Since the advent of the modern factory, entrepreneurs and engineers have sought to optimize and refine the processes inherent to manufacturing technology. Contemporary tools on the global framework include computer-aided solutions with an emphasis on data acquisition and analysis applied to continuous closed-loop feedback. Given enough feedback data, the need for a traditional human manager is diminished, driving down inefficiencies such as production delays to unprecedented levels. However, the addition of sensory networks to achieve such autonomy is expensive and highly complex, making such systems susceptible to malfunction during commissioning. To reduce these upfront delays, it is increasingly common for entire production assemblies to be simulated in near-perfect virtual environments, or cells, to diagnose and resolve errors and design defects before factory implementation in a process called Virtual Commissioning (VC). According to the literature review on Industry 4.0, there is a need in exploring such digital manufacturing tools compatible with Industrial Internet of Things (IIoT) functionalities. The concept of the Virtual Commissioning of a Digital Twin is discussed further including applications in present and near-future advanced production and education. Specifically, global trends towards Industry 4.0 and virtual manufacturing processes are explored in addition to how and why these emerging technologies could be applied. Furthermore, the advantages of Virtual Commissioning processes are contrasted to Traditional Commissioning to highlight the evolution of Product Lifecycle Management (PLM) software and the optimization of manufacturing processes since the turn of the century. This research aims to create a Digital Twin in state-of-the-art PLM software that links a virtual and physical prototype in a closed feedback loop. Avenues for data collection and data reuse for a control variable using a sensor with IIoT connectivity are discussed. Developing a methodology for this research work, the analysis is followed by a case study involving a Mini Festo Pick-and-Place unit. The pick-and-place twin environment is developed in Siemens Tecnomatix Process Simulate (Tecnomatix) and controlled via ladder logic executed in Totally Integrated Automation (TIA) Portal. Communication between the 3D-simulated environment and TIA Portal is managed through PLCSIM Advanced and is linked to the physical pick-and-place prototype via a Simatic IOT2000 I/O module over a LAN WI-FI network. This network configuration allows for the direct control of the master simulation, and hence the slave prototype, through a virtual Human Machine Interface (HMI). Additional digital manufacturing tools used in this study include a virtual Siemens SIMATIC S7-1200 Programmable Logic Controller (PLC) and an S7-1200 PLC paired with the physical pick-and-place prototype. The novelty contribution in this work is the exploration of IIoT functionalities in an intelligent automation feedback system. As expected, the results of this case study validate the potential for optimized contemporary manufacturing solutions in which higher-quality goods are reliably produced with minimal delays at all-time low principal investments. It is shown that the development of a virtual simulation before system commissioning allows for unmatched versatility in product realization and troubleshooting, all with mitigated plant downtime for diagnosing and correcting said defects. Furthermore, the present research emphasizes the capabilities and importance of the IIoT communication paradigm in the future of the autonomous automation and process control of intelligent, interconnected systems. Finally, the recommended future work of the project is developed which encourages additional system versatility via the development of additional IIoT functionality.


Virtual Commissioning for Advanced Manufacturing Using Digital Tools

Division / Sponsors: 
Aerospace, Bioengineering, Applied Mechanics, Design Engineering Division, Advanced Energy Systems, Manufacturing Engineering Division, Noise Control and Acoustics, Nondestructive Evaluation, Diagnosis, and Prognosis (NDPD), Nuclear Engineering Division, Process Industries Division, Fluids Engineering, Heat Transfer, Materials, Microelectromechanical Systems, Safety Engineering and Risk Analysis, Computers & Information in Engineering


Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2020/volume/84478

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