Abstract
In today’s complex environment, it is not only important to handle/control digital manufacturing tools, but also essential to capture tacit knowledge from people. Creating a digital twin, it is an extensive effort including different fields and subjects. For example, creating a physical prototype and connecting it with a virtual prototype. From this, two questions arise. What will be the framework used to create the digital twin and what method will be used to capture the experiences to develop Next Generation Automation System (NGAS). This research explores a new method capturing tacit knowledge creating a digital twin for a NGAS, worked at station level connecting machines and humans implementing knowledge modelling and providing guidance in design for manufacturability at NGAS. The motivation of this research is that capturing tacit knowledge is an important aspect in Industry 4.0.
According to literature review, different researchers have been exploring digital twins using digital tools. This research proposal explores the effects of automation in the workplace using Digital Manufacturing Tools (DMT). The proposed approach demonstrates how to capture valuable experiences we can transfer or communicate between the digital twins, increasing productivity to fulfill the need to adopt new and emerging technologies in the workplace. The research will talk about capturing Tacit Knowledge in different forms like experiences, analysis, and intuitions etc and how this type of knowledge is processed by DMT and communicated to the other digital twin. Tacit knowledge modeling and sharing is used by implementing the Internet of Things (IoT) to understand the interaction among humans, instruments, controls, and robots. Understanding tacit manufacturing knowledge types is required to create better digital twins.
Realization of AI-enhanced industrial automation systems using intelligent Digital Twins
