Collaborative reconfiguration mechanism for holonic manufacturing systems

Although holonic manufacturing systems (HMS) are recognized as a paradigm to cope with the changes in manufacturing environment based on a flexible architecture, development of reconfiguration mechanism is required to realize the advantages of HMS. Finding a solution from scratch to deal with changes in HMS is not an appropriate approach as it may lead to chaos at the shop floor. The objective of this paper is to propose a viable design methodology to achieve effective reconfiguration in HMS based on the cooperation of holons. We formulate and study a holarchy reconfiguration problem and define an impact function to characterize the impact of resource failures on different holons in a holarchy. A collaborative reconfiguration algorithm based on the impact function is proposed to effectively reconfigure the systems to achieve minimal cost solutions.     

A holonic approach to dynamic manufacturing scheduling

Manufacturing scheduling is a complex combinatorial problem, particularly in distributed and dynamic environments. This paper presents a holonic approach to manufacturing scheduling, where the scheduling functions are distributed by several entities, combining their calculation power and local optimization capability. In this scheduling and control approach, the objective is to achieve fast and dynamic re-scheduling using a scheduling mechanism that evolves dynamically to combine centralized and distributed strategies, improving its responsiveness to emergence, instead of the complex and optimized scheduling algorithms found in traditional approaches.     

Holarchy formation and optimization in holonic manufacturing systems with contract net

Holonic manufacturing systems (HMS) is based on the notion of holon, an autonomous, cooperative and intelligent entity to provide a econfigurable, flexible and decentralized manufacturing environment to respond to changing needs and opportunities. A set of holons that cooperate to achieve a goal forms a holarchy. How to design a mechanism to form a holarchy to achieve a goal while minimizing the overall cost is a challenge. The objectives of this paper are to propose models and develop collaborative algorithms to guide the holons to form a holarchy to coherently move toward the desired goal state ultimately. We adopt contract net protocol (CNP) to model mutual selection of holons in forming a holarchy. We formulate a holarchy optimization problem to minimize the cost subject to the feasibility constraints. To analyze the feasibility of a holarchy, a Petri net (PN) model is proposed. As classical PN models do not take into account the cost involved in firing transitions, we augment the PN model with cost functions in the problem formulation. Due to the distributed architecture of HMS, the internal structure of each potential holarchy that acts as bidder in CNP is not available to the manager. A key issue is to determine the feasibility of a holarchy without constructing the whole PN model of the given hierarchy. We study the feasible conditions for a holarchy and propose a collaborative algorithm to analyze the feasibility and award contracts to holons without constructing the whole model of a holarchy.     

Model and control holonic manufacturing systems based on fusion of contract nets and Petri nets

Holonic manufacturing systems (HMS) can be modeled as multi-agent systems to which contract net protocol can be effectively and robustly applied. However, the lack of analysis capability of contract nets makes it difficult to avoid undesirable states such as deadlocks in HMS. This paper presents a framework to model and control HMS based on fusion of Petri net and multi-agent system theory. The main results include: (1) a multi-agent model and a collaboration process to form commitment graphs in HMS based on contract net protocol, (2) a procedure to convert commitment graph to collaborative Petri net (CPN), and (3) feasible conditions and collaborative algorithms to award contracts in HMS based on CPNs.     

Collaborative composition of processes in holonic manufacturing systems

Although it provides a flexible architecture to deal with changes and uncertainties, holonic manufacturing systems (HMS) also pose challenges in design and implementation. A challenge is to design a problem solving environment to guide the holons in HMS such that the decisions made by the individual holons as a whole collaboratively compose the production processes for the tasks. The objective of this paper is to propose a problem solving environment for the composition of minimal cost processes in HMS. Given a specific product type and due date, the problem is to dynamically compose a complete process in HMS to process the product by the due date. To achieve the objective, we combine multi-agent systems technology with Petri nets in this paper. We first propose architecture and a two-layer contract net protocol to describe the negotiation between order holons, product holons and resource holons in HMS. To determine whether it is feasible for a set product holons and resource holons to compose a process for an order holon, we propose Petri net models to capture the workflows and activities in product holons and resource holons, respectively. To optimize the cost in the composed manufacturing process, the concept of activity-based costing is adopted to assign the cost of the activities to Petri nets. The advantages of our design methodology include specification of workflows and resource activities with PNML to minimize the cost. To realize the two-layer contract net protocol relies on a mechanism for a holon to discover the services provided by other holons. We proposed a scheme for publication and discovery of holon services based on FIPA compliant multi-agent system platform. Based on the service publication and discovery scheme, interactions between holons with the two-layer contract net protocol can be realized. We develop a HMS system to solve the process composition problem.     

Petri net based process scheduling: A model of the control system of flexible manufacturing systems

In this paper, we propose a class of algorithms for the sub-optimal solution of a particular class of problems of process scheduling, particularly focusing on a case study in the area of flexible manufacturing systems (FMSs). The general class of problems we face in our approach is characterized as follows: there is a set of concurrent processes, each formed by a number of temporally related tasks (segments). Tasks are executable by alternate resource sets, different both in performance and costs. Processes and tasks are characterized by release times, due dates, and deadlines. Time constraints are also present in the availability of each resource in resource sets. It has been proven that such a problem does not admit an algorithm for an optimal solution in polynomial time. Our proposed algorithm finds a sub-optimal schedule according to a set of optimization criteria, based on task and process times (earliness, tardiness), and/or time independent costs of resources. Our approach to process scheduling is based on Timed Coloured Petri Nets. We describe the structure of the coordination and scheduling algorithms, concentrating on (i) the general-purpose component, and (ii) the application-dependent component. In particular, the paper focuses on the following issues: (i) theautomatic synthesis of Petri net models of the coordination subsystem, starting from the problem knowledge base; (ii) the dynamic behavior of the coordination subsystem, whose kernel is a High Level Petri net executor, a coordination process based on an original, general purpose algorithm; (iii) the structure of the real-time scheduling subsystem, based on particular heuristic sub-optimal multi-criteria algorithms. Furthermore, the paper defines the interaction mechanisms between the coordination and scheduling subsystems. Our approach clearly distinguishes the mechanism of the net execution from the decision support system. Two conceptually distinct levels, which correspond to two different, interacting implementation modules in the prototype CASE tool, have been defined: theexecutor and thescheduler levels. One of the outstanding differences between these levels is that the executor is conceived as a fast, efficient coordination process, without special-purpose problem-solving capabilities in case of conflicts. The scheduler, on the other hand, is the adaptive, distributed component, whose behavior may heavily depend on the problem class. If the scheduler fails, the executor is, in any case, able to proceed with a general-purpose conflict resolution strategy. Experimental results on the real-time performance of the kernel of the implemented system are finally shown in the paper. The approach described in this paper is at the basis of a joint project with industrial partners for the development of a CASE tool for the simulation of blast furnaces.     

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.     

A three-level knowledge-based system for the generation of live and safe Petri nets for manufacturing systems

New generation manufacturing systems are involved in a transformation process which aims for more reliable production processes and with a lower response time to the demand of the market. This work presents an application of artificial intelligence planning techniques for the automatic generation of the control program for a manufacturing system expressed as a safe and live Petri net. The advantage of the system presented here is straightforward: it allows for a fast generation of sound results free of human errors, reducing the cost and duration of the development phase of control programs.     

Process vs resource‐oriented Petri net modeling of automated manufacturing systems

Since the 1980s, Petri nets (PN) have been widely used to model automated manufacturing systems (AMS) for analysis, performance evaluation, simulation, and control. They are mostly based on process‐oriented modeling methods and thus termed as process‐oriented PN (POPN) in this paper. The recent study of deadlock avoidance problems in AMS led to another type of PN called resource‐oriented PN (ROPN). This paper, for the first time, compares these two modeling methods and resultant models in terms of modeling power, model complexity for analysis and control, and some critical properties. POPN models the part production processes straightforwardly, while ROPN is more compact and effective for deadlock resolution. The relations between these two models are investigated. Several examples are used to illustrate them. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Discrete event diagnosis using labeled Petri nets. An application to manufacturing systems

In this paper an approach to on-line diagnosis of discrete event systems based on labeled Petri nets is presented. The approach is based on the notion of basis markings and justifications and it can be applied both to bounded and unbounded Petri nets whose unobservable subnet is acyclic. Moreover it is shown that, in the case of bounded Petri nets, the most burdensome part of the procedure may be moved off-line, computing a particular graph called Basis Reachability Graph.Finally, the effectiveness of the proposed procedure is analyzed applying a MATLAB diagnosis toolbox we developed to a manufacturing example taken from the literature.     

基于自学习模糊Petri网的知识化制造系统采购预测

对模糊Petri网进行改进,使其增加自学习能力,即自学习模糊Petri网(SFPN).提出了自学习模糊Petri网模型知识库的建立方法,通过构造SFPN模型知识库,建立并保存现有产品的SFPN模型,开发新产品或进行新的决策时调出并进行修正后作为新产品模型.通过较短时间和少量样本的自学习训练,便可用于新产品的预测或决策.最后通过采购预测实例验证了该方法的有效性.     

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.     

信标基底的可选择性在制造系统死锁控制中的应用

本文基于Petri网模型,讨论柔性制造系统的死锁控制问题.为了建立结构简单的Petri网控制器,本文在以前的工作中提出了信标基底的概念.信标基底是一组满足特定条件的严格极小信标集合.本文证明基于不同的信标基底,建立的受控系统其容许性能也不同.而容许性是评价死锁控制策略优劣的重要标准之一.故如何选择信标基底,提高受控系统的容许性能是值得研究的问题.本文讨论了使受控系统容许性能大大提高的信标基底的选择条件.基于该条件,为柔性制造系统建立有效的死锁控制策略.最后,通过两个例子解释该条件和策略.     

Modeling and scheduling of ratio-driven FMS using unfolding time Petri nets

In this paper, we focus on the analysis of a cyclic schedule for the determination of the optimal cycle time and minimization of the Work in Process (WIP for short). Especially, this paper deals with product ratio-driven FMS cyclic scheduling problem with each other products and ratios using Timed Petri nets unfolding (TPN for short). TPN slicing and unfolding are applied to analyze this FMS model. We can divide original system into subsystem using TPN slices and change iterated cycle module into acyclic module without any loss of other behavior properties.     

资源配置混杂Petri网的混杂系统生产过程动态调度

为了增强混杂生产过程应对突发事件的能力,以一种新的混杂Petri网(资源配置混杂Petri网)为研究模型,给出了相应的使能和激发规则.并在资源配置混杂Petri网建立的仿真模型的基础上,融入事件逻辑网和逻辑规划,提出一种适用于混杂系统动态生产调度建模和优化的方法.以典型的混杂生产过程为例,研究混杂系统生产过程建模及优化.研究结果表明,资源配置混杂Petri网模型描述能力强,能够有效描述混杂系统生产过程,所提出的动态调度方案切实有效.     

Petri net based decision system modeling in real-time scheduling and control of flexible automotive manufacturing systems

This paper presents the design and the implementation of a Petri net (PN) model for the control of a flexible manufacturing system (FMS). A flexible automotive manufacturing system used in this environment enables quick cell configuration, and the efficient operation of cells. In this paper, we attempt to propose a flexible automotive manufacturing approach for modeling and analysis of shop floor scheduling problem of FMSs using high-level PNs. Since PNs have emerged as the principal performance modeling tools for FMS, this paper provides an object-oriented Petri nets (OOPNs) approach to performance modeling and to implement efficient production control. In this study, we modeled the system as a timed marked graph (TMG), a well-known subclass of PNs, and we showed that the problem of performance evaluation can be reduced to a simple linear programming (LP) problem with m − n + 1 variables and n constraints, where m and n represent the number of places and transitions in the marked graph, respectively. The presented PN based method is illustrated by modeling a real-time scheduling and control for flexible automotive manufacturing system (FAMS) in Valeo Turkey.     

A process-control and diagnostic tool based on continuous fuzzy Petri nets

The use of Petri nets and fuzzy logic in intelligent process control has caught the attention of many researchers. In this paper, a Continuous Fuzzy Petri Net (CFPN) tool which integrates the three technologies of fuzzy control, Petri nets and real-time expert systems is presented. The CFPN approach can deal with real-time continuous inferencing, for the purpose of process monitoring and diagnostics, at a high level in the presence of uncertainty. This tool has been implemented in the G2 real-time expert-system environment and is currently being used by ESSO Canada.     

Discovery of path-attribute dependency in manufacturing environments: A process mining approach

The more knowledge industrial practitioners detain of their production processes, the more they are capable of performing process improvements. Nonetheless, there may exist process characteristics and dependencies that are not easily extractable from business models, such as routing dependent attributes. This paper introduces an algorithm-driven framework to establish whether process path decisions influence the attributes in non-direct sequences, e.g., deploying machine A instead of machine B affects the % of rejected parts on the process, 4 stages down the line. This problem is shown to bears similarities with sequential pattern mining problems. The basis of the solution framework relies on process mining and data mining techniques. The approach proposed is applied on a real industrial log, unveiling deficiencies in the system and providing further improvement recommendations.