## 1 Introduction
[PERSON] and [PERSON] [29] introduced a hierarchical structure and a framework for modeling, analysis, specification, and design of logic controllers for RMSs, which allows rapid reconfigurability and reusability of the controller during reconfiguration. In [23], reconfigurable manufacturing systems were used to replace the existing manufacturing systems to offer higher convertibility and flexibility such as dedicated production systems. Serial and parallel configurations, a rules-based matrix approach has been developed and implemented. In addition, a higher-level deadlock control method is presented for the serial and parallel configurations. Net Rewriting Systems (NRS) are another graph-based reconfiguration mechanism [34]. In terms of pattern matching and dynamic structure replacements, the reconfiguration occurs. By the implementation of a Turing machine the expressive power was shown to be Turing equivalent. A subset of net rewriting systems, called reconfigurable nets, have also been provided with an algorithm to flatten a Petri net to standard. This subset only restricts NRS to those transformations that remain unchanged in the number of places and transitions, that is, only the flow relation can be changed. Flattening significantly increases the size of transitions by multiplying the number of reconfigurations by the amount of transitions. The NRS is used in logic controllers with improved net rewriting systems [35]. The improved NRS version restricts the rewriting rules to ensure important structural characteristics such as boundedness, liveness, and reversibility are not invalidated. In addition, in [24], an improved net rewriting system (INRS) was developed with the aim of reconfiguring an RMS supervisory controller based on PNs. Changes to an RMS modification were made to rewrite rules that were then applied in the initial PN controller. The INRS is first proposed as a reconfiguration basis. The structure of a Petri net model can be changed dynamically. Then, the study provided three representations of the RMS modification and suggested an INRS-based method to the design of the Petri net controller of an RMS. In this approach, the properties of behavioral, i.e., the boundedness, reversibility, and liveness of a modified system, were not verified or validated. In [31], colored timed PNs (CTPN) were used in the modelling of RMSs and a mechanism to describe reconfigurability in the CTPN architecture was introduced that leads to a new architecture supporting the reconfiguration. This mechanism includes reconfigurable transitions, specific places, and inhibitor arcs. [PERSON] and [PERSON] introduced intelligent token Petri net (ITPN) [25]. In their model, tokens representing job instances carry real-time knowledge about system states and changes, just like intelligent cards in practice such that dynamical changes of a system can be easily modeled. These formalisms can describe the reconfiguration behavior of the system. However, some of dynamic changes do not clearly define the modularity, which brings confusion to engineers in designing, understanding, and future redevelopment. Correctness of the system such as coherence of states before and after system reconfigurations is not considered. In addition, temporal constraints, which are of great significance in real-time systems are not mentioned. In [32], reconfigurable object nets (RONs) are used to model, simulate, and analyze RMSs. A formal method was proposed for fulfilling a new production requirement. The configuration consists of new extrusion and cutting machines. The reconfiguration is represented as graph transformations, RON tool was used to simulate the reconfigured systems and TINA [37] and PIPE [38] software tools were used to carry out the analysis. The work of [PERSON] et al. [36] explored the principles of the different approaches and takes from them the best practices. Configuration mechanisms were proposed using Holonic and multiagent system methods to allow a reconfigurable distributed production control system to systematically detect faults.