Accelerated ramp-up of assembly systems through self-learning

Abstract

The ramp-up process of assembly systems has a huge impact on both the productivity of those systems and the quality of the output. In this work we present a new technique for accelerating the ramp-up process by automatically capturing knowledge about a machine and subsequently reusing it to inform an engineer performing ramp-up. This technique relies on a novel process called the Knowledge Object Algorithm. The technique is explained and demonstrated using synthetic data, designed to emulate a typical use case of such a system. The future direction for this work is also outlined and further experiments detailed. © 2012 IFIP International Federation for Information Processing.