Even small mistakes along the production lines of the Fiesta and Fusion models could cause serious problems. If an error in the assignment of a vehicle occurred, a five-door model could be identified as a three-door model, or the other way around. If a robot was, for example, working on the roof seam of the mixed-up vehicle, this would lead to a “crash,” and the line would come to a standstill for quite some time. More than 45 vehicle types must be distinguished and individually identified. Safe identification is therefore essential for a smooth production process and vehicle quality.
For more than a year, two reading systems installed at the Ford–Werke facilities have been recognizing the ID plates in the assembly shop. In three-shift operation, and presently producing about 1,900 vehicles per day, every ID plate is identified with a high degree of safety.
Safe and reliable functions along all production facilities are of utmost importance to Ford–Werke. Furthermore, the regulations and functional specifications for the suppliers of automation systems are correspondingly rigorous in the automotive industry.
Highest DemandsIn the past, the car bodies in the production process were equipped with radio-controlled data carriers. But after a few hundred runs through the car body pretreatment and the paint shop, the data carriers resembled shapeless lumps, and it was not possible to clean them. This spoke in favor of searching for a new system solution. Ford–Werke then engaged RESA System Engineering GmbH (Cologne, Germany) to provide a modern system solution with a more sophisticated technology. RESA provides solutions in the field of control and automation engineering and has been a partner of Ford–Werke for years.
Harald Maaß, project manager for RESA, who is responsible for the new system solution, says, “The only option under discussion from the very beginning was to employ optical character recognition (OCR) to read the characters. And for this purpose, we needed a competent image processing partner who would be able to meet the restrictive demands.”
The intention was to have a system read the type plates with the inscribed characters. These plates had to remain durably connected to the car body. Ford–Werke demanded a reading reliability of 99.9%, and every car was meant to be guided by this OCR identification. An error of 1 per 1,000 during steady production would, however, mean that at least one problem would occur per day. This had to be excluded by all possible means. And that is why the second decimal place of the reading reliability rating is still an important factor regarding the effectiveness of the production process and its costs. The demand was therefore to improve the 99.9% toward 100% as far as possible.
A variety of different requirements had to be fulfilled in this context. The type plate and the fastening surroundings of the raw car body in the department consisted of shiny, strongly reflective metal. The pretreatment of the car body through electro-galvanic surface treatment using the dipping method created a phosphate coating with strong light absorbing properties.
Thus it was necessary to be able to cope with both situations with extreme reliability.
Various providers of image processing systems were given small sample plates and asked to offer solutions to the problem. The solution that machine vision integrator AIT Göhner GmbH (Stuttgart, Germany) had to offer stood out from the other competitors with regard to guaranteed reading reliability. The operation of the vision software was the key factor in the decision to use AIT’s solution.
Efficient Vision AlgorithmsReading characters by means of OCR belongs to the most advanced forms of identifying imprinted plain characters. The high degree of certainty in reading requires a considerable amount of computer power because of the algorithms used in the evaluation process. Such particularly advanced tasks are still primarily restricted to PC-based systems. As opposed to validating the readability of the trained characters by means of optical character verification (OCV) inspection, in OCR inspection, every character is compared with the sample characters of the alphabet and the numerals. This leads to an up to 40-fold increase of the complexity of algorithm computation. The characters engraved in the type plate must fulfill the requirements for clear readability within a narrowly configurable quality threshold. It is necessary to be able to cope with variations in processing quality and the reflection behavior of the individual metal-bright engraved characters.
The gray value correlation procedure generally used in image processing reaches the limits of its applicability very quickly if the highest degree of precision is in demand, and influences such as varying illumination and contrast conditions must be handled. The OCR software used at the Ford–Werke plant is based on the geometry-based vision software PatMax from Cognex Germany Inc. (Karlsruhe, Germany). Unlike the gray value correlation, these patented techniques use the basic geometrical structures of objects in a three-step procedure.
First, the most important individual features in the image of the object, such as edges, measurements, shapes, angles, bends and shades, are separately identified. The spatial relations between these central features of the trained pattern are compared with the real-time image. The position of the object and its qualities are then determined from the analysis of the geometrical information of the features and their spatial relation to each other. Features, such as the contours of the characters with low contrast, can then be recognized with a considerably high degree of reliability, precision and speed. This procedural method, up to computer-aided design (CAD) reference models, provides an important contribution to the reliable recognition of characters.
For example, PatMax can immediately recognize where further features are to be found on the basis of a partial contour, despite distortion, displacement and shifting, or coverage. It is not necessary to first conduct a linear analysis of the complete image, which simplifies feature-finding.
PatMax also can handle very high resolutions down to the sub-pixel range and the determination of angles down to 0.02 degrees. The vision tool is invariant with regard to positioning, orientation and varying scales of an object. The simultaneous examination of contour and structure of the object image also compensates changing lighting and contrast conditions.
Reliability from ScratchA speedy and reliable solution was important for this image-processing task. Because when the plant shuts down for vacation, the production line at Ford–Werke starts up in three-shift operation, five days a week. That is why the reading station had to be up and running without problems from the very beginning. The PC-based vision system with the MVS 8500 frame grabber has a vibration-proof industrial PC, and a second PC is held in stand-by as a redundant system.
Regarding the installation phase, Maaß says, “After the training phase, the system ran with a reading reliability as good as 100% dependability.”
However, several problems were to be solved beforehand. The riveting point of the plate serves as a reference point for image processing. The numerals may in some instances show displacement to the reference point. Incorrect placement of the plates will immediately trigger an error message, and the car body will be removed from the line to a repair area.
In raw condition, the ID plate, and the car body as well, displays a metal- bright surface. Even insignificant alterations of the position of the plate make the human eye perceive totally different reading conditions. The reading reliability was an issue for the vehicle type Fiesta, and later on for the Fusion model. This required the optimal customization of the illumination by means of fluorescent lamps and the training of the characters.
Strong light-absorbing conditions were created by the pretreatment using the electro-galvanic dipping technique, warranting the use of a reflector light. The reading station installed after the pre-treatment has an important function. The read ID data (Carin-number) is sent to the Siemens control S7 and the central production administration system (PAS) and compared there. If it should occur that, for example, an F is sent to the PAS from the reading station instead of an H, an error message will be immediately returned because the comparison and the assessment do not make sense. The PAS will then send the data for a label according to the type of vehicle and its accessories, which is glued to the bottom side of the floor of the vehicle. A control scan and a comparing check with the PAS is carried out after the application of this label. This course of procedures ensures that no mix-ups regarding the vehicle equipment occur, and that only faultless quality remains in the production process. This label is needed at about another 20 production stations for the definite identification of vehicles and their equipment. This complete procedure at the reading station must be carried out within a cycle time of 37 seconds.
Regarding the production, Maaß says, “After about one year on the production line, we can say that we have not only met our specifications, we have clearly exceeded them. Our reading reliability and the availability have proven themselves to be important contributions to a smooth and efficient process.”
Benefits- With PatMax-based OCR software, Ford–Werke is experiencing a near 100% dependability rate.
- The software’s algorithms allow the reading of characters on both dull and shiny surfaces-a requirement for Ford–Werke.
- The machine vision solution eliminates the hassle of radio-controlled data carriers, which were ruined after a few hundred production runs.