JUL-AUG 2017

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34 INTECH JULY/AUGUST 2017 WWW.ISA.ORG By Mathew Daniel M achine vision is a multibillion-dollar mar- ket as manufacturers increasingly turn to this technology for automated quality inspec- tion. And yet, the data from these sophisticated systems is often managed and used in simplistic ways. Even in case studies that examine the value and benefits of using a vision inspection system, data often earns only passing reference. The result is data silos scattered throughout the plant that contain images and only the most basic of image data (such as pass/fail status). Although this approach makes access and retrieval difficult, there is at least basic traceability when needed. But machine vision images and related data can do so much more. They can be collected and used to help drive quality, improve yield, and contrib- ute to faster resolution of quarantines and recalls. In this article, I present how vision data can be used and the basics of how to architect the system required for its collection, storage, and analysis. Driving Manufacturing 4.0 Using vision data with other datasets in a ho- listic fashion is fundamental to creating a mod- ern factory capable of achieving the standards of not just Industry 4.0, but Manufacturing 4.0. Frost & Sullivan's Manufacturing Leadership Council defines Manufacturing 4.0 as charac- terized by highly intelligent, agile, information- driven factories that are able to respond rapidly to change, with connected sensor networks and advanced data analytics, and new, customized smart products and services. It is surprising how many industry experts who evangelize the precepts of Manufacturing 4.0 ne- glect to include vision. Perhaps it is because vi- sion systems on large original equipment manu- facturer production lines generate so much data it is a nightmarish prospect to leverage it strate- gically. This is a misconception. It just takes the right tools and network architecture. What you can do with machine vision data Vision data can do much more than provide simple pass/fail determinations and basic traceability, if it is collected and stored in the right way. What is the right way? Collect the im- ages and their related data into a central data- base, indexed by serial number. In this way, vi- sion data can be consolidated with all the other Data management principles for machine vision Manufacturing 4.0

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