The Meister Group, a Belgian industrial group supplying the automobile market, successfully deployed Cognex’s machine vision system to help its robotic assembly cell sort out defective parts. The result has been a significant decline in part defect rates and a six-month payback on investment.

Belgian parts supplier Meister Group uses a Cognex machine vision system to sort out defective or missing parts.
Meister has factories in Belgium, France and the Czech Republic, specializing in mass producing cut steel parts. The company’s French factory, located at Scionzier in Haute-Savoie, manufactures electric valve parts for automobile equipment manufacturers specializing in ABS braking systems. Nearly 24 multi-spindle lathes produce 120,000 parts each day, representing an annual production of 35 to 40 million parts.

The challenge for these modern production units, which use specialized precision lathes, is to manufacture relatively complex parts in a few seconds, and to guarantee part conformity on delivery, without ignoring the essential and continual search for productivity gains. In a sector where the smallest assembly line incident can lead to exhaustive investigations and complicated and costly procedures for the subcontractor, the quest to achieve zero faults is the only acceptable way forward.

One key assembly task is to sort out and separate defective or missing parts. Previously, operators manually checked for defective parts, a process yielding a part defect rate of 1 in a thousand – still considered too high. Besides reducing part defect rates, the company needed to reduce the impact of manpower costs on part cost.

Automating these vision tool checks was natural for Meister’s technicians, who already utilized industrial vision systems for a dimension checking application. Alpsitec, an approved system integrator of Cognex, enabled Meister to find out about the performance and capacities of the Cognex’s In-Sight vision systems.

Alpsitec was asked to verify that Cognex’s In-Sight cameras could “see” the faults they had to detect, in a production environment. After this first feasibility test, a prototype was assessed over a month. The simplicity of the use of the In-Sight systems was a decisive factor in choosing the system.

Comprising two independent test benches, the inspection system was installed at the end of the production line, in order to carry out a final check of all parts produced before shipment packing. In operation, the robot puts the part into mesh packaging, before picking it up and placing it on the test surface. The robot then takes hold of the Cognex In-Sight 1000 vision system linked to a lighting system and passes it along the mesh, over the part.

It’s important to remember that the vision system must inspect each part in order to detect any of four fault types resulting in removal: presence of metal shavings, missing components, loose components, and damage from knocks or vibration. The system sends information on the checks carried out to the robot’s control center. The robot then puts the vision system down and deposits the defective parts into separate chutes for each type of fault, which then carries them to a hopper. The system then continues operation.

One of the test benches is fitted with two In-Sight 1000 systems and operates at a rate of 6,000 parts per hour. The other system comprises a single sensor and works at a rate of 4,000 parts per hour. Both systems worked as dual sorters during the first few months of the operation.

The important part of updating the application consisted of identifying the various faults which the checking systems had to recognize and to “teach” them to the vision sensors. This procedure is essential to optimize the efficiency of the checking system.

The rate of faulty parts delivered to customers has rapidly dropped to 40 per million. The power of the processor algorithms of the In-Sight system and the finer analysis of the faults to be removed should allow this rate to be brought down even more to below 20 ppm.

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