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A Classification Framework for Automated Control Code Generation in Industrial Automation
Journal of Systems and Software ( IF 2.559 ) Pub Date : 2020-03-16 , DOI: 10.1016/j.jss.2020.110575
Heiko Koziolek; Andreas Burger; Marie Platenius-Mohr; Raoul Jetley

Software development for the automation of industrial facilities (e.g., oil platforms, chemical plants, power plants, etc.) involves implementing control logic, often in IEC 61131-3 programming languages. Developing safe and efficient program code is expensive and today still requires substantial manual effort. Researchers have thus proposed numerous approaches for automatic control logic generation in the last two decades, but a systematic, in-depth analysis of their capabilities and assumptions is missing. This paper proposes a novel classification framework for control logic generation approaches defining criteria derived from industry best practices. The framework is applied to compare and analyze 13 different control logic generation approaches. Prominent findings include different categories of control logic generation approaches, the challenge of dealing with iterative engineering processes, and the need for more experimental validations in larger case studies.
更新日期:2020-03-20

 

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