The assembly collaborative robot considers both the operation being performed and operator’s anthropometric characteristics for control program selection and part positioning. Besides, the workplace includes multimodal interactions with both the dual arm assembly and logistic robots as well as with the Manufacturing Execution System. Verbal interaction includes natural speaking (i.e. Spanish language) and voice-based feedback messages, while nonverbal interaction is based on gesture commands considering both left and right-handed workers and multichannel notifications (e.g. push notifications, emails, etc.). Furthermore, the maintenance technician is assisted by on event Intervention request alerts, maintenance decision support dashboard and AR/VR based step by step on the job guidance.

An AR based solution is proposed for instructions visualization enabling also on-job training activities and guidance. Regarding the ergonomics, an autonomous tool-trolley has been integrated including voice command and AR based gesture steering.

The proposed solution comprises an adaptive smart tool and an AR instruction application using HoloLens wearable devices and a framework for ensuring digital continuity starting from the data recorded in the system for manufacturing engineering up to the execution and analysis phase

The Battery Pilot will aim at demonstrating that the DigiPrime platform can unlock a sustainable business case targeting the remanufacturing and re-use of second life Li-Ion battery cells with a cross-sectorial approach linking the e-mobility sector and the renewable energy sector, specifically focusing on solar and wind energy applications.

As the proactive exploitation of the DigiPrime platform enables the car-monitored SOH tracing and availability, less testing is needed to assess the residual capacity of the battery. Moreover, by knowing the structure of the battery packs, a decision support system can be implemented to adjust the de-and remanufacturing strategy accordingly and select the most proper cells for re-assembly second-life modules, thus unlocking a systematic circular value chain for Li-ion battery cells re-use. Furthermore, excessively degraded cells which cannot be re-used can be sent to high-value recycling, based on the knowledge of their material compositions.

Benefits:

• Interoperability with legacy data management solution (e.g. MindSphere, HANA, etc.)
• Open solution acting as horizontal stack that connects legacy systems.
• Speeding up the development of digitalized industrial processes both in pilot and factory scale.

Manufacturing systems are often characterised by ‘silos’ of data which cannot be accessed easily horizontally, and by varied and incompatible data types. By utilising a single data bus for all data to be transmitted on, standards are more easily implemented and all data is accessible by all equipment.
This is particularly important in this context where diverse sources of data (such as metrology systems, CAD data) must be analysed by software (e.g. data analytics, metrology software), and then used to adapt a process (e.g. robotic pathing, machining processes).

When a manufacturing system is fixed and will repeat the same tasks, having hard-coded and non-dynamic data exchange may be sufficient. When a system is reconfigurable and flexible, being able to define data sources and destination in software is critical (so-called software-defined networking).

Integration of adaptive robot control technology into a complex and variable manufacturing process allows for accurate positioning of assembly components despite variability in component manufacture, existing assembly deviation, and the robots themselves.

This allows for progress towards jig-less assembly – saving non-recurring costs in the assembly of large, low batch products. Rather than building large, welded jigs and fixtures, robots are used to position and align parts. As the robots can easily be reused, this saves significant time and money.

Note: Since this demonstrator implementation, the Adaptive Robot Control and K-CMM technologies are now available from True Position Robotics .

The realized progress advances the state of the art in several aspects:                                               

• Electric machine design process including electromagnetic finite element computation, winding design, and post-processing are available on a pay-per-use basis as a cloud solution. To the knowledge of the experiment partners, such a solution has never before been presented.
• Seamless, automated creation of production data avoids data handover errors and provides fast transition from simulation and design to manufacturing of motor prototypes. The full parametric manner of realization also provides a feature never available before.
• The capability to bring a customer requirement in the form of a motor specification to a fully functional motor prototype within one week is a revolutionary USP for Hanning. Despite the fact that this capability still needs to be demonstrated in real life, the steps taken into this direction have greatly improved Hanning’s process know-how and agility.

CETMA was able to exploit the possibilities that customized simulation offers to SME’s specialized in boat hulls manufacturing. Thanks to cloud resources, enough power computing is available to analyze different scenarios in a few days instead of several weeks.
Designers of CATMARINE and SKA are now able to achieve high-quality products by analyzing different manufacturing scenarios without wasting time, money and material. The platform is able to optimize the resin injections points/vents and verify the presence of defects in the final product, thus ensuring a complete and correct mold-filling.

https://www.cloudifacturing.eu/experiment2outcome/