Automating Small Parts Assembly 102 – Inspection <\/strong> <\/p>\n\n\n\n\n\n\n\n Start at the beginning. Don\u2019t let anything in that doesn\u2019t meet specifications.<\/strong> Require a consistent, validated incoming inspection process for all the individual parts being assembled. Ensure that incoming part dimensions and tolerances meet specifications and suit what the machine, nest, tooling, etc. was designed for. Simplify. <\/strong>Use the simplest inspection method that can quickly and reliably perform the required inspection or testing. Rely on lasers, sensors or other instrumentation to screen for defects that don\u2019t require the precision of machine vision. <\/p>\n\n\n\n Include proper lighting for vision systems in early planning stages. When using vision systems for part inspection, location and orientation verification, or barcode reading, proper lighting must be a primary concern. Vision system lighting is critical for accuracy and reliability, and can be challenging to incorporate into the late stages of an automation plan. Analyze the data collected. By combining inspection data with system data, correlations can be detected. Do more defects appear after a certain amount of time, or when the machine is hot? Does a tooling change affect the number of defects detected? Data analysis of the big picture gives invaluable insights to discover root causes and prevent problems from recurring. If you are looking to purchase a custom automation solution, need a robot integrator or to learn more about how automation can help you become more successful, contact Ehrhardt Engineered Systems at 877-386-7856 or email us at sales@ehrhardtsolutions.com<\/a><\/p>\n\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" Automation of small part assemblies using machine vision and lighting<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[4],"tags":[5,2,6],"class_list":["post-11","post","type-post","status-publish","format-standard","hentry","category-factory-automation","tag-automating-inspection","tag-factory-automation-systems","tag-small-parts-assembly"],"_links":{"self":[{"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/posts\/11","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/comments?post=11"}],"version-history":[{"count":10,"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/posts\/11\/revisions"}],"predecessor-version":[{"id":81,"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/posts\/11\/revisions\/81"}],"wp:attachment":[{"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/media?parent=11"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/categories?post=11"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ehrhardtautomation.com\/blog\/wp-json\/wp\/v2\/tags?post=11"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Advances in sensor technology and machine vision capabilities are making automated inspection a strategic, cost-effective solution. The benefits of properly implemented inspection automation include time savings, consistency, increased quality, and reduced labor requirements. With data collection and analysis built into the system, defect prevention and process improvements can also be achieved. When incorporating inspection into an automated assembly process, there are many important factors to consider.<\/strong><\/p>\n\n\n\nStart at the beginning<\/h4>\n\n\n\n
Continuously inspect and validate each part as it progresses through the assembly process. Once a defect is discovered, eject it or lock it out at subsequent stations. Adding value to an already proven defective part wastes resources.
Flag critical specifications and tolerances. Rejecting every part that doesn\u2019t meet specifications by 100% could result in excessive scrap levels. A specific set of quality control criteria and inspection requirements must be defined for every step of the process to prevent unnecessary checks.
Define quantifiable criteria. If \u201cvisible scratches\u201d are considered a defect, what resolution should be used to \u201csee\u2019 those scratches? What is a surface defect? Collect samples of what is and is not a defect.<\/p>\n\n\n\nKISS: Simplify<\/h4>\n\n\n\n
Define short and long-term requirements.<\/strong> If automated inspection is being phased in, be sure to communicate immediate plans and longer-term goals with the automation builder so they can plan for future needs.
Check timing. Can the inspection be done within the required cycle time?<\/p>\n\n\n\nIt’s in the lighting<\/h4>\n\n\n\n
\nUnderstand how to train a vision system. A machine vision system will look for anomalies, which is different from humans looking for defects. The machine needs to learn what is acceptable and not acceptable by cataloguing hundreds, even thousands, of samples. You will also need samples to use for validation. The wider the range of samples, the better the results will be. If small chips or scratches on a non-critical area of the part are acceptable, the machine must be trained to understand that. If the level of polish on a part or the colour will vary depending on the supplier, the vision system must be trained to recognize those variances as acceptable or not acceptable.
\nAllow time for analysis. Acquiring an image is just one step in the machine vision process. Each image must then be analyzed for anomalies using an algorithm. How long does the analysis take?
\nIncorporate monitoring and alert thresholds. At what point does an operator need to be alerted? What triggers a shutdown? The machine will simply keep flagging parts as defective if thresholds, alerts, alarms, and monitoring aren\u2019t properly defined. <\/p>\n\n\n\nAnalyze the data<\/h4>\n\n\n\n
\nInspection solutions must be right-sized for each assembly process; not excessively precise (and expensive), but not too simplistic and inadequate for the requirements. With more manufacturers turning to automated inspection, a properly implemented system is proving to be a strategic advantage and worthwhile investment that can speed production, improve quality and reduce costs. <\/p>\n\n\n\n