Specification and performance analysis of embedded systems with coloured petri nets

To analyze synchronization, concurrency, communication protocols and system performance, a system level specification is modelled in a coloured Petri net. A toolbox collects information for the implementation, e.g., processing times, waiting times, idle times, data accesses, processing requests. This is illustrated with a data-link protocol system, where the disturbance on the communication channels is modelled, too.     

一种自适应模糊Petri网及其应用*

模糊Petri网(fuzzy Petri nets, FPN)是基于模糊产生式规则的知识库系统的有力建模工具,但其缺乏较强的自学习能力。在FPN的基础上引入神经网络技术,给出了一种自适应模糊Petri网(adapt fuzzy Petri nets, AFPN)模型。该模型将神经网络中的BP网络算法引入到FPN模型中,对FPN中的权值进行反复的学习训练,避免了依靠人工经验设置带来的不确定性。AFPN具有很强的推理能力和自适应能力,对知识库系统的建立、更新和维护有着重要的意义。     

基于对象的扩展Petri网协同设计过程分析

针对协同设计中任务的执行流程缺乏柔性,不利于分析实际设计过程的现状,提出一种单元调用变迁对与决策变迁相集成的基于对象的扩展Petri网,扩展了Petri网的可达图以适应分析OEPNs模型.采用OEPNs中的过程网和单元阿对协同设计过程楚模,利用模型中的单元调用变迁对和决策变迁对过程本身和可能状态进行分析.最后与相关的研究工作进行比较并给出了结论.     

Coloured Petri nets and graphical simulation for the validation of a robotic cell in aircraft industry

This paper proposes a mixed validation approach based on coloured Petri nets and 3D graphic simulation for the design of supervisory systems in manufacturing cells with multiple robots. The coloured Petri net is used to model the cell behaviour at a high level of abstraction. It models the activities of each cell component and its coordination by a supervisory system. The graphical simulation is used to analyse and validate the cell behaviour in a 3D environment, allowing the detection of collisions and the calculation of process times. The motivation for this work comes from the aeronautic industry. The automation of a fuselage assembly process requires the integration of robots with other cell components such as metrological or vision systems. In this cell, the robot trajectories are defined by the supervisory system and results from the coordination of the cell components. The paper presents the application of the approach for an aircraft assembly cell under integration in Brazil. This case study shows the feasibility of the approach and supports the discussion of its main advantages and limits.     

装配可靠性的模糊广义随机Petri网建模与分析

针对一般广义随机Petri网模型精度低的问题,将模糊数引入到广义随机Petri网,提出模糊广义随机Petri网的概念.结合模糊数包含信息多的优点,利用模糊广义随机Petri网对装配过程进行建模,通过同构的Markov链对模型进行定量分析.用模糊广义随机Petri网模型计算得到的装配可靠度与一般广义随机Petri网模型的装配可靠度进行分析比较,结果表明了模糊广义随机Petri网模型的精度更高.以数控磨床砂轮架为例,证明了上述方法的有效性.     

Robust manufacturing system design using multi objective genetic algorithms,Petri nets and Bayesian uncertainty representation

Decisions involving robust manufacturing system configuration design are often costly and involve long term allocation of resources. These decisions typically remain fixed for future planning horizons and failure to design a robust manufacturing system configuration can lead to high production and inventory costs, and lost sales costs. The designers need to find optimal design configurations by evaluating multiple decision variables (such as makespan and WIP) and considering different forms of manufacturing uncertainties (such as uncertainties in processing times and product demand). This paper presents a novel approach using multi objective genetic algorithms (GA), Petri nets and Bayesian model averaging (BMA) for robust design of manufacturing systems. The proposed approach is demonstrated on a manufacturing system configuration design problem to find optimal number of machines in different manufacturing cells for a manufacturing system producing multiple products. The objective function aims at minimizing makespan, mean WIP and number of machines, while considering uncertainties in processing times, equipment failure and repairs, and product demand. The integrated multi objective GA and Petri net based modeling framework coupled with Bayesian methods of uncertainty representation provides a single tool to design, analyze and simulate candidate models while considering distribution model and parameter uncertainties.     

模糊Petri网在压缩机故障诊断中的应用

为克服Petri网在推理分析复杂、不确定的故障信息中的不足,引入置信度最大及深度搜索优先的诊断方法,将Petri网和模糊推理知识相结合,提出模糊Petri网故障诊断方法及其概念与规则表示,采用反向推理算法根据已发生的故障来定位故障源,给出推理算法的具体步骤。通过逻辑推理和离心式压缩机故障的实例分析,验证了该算法的有效性和可行性,提高了故障诊断的准确性和高效性。     

Modeling temporal processes via belief networks and Petri nets,with application to expert systems

We show how Bayesian belief networks (BNs) can be used to model common temporal knowledge. Two approaches to their structuring are proposed. The first leads to BNs with nodes representing states of a process and times spent in such states, and with a graphical structure reflecting the conditional independence assumptions of a Markovian process. A second approach leads to BNs whose topology represents a conditional independence structure between event-times. Once required distributional specifications are stored within the nodes of a BN, this becomes a powerful inference machine capable, for example, of reasoning backwards in time. We discuss computational difficulties associated with propagation algorithms necessary to perform these inferences, and the reasons why we chose to adopt Monte Carlo-based propagation algorithms. Two improvements to existing Monte Carlo algorithms are proposed; an enhancement based on the principle of importance sampling, and a combined technique that exploits both forward and Markov sampling. Finally, we consider Petri nets, a very interesting and general representation of temporal knowledge. A combined approach is proposed, in which the user structures temporal knowledge in Petri net formalism. The obtained Petri net is then automatically translated into an equivalent BN for probability propagation. Inferred conclusions may finally be explained with the aid of Petri nets again.     

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.     

Modelling of cognitive activity during normal and abnormal situations using Object Petri Nets, application to a supervision system

This article presents a method for the modelling of cognitive activity using Object Petri Nets. The method includes the recognition of the various classes of situation (normal and abnormal) which human operators are likely to meet whilst performing their tasks. Each of these classes is described according to the characteristics of the state of the system. We will present the various mental representations used during the control/command activity according to the main aims set by the operator. The examples given come from a project dealing with the integration of a a supervision system in a railway traffic regulation room.     

Suboptimal liveness-enforcing supervisor design for a class of generalised Petri nets using partial siphon enumeration and mathematical programming

This article develops a deadlock prevention policy for a class of generalised Petri nets, which can well model a large class of flexible manufacturing systems. The analysis of such a system leads us to characterise the deadlock situations in terms of the insufficiently marked siphons in its generalised Petri-net model. The proposed policy is carried out in an iterative way. At each step a minimal siphon is derived from a maximal deadly marked siphon that is found by solving a mixed integer programming (MIP) problem. An algorithm is formalised that can efficiently compute such a minimal siphon from a maximal one. A monitor is added for a derived minimal siphon such that it is max-controlled if it is elementary with respect to the siphons that have been derived. The liveness of the controlled system is decided by the fact that no siphon can be derived due to the MIP solution. After a liveness-enforcing net supervisor computed without complete siphon enumeration, the output-arcs of the additional monitors are rearranged such that the monitors act while restricting the system less. Examples are presented to demonstrate the proposed method.     

Software ergonomics: effects of computer application design parameters on operator task performance and health

Abstract

Evidence is reviewed that the operating characteristics of computer application systems, in addition to physical characteristics of display units (CRTs), are the cause of many observed effects on operator health and task effectiveness. These effects are hypothesized to occur through changes in task structure, and the man-machine redivision of labour that results when computer application systems are introduced into work setting. First, the association between task dimensions and models of operator performance effectiveness and well-being are reviewed. Second, application system design parameters that affect task structure are identified. Then, empirical evidence supporting this three-part causal linkage—application system parameters to task characteristics to operator effectiveness and health—is presented. The findings suggest that by improving dialogue quality, taking advantage of two-way communication to reduce uncertainty, using smaller and less integrated systems and matching system performance to operator needs a job can be created that is likely to improve both operator well-being and effectiveness.     

Neurovision-based logic control of an experimental manufacturing plant using neural net le-net5 and automation Petri nets

In this paper, Petri nets and neural networks are used together in the development of an intelligent logic controller for an experimental manufacturing plant to provide the flexibility and intelligence required from this type of dynamic systems. In the experimental setup, among deformed and good parts to be processed, there are four different part types to be recognised and selected. To distinguish the correct part types, a convolutional neural net le-net5 based on-line image recognition system is established. Then, the necessary information to be used within the logic control system is produced by this on-line image recognition system. Using the information about the correct part types and Automation Petri nets, a logic control system is designed. To convert the resulting Automation Petri net model of the controller into the related ladder logic diagram (LLD), the token passing logic (TPL) method is used. Finally, the implementation of the control logic as an LDD for the real time control of the manufacturing system is accomplished by using a commercial programmable logic controller (PLC).     

Modelling of an interactive system with an agent-based architecture using Petri nets, application of the method to the supervision of a transport system

This article presents an original method using high level Petri nets for the specification and design of interactive systems. We suggest an agent oriented architecture based on the classic components of an interactive application (application, dialogue control, interface with the application). Our approach is validated via the specification and design of a human–machine interface used in the supervision of a land-based transport system (bus/tramway).     

Robust design of flexible manufacturing systems using, colored Petri net and genetic algorithm

A method is presented for the robust design of flexible manufacturing systems (FMS) that undergo the forecasted product plan variations. The resource allocation and the operation schedule of a FMS are modeled as a colored Petri net and an associated transition firing sequence. The robust design of the colored Petri net model is formulated as a multi-objective optimization problem that simultaneously minimizes the production costs under multiple production plans (batch sizes for all jobs), and the reconfiguration cost due to production plan changes. A genetic algorithm, coupled with the shortest imminent operation time (SIO) dispatching rule, is used to simultaneously find the near-optimal resource allocation and the event-driven schedule of a colored Petri net. The resulting Petri net is then compared with the Petri nets optimized for a particular production plan in order to address the effectiveness of the robustness optimization. The simulation results suggest that the proposed robustness optimization scheme should be considered when the products are moderately different in their job specifications so that optimizing for a particular production plan creates inevitably bottlenecks in product flow and/or deadlock under other production plans.     

Petri net modelling and design of task oriented messaging system for robot control

Manufacturing Message Specification (MMS) is an international standard for shop floor machine control. It defines a set of conceptual schema and an interactive software object known as Virtual Manufacturing Device (VMD). Many systems have been established using this protocol but very few formal methods have been used to build such systems. This paper addresses the problems of the design and analysis of a network-based task oriented messaging system for flexible robot task control using a Petri net. The information and message transfer processes of the MMS systems were analysed. The modelling methodology allows a top down approach by which the net model is decomposed into fine details with clear identification of components which can be realised directly from the model. This approach is illustrated in this paper by a Windows-based robot control prototype system implemented from the Petri net model. The prototype was built using Object Windows Library and the NetBIOS session layer protocol on a PC network.     

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.     

A new fuzzy operator and its application to topology design of distributed local area networks

Topology design of distributed local area networks can be classified as a hard combinatorial optimization problem. The problem has several conflicting objectives, such as cost, reliability, network delay, and number of hops between source and destination. These objectives can conveniently be expressed in linguistic terms - a key component of fuzzy logic. This paper presents an approach based on fuzzy logic that combines the conflicting objectives into a single optimization function. A new fuzzy operator, namely, the unified AND-OR (UAO) operator is also proposed, and a decision-making approach based on fuzzy rules and preference rules is introduced. The UAO operator is empirically compared with the well-known ordered weighted averaging (OWA) operator through application to an evolutionary algorithm. Results show that the UAO operator exhibits comparatively better performance than the OWA operator.     

A strategy for improving worker satisfaction and job attitudes in a repetitive industrial task: application of production standards and performance feedback

Worker satisfaction improved significantly as a consequence of the provision of the assigned and participative standards with performance feedback in a repetitive industrial production task. The maximum improvement in worker satisfaction was found for the participative standard and feedback condition. Only this condition had a significant positive effect on worker job attitudes. Monetary incentive, when provided with an assigned or participative standard with feedback, added no incremental worker satisfaction or job attitudes gain. The participative standard with feedback condition emerges as the optimum strategy for improving worker satisfaction and job attitudes in a repetitive industrial production task.