FA3D mapped on Significant innovations and lessons learned, training aspects

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 .

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).

Though the integration of adaptive robot control represents a significant upfront cost, the ability to save money on fixturing in the long term makes the creation of low batches of large, accurate products a more realistic proposition for small to medium enterprises.

As the robots can be re-used over and over for different situations, it enables significant flexibility in what products and product variants can be built.

SMEs often have an advantage over larger companies by being agile and able to change to meet demands more easily. However, this is only possible with an agile and flexible data system. For many SMEs, this burden is carried by human workers, with manual and often paper-based data management and exchange systems.

By implementing a common manufacturing service bus for data, this reliance on human data input (and the associated risk of error and time burden for skilled engineers) can be reduced, and data standards can be more easily implemented.

The ARC robotic control system is extremely effective for bringing a robot / part to a specific and highly accurate location. However, it does not allow for accuracy along a path, so would not be appropriate for continuous path accuracy e.g. robotic milling or welding.

The large amount of metal in the cell (robots, parts) dramatically lowered the accuracy that was possible with the RFID positioning system. Rather than being able to track parts to a specific location, we could determine no better than if a part was inside or outside the cell. Active RFID tags may help mitigate this.

K-CMM technology was extremely effective, but subject to line-of-sight restrictions for large assemblies such as aerospace fuselages.

When integrating technologies and solutions from multiple equipment vendors, the challenge is almost always interoperability and standards compliance. The ARC system was comparatively simple to integrate and commission, but integration into the larger context of a manufacturing process with a SCADA and other physical devices was more of a challenge.

For flexible, reconfigurable systems where everything is connected together and must utilise a common data format, selecting the correct data format and a common structure for its use is key. B2MML worked very well for this application, but there is still scope for variation in the way terms and variables are defined, which must be settled on.

Converting an agreed process plan for manufacturing into the B2MML has some degree of automation, but also required a large amount of manual processing. More time should have been spent on automating this process.
Ideally, all components of the system would communicate directly with the service bus. Practically, not all devices will support the service bus, so use of an intermediary communication protocol such as OPC UA may be necessary. 

Although process control may all be centralised with a manufacturing service bus, safety systems may not be. This can cause unexpected system behaviour when the system starts a new process unless the safety system is fully understood by the users. 

Selection of flexible technologies and standards does not necessarily mean that any given implementation using those technologies will be flexible. A system implementation must be designed specifically to be flexible and future proof.