Products Machine Vision Inspecting automotive connectors for bent pins
viding a view of the connector’s datum to measure from. The system is integrated into a stand alone machine, with
removable tooling to allow different product types to be inspected. The complete vision system is shrouded, with only a ‘letter box’ viewing window, to stop ambient lighting conditions affecting the vision system result. To supply the system’s operator with information
Industrial Vision Systems (IVS) have provided a final inspection cell for an automotive electronics supplier to confirm that no pins have been bent during the produc- tion process of its complex engine management compo- nents. By utilising a vision system, rather than a mechanical method, it means that no material comes into contact with the pins - as there is always a danger with a mechanical method of the inspection process itself causing the pins to bend. IVS integrated multiple high resolution digital cameras, combined with four LED line lights to provide inspection of the end face of electrical modules for bent pins. The digital cameras utilise telecentric lenses over a small field of view, giving micron level detection of movement of the interface pins in the module. The vari- ous angled lights give the ability to process images of the pins in different lighting conditions as well as pro-
regarding each connector, IVS used Neurocheck to develop a graphical user interface to display images and the results of each inspection. As each connector is inspected, the operator is presented with an image of the board and the highlighted regions of interest (ROIs). The results of each pass or fail on each board is displayed as well as a running total of the number of products inspected and passed by the software. The machine vision software interface designed by Industrial Vision System completes the complex gauging measurement across the pins and a custom designed front end screen is displayed for simplicity for the operator. The system is connected to the factory information system via Ethernet for statistical data upload. Because such information is stored in a standard data- base format, it can be networked to existing database systems to provide management about the integrity of each system in the products production process. This information can be transferred from the system’s PC using a standard Ethernet interface.
While gauging algorithms such as those developed by IVS can check for specific placement, position and con-
WebSPECTOR provides machine vision for textile inspection interior, parachutes).
An extreme example is textiles used for automotive interiors where the aesthetic appeal and wear characteristics are a critical part in achieving the overall appeal of a vehicle in a showroom, and so the perceived value of the vehicle.
The consequences of a visible defect being missed during manual fabric inspection and ending up in a vehicle component (seat, head- liner etc) are costly.
Manual inspection often takes place at a time lapse after manufac- ture due to manufacturing process speeds exceeding manual inspec- tion capability, or because access to the production process presents H&S issues. Therefore, repeating defects could continue without detec- tion for some time. The slower manual inspection process requires a disproportionately high number of people.
Textiles are produced in many forms and for a wide variety of end uses including automotive, aerospace, military, recreation, construction, home decoration, insulation and apparel.
Each end use will have specific criteria and requires functionality, often uniquely satisfied by a combination of textile properties. A full surface area visual check by human eyes is traditionally the main method used to detect functionality and aesthetic appearance. In most cases manufacture of a textile fabric is part of a multi- stage process to arrive at a final product, of which the textile fabric would account for a small proportion of the total costs, but a high level of aesthetic appeal and performance (e.g. garments, automotive
S18
The solution is an inspection system with 100% attention that can cope with full production speeds and apply consistent and auditable quality standards at the point of manufacture. Such real time quality con- trol can be used to identify and grade defects in real time to prevent them getting through to a customer, to provide information to process improve- ment engineers to reduce the defect rate and for supplier regulation. Shelton Vision has applied its expertise from the multi-faceted disci- plines of machine vision to overcoming the unique demands of textile inspection and has developed a versatile, multi-application inspection system - Shelton WebSPECTOR.
This system is capable of providing a cost effective solution for all textile inspection demands, as well as similar web type products, from simple plain cloth for basic apparel to critical safety/performance cloth for parachutes, airbags and automotive end use including car interior and transmission belts.
The application of machine vision to textile and related inspection processes unlocks a wide source of financial benefits, usually conclud- ing in ROI periods of between six and 18 months. Shelton Vision
www.sheltonvision.co.uk T: 0116 279 0920
Enter 240 OCTOBER 2013 Machine Vision
nector integrity, they can also be used in many other areas of automotive engineering design and inspection. This vision technology provides manufacturers with a clear end of line goalkeeper to stop rogue bad products reaching the customer.
Industrial Vision Systems (IVS)
www.industrialvision.co.uk T: 01865 823 322
Enter 239
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72