Process modeling and analysis of manufacturing supply chain networks using object-oriented Petri nets

This paper presents a systematic methodology for modeling and analysis of manufacturing supply chain business processes. The proposed approach first employs Computer Integrated Manufacturing Open System Architecture (CIMOSA) behavior rules to model the business process routing structures of manufacturing supply chain networks. Object-oriented predicate/transition nets (OPTNs) are then developed for the modular modeling and analysis of process models. Based on the structure of OPTNs, a procedure to obtain the system's P-invariants through objects’ P-invariants is suggested. From the P-invariants obtained, system structural properties such as deadlock and overflow can be analyzed. By using Petri net unfolding techniques and by extracting the process model of each object from the entire process model, the sequencing analysis for operations in supply chain processes becomes possible. Several manufacturing supply chain examples are used to illustrate the effectiveness of the proposed method.     

基于Petri网的服装供应链仿真模型

为获得服装供应链运行决策的最佳方案,提高服装产品的快速响应能力,采用面向对象Petri网技术构建了基于节点响应时间的服装供应链动态仿真模型,并运用Flexsim软件,对一个五级服装供应链仿真模型进行了仿真计算。仿真结果发现,市场需求的不确定对该服装供应链运作效率有较大的影响;当需求量变小时,通过减少供应链生成节点的设备使用数量可以提高供应链运作效率;当需求量变大时,提高设备和人员的工作效率比增加设备数量更能提高供应链的运作效率;供应链节点企业间只有相互协作,才能使供应链运作效率达到最优,实现服装产品对市场需求的快速响应。该仿真模型为服装企业制定有效的产品生产计划,以及提高快速反应能力提供了定量的参考依据。     

Supervisory control based on minimal cuts and Petri net sub-controllers coordination

This paper addresses the synthesis of Petri net (PN) controller for the forbidden state transition problem with a new utilisation of the theory of regions. Moreover, as any method of control synthesis based on a reachability graph, the theory of regions suffers from the combinatorial explosion problem. The proposed work minimises the number of equations in the linear system of theory of regions and therefore one can reduce the computation time. In this paper, two different approaches are proposed to select minimal cuts in the reachability graph in order to synthesise a PN controller. Thanks to a switch from one cut to another, one can activate and deactivate the corresponding?PNcontroller. An application is implemented in a flexible manufacturing system to illustrate the present method. Finally, comparison with previous works with experimental results in obtaining a maximally permissive controller is presented.     

Risk assessment and management for supply chain networks: A case study

The aim of this study is to show how a timed Petri nets framework can be used to model and analyze a supply chain (SC) network which is subject to various risks. The method is illustrated by an industrial case study. We first investigate the disruption factors of the SC network by a failure mode, effects and criticality analysis (FMECA) technique. We then integrate the risk management procedures into design, planning, and performance evaluation process of supply chain networks through Petri net (PN) based simulation. The developed PN model provides an efficient environment for defining uncertainties in the system and evaluating the added value of the risk mitigation actions. The findings of the case study shows that the system performance can be improved using risk management actions and the overall system costs can be reduced by mitigation scenarios.     

SCOlog: A logic-based approach to analysing supply chain operation dynamics

In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.     

Developing a supply chain disruption analysis model: Application of colored Petri-nets

As a result of globalization in the past two decades, supply chains are encountering more unknown conditions and risks. One important category of risks is disruptions that block material flowing through a supply chain and that may even result in end-product manufacturing failure. This paper uses a Petri nets-based model as a tool to understand the dissemination of disruptions and to trace the operational performance of a supply chain. The presented approach models how changes propagate through a supply chain and calculates the impact of disruptions on supply chain attributes by concluding the states that are obtainable from a given initial status in the supply chain.     

一种扩展了价格信息的Petri网

提出一种扩展了价格信息的Petri网——价格Petri网，讨论了相应的分析方法和应用前景。主要工作是：为Petri网的变迁引入价格参数，并用价格变迁系统给出价格Petri网的语义；对价格Petri网进行了可达性分析并讨论了最小成本可达问题的可判定性；最后用价格Petri网建立一个业务流程的成本模型。结论是：为Petri网扩展价     

Suboptimal supervisory control of Petri nets in presence of uncontrollable transitions via monitor places

This paper deals with the problem of enforcing generalized mutual exclusion constraints (GMEC) on place/transition nets with uncontrollable transitions. An efficient control synthesis technique, which has been proposed in the literature, enforces GMEC constraints by introducing monitor places to create suitable place invariants. The method has been shown to be maximally permissive and to give a unique control structure in the case that the set of legal markings is controllable. This paper investigates on and formally shows that the class of controllers obtained by this technique may not have a supremal element for uncontrollable specifications. Moreover, it is shown that the family of monitor places enforcing an uncontrollable specification can be parameterized with respect to the solution of a linear system of equation. An algorithm to obtain such parameterization is presented here.     

A two phase optimization method for Petri net models of manufacturing systems

Optimization is a key issue in the design of large manufacturing systems. An adequate modeling formalism to express the intricate interleaving of competition and cooperation relationships is needed first. Moreover, robust and efficient optimization techniques are necessary. This paper presents an integrated tool for the automated optimization of DEDS, with application to manufacturing systems. After a very quick overview of optimization problems in manufacturing systems, it presents the integration of two existing tools for the modeling and evaluation with Petri nets and a general-purpose optimization package based on simulated annealing. The consideration of a cache and a two phase technique for optimization allows to speed-up the optimization by a factor of about 35. During the first preoptimization phase, a rough approximation of the optimal parameter set is computed based on performance bounds. Two application examples show the benefits of the proposed technique.     

Measuring supply chain resilience using a deterministic modeling approach

To achieve a competitive edge in an uncertain business environment where change is imperative, one of the significant challenges for an organization is to mitigate risk by creating resilient supply chains. This research proposes a model using graph theory which holistically considers all the major enablers of resilience and their interrelationships for analysis using an Interpretive Structural Modeling approach. The uniqueness of this model lies in its ability to quantify resilience by a single numerical index. The quantification of resilience will help organizations assess the effectiveness of various risk mitigation strategies. This will provide tools for managers to compare different supply chains while offering a deeper knowledge of how supply chain characteristics increase or decrease resilience and consequently affect supply chain risk exposure. Thus, the research supports organizations in measuring and analyzing supply chain resilience and facilitates supply chain decision-making. The proposed method could simplify the dynamic nature of environment for managing disruptions in a supply chain. This novel approach for determining the supply chain resilience index (SCRI) advocates the consideration of resilience aspects in supply chain design, thus giving a competitive advantage to achieve market share even during a disruption.     

Synthesis a Petri net based control model for a FMS cell

Petri nets have been recognised as a high level formal and graphical specification language for modelling, analysis, and control of concurrent asynchronous distributed systems. This paper presents a PN model, synthesised by an extended version of the knitting synthesis technique. This method, as an incremental design approach, establishes the conditions under which the fundamental behavioural properties of the synthesised systems are fulfilled and preserved. That is, the synthesised models are live, bounded, and reversible (cyclic). A Petri net with the aforementioned properties is called a well-behaved Petri net system which is guaranteed to operate in a deadlock-free, stable, and cyclic fashion. Well-behaved Petri net models, synthesised using the proposed method can be compiled into control codes and implemented as real-time controllers for flexible manufacturing systems. The significance of this paper is due to the application of an extended version of knitting synthesis technique to a real life example of a flexible manufacturing system.     

Detecting Data-flow Errors Based on Petri Nets With Data Operations

In order to guarantee the correctness of business processes, not only control-flow errors but also data-flow errors should be considered. The control-flow errors mainly focus on deadlock, livelock, soundness, and so on. However, there are not too many methods for detecting data-flow errors. This paper defines Petri nets with data operations (PN-DO) that can model the operations on data such as read, write and delete. Based on PN-DO, we define some data-flow errors in this paper. We construct a reachability graph with data operations for each PN-DO, and then propose a method to reduce the reachability graph. Based on the reduced reachability graph, data-flow errors can be detected rapidly. A case study is given to illustrate the effectiveness of our methods.      

Dynamic modeling and control of supply chain systems: A review

Supply chains are complicated dynamical systems triggered by customer demands. Proper selection of equipment, machinery, buildings and transportation fleets is a key component for the success of such systems. However, efficiency of supply chains mostly depends on management decisions, which are often based on intuition and experience. Due to the increasing complexity of supply chain systems (which is the result of changes in customer preferences, the globalization of the economy and the stringy competition among companies), these decisions are often far from optimum. Another factor that causes difficulties in decision making is that different stages in supply chains are often supervised by different groups of people with different managing philosophies. From the early 1950s it became evident that a rigorous framework for analyzing the dynamics of supply chains and taking proper decisions could improve substantially the performance of the systems. Due to the resemblance of supply chains to engineering dynamical systems, control theory has provided a solid background for building such a framework. During the last half century many mathematical tools emerging from the control literature have been applied to the supply chain management problem. These tools vary from classical transfer function analysis to highly sophisticated control methodologies, such as model predictive control (MPC) and neuro-dynamic programming. The aim of this paper is to provide a review of this effort. The reader will find representative references of many alternative control philosophies and identify the advantages, weaknesses and complexities of each one. The bottom line of this review is that a joint co-operation between control experts and supply chain managers has the potential to introduce more realism to the dynamical models and develop improved supply chain management policies.     

A Petri net model for integrated process and job shop production planning

In this paper a new Petri net class (Chameleon systems) for modeling and analyzing joined process planning and job shop production planning is proposed based on the multi-level Petri net model introduced by Valk (1995). Chameleon system is a High-level Petri net extended with time that consists of a High-level Petri net modeling the workshop which is called system net and ordinary Petri net modeling the jobs and setups which act as tokens of the system net and therefore are called token nets. Process plans of the jobs are partial orders of operation groups and alternatives. The uncertainty of operation duration is captured by a new time model. The advantages of this new modeling approach are the following: (i) a modular construction of the joined process and job shop planning is allowed, (ii) classical known Petri net analysis methods can be applied and (iii) the analysis can be done at different levels of abstraction.     

Petri网上的禁止状态监控器综合

给出了Petri网上广义互斥约束的最大允许监控器综合方法,其中该监控问题满足两个条件：正权值禁止库所的影响子网是状态机;负权值禁止库所的输入和输出变迁均只有一个输入库所.首先得到了监控器存在的充分和必要条件;其次构造了约束等价转换的方法,该方法可将存在不可控变迁的监控问题简化为相当于变迁全部可控的监控问题.最后通过一个例子说明了该方法的可行性.     

Integrated design of optimal supervisors for the enforcement of static and behavioral specifications in Petri net models

Petri net (PN) supervisory control is often performed through a sequential procedure that introduces additional constraint layers over an initial unconstrained PN model, using generalized mutual exclusion constraints (GMECs) implemented as monitor places. This is typical, e.g., in the context of flexible manufacturing systems, where the initial model represents the production sequences and the constraints are used to express static specifications, such as job limitations or the usage of resources, and behavioral ones, as liveness, controllability, etc. This sequential procedure may yield a redundant model, that is not easily reduced a posteriori. Also, it is difficult to ensure maximal permissivity with respect to multiple behavioral specifications. This paper, building on recent results regarding optimal supervisor design with branch & bound methods, proposes an integrated modeling approach that can be used to derive a minimal supervisor guaranteeing the attainment of an arbitrary set of static and behavioral specifications in a maximally permissive way. Among behavioral specifications, deadlock-freeness, liveness, reversibility and behavioral controllability are considered in the paper. The supervisor comes in the form of a simple set of GMECs or of a disjunction of sets of GMECs. Some examples emphasize the potential model size reductions that can be achieved.     

Robust control reconfiguration of resource allocation systems with Petri nets and integer programming

Supervisory control reconfiguration can handle the uncertainties including resource failures and task changes in discrete event systems. It was not addressed to exploit the robustness of closed-loop systems to accommodate some uncertainties in the prior studies. Such exploitation can cost-efficiently achieve reconfigurability and flexibility for real systems. This paper presents a robust reconfiguration method based on Petri nets (PNs) and integer programming for supervisory control of resource allocation systems (RASs) subject to varying resource allocation relationships. An allocation relationship is seen as a control specification while the execution processes requiring resources as an uncontrolled plant. First, a robust reconfiguration mechanism is proposed. It includes updating the P$P$-invariant-based supervisor and evolving the state of the closed-loop system. The latter adapts to the control specification changes by the self-regulation of the closed-loop system’s state. Next, two novel integer programming models for control reconfiguration are proposed, called a reconfiguration model with acceptability and reconfiguration one with specification correction. Since both models integrate the firability condition of transitions, no additional efforts are required for the state reachability analysis. Finally, a hospital emergency service system is used as an example to illustrate them.     

用直觉模糊Petri网构建的供应链可靠性诊断模型

针对不断变化的供应链系统内外部环境因素,围绕供应链系统可靠性诊断问题,将直觉模糊集引入模糊Petri网建模,用直觉模糊数表示库所状态、变迁阈值和变迁输出置信度,构建了基于直觉模糊Petri网的供应链可靠性诊断模型。对直觉模糊产生式规则按照变迁激发前后变迁和库所之间的与或关系,将供应链可靠性诊断模型模糊推理规则划分为四种类型,得到了变迁触发前和触发后的与或直觉模糊推理规则。同时提出了相应的模糊推理算法,并通过实例验证了模型和算法的有效性,能够及时发现供应链系统故障。     

基于自控网系统的混杂控制

混杂控制系统通常是复杂的非线性控制系统,难以用统一的模型进行建模. David和Alla提出的混杂Petri网,虽然可以解决一般混杂系统的建模问题,并得到了广泛的应用,但对于传统的如PID这类控制器,缺乏统一建模的能力.探讨了基于广义自控网系统的混杂控制方法,实现了对混杂控制器中监控器和数字控制器进行统一的Petri网建模.仿真实例设计了基于广义同步自控网系统的电加热炉控制系统,给出了可根据不同温度状态实施多种控制策略的变结构数字控制器模型,并详细分析了控制器的性能,证明了广义自控网系统具有十分强大的建模能力和广泛的应用前景.