Discrete event systems: Modeling and performance analysis: by Christos G. Cassandras, Richard D. Irwin, Inc., and Aksen Associates, Inc., Homewood, IL, 1993. xix + 790 pp. ISBN 0-256-11212-6

Deadlocks are a rather undesirable situation in a highly automated flexible manufacturing system. Their occurrences often deteriorate the utilization of resources and may lead to catastrophic results in safety-critical systems. Graph theory, automata, and Petri nets are three important mathematical tools to handle deadlock problems in resource allocation systems. Particularly, Petri nets are considered as a popular formalism because of their inherent characteristics. They received much attention over the past decades to deal with deadlock problems, leading to a variety of deadlock-control policies. This study surveys the state-of-the-art deadlock-control strategies for automated manufacturing systems by reviewing the principles and techniques that are involved in preventing, avoiding, and detecting deadlocks. The focus is deadlock prevention due to its large and continuing stream of efforts. A control strategy is evaluated in terms of computational complexity, behavioral permissiveness, and structural complexity of its deadlock-free supervisor. This study provides readers with a conglomeration of the updated results in this area and facilitates engineers in finding a suitable approach for their industrial scenarios. Future research directions are finally discussed.

Deadlock Control of Automated Manufacturing Systems Based on Petri Nets—A Literature Review

Automated guided vehicle systems, state-of-the-art control algorithms and techniques

We propose a life cycle optimization framework for the design of sustainable product systems and supply chains considering the concept of “functional unit” under economic and environmental criteria. This general modeling framework integrates the life cycle analysis methodology with multiobjective optimization and measures both the economic and environmental performances based on a standard quantity of functional unit associated with final products. The Pareto-optimal frontier returned by the multiobjective optimization problem reveals the trade-off between the economic and environmental objectives. We also present tailored optimization algorithms for efficiently solving the mixed-integer linear fractional programming problems, which result from the life cycle optimization framework. We apply the proposed life cycle optimization framework to a case study on the hydrocarbon biofuels through a spatially explicit model for the county-level supply chain in Illinois. The Pareto-optimal results show that the env...

Design of Sustainable Product Systems and Supply Chains with Life Cycle Optimization Based on Functional Unit: General Modeling Framework, Mixed-Integer Nonlinear Programming Algorithms and Case Study on Hydrocarbon Biofuels

The design, planning, and implementation of intelligent manufacturing are mainly carried out from the perspectives of meeting the needs of mass customization, improving manufacturing capacity, and innovating business pattern currently. Environmental and social factors should be systematically integrated into the life cycle of intelligent manufacturing. In view of this, a green performance evaluation methodology of intelligent manufacturing driven by digital twin is proposed in this paper. Digital twin framework, which constructs the bidirectional mapping and real-time data interaction between physical entity and digital model, provides the green performance evaluation with a total factor virtual image of the whole life cycle to meet the monitoring and simulation requirements of the evaluation information source and demand. Driven by the digital twin framework, a novel hybrid MCDM model based on fuzzy rough-sets AHP, multistage weight synthesis, and PROMETHEE II is proposed as the methodology for the green performance evaluation of intelligent manufacturing. The model is tested and validated on a study of the green performance evaluation of remote operation and maintenance service project evaluation for an air conditioning enterprise. Testing demonstrates that the proposed hybrid model driven by digital twin can enable a stable and reasonable evaluation result. A sensitivity analysis was carried out by means of 27 scenarios, the results of which showed a high degree of stability.

/pdf/digital-twin-driven-green-performance-evaluation-methodology-53899sstzq.pdf

Digital Twin Driven Green Performance Evaluation Methodology of Intelligent Manufacturing: Hybrid Model Based on Fuzzy Rough-Sets AHP, Multistage Weight Synthesis, and PROMETHEE II

An approach using petri nets and improved heuristic search for manufacturing system scheduling

The construction of error recovery Petri subnets and similar representations have received considerable attention in the literature. Previous work has presented a multi-agent system representing various levels of control in a reconfigurable architecture. Agents pertaining to production, mediation, and error recovery within such an architecture were considered. Our focus here is on the workstation level of a hierarchy where the workstation has the capability for recovery from physical errors. The implications of error recovery tasks from the perspective of control are also discussed. The approach is based on integrating Petri subnet models within a general Petri Net model for a manufacturing system environment. In essence, the error recovery plan consists of a trajectory (Petri subnet) having the detailed recovery steps that are then incorporated into the workstation control logic. The logic is based on a Timed Petri Net model of the total production system. The Petri subset models consist of a sequence of steps required to reinstate the system back to a normal state. Once generated, the recovery subnet is incorporated into the Petri Net model of the original expected (error-free) model. Petri Net augmentations pertaining to various issues are discussed in detail throughout the paper. Issues include the implication of generated error recovery trajectories in the production activities, linking of production activity Net and the error recovery subnet, potential deadlocks, the role of resources, and part handling.

An augmented Petri Net approach for error recovery in manufacturing systems control

In this paper we propose the GAPN (genetic algorithms and Petri nets) approach, which combines the modelling power of Petri nets with the optimisation capability of genetic algorithms (GAs) for manufacturing systems scheduling. This approach uses both Petri nets to formulate the scheduling problem and GAs for scheduling. Its primary advantage is its ability to model a wide variety of manufacturing systems with no modifications either in the net structure or in the chromosomal representation. In this paper we tested the performance on both classical scheduling problems and on a real life setting of a manufacturer of car seat covers. In particular, such a manufacturing system involves features such as complex project-like routings, assembly operations, and workstations with unrelated parallel machines. The implementation of the algorithm at the company is also discussed. Experiments show the validity of the proposed approach.

Petri nets and genetic algorithms for complex manufacturing systems scheduling

In this paper, we study the open shop scheduling problem with blocking and deadlocks. First, we develop a new Petri net class that extends the well-known $\text{S}^{3}\text{R}$ nets to handle the features of open shop systems. Next, we establish necessary conditions for deadlock-free operation based on the properties of a particular structural siphon. Then, we implement a graph search algorithm that intelligently explores the net reachability graph and uses a search strategy based on a double filtering mechanism and new evaluation functions. We conducted computational tests on a set of classical instances adapted from the literature. The quality of the solutions was established with a lower bound calculated with the aforementioned siphon. The results show the validity of the approach: the proposed algorithm found solutions with values that were very close to the lower bound in most cases.

Petri Nets and Deadlock-Free Scheduling of Open Shop Manufacturing Systems

This paper introduces a Petri net-based approach for scheduling manufacturing systems with blocking. The modelling of the job routings and the resource and blocking constraints is carried out with the Petri net formalism due to their capability of representing dynamic, concurrent discrete-event dynamic systems. In addition Petri nets can detect deadlocks typically found in systems with blocking constraints. The scheduling task is performed with an algorithm that combines the classical A* search with an aggressive node-pruning strategy. Tests were conducted on a variety of manufacturing systems that included classical job shop, flexible job shop and flexible manufacturing scheduling problems. The optimisation criterion was makespan. The experiments show that the algorithm performed well in all types of problems both in terms of solution quality and computing times.

Gonzalo Mejía

Papers

An approach using petri nets and improved heuristic search for manufacturing system scheduling

An augmented Petri Net approach for error recovery in manufacturing systems control

Petri nets and genetic algorithms for complex manufacturing systems scheduling

Petri Nets and Deadlock-Free Scheduling of Open Shop Manufacturing Systems

Scheduling manufacturing systems with blocking: a Petri net approach