Simulation framework for the verification of PLC programs in automobile industries

Koo, Lock-Jo; Park, Chang Mok; Lee, Chang Ho; Park, Sang-Chul; Wang, Gi-Nam

doi:10.1080/00207543.2010.492404

Cited by 29 publications

(10 citation statements)

References 9 publications

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“…Therefore, virtual commissioning is to identify and address design flaws and operational faults without real plant nor controllers so that a significant savings can be achieved in the actual implementation of the manufacturing system. A recent study [21] showed the positive effect of virtual commissioning on the error rate during real commissioning. They showed a reduction of real commissioning time by 75%, resulting from enhanced quality of the manufacturing system at the start of real commissioning.…”

Section: Introductionmentioning

confidence: 99%

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Survey on the virtual commissioning of manufacturing systems

Lee

Park

2014

Journal of Computational Design and Engineering

137

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This paper reviews and identifies issues in the application of virtual commissioning technology for automated manufacturing systems. While the real commissioning of a manufacturing system involves a real plant system and a real controller, the virtual commissioning deals with a virtual plant model and a real controller. The expected benefits of virtual commissioning are the reduction of debugging and correction efforts during the subsequent real commissioning stage. However, it requires a virtual plant model and hence still requires significant amount time and efforts. Two main issues are identified, the physical model construction of a virtual device, and the logical model construction of a virtual device. This paper reviews the current literature related to the two issues and proposes future research directions to achieve the full utilization of virtual commissioning technology.

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Section: Introductionmentioning

confidence: 99%

“…Virtual commissioning enables the full verification of a manufacturing system by performing a simulation involving a virtual plant and a real controller [19][20][21][22][23][24][25][26]. This requires the virtual plant model to be fully described at the level of sensors and actuators.…”

Section: Introductionmentioning

confidence: 99%

Survey on the virtual commissioning of manufacturing systems

Lee

Park

2014

Journal of Computational Design and Engineering

137

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“…Lee and Hsu (2005) and Silva et al (2010) describe a systematic approach to the design and implementation of the sequence controller in manufacturing systems. Koo et al (2010) propose a framework for verification of PLC logic through modelling and simulation. Park et al (2010) present a systematic procedure for generating a plant model from the symbol table of a PLC program.…”

Section: Related Workmentioning

confidence: 99%

A computational control implementation environment for automated manufacturing systems

Diogo

Santos

Vieira

et al. 2012

International Journal of Production Research

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2012) A computational control implementation environment for automated manufacturing systemsThis paper presents a computational environment as a tool for supporting the implementation of control coding of an automated manufacturing system. The proposed environment considers a cyclic three-stage control development -modelling, synthesis and implementation -until the real system accomplishes the required specification, resulting in the automated and integrated manufacturing system. The research details the three stages and describes the steps executed for each one. The mathematical formalism used in this work is also presented, as a basis for control implementation. The implementation environment is proposed in order to validate the control structure of this formalism and to allow a progressive integration of control hardware and software. To submit to a test and validate the proposal environment, two experiments are performed, in two different manufacturing systems. Thus, it is demanded that the control system can be reconfigurable in a fast and reliable way.

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“…Especially useful is the virtual commissioning technology in the design of manufacturing systems (Fratczak et al, 2013;Kim et al, 2011;Ko et al, 2013a,b;Ko and Park, 2014;Koo et al, 2011;Lee and Park, 2014), but also continuous processes (Barth and Fay, 2013;Bradu et al, 2009;Geist et al, 2013;Gerlach et al, 2013), where a real controller is tested through simulations with a virtual plant. Another possibility is to use supporting applications and tools that are offered by many manufacturers of the control equipment.…”

Section: Introductionmentioning

confidence: 99%

A metamorphic controller for plant control system design

Klopot¹,

Skupin²,

Choinski³

et al. 2016

MIC

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One of the major problems in the design of industrial control systems is the selection and parameterization of the control algorithm. In practice, the most common solution is the PI (proportional-integral) controller, which is simple to implement, but is not always the best control strategy. The use of more advanced controllers may result in a better efficiency of the control system. However, the implementation of advanced control algorithms is more time-consuming and requires specialized knowledge from control engineers. To overcome these problems and to support control engineers at the controller design stage, the paper describes a tool, i.e., a metamorphic controller with extended functionality, for selection and implementation of the most suitable control algorithm. In comparison to existing solutions, the main advantage of the metamorphic controller is its possibility of changing the control algorithm. In turn, the candidate algorithms can be tested through simulations and the total time needed to perform all simulations can be less than a few minutes, which is less than or comparable to the design time in the concurrent design approach. Moreover, the use of well-known tuning procedures, makes the system easy to understand and operate even by inexperienced control engineers. The application was implemented in the real industrial programmable logic controller (PLC) and tested with linear and nonlinear virtual plants. The obtained simulation results confirm that the change of the control algorithm allows the control objectives to be achieved at lower costs and in less time.

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Simulation framework for the verification of PLC programs in automobile industries

Cited by 29 publications

References 9 publications

Survey on the virtual commissioning of manufacturing systems

Survey on the virtual commissioning of manufacturing systems

A computational control implementation environment for automated manufacturing systems

A metamorphic controller for plant control system design

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