Owing to the aforementioned problems, this work discusses a methodology for plant and control modeling and validating of the manufacturing systems that include sequential, parallel and timed operations, using a formalism based on Statecharts, denominated Basic Statechart (BSC). It extends conventional finite state machine with notions of hierarchy, concurrency,and communication. The Statechartsformalism, described by David Harel (1987), makes the specification and design of complex DES easier. We believe that such approaches are still low-level formalisms, resulting in large and unwieldy systems. However, despite significant research advances in recent years, these formal techniques have not been widely employed in industry ( Endsley et al., 2006).
Plant simulation tm verification#
The two most common approaches are Finite State Machines (FSM)and Petri nets both allow for formal verification of the correctness of a control system.
![plant simulation tm plant simulation tm](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13068-021-01977-z/MediaObjects/13068_2021_1977_Figa_HTML.png)
In literature, there are several approaches that present methodologies, languages, and patterns for modeling industrial applications, especially for Discrete Event Systems (DES)( Cassandras & Lafortune, 2008).
![plant simulation tm plant simulation tm](https://i.servimg.com/u/f39/13/48/15/82/tm/go_bon10.png)
Our focus is in forward engineering, which investigate the model generation from requirements specified by users. The “Reengineering” arc represents the research area, which investigates the generation of a model from legacy code. The “Modifications” arc represents multiple iterations that can occur in softwaremodeling processes.
![plant simulation tm plant simulation tm](https://m.media-amazon.com/images/I/61etdiYhlaL._SL1024_.jpg)
Modeling is phase that demands more time in application lifecycle. In short, an application life-cycle can be divided in three phases: Modeling - Validation - Implementation(see Figure 1). Boehm (2006) presents an overview of the best softwareengineer practices used since 1950 (decade to decade) and he identifies the historical aspects of each tendency.
Plant simulation tm software#
Examples of the latter are: Adaptive Software Development, Crystal, Dynamic Systems Development, eXtreme Programming (XP), Feature Driven Development, and Scrum. In the Computer Science area, several models guide the software development process such as the Waterfall Model( Royce, 1970), a sequential software development model in which development is seen as sequence of phases the Spiral model( Boehm, 1988), an iterative software development model which combines elements of software design and prototype stages and agile methods, which emerged in the 1990. Software reuse is a complicated problem and depends not only on the means provided by the modeling language, but also on the overall application structure. In the Industrial area, the IEC-61499 (2005) standard allows reuse of application parts (function block, sub-application) in different applications. On the other hand, softwarereusability and composability have been discussed since the 80’s, with the use of object-oriented methods ( Boehm, 2006). In general, PLC are still programmed by conventional “trial-and-error” methods and there is no written documentation on these systems. As a result, “for practically no implemented controller does a formal description exist”( Bani Younis & Frey, 2006). Furthermore, controllers are often reprogrammed during plant operation life-cycle to adapt them to new requirements. Industrial controller programming is currently performed by qualified technicians using one of the five languages defined by IEC-61131-3 (1993) standard and who seldom have knowledge of modern software technologies. The actuatorsare associated with the actions produced by the PLC program and represent output variables. Considering an industrial automation process based on Programmable Logic Controllers (PLC), the sensorsare installed in the plant and generate events that represent input variables to the PLC.
![plant simulation tm plant simulation tm](https://scg-de.s3.amazonaws.com/images/article/DE2010_F_Smartfactory_DELMIA_TM_Final_Assembly2_600.jpg)
The automation area uses concepts of the theory of systems to control machines and industrial processes. In this context, state-based methods such as Finite State Machines (FSM) and Petri Nets have been traditionally used to describe these systems. In their definition, DES are systems that have discrete state space and an event-driven dynamic, i.e., the state can only change as a result of instantaneous events occurring asynchronously over time. Cassandras & Lafortune (2008) discuss systems classification, especially for Discrete Event Systems (DES). The key point in this definition is the interaction among system components. Based on the IEEE Standard Glossary of Software Engineering Terminology ( IEEE Std 610.12-1990, 1990), “a system can be regarded as a collection of components organized to accomplish a specific function or set of functions”.