Use cases
The PERKS project supports the holistic governance of industrial PK in its entire life cycle, from elicitation to management and from access to exploitation. PERKS bases its solutions on leading-edge AI (both symbolic and subsymbolic) and data technologies, by advancing and integrating existing methodologies and tools in terms of readiness, flexibility and user acceptance. Besides AI and data, the third pillar of PERKS consists of people: the goal is to put industry workers at the centre, in line with the Industry 5.0 vision, to satisfy their concrete needs, to provide AI-powered digital tools to perform their tasks better and more easily, following a human-in-the-loop paradigm to enhance the technologies and the solutions.
The results are applied in
three industrial scenarios
White Goods Production Plant
Beko will test and validate the PERKS AI solutions for the Procedural Knowledge management, in particular of the LOTO procedures used in the factory maintenance.
According to the AS IS situation, the LOTO digital sheets are created by process/maintenance engineers and have to be integrated, completed, validated and approved by Health and Safety engineers who make them available in a shared repository and printed for use. LOTO sheets are printed in paper format and distributed in the shop floor and used in paper format by maintenance/production operators during activities on the machine. Thus, it is a time consuming activity for whole management process (creation, updating, validation, publishing, printing, distributing, deleting); moreover, there is a limited coverage of installed machinery by LOTO procedures (often not available or not updated); also the full execution certification is not available.
Thanks to the PERKS AI solutions, in the TO BE situation it will be possible to:
- Support operators to retrieve in the shop floor the right LOTO procedure to be executed
- Guide operators in the right sequence execution
- Capture feedback (manual or automatic) to certify the proper and complete execution
- Support engineers in LOTO procedures creation, maintenance, validation and publishing process
- Allow operators to contribute to LOTO maintenance
- Create a digital twin of the LOTO Knowledge
The AI solutions will have a strong impact since it will be possible to boost LOTO procedures definition and support to sustainable management, to support the safety requirements respect and safety policies compliance for workers protection, to support maintenance activities execution efficiency through digital tools and to engage workers for deeper awareness on safety risks.
CNC machines
Fagor Automation’s use case focuses on CNC system, which automates the control, movement and precision of a machine. It is a very complex system that must be correctly configured and parametrized on a machine. These machines usually have different configurations depending on the application and on the parts to be machined (milling machines, lathes, laser machines, grinding machines, etc.). This process is very time consuming and must be done by specialized and experimented staff.
There are two major tasks in this labor: on the one hand, the definition of the machine configuration, with increasing complexity depending on the number of channels, spindles, axes, etc.; and, on the other hand, the programming of the PLC, in charge of managing the automation of auxiliary equipment of the machine (including tool magazines, valves and protection elements).
The objective of the project is to improve the knowledge transfer of the machine commissioning process, from a senior technician to a new technician, using Artificial Intelligence based digital tools. At present the information is included in several manuals and the support of an expert technician is essential for a fairly long period of time, as each machine is different due to customizations to optimize its function in the workshop. The tools developed during this project will guide the new technicians through machine commissioning, ensuring that all steps are correctly done and checked, and offering them support in case of doubts.
Optimizing and standardizing this knowledge management will help our new technicians in their learning process, and will guide every technician during machine commissioning process, reducing time and errors.
Microgrid Testbed
Siemens will test and validate the PERKS AI solutions for the Procedural Knowledge management on its Microgrid (incl. e-mobility charging) testbed on the Siemens campus in Vienna. Offices and factories are linked to photovoltaic power plants, energy storage, charging points for electric cars, a microgrid controller, and a connection point to the external energy grid. Sensors measure the electricity flow and other related values at different points in the microgrid. With the help of the microgrid controller, the time-series data is collected using well-integrated interfaces and stored in a database. Energy usage optimization “rules” are currently automatically generated but not properly explained/documented (ad-hoc). The users of the microgrid are not involved in the optimization task although they are very relevant. The goal within this use case is to avoid energy peaks, to find optimised battery charging/discharging cycles (based on battery technical data) and increase sustainability by eliciting and exploiting procedural knowledge mined from expert and historical data.
White Goods Production Plant
Whirlpool will test and validate the PERKS AI solutions for the Procedural Knowledge management, in particular of the LOTO procedures used in the factory maintenance.
According to the AS IS situation, the LOTO digital sheets are created by process/maintenance engineers and have to be integrated, completed, validated and approved by Health and Safety engineers who make them available in a shared repository and printed for use. LOTO sheets are printed in paper format and distributed in the shop floor and used in paper format by maintenance/production operators during activities on the machine. Thus, it is a time consuming activity for whole management process (creation, updating, validation, publishing, printing, distributing, deleting); moreover, there is a limited coverage of installed machinery by LOTO procedures (often not available or not updated); also the full execution certification is not available.
Thanks to the PERKS AI solutions, in the TO BE situation it will be possible to:
- Support operators to retrieve in the shop floor the right LOTO procedure to be executed
- Guide operators in the right sequence execution
- Capture feedback (manual or automatic) to certify the proper and complete execution
- Support engineers in LOTO procedures creation, maintenance, validation and publishing process
- Allow operators to contribute to LOTO maintenance
- Create a digital twin of the LOTO Knowledge
The AI solutions will have a strong impact since it will be possible to boost LOTO procedures definition and support to sustainable management, to support the safety requirements respect and safety policies compliance for workers protection, to support maintenance activities execution efficiency through digital tools and to engage workers for deeper awareness on safety risks.
CNC machines
Fagor Automation’s use case focuses on CNC system, which automates the control, movement and precision of a machine. It is a very complex system that must be correctly configured and parametrized on a machine. These machines usually have different configurations depending on the application and on the parts to be machined (milling machines, lathes, laser machines, grinding machines, etc.). This process is very time consuming and must be done by specialized and experimented staff.
There are two major tasks in this labor: on the one hand, the definition of the machine configuration, with increasing complexity depending on the number of channels, spindles, axes, etc.; and, on the other hand, the programming of the PLC, in charge of managing the automation of auxiliary equipment of the machine (including tool magazines, valves and protection elements).
The objective of the project is to improve the knowledge transfer of the machine commissioning process, from a senior technician to a new technician, using Artificial Intelligence based digital tools. At present the information is included in several manuals and the support of an expert technician is essential for a fairly long period of time, as each machine is different due to customizations to optimize its function in the workshop. The tools developed during this project will guide the new technicians through machine commissioning, ensuring that all steps are correctly done and checked, and offering them support in case of doubts.
Optimizing and standardizing this knowledge management will help our new technicians in their learning process, and will guide every technician during machine commissioning process, reducing time and errors.
Microgrid Testbed
Energy Consumption Optimisation