This paper introduces a methodology for modeling and analyzing fault-tolerant manufacturing systems that not only optimizes normal productive processes, but also performs detection and treatment of faults. This approach is based on the hierarchical and modular integration of Petri nets. The modularity provides the integration of three types of processes: those representing the productive process, fault detection, and fault treatment. The hierarchical aspect of the approach allows us to consider processes on different levels of detail (i.e., factory, manufacturing cell, or machine). Case studies considering detection and treatment of faults are presented, and a simulation tool is applied to verify the models.

Presents a framework for a supervisor in balanced automation systems (BAS). The concept of BAS is based on an appropriate technological level considering human factors and highly automated machines. The supervisor not only considers a normal process but also detection and treatment of failures. The framework is based on distributed Petri nets (DPNs). DPNs permit the integration of several modules of Petri nets , where each module represents a particular process such as, normal processes, detection and treatment of failures. A case study of detection and treatment of failure in machining operations is considered, in which, the normal process, the detection and treatment of failures in a BAS are integrated through modules based on DPNs.

This work introduces the concept of Distributed Petri Nets as a tool to model and to analyze manufacturing systems. Distributed Petri Nets can integrate Petri Nets models of different types, in which each model represent a specific feature of the system. Also, a simulation tool was developed to analyze models based on Distributed Petri nets. A fault-tolerant approach to detect and treat failures by tool-wear, tool-break, or programming mistakes was analyzed in the simulation tool.

This paper presents a framework for a supervisor in manufacturing systems operations. The supervisor not only considers normal process in the manufacturing system but also detection and treatment of failures. The framework is based on the formalism of Petri nets (PN). In particular, an extension of PN, Distributed Petri Net (DPN), is introduced, which permit to develop the supervisor framework. A case study of detection and treatment of failure in machining operations will be considered, in which, the normal process, the detection and treatment of failures in a manufacturing system are integrated through modules based on DPN.

In this research, a variation of Petri nets called Self-Modifying Petri nets is applied for modeling failure treatments in manufacturing systems. The failure detection and treatment problem is discussed and the main concepts of Self-Modifying Petri nets are presented for modeling manufacturing systems. An example of a manufacturing system is presented to illustrate the effectiveness of modeling through Self-Modifying Petri nets. The proposed approach facilitates the analysis of the modeled system when compared to other types of nets especially in the case of discrete event dynamic systems with structural changes.