The use of machine vision technology is growing very rapidly, spurred by the need of manufacturers for increasingly fine control over the quality of manufactured parts. Melles Griot is a leading supplier of machine vision components and custom vision modules.

Machine vision technology integrates imaging components and electronics with computerized analysis and control systems to identify, measure, sort, and inspect components as they proceed through an automated process. Machine vision systems typically are fast enough to inspect 100% of the product being processed without slowing up the manufacturing line. This ability is extremely important since more and more manufacturers are requiring "six-sigma" (fewer than three defective parts per million) results in order to be competitive in today's quality-conscious market. Furthermore, these systems are ideally suited to statistical process control (SPC). They deliver the continuous, consistent, and precise measurements SPC demands, enabling the manufacturer to adjust process parameters before the process goes out of control or produces bad parts. Machine vision systems are more adaptable than traditional optical or mechanical sensors. They offer the versatility and flexibility of a robot. When alterations to the manufacturing process are required, these systems are easily reconfigured, often with only minor software changes.

What is Machine Vision?

Machine vision technology uses a imaging system and a computer to analyze an image and to make decisions based on that analysis. There are two basic types of machine vision applications - inspection and control. In inspection applications, the machine vision optics and imaging system enable the processor to "see" objects precisely and thus make valid decisions about which parts pass and which parts must be scrapped. In control applications, sophisticated optics and software are used to direct the manufacturing process. Machine vision-guided assembly can eliminate any operator error that might result from doing difficult, tedious, or boring tasks; can allow process equipment to be utilized 24 hours a day; and can improve the overall level of quality. The following process steps are common to all machine vision applications:

• Image acquisition: An optical system gathers an image, which is then converted to a digital format and stored into computer memory.
  
  
• Image processing: A computer processor uses various algorithms to enhance elements of the image that are of specific importance to the process.
  
  
• Feature extraction: The processor identifies and quantifies critical features in the image (e.g., the position of holes on a printed circuit board, the number of pins in a connector, the orientation of a component on a conveyor) and sends the data to a control program.
  
  
• Decision and control: The processor's control program makes decisions based upon the data. Are the holes within specification? Is a pin missing? How must a robot move to pick up the component? Machine vision technology is used extensively in the automotive, agricultural, consumer product, semiconductor, pharmaceutical, and packaging industries, to name but a few. Some of the hundreds of applications include vision-guided circuit board assembly, and gauging of components, razor blades, bottles and cans, and pharmaceuticals.

Advantages of Machine Vision

A machine vision system that has been carefully engineered to meet a well-defined set of requirements will perform well and be very cost effective. Specific advantages of such a system include the following:

• Precision: The well-designed vision system is capable of measuring dimensions to one part in a thousand or better. Because these measurements do not require contact, there is no wear or danger to delicate components.
  
  
• Consistency: Because vision systems are not prone to the fatigue suffered by human operators, operational variability is eliminated. Furthermore, multiple systems can be configured to produce identical results.
  
  
• Cost effectiveness: With the price of computer processing dropping rapidly, machine vision systems are becoming increasingly cost effective. A $10,000 vision system can easily replace three human inspectors who each earn $20,000 per year or more. Furthermore, the operating and maintenance costs of vision systems are low.
  
  
• Flexibility: Vision systems can make a wide variety of measurements. When applications change, the software can be easily modified or upgraded to accommodate new requirements.

Key System Elements

A variety of components are included in a machine vision system. Decisions about components depend on the environment, the application, and the budget. There are, however, several common ingredients to all vision systems :

• Front-end optics: The "front end" includes the lighting, the lens, and the camera.
  
  
• Frame grabber: A frame grabber is a processor board that accepts the video input from the camera, digitizes it, and stores it for analysis.
  
  
• Processor: A processor is required to control the vision application. Pentium-class personal computers are capable of running vision applications without the addition of special processing hardware.
  
  
• Control Software: Computer software for controlling and executing vision tasks is readily available.