Towards increased intelligence and automatic improvement in industrial vision systems
Paper i proceeding, 2018

Robots and in-process inspection systems equipped with machine vision solutions are used for increased flexibility and quality in automated manufacturing. Although vision systems have found wide industrial use, there are still problems regarding optimization of vision system robustness and capabilities. This paper presents a comprehensive case study of vision system functions, techniques and capabilities in an automotive 1-tiers supplier. Based on the study, the paper further describes a method for systematic improvement of industrial vision systems on a continuous basis. This is proposed to be done by establishing a data store and data analysis system, based on training machine learning models in an off-line mode using the historical data, as well as on on-line stream processing.

Stream processing

Data flow

Machine vision

Optimization

Machine learning

Författare

O. Semeniuta

Norges teknisk-naturvitenskapelige universitet

S. Dransfeld

SINTEF Raufoss Manufacturing AS

Kristian Martinsen

Norges teknisk-naturvitenskapelige universitet

Petter Falkman

Chalmers, Elektroteknik, System- och reglerteknik, Automation

Procedia CIRP

22128271 (ISSN)

Vol. 67 256-261

11th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2017
Ischia, Naples, Italy,

Ämneskategorier

Produktionsteknik, arbetsvetenskap och ergonomi

Inbäddad systemteknik

Robotteknik och automation

DOI

10.1016/j.procir.2017.12.209

Mer information

Senast uppdaterat

2019-01-07