IIoT / Smart Manufacturing
Machine vision images and data are a valuable part of the Manufacturing 4.0 equation. The problem is that machine vision images and data are often trapped in silos across the plant floor, with images stored in formats that make them difficult to access and analyze. With the right data management strategy, you can make this data accessible to your team so it can drive value.
Machine vision images and related data can be used for much more than basic pass/fail determination during the process cycle. We get into how this data can be collected, correlated and analyzed will all other production data as part of a comprehensive IIoT strategy.
So, your plant collects data—but how are you using that data to take quick, decisive action on the plant floor and inform timely decision-making in the corner office? We dive into five ways smart manufacturers are using their data to raise the bar on quality and competitiveness.
Aaron Alberts explores how, when it comes to collecting process data to raise the bar on quality and productivity, you can never have too much. The key is to break down the data silos across the plant floor and get all that data into one centralized database for analysis.
In process testing and digital waveform analysis isn’t only for discrete manufacturing where each part is serialized. Ron Pawulski explores how it can also be used to improve yield and quality control in pharmaceutical and medical device batch manufacturing.
We give a primer on how comprehensive data collection from across the plant floor, coupled with digital process signature analysis, can achieve the sometimes contradictory goals of reduced production costs and improved quality.