State-based verification of industrial control programs with the use of a Digital Model

Today, the verification of the control logic of automation projects is mainly a manual task during real commissioning phase on the physical installation. This involves a lot of risks towards possible damage and unanticipated delays of project completion. Virtual commissioning allows the verification to start earlier in the project timeline, but is often also a manual task and requires a lot of human knowledge and expertise. This paper proposes a workflow to provide additional support to the automation engineer based on a 3D Digital Model that interacts with the real control logic. The digital model records all occurring states and transitions in the background and visualizes the state graph to highlight unexpected behaviour and to support troubleshooting. The proposed approach is validated on a test case confirming (1) the effectiveness of highlighting unexpected behaviour during programming phase and (2) the substantial reduction in real commissioning time. The added value of the approach is concluded, although a number of limitations still exist. Future research includes the validation of the approach on real industrial cases.Today, the verification of the control logic of automation projects is mainly a manual task during real commissioning phase on the physical installation. This involves a lot of risks towards possible damage and unanticipated delays of project completion. Virtual commissioning allows the verification to start earlier in the project timeline, but is often also a manual task and requires a lot of human knowledge and expertise. This paper proposes a workflow to provide additional support to the automation engineer based on a 3D Digital Model that interacts with the real control logic. The digital model records all occurring states and transitions in the background and visualizes the state graph to highlight unexpected behaviour and to support troubleshooting. The proposed approach is validated on a test case confirming (1) the effectiveness of highlighting unexpected behaviour during programming phase and (2) the substantial reduction in real commissioning time. The added value of the approach is concluded, although a number of limitations still exist. Future research includes the validation of the approach on real industrial cases.A