Verifying functional and non-functional properties of manufacturing control systems

Preuse, Sebastian; Hanisch, Hans-Michael

doi:10.1109/dcds.2011.5970316

Cited by 11 publications

(7 citation statements)

References 4 publications

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“…Some works deal with graphical, intuitive, and more userfriendly front-end specification languages that are aimed at making formal methods more accessible. In [88], requirements specified using symbolic timing diagrams and safety-oriented technical language are translated to temporal logic leading to a model checking of closed-loop system models. Other works include specification patterns for the nuclear automation sector [89] and user-friendly visualization and handling of counterexamples generated by model checkers [90].…”

Section: Formal Verificationmentioning

confidence: 99%

A Survey of Static Formal Methods for Building Dependable Industrial Automation Systems

Sinha

Patil

Gomes

et al. 2019

IEEE Trans. Ind. Inf.

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Industrial automation systems (IAS) need to be highly dependable; they should not merely function as expected but also do so in a reliable, safe, and secure manner. Formal methods are mathematical techniques that can greatly aid in developing dependable systems and can be used across all phases of the system development life cycle (SDLC), including requirements engineering, system design and implementation, verification and validation (testing), maintenance, and even documentation. This state-of-the-art survey reports existing formal approaches for creating more dependable IAS, focusing on static formal methods that are used before a system is completely implemented. We categorize surveyed works based on the phases of the SDLC, allowing us to identify research gaps and promising future directions for each phase.

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Section: Formal Verificationmentioning

confidence: 99%

A Survey of Static Formal Methods for Building Dependable Industrial Automation Systems

Sinha

Patil

Gomes

et al. 2019

IEEE Trans. Ind. Inf.

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“…It is also necessary to develop user interfaces and natural language support along the lines of V-OPL, templates for the automatic description of the system to be verified, and process modules that can be combined to form models quickly and reliably. 50 Professor Powers and his students pioneered the use of formal tools for model checking to evaluate the correctness of logic control systems operating and procedures for batch and continuous process plants. They were able to show that the tools developed in computer science could be adapted to chemical process problems.…”

Section: ■ Future Directions In Model Checkingmentioning

confidence: 99%

Section: ■ Future Directions In Model Checkingmentioning

confidence: 99%

Symbolic Verification of Control Systems and Operating Procedures

Rawlings

Kim

Moon

et al. 2014

Ind. Eng. Chem. Res.

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In this paper, we provide a review of Professor Powers's and his students' work on connecting fault analysis, discrete process control, human operating procedures, and symbolic model checking. In recent years, this type of research is placed under the banner of "cyber-physical systems research". Some of the techniques and procedures Powers and his students developed can be found in the open literature and conference proceedings. However, they have not been published broadly due to the untimely passing of Professor Powers. A complete overview of the methods are not available, and the cap-stone results obtained in the two last Ph.D. theses have not been published. ■ INTRODUCTION AND LITERATURE REVIEWProfessor Powers's research at Carnegie Mellon University centered on design research and systems analysis. In particular, he was interested in developing rigorous methods for chemical process risk and reliability assessment. Rigorous means that a system consisting of chemical processes, discrete and continuous control logic, and human operator intervention would be provably correct with respect to a given set of specifications. Such specifications would include the property that a safe shut down procedure can always be executed, unsafe states are avoided, and failure of critical measurements do not lead to unsafe conditions. The strength of the method is that very large systems with 10 20 states and more can be verified. 1 However, realistic problems may have much larger state spaces. Modular decompositions are needed, and great care must be taken to make sure that the models and specifications have sufficiently rich structure to capture all eventualities. These problems were recognized in Professor Powers's research and in his later research methods were developed for modular construction of very complex systems combining automation and human operator intervention using the verification-operating procedure language (V-OPL). 2,3,4,5 The key idea behind this seminal work was that logic faults in real-time control systems and operating procedures for chemical processes could be found by combining discrete state models of systems with model checking. In particular, Powers and his students showed that efficient strategies for reliability analysis could be developed using formal methods for model checking developed in the Department of Computer Science at Carnegie Mellon University by Professor Edmund Clarke and his students. The work was distinct from parallel work in the area of discrete event control systems and supervisor synthesis. 6 Powers and his students focused on the analysis of existing control systems and operating procedures, whereas the work in the area of supervisory control focused on how to synthesize control systems. The application domain, namely chemical process control, also presented unique challenges.The earliest ideas were described in the paper by Moon, Powers, Burch, and Clarke. 7 In this paper, the authors showed how the model checking tool SMV (symbolic model verifier) could be used to model an...

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“…Otherwise, a counterexample will be returned. Therefore, TNCESs have been widely applied in verification and validation of industry control systems especially for manufacturing systems [45][46][47]. The verification of a R-TNCES can be performed with the assistance of SESA [30,31].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Verification of Reconfigurable and Energy-Efficient Manufacturing Systems

Zhang

Khalgui

Boussahel

et al. 2015

Discrete Dynamics in Nature and Society

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This paper deals with the formal modeling and verification of reconfigurable and energy-efficient manufacturing systems (REMSs) that are considered as reconfigurable discrete event control systems. A REMS not only allows global reconfigurations for switching the system from one configuration to another, but also allows local reconfigurations on components for saving energy when the system is in a particular configuration. In addition, the unreconfigured components of such a system should continue running during any reconfiguration. As a result, during a system reconfiguration, the system may have several possible paths and may fail to meet control requirements if concurrent reconfiguration events and normal events are not controlled. To guarantee the safety and correctness of such complex systems, formal verification is of great importance during a system design stage. This paper extends the formalism reconfigurable timed net condition/event systems (R-TNCESs) in order to model all possible dynamic behavior in such systems. After that, the designed system based on extended R-TNCESs is verified with the help of a software tool SESA for functional, temporal, and energy-efficient properties. This paper is illustrated by an automatic assembly system.

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Verifying functional and non-functional properties of manufacturing control systems

Cited by 11 publications

References 4 publications

A Survey of Static Formal Methods for Building Dependable Industrial Automation Systems

A Survey of Static Formal Methods for Building Dependable Industrial Automation Systems

Symbolic Verification of Control Systems and Operating Procedures

Modeling and Verification of Reconfigurable and Energy-Efficient Manufacturing Systems

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