Development of a cloud-based digital twin simulation platform for flexible manufacturing systems with IoT technology

点击翻译按钮获取中文摘要

Digital twin (DT) technology has received widespread attention in Canada's manufacturing sector. This technology creates a digital replica of a corresponding physical object, such as a human, device, system, or process that mirrors the actual process with full knowledge of its historical performance. It has the advantage of enabling agility and convergence of understanding to support more effective decision-making and resource allocation optimization. However, existing DT simulation platforms are either monolithic and function-oriented or dedicated in a captive software suite. Moreover, most digital twin platforms are standalone and only support offline simulation. Since DT is not a catch-all solution, educating a workforce on the new technology to see if it might be of value bears a significant risk for small-to-medium enterprises (SMEs). The COVID-19 pandemic has added an enormous challenge and disruption in current manufacturing plant operations due to strict quarantine rules and reduced human activities. There is an urgent demand for an online DT platform to monitor all the processes, capture real-time performance, and provide remote control. This project includes a partnership between the digital manufacturing team (Drs. Yang and Defersha) at the University of Guelph and Aleo Canada Inc. (Montreal, Quebec). The primary goal of this collaborative research is to develop a cloud-based DT platform that reliably captures the real-time performance of a flexible manufacturing system (i.e., a computerized and reconfigurable production unit to manufacture a variety of parts) with Internet of Things (IoT) sensor data. The expected impacts and outcomes of this project include: 1) develop the ability to conduct real-time monitoring and control of a flexible manufacturing system to support economic recovery; 2) develop the pipeline and infrastructures for cloud-based DT simulation with IoT technology; 3) provide a new testbed for AI algorithms and closed-loop control; and 4) provide training of HQP in digital transformation, IoT, Artificial Intelligence (AI), and cloud services. The expected outcomes of the proposed project will positively contribute to Canada's digital economy and post-pandemic recovery.