Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

‘SMART’ quality control system cuts risk of human error on assembly lines

16.12.2008
Artificial intelligence has been used in a EUREKA-backed project to develop a quality control system that greatly reduces the risk of human error on assembly lines.

The four teams who worked on Project E!3450-QSPAI have achieved a non-contact activation program that commands and monitors laser-scanning for precise panel measurement, and triangulation methods for positioning components.

Although existing technologies, notably in computing and lasers, have been used, it is their integration that makes this control system unique.

The project was instigated and led by Trimo d.d., a specialist engineer and producer of prefabricated steel buildings and components, based at Trebnje, some 50 km south-west of Ljubljana. The other partners were two faculties of the University of Ljubljana – Computer and Information Science, and Electrical Engineering – and the Institut fuer Sandwichtechnik, of Mainz, Germany.

The challenge
Trimo wanted greater quality control during its manufacture of Trimoterm lightweight, fireproof sandwich-panels as the process was prone to delays and other glitches, including human actions, which impact on product quality.

Operators were unable to monitor continuously each of the many production steps; neither could they predict all the indirect consequences of actions performed on the line. And manual inspection could miss such faults as measurement errors, and colour deviations between batches.

The main concern was the long reaction time in correcting errors. As destructive and discrete analysis of sample panels was practical only a few times each day, faulty panels could go unnoticed until arrival at the construction site, or, worse, after application.

The achievement
The project task teams have created a system that achieves control of disparate parameters, ranging from the type and quality of input materials to the settings and current state of the assembly line. The unified system governs both the speed of production, and, even more importantly, the individual processes that take place on the line.

One of the first development tasks was to write a program for artificial intelligence (AI) – advanced data processing – that could “learn” the manufacturing process by “mining” the records of assembly line parameters. AI proved its value in detecting errors, discovering correlations between parameters, and indicating areas where the process could be improved.

Initial monitoring of the process identified numerous reasons for delays. These reasons fell into three basic categories: organizational demands, processing errors, and inappropriate quality of material. Organisational delays could occur when equipment was re-set for different types of product, during the changeover to other components, and even in the scheduling of workers' rest breaks. Production delays included breakdowns of mechanical equipment, poor line control, and process errors. The human factor proved especially difficult to determine as actions could have indirect influences.

Results and outlook
A prototype system – which was installed without disrupting the factory’s production schedule – is running successfully, but without the AI program. Although AI was central to the initial phase of development, the reliability of the learning algorithms (instruction sequences) needs to be improved, especially concerning the measurement of input material, and the speed of gathering information.

The present system, however, is providing a high degree of control, resulting in a significant increase in productivity with fewer rejects. Viktor Zaletelj, the QSPAI Project Manager at Trimo, says that feedback from continuous monitoring of the entire process enables operators to correct faults almost as soon as they develop, and even to spot potential problems.

“These results have encouraged the participants to continue developing the AI program so that it can be interfaced with the control system’s measurement and data processing capabilities. It is feasible that we can fulfil our original intent to build a system that mostly relies on ‘machine learning’ to maintain quality.”

Shar McKenzie | alfa
Further information:
http://www.eureka.be/qspai

More articles from Information Technology:

nachricht Who can find the fish that makes the best sound?
28.02.2017 | Technische Universität Wien

nachricht Many Android password managers unsafe
28.02.2017 | Fraunhofer-Institut für Sichere Informationstechnologie SIT

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Researchers Imitate Molecular Crowding in Cells

Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to simulate these confined natural conditions in artificial vesicles for the first time. As reported in the academic journal Small, the results are offering better insight into the development of nanoreactors and artificial organelles.

Enzymes behave differently in a test tube compared with the molecular scrum of a living cell. Chemists from the University of Basel have now been able to...

Im Focus: Safe glide at total engine failure with ELA-inside

On January 15, 2009, Chesley B. Sullenberger was celebrated world-wide: after the two engines had failed due to bird strike, he and his flight crew succeeded after a glide flight with an Airbus A320 in ditching on the Hudson River. All 155 people on board were saved.

On January 15, 2009, Chesley B. Sullenberger was celebrated world-wide: after the two engines had failed due to bird strike, he and his flight crew succeeded...

Im Focus: Breakthrough with a chain of gold atoms

In the field of nanoscience, an international team of physicists with participants from Konstanz has achieved a breakthrough in understanding heat transport

In the field of nanoscience, an international team of physicists with participants from Konstanz has achieved a breakthrough in understanding heat transport

Im Focus: DNA repair: a new letter in the cell alphabet

Results reveal how discoveries may be hidden in scientific “blind spots”

Cells need to repair damaged DNA in our genes to prevent the development of cancer and other diseases. Our cells therefore activate and send “repair-proteins”...

Im Focus: Dresdner scientists print tomorrow’s world

The Fraunhofer IWS Dresden and Technische Universität Dresden inaugurated their jointly operated Center for Additive Manufacturing Dresden (AMCD) with a festive ceremony on February 7, 2017. Scientists from various disciplines perform research on materials, additive manufacturing processes and innovative technologies, which build up components in a layer by layer process. This technology opens up new horizons for component design and combinations of functions. For example during fabrication, electrical conductors and sensors are already able to be additively manufactured into components. They provide information about stress conditions of a product during operation.

The 3D-printing technology, or additive manufacturing as it is often called, has long made the step out of scientific research laboratories into industrial...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

Booth and panel discussion – The Lindau Nobel Laureate Meetings at the AAAS 2017 Annual Meeting

13.02.2017 | Event News

Complex Loading versus Hidden Reserves

10.02.2017 | Event News

International Conference on Crystal Growth in Freiburg

09.02.2017 | Event News

 
Latest News

A better way to measure the stiffness of cancer cells

01.03.2017 | Health and Medicine

Exploring the mysteries of supercooled water

01.03.2017 | Physics and Astronomy

Research team of the HAW Hamburg reanimated ancestral microbe from the depth of the earth

01.03.2017 | Life Sciences

VideoLinks
B2B-VideoLinks
More VideoLinks >>>