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 Five developments for improved data exploitation
19.04.2017 | Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, DFKI

nachricht Smart Manual Workstations Deliver More Flexible Production
04.04.2017 | Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, DFKI

All articles from Information Technology >>>

The most recent press releases about innovation >>>

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

Im Focus: Deep inside Galaxy M87

The nearby, giant radio galaxy M87 hosts a supermassive black hole (BH) and is well-known for its bright jet dominating the spectrum over ten orders of magnitude in frequency. Due to its proximity, jet prominence, and the large black hole mass, M87 is the best laboratory for investigating the formation, acceleration, and collimation of relativistic jets. A research team led by Silke Britzen from the Max Planck Institute for Radio Astronomy in Bonn, Germany, has found strong indication for turbulent processes connecting the accretion disk and the jet of that galaxy providing insights into the longstanding problem of the origin of astrophysical jets.

Supermassive black holes form some of the most enigmatic phenomena in astrophysics. Their enormous energy output is supposed to be generated by the...

Im Focus: A Quantum Low Pass for Photons

Physicists in Garching observe novel quantum effect that limits the number of emitted photons.

The probability to find a certain number of photons inside a laser pulse usually corresponds to a classical distribution of independent events, the so-called...

Im Focus: Microprocessors based on a layer of just three atoms

Microprocessors based on atomically thin materials hold the promise of the evolution of traditional processors as well as new applications in the field of flexible electronics. Now, a TU Wien research team led by Thomas Müller has made a breakthrough in this field as part of an ongoing research project.

Two-dimensional materials, or 2D materials for short, are extremely versatile, although – or often more precisely because – they are made up of just one or a...

Im Focus: Quantum-physical Model System

Computer-assisted methods aid Heidelberg physicists in reproducing experiment with ultracold atoms

Two researchers at Heidelberg University have developed a model system that enables a better understanding of the processes in a quantum-physical experiment...

Im Focus: Glacier bacteria’s contribution to carbon cycling

Glaciers might seem rather inhospitable environments. However, they are home to a diverse and vibrant microbial community. It’s becoming increasingly clear that they play a bigger role in the carbon cycle than previously thought.

A new study, now published in the journal Nature Geoscience, shows how microbial communities in melting glaciers contribute to the Earth’s carbon cycle, a...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

Expert meeting “Health Business Connect” will connect international medical technology companies

20.04.2017 | Event News

Wenn der Computer das Gehirn austrickst

18.04.2017 | Event News

7th International Conference on Crystalline Silicon Photovoltaics in Freiburg on April 3-5, 2017

03.04.2017 | Event News

 
Latest News

New quantum liquid crystals may play role in future of computers

21.04.2017 | Physics and Astronomy

A promising target for kidney fibrosis

21.04.2017 | Health and Medicine

Light rays from a supernova bent by the curvature of space-time around a galaxy

21.04.2017 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>