In MODAPTO’s Use Case 1, our primary objective is to advance the capabilities of robotic systems by fostering interoperability and expanding functionalities to include sustainability analytics and energy optimization. Our approach involves the integration of virtual commissioning features, rooted in the design of energy-optimised production modules. This empowers users in the plant engineering phase to make informed decisions, steering production methods towards sustainability.
FFT, a prominent global manufacturer of production equipment, is currently channeling efforts into the development of innovative production modules. These modules incorporate robotic systems equipped with specialised tools, customised for clients within the MODAPTO project. The emphasis lies in creating modules fortified with sustainability and optimization features. Notably, these modules facilitate detailed modeling and calculation of energy consumption and corresponding carbon emissions associated with specific manufacturing tasks. This information, in turn, serves as a foundation for devising optimisation strategies for robotic movements, thereby enhancing environmental efficiency.
Moreover, over the past few years, the focus on reducing energy consumption and emissions in research and development has become increasingly significant. These concerns extend beyond individual production component vendors, impacting the entire value chain and lifecycle, involving various parties in the process, such as calculating the carbon footprint of a product. This underscores the crucial need for information exchange throughout the lifecycle and across company barriers through vertical and horizontal integration. Standardised industrial Digital Twins (e.g., via AAS) emerge as ideal enablers for achieving this integration.
The exploitation of collected information goes beyond mere production resource and product mapping; it delves into the intricacies of the actual production process. This detailed approach allows for the calculation of the energy equivalent or carbon footprint for individual operations, such as spot-welding processes using pneumatic or electric-driven guns or roller hemming processes with different robot sizes. This information is essential for contributing to the life cycle assessment (LCA) and eco-balancing of produced products. Standardised methodologies for corresponding key performance indicators (KPIs) form the basis for these calculations.
A module endowed with such capabilities becomes instrumental in providing valuable information, insights, and tools for both production plant developers/programmers and end-users. Specifically, it facilitates decision support for selecting appropriate modules for developing one or more robotic systems for a given task. This involves considering factors such as robot sizes, payloads, and available technology systems when selecting the right combination of robots and accordingly mounted tools. Additionally, virtual commissioning functionalities, based on energy-optimised production layout design, further support end-user decisions towards more sustainable production schemes.