Mechatriks automation - Vision Inspection/Machine Vision System
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Mechatriks automation - Vision Inspection/Machine Vision System

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Vision based inspection system overview; for improved productivity and quality.

Vision based inspection system overview; for improved productivity and quality.

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Mechatriks automation - Vision Inspection/Machine Vision System Presentation Transcript

  • 1. MECHATRIKS AUTOMATION WWW.MECHATRIKS.COM Vision Based Quality Inspection Systems Vol:01
  • 2. Advances in machine vision (MV) technology are creating new opportunities to increase productivity, quality, and efficiency in a wide range of applications. MV uses computer cameras in manufacturing to capture and analyze images by extracting data and assigning properties to the features of the target item. 1. In the past, vision systems were expensive and difficult to use, but today, these systems are cost effective, have more capabilities, and are easy to apply thanks to advances in software. 2. MV encompasses a large number of related technologies, hardware, and software products integrated into a system solution. MV continues to be applied in a number of creative ways in a range of industries. 3. Initially MV systems were totally custom designs requiring a wide range of specialized skills. Today, icon-based programming environments that require no programming expertise result in short development cycles, higher performance, and flexibility. 4. The latest smart machine vision cameras incorporate a processor providing a complete vision inspection solution.
  • 3. 1. The main categories into which MV applications fall are quality assurance, sorting, material handling, robot guidance, and controlling production. 2. Visions systems have a great deal of advantages including elimination of human vision bias. Consider the example of the circles and the square box, where to the human eye the lines of the box do not appear to be straight. In fact, they are straight, and a vision system will objectively detect this. 3. MV can provide precise inspections at high speeds verifying attributes and guide products through a process. The value includes removing human inconsistency, increased productivity, higher production throughput, improved cycle time, higher quality, and scrap reduction. 4. Technology improvements such as more powerful computer processors, high-speed cameras, and icon-based software are making machine vision systems easier to apply. In addition, bandwidth is increasing to allow faster image capture.
  • 4. Mechatriks Automation vision systems are unmatched in their ability to inspect, identify and guide parts. These self-contained, industrial grade vision systems combine a library of advanced vision tools with high-speed image acquisition and processing. Best of all, configuring and deploying an In-Sight vision system has never been easier.
  • 5. SIMPLE-TO-FOLLOW 1. Configuration software helps users of all experience levels to quickly setup their entire In-Sight application—no programming or spreadsheet knowledge required. 2. The suite of communications capabilities ensures that In-Sight vision systems easily integrate with any factory network or automation control system. 3. The operator display panel provides a "plug-and-go" solution, a PC software version as well as a VGA adapter for monitoring the runtime operation of any In-Sight vision system on the network.
  • 6. Major Illumination Detection of floating height of a cap: This is the most common shape, allowing uniform intensity of light to be obtained over the entire ring. There are various types of light sources such as fluorescent lamps, LEDs, and halogen (fiber) units, with internal diameters varying from a few dozen to a few hundred mm. Detection of contamination of a sheet; Uniform light can be obtained in a linear shape. This is suitable for lighting up the front of a sheet widthwise and the size ranges up to 2 m. Detection of a hole: Uniform light can be obtained over the flat surface. Generally, this is used as a backlight to light up a transparent container or lead frame from the back. The size varies from a few dozen square mm on the side to 500 x 800 mm. Determining of direction: This mostly includes fiber lights using halogen light, allowing high illumination light to be locally obtained. This is also suitable for expanded images, etc. Various branched types, such as single, twin, and triple are available.
  • 7. Major Image Processing Binarization: The images captured by a camera are composed of black and white greyscale pictures of 256 tones. Binarization defines all tones which are brighter than a certain threshold as white and the others as black. This technique is used to detect the existence or sizes of an object by categorizing the non-detecting and detecting areas into black and white respectively by binarization. Edge detection: By setting the edge detection window, you can locate the section where the transition from white to black or black to white happens within the image and recognize it as an edge. This method is effective for detecting the absolute position of an edge. Recognizes the pattern of an image: The target pattern is registered and stored in a pattern window. The pattern window then scans the specified search window to detect the position that best matches the registered image.
  • 8. Testimonial “If you haven’t incorporated machine vision on your automation line or machines recently, you could be missing out on some powerful and cost-effective solutions that you probably didn’t know were out there. Take it from Balaji, Manager of Automation Engineering at Mechatriks Automation (Chennai, India), which provides turnkey custom automation solutions for a variety of industries using advanced computer and automation technologies.” - S. Janakiraman Gala Precision Technology Pvt. Ltd. (A Hoerbiger Group Company)
  • 9. M echatriks Autom ation 1 7 7 /F3 , Sud ha rs un A p a rtm e nts , p Ra d ha N g a r M in Ro a d , a a Chro m e p e t, Che nna i – 6 0 0 0 44. P 0 44-2 2 6 5 1 6 0 6 h: M 91 ob: 9 8 40 43 6 442 /9 8 9 47 3 6 6 9 3 W www. m e c ha triks . c o m eb: Em a il: http s : //www. fa c e bo o k. c o m /M c ha triks e ba la . m e c ha triks @ g m a il. c o m http s : //twitte r. c o m /M c ha triks e http : //in. linke d in. c o m /in/m e c ha triks Fa c e bo o k: Twitte r: Linke d I n: Yo utube : http : //www. y o utube . c o m /us e r/M c ha triks A m a tio n e uto Slid e s ha re : http : //www. s lid e s ha re . ne t/M c ha triks A m a tio n e uto Blo g s : http : //m e c ha triks . blo g s p o t. in/
  • 10. M echatriks Autom ation 1 7 7 /F3 , Sud ha rs un A p a rtm e nts , p Ra d ha N g a r M in Ro a d , a a Chro m e p e t, Che nna i – 6 0 0 0 44. P 0 44-2 2 6 5 1 6 0 6 h: M 91 ob: 9 8 40 43 6 442 /9 8 9 47 3 6 6 9 3 W www. m e c ha triks . c o m eb: Em a il: http s : //www. fa c e bo o k. c o m /M c ha triks e ba la . m e c ha triks @ g m a il. c o m http s : //twitte r. c o m /M c ha triks e http : //in. linke d in. c o m /in/m e c ha triks Fa c e bo o k: Twitte r: Linke d I n: Yo utube : http : //www. y o utube . c o m /us e r/M c ha triks A m a tio n e uto Slid e s ha re : http : //www. s lid e s ha re . ne t/M c ha triks A m a tio n e uto Blo g s : http : //m e c ha triks . blo g s p o t. in/