Generating Correct, Compact, and Efficient PLC Code from Scenario-based Assume-Guarantee Specifications

Gritzner, Daniel; Greenyer, Joel

doi:10.1016/j.promfg.2018.06.046

Cited by 12 publications

(2 citation statements)

References 12 publications

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“…Programmable Logic Controllers (PLCs) Code Generation was presented in [55] using Scenario Modeling Language (SML). In the same manner, implementation of PLC code generation was presented in [124] using Compositional Interchange Format (CIF).…”

Section: Code Generationmentioning

confidence: 99%

A Systematic Literature Review on Model-driven Engineering for Cyber-Physical Systems

Mohamed¹,

Kardaş²,

Challenger³

2021

Preprint

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This technical report presents a Systematic Literature Review (SLR) study that focuses on identifying and classifying the recent research practices pertaining to CPS development through MDE approaches. The study evaluates 140 research papers published during 2010-2018. Accordingly, a comprehensive analysis of various MDE approaches used in the development life-cycle of CPS is presented. Furthermore, the study identifies the research gaps and areas that need more investigation. The contribution helps researchers and practitioners to get an overall understanding of the research trends and existing challenges for further research/development.

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Section: Code Generationmentioning

confidence: 99%

A Systematic Literature Review on Model-driven Engineering for Cyber-Physical Systems

Mohamed¹,

Kardaş²,

Challenger³

2021

Preprint

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“…However, several other researchers use SysML to generate PLC code. Gritzner and Greenyer (2018) report an approach for generating from scenario-based specifications written in Scenario Modeling Language, a compact and efficient Structured Text executable on PLCs. In Vogel-Heuser, Schtz, Frank, and an approach for the model-driven development of automation software for manufacturing systems is presented.…”

Section: Automated Configurationmentioning

confidence: 99%

Knowledge-based cyber-physical systems for assembly automation

Merdan¹,

Hoebert²,

List³

et al. 2019

Production & Manufacturing Research

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Current assembly systems are handling the increased requirements for mass customization with difficulties and need to be updated with new approaches and technologies. Cyber-Physical Systems (CPS) auto-configuration is regarded as an important asset towards automation components, which autonomously embed themselves into the system. In this context, knowledge-based technologies pave the way for highly flexible and reconfigurable CPS. This paper introduces and demonstrates a model-driven engineering approach for automatically configuring the control layer of a CPS based on knowledge representation of the environment and component capabilities. The approach encompasses a control architecture that is tested in two industrial use cases. The first case employs a configuration infrastructure for control software based on IEC 61499 to automatically configure the hardwarenear control layer of a CPS within an assembly line. The second case is concerned with autonomously generating assembly plans, which are then transformed into actions that an industrial robot sequentially executes.

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