High flexibility in both industries organization and production systems is the requirement to face the demand growing stress on shorter development lead-time and the uncertainty of a more and more complex market.
Small and medium enterprises (SMEs) typically face high-mix low-volume production and so handwork is preferred to hard automation as it cannot deal with a high variety of products which are produced in small batches. Additionally, the growing competition coming from the global market increases the industry attention to productivity, costs and keeping the risk low.
Robotic manufacturing and assembly systems are considered the way ahead in providing a solution to the above challenges.
Among the different manufacturing processes, assembly has always drawn the biggest challenges in factory automation due to operations high complexity and variety. As a result, many assembly processes are still carried on manually.
Nonetheless, as quality, productivity and repeatability rate in the assembly increases, automating the process becomes utterly essential for the manufacturing industries. Coupling, joining, handling, recognition (orienting and placing bulk-fed components) and inspection of parts are among the most typical operations in the assembly. All of the above requires accurate, precise and repeatable material handling.
Typical material to be handled is components infeed, pallets, fixtures, tools and finished parts outfeed. Parts feeding has always been the highest challenge in the assembly.
Though dedicated solutions that orient and position parts mechanically is the typical approach to parts feeding, key academics and applied researches are lately stressing the need of applying feeding systems that are modular, reconfigurable and easy to set up, such as vision-based solutions.
Machine vision is widely applied in factory automation for quality and dimensional check and robot guidance. Flexibility and a higher production quality can be obtained if a vision system is properly introduced in the assembly operations. Above all, flexibility is worthy of special attention. Pallets and other fixed placing equipment may involve significant resources which could be kept for investments with higher return if vision system is applied into assembly cells.
There’s a number of aspects that influences the results of a vision system application, such as:
- Parts characteristics (size, shape, colour and texture);
- Camera specs (sensor resolution, quality of lenses);
- Quality of the system calibration;
- Working environment (lighting conditions and position). Vision algorithms are typically sensitive to the environment.
Processing time is a key factor when applying a vision system for robot guidance in assembly processes. Pictures in high-resolution requires efficient algorithms to be run in order to keep the processing time as tight as possible. Manufacturing flexibility can only be achieved by keeping machines updated with smart and efficient industrial technologies.
100 x 3 mm
1 x 1 mm
30 x 30 mm
10 x 4 mm
What advantages does the FlexiBowl® solution bring in for flexible parts assembly operations?
FlexiBowl® is a flexible feeding device that can be smoothly integrated with every robot and vision system brand. Entire families of parts within 1-250 mm and 1-250 g can be handled by a single FlexiBowl® replacing a whole set of dedicated vibratory bowl feeders. No more parts jams and exhausting mechanical adjustments.
An oil channel can be applied optionally to dry the FlexiBowl® up of working fluids left on the parts during upstream processes. The rotary discs can be switched over rapidly thanks to the quick changeover mechanism that minimizes downtime during maintenance operations.
Its lack of dedicated tooling and its easy to use and intuitive software allows quick and multiple product changeovers inside the same work shift.