A comparison of the manufacturing resilience between fixed automation systems and mobile robots in large structure assembly
conference contributionposted on 29.07.2016 by Spartak Ljasenko, Niels Lohse, Laura Justham
Any type of content contributed to an academic conference, such as papers, presentations, lectures or proceedings.
The modern manufacturing industry is undergoing major transformations due to global competition and rapidly changing market demands. Traditional systems with rigid structures are very difficult to reconfigure every time a change in production is required. A promising alternative to these is seen in mobile, self-organising manufacturing systems, where self-deploying and independent entities such as mobile robots are used to facilitate a more reconfigurable assembly process. In addition, an integral part of manufacturing is the transportation of components within the manufacturing environment. Conveyor systems are often unsuitable for moving components that are large, heavy or awkward, making them difficult to use in large structure assembly. Currently, such components are commonly transported by cranes to dedicated automation systems which are seen as expensive and unadaptable. In this paper we investigate the differences in resilience to variations between a set of mobile robots and the widely accepted fixed automation systems under different conditions. Therefore, instead of transporting components or parts to manufacturing equipment we analyse the potential benefits of transporting the equipment to the large parts. By means of simulations, the two systems are compared to one-another in scenarios of identical part arrival times and part processing capacities. Assuming equal production rates, we assess their ability to respond to (1) rush orders, (2) variable arrival times and (3) production mix variation. Currently, there are no specific algorithms for process control of such mobile systems. For this reason we apply the First-In-First-Out task-selection rule. We present a comparison of resilience measures between the systems.
- Mechanical, Electrical and Manufacturing Engineering