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 Drones learn to navigate autonomously by imitating cars and bicycles
23.01.2018 | Universität Zürich

nachricht Cloud technology: Dynamic certificates make cloud service providers more secure
15.01.2018 | Technische Universität München

All articles from Information Technology >>>

The most recent press releases about innovation >>>

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

Im Focus: Optical Nanoscope Allows Imaging of Quantum Dots

Physicists have developed a technique based on optical microscopy that can be used to create images of atoms on the nanoscale. In particular, the new method allows the imaging of quantum dots in a semiconductor chip. Together with colleagues from the University of Bochum, scientists from the University of Basel’s Department of Physics and the Swiss Nanoscience Institute reported the findings in the journal Nature Photonics.

Microscopes allow us to see structures that are otherwise invisible to the human eye. However, conventional optical microscopes cannot be used to image...

Im Focus: Artificial agent designs quantum experiments

On the way to an intelligent laboratory, physicists from Innsbruck and Vienna present an artificial agent that autonomously designs quantum experiments. In initial experiments, the system has independently (re)discovered experimental techniques that are nowadays standard in modern quantum optical laboratories. This shows how machines could play a more creative role in research in the future.

We carry smartphones in our pockets, the streets are dotted with semi-autonomous cars, but in the research laboratory experiments are still being designed by...

Im Focus: Scientists decipher key principle behind reaction of metalloenzymes

So-called pre-distorted states accelerate photochemical reactions too

What enables electrons to be transferred swiftly, for example during photosynthesis? An interdisciplinary team of researchers has worked out the details of how...

Im Focus: The first precise measurement of a single molecule's effective charge

For the first time, scientists have precisely measured the effective electrical charge of a single molecule in solution. This fundamental insight of an SNSF Professor could also pave the way for future medical diagnostics.

Electrical charge is one of the key properties that allows molecules to interact. Life itself depends on this phenomenon: many biological processes involve...

Im Focus: Paradigm shift in Paris: Encouraging an holistic view of laser machining

At the JEC World Composite Show in Paris in March 2018, the Fraunhofer Institute for Laser Technology ILT will be focusing on the latest trends and innovations in laser machining of composites. Among other things, researchers at the booth shared with the Aachen Center for Integrative Lightweight Production (AZL) will demonstrate how lasers can be used for joining, structuring, cutting and drilling composite materials.

No other industry has attracted as much public attention to composite materials as the automotive industry, which along with the aerospace industry is a driver...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

10th International Symposium: “Advanced Battery Power – Kraftwerk Batterie” Münster, 10-11 April 2018

08.01.2018 | Event News

See, understand and experience the work of the future

11.12.2017 | Event News

Innovative strategies to tackle parasitic worms

08.12.2017 | Event News

 
Latest News

Rutgers scientists discover 'Legos of life'

23.01.2018 | Life Sciences

Seabed mining could destroy ecosystems

23.01.2018 | Earth Sciences

Transportable laser

23.01.2018 | Physics and Astronomy

VideoLinks Science & Research
Overview of more VideoLinks >>>