Machine vision makes its mark on the automotive industry

Automotive Manufacturing & Production, March, 1997 by Stephen Kress

What has changed? Most importantly, the systems themselves have become more powerful while gaining much greater ease of use. Thanks to advances in several related technologies - especially computer interfaces and microprocessors - machine vision has evolved into a highly capable and flexible tool for both mass-production and custom manufacturing of suppliers and OEMs alike.

The Basics of Vision Technology

The primary goal of most machine vision systems is to improve productivity and quality in the manufacturing process. On a typical production line, a sensor detects the presence of a part and signals the vision system to activate a video camera, positioned above or to the side of the inspection point, to capture an image of a part or subassembly and send it to a machine vision processor. This processor is usually configured as either a box-level unit or a plug-in board for the PC or the VMEbus.

Using a combination of hardware and machine vision software, the vision system analyzes the image, usually in a fraction of a second. In this stage, it might determine where the part is located, analyze its orientation, measure critical dimensions, read or verify an identification code, or verify correct assembly. At the completion of each image analysis, the machine vision communicates the results to other factory equipment - such as programmable logic controllers (PLCs), robots or data collection computers.

Advanced vision systems each have their own application development software. Traditionally, the development tools for these systems have required extensive programming expertise - usually in the "C" computer language. However, the newest generation of systems makes it relatively easy to take advantage of powerful machine vision capabilities through easy "point and click" graphical environments.

On a typical automotive production line two important factors can affect the performance of a machine vision system: materials handling and lighting. Typically, most lines use conveyors, indexing tables, or robotic arms to move the parts into position for inspection. Lighting requirements vary from one application to another - ranging from the simple use of ambient room illumination to filters, backlights and strobes that "freeze" images for vision processing on high-speed lines.

How Vision Applications Work

Most vision applications in the automotive industry are for machine guidance or quality inspections. In quality control inspections, the vision system determines whether parts or subassemblies are acceptable or defective and then directs motion control equipment to reject or accept them. Machine guidance applications use vision systems to improve the accuracy and speed of assembly robots and automated material handling equipment.

Although they can vary in a number of ways, the applications are usually in one of several general categories.

Robotics. The most advanced machine vision systems enable a robot to locate the part or subassembly on which it is working, regardless of rotation or scale. In most applications, machine vision systems provide real-time data and live feedback to guide robots as they go through programmed sequences of operations. To perform this level of machine guidance, a vision system usually locates parts for the robot to pick up, identifies the correct locations at which to place or fasten the parts, and sends this information to the robot for the assembly procedure.

Dimensional Gaging. With their precise recognition capabilities and easy programmability, the new generation of machine vision systems excels at ensuring that those measurements are correct. Dimensional gaging by machine vision often involves a variety of odd lines, angles, arcs, diameters, and tolerances. Almost without exception, the systems can measure them much more quickly, and with far greater reliability and accuracy than would be possible with even the most sophisticated manual methods.

Assembly Verification. Once again, here is an area in which the new generation of machine vision is proving its worth. Users easily "train" vision systems to look for detailed patterns and shapes that match templates for correctly made subassemblies. The systems accomplish those inspections better than virtually any other quality control method - manual or automated.

Flaw Detection. This has become a primary mission for many machine vision systems on automotive industry production lines. These vision systems use powerful pattern recognition capabilities to find missing material, chips, scratches, dents, misplaced markings, and a wide variety of other flaws. In addition to ensuring the quality of finished parts and products, they also enable manufacturers to reduce costs by eliminating defective pieces before wasting additional material and production time on them.

Print Verification. Using various optical character verification (OCV) methods, machine vision systems inspect parts, components and labels to make sure that they are labeled and marked correctly. Due to various types of marking methods commonly used on automotive parts, this task is not always as simple as it may initially seem. The vision systems must often learn to deal with variations in character density, inking and shapes, as well as the secondary effects of laser etching, stamping and engraving.