Digital Twin Model Development for Condition-Base Maintenance Assessment in Robotic Manufacturing Processes Within a Shipyard

The Industrial Robots have a very important impact mainly in labor intensive industries and with strong demands on skilled workers. Both aspects are found in the shipbuilding industry. Like in any industrial sectors, shortening of the manufacturing processes is a requirement of ship owners. Industrial robots will help the increasing of production efficiency and quality in the shipyards. Predictive maintenance of the manufacturing equipment including robots and different type of tools and equipment producing diverse parts becomes a complex task. In other words, the predictive maintenance of these new adaptable and highly automatized robotic cells, able to manage different loads and design changes, through their lifetime is a complex task which needs new tools. Virtual Commissioning (VC) has shown its capability for verifying the mechanical behavior of a system. It can help in generating simulation models based on plant engineering data too. For this reason, a physical-data model that evaluates the accumulated work of a manufacturing cell in conjunction with a digital twin has been developed.