blocks are quite useful and convenient to fill the structure model to fulfil its function modelling. With the approach of structure modelling and function filling, not only can the process of agent-based supply chain network modelling be accelerated, but also the built models can be reused and expanded. Because the hierarchical framework is based on the conceptual framework of SCOR model and agent building blocks integrate the standard processes from SCOR model, the proposed methodology is more generic. In addition, the issues of sub-model synchronisation and data distribution management in the agent-based distributed simulation implementation are taken into consideration and the corresponding solutions for these issues are proposed. Finally, an example of a supply chain network is modelled and implemented to illustrate the proposed methodology and related solutions.     

精益与敏捷集成的供应链

市场竞争迫使制造企业运用精益思想降低成本,但顾客需求越来越个性化,要求快速响应．需要企业具备敏捷性。本文通过简单模型和案例,分析精益与敏捷相集成的优势和运作模式。从产品需求模式看,精益供应链与标准化产品、功能性产品匹配,敏捷供应链与定制化产品、创新性产品相匹配。从产品模块化设计以及全球供应考虑,精益与敏捷集成的供应链是最有效的选择。     

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.     

Supply chain focus dependent sensitivity of the point of product differentiation

Customer preferences for variety in the product(s) with improved customer service and lower prices are forcing the supply chains to overhaul the current practices from design to operational level. Postponement or delayed differentiation of the products is one such strategy, primarily deployed in mass customisation settings. Life cycles are shrinking not only for individual products but for product families as well. In this context, supply chain responsiveness becomes one of the crucial factors that need to be effectively managed to succeed in the present day competitive markets. Our model, that considers inventory costs and the supply chain responsiveness costs would aid a supply chain manager to make informed decisions with regard to the ideal location for the point of differentiation (POD), while striking the right balance between holding costs and the supply chain responsiveness costs. We also make use of a dimensionless parameter called the ‘coefficient of inverse responsiveness’ that not only facilitates the introduction of responsiveness related costs into the model but also improves the scalability and simplifies the analysis and interpretation of the results. Based on the strategic model developed, we offer some context-specific counter-intuitive managerial insights with respect to the sensitivity of the location of the POD in a supply chain.     

Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain

With large volume of product flows and complex supply chain processes, more data than ever before is being generated and collected in supply chains through various tracking and sensory technologies. The purpose of this study is to show a potential scenario of using a prototype tracking tool that facilitate the utilisation of sensor data, which is often unstructured and enormous in nature, to support supply chain decisions. The research investigates the potential benefits of the chilled food chain management innovation through sensor data driven pricing decisions. Data generated and recorded through the sensor network are used to predict the remaining shelf-life of perishable foods. Numerical analysis is conducted to examine the benefit of proposed approach under various operational situations and product features. The research findings demonstrate a way of modelling pricing and potential of performance improvement in chilled food chains to provide a vision of smooth transfer and implementation of the sensor data driven supply chain management. The research finding would encourage firms in the food industry to explore innovation opportunities from big data and develop proper data driven strategies to improve their competitiveness.     

An optimisation model for purchase,production and distribution in fish supply chain – a case study

This paper presents an optimisation model for spawn purchase, fish culturing production process and harvested fish distribution in a fish supply chain. Due to the complexity and variety of real-world fish supply chains, the model is built based on a case study for a real trout fish farm to illustrate the methodology on how to incorporate influential factors from both warm chain and cold chain. Warm chain mainly considers the biological factors while fish is alive and cold chain mainly considers the economic factors after fish is ready for harvest, harvested, and processed. The model seeks to improve the trout farm production planning to help decision-making on spawn purchase quantity, the best time to harvest fish, and the farming periods. In addition, the model adopts a customer classification method in distribution planning that is able to prioritise the delivery of fresh fish to the most profitable customers. A mixed integer linear programming (MILP) model was developed to maximise the total profit. The experimental results demonstrate that farmers’ total profit can be increased after applying the proposed optimisation strategy, compared to the traditional farming strategy.     

An analysis of the general benefits of a centralised VMI system based on the EOQ model

Within a vendor-managed inventory (VMI) agreement, the upstream supply chain member (the vendor) takes responsibility for managing the inventory of the downstream member (the customer) within specific levels previously agreed upon without the need of orders from the customer side to be placed. Therefore, the vendor can focus on optimising production efficiency and capacity planning, while the customer has to improve forecast accuracy. This paper analyses the benefits a VMI agreement could bring for a one-supplier, multiple-customer case through analysing two cases: a supply chain managed in a traditional manner and VMI when both the vendor and the customers belong to the same organisation. The analysis is based on the economic ordering quantity (EOQ) formula and its related total cost, and the novelty is captured by evaluating one vendor, multiple buyers, and multiple product situations. The modelling is done so as to capture the needs and factors which occur within the pharmaceutical industry and a numerical application will be executed with data from one of the main leaders within the pharmaceutical field.     

Manufacturing supply chain modelling and reengineering

The first-wave of reengineering, during the first half of the nineties, focused on making organizational changes and used primarilyinformation models of supply chains to integrate business processes.Quantitative models are expected to have a significant impact in the second-wave of reengineering through the deployment of performance and optimization models, economic analysis, and decision support systems. In this paper, we focus on the vital role that quantitative modelling techniques such as those founded in Operations Research and Industrial Engineering can play in reengineering supply chains. These quantitative models can extend the business process reengineering concepts to provide a concurrent reengineering framework for modelling the supply chain processes, identifying reengineering opportunities, evaluating design alternatives, guiding the selection of the best alternative, and deploying tools to implement the design. We illustrate such use by surveying current industrial practice and introducing real world examples based on our practical experience in solving supply chain and reengineering problems.     

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.     

Global sensitivity analysis and aggregation of risk in multi-product supply chain networks

Manufacturing firms manage complex supply chain networks which are exposed to a plethora of hazard events. An essential part of the risk management process is the calculation of the stand-alone risk exposures of the product-specific supply chains, but also of the entire multi-product system. In this paper, first, a global sensitivity analysis of the statistical supply chain risk model is conducted. This method helps the decision-makers to understand the risk of the model they are using. Second, a methodology for risk aggregation in multi-product supply chain networks is proposed. The real-world data is used to analyse and validate the model. Supply chain managers equipped with the proposed method will better cope with the risk in supply chains for different product configurations.     

Assembly/disassembly task planning and simulation using expert Petri nets

Automatic assembly/disassembly planning is recognized as an important tool for reducing the manufacturing costs in concurrent product and process development. This paper developed a knowledge-based expert Petri net model by incorporating expert system techniques in artificial intelligence into ordinary Petri nets for an analytical framework of understanding, representing and reasoning the assembly/disassembly tasks. Substantial extensions have been made to ordinary Petri nets by adding control places, time constraints, and place and transition knowledge annotations. The proposed expert Petri net model can be considered as the hybrid of expert systems and ordinary Petri nets. Through these extensions, the capacities of modelling and representation of ordinary Petri net models are largely enhanced, and thus the expert Petri net models are more powerful than ordinary Petri nets. Such intelligent Petri net models can combine the abilities of modelling, planning, and performance evaluation for assembly/disassembly tasks in an integrated and intuitive way, and can therefore be applied to either linear/non-linear, static/dynamic, or on-line/off-line assembly/disassembly tasks at both high and low levels. The developed assembly/disassembly planning system can generate the best strategies and plans for assembly/disassembly. The research findings are exemplified with a real assembly to show the effectiveness of the method.     

Comprehensive framework for the development of a supply chain strategy

Current competition among companies is fought through their supply chains. As the performance of the supply chain depends not only on manufacturing and marketing attributes, it becomes necessary to establish a framework upon which to develop a supply chain strategy. The paper presents the rationale and principles of a customer–product–process–resource (CPPR) framework for the simultaneous analysis of the business, supplier, manufacturing, planning, marketing and customer dimensions of a supply chain strategy. The originality of the CPPR framework is that it establishes a set of supply chain structural elements, that when put together determine the degree of alignment of a supply chain strategy. As the main objective of a supply chain strategy is to achieve customer satisfaction as an output of the supply chain operations, the CPPR framework becomes a realignment tool when used in combination with a realignment methodology, which is also presented in the paper.     

电子商务环境下我国农产品供应链体系的结构优化

首先回顾了我国农产品供应链体系的现状，其中包括现货市场供应链子体系、远期市场供应链子体系与期货市场供应链子体系。其次分析了当前我国农产品流通的主体——现货市场供应链体系的结构特性及其负面影响，并结合现实将农产品电子商务对供应链的改善作用总结为非中介化、再中介化、信息中介、垂直门户以及价值网五种不同的实现方式，最后提出了农产品供应链利用价值网实现优化的远景目标。