Industry 4.0 concept enables connecting a multitude of equipment to computer simulations through IoT and virtual commissioning, but using conventional interfaces for each separate piece of equipment for control and maintenance of Digital Twins is not always an optimal solution. Industrial Digital Twins software toolkits usually consist of simulation or offline programming tools. It can even connect real machines and controllers and sensors to feed a simulation with actual production data and later analyze it. Moreover, Virtual Reality (VR) and Augmented Reality (AR) are used in different ways for monitoring and design purposes. However, there are many software tools for the simulation and re-programming of robots on the market already, but those are a limited number of software that combine all these features, and all of those send data only in one way, not allowing to re-program machines from the simulations. The related research aims to build a modular framework for designing and deploying Digital Twins of industrial equipment (i.e., robots, manufacturing lines), focusing on online connectivity for monitoring and control. A developed use-case solution enables one to operate the equipment in VR/AR/Personal Computer (PC) and mobile interfaces from any point globally while receiving real-time feedback and state information of the machinery equipment. Gamified multi-platform interfaces allow for more intuitive interactions with Digital Twins, providing a real-scale model of the real device, augmented by spatial UIs, actuated physical elements, and gesture tracking.

The introduced solution can control and simulate any aspect of the production line without limitation of brand or type of the machine and being managed and self-learning independently by exploiting Machine Learning algorithms. Moreover, various interfaces such as PC, mobile, VR, and AR give an unlimited number of options for interactions with your manufacturing shop floor both offline and online. Furthermore, when it comes to manufacturing floor data monitoring, all gathered data is being used for statistical analysis, and in a later phase, predictive maintenance functions are enabled based on it.

However, the research scope is broader; this particular research paper introduces a use-case interface on a mobile platform, monitoring and controlling the production unit of three various industrial- and three various mobile robots, partially supported by data monitoring sensors. The solution is developed using the game engine Unity3D, Robot Operation System (ROS), and MQTT for connectivity. Thus, developed is a universal modular Digital Twin all-in-one software platform for users and operators, enabling full control over the manufacturing system unit.

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