How to elevate Statistical Process Control (SPC) in vision system inspection (and how to connect to Industrial IoT!)

It’s the Production Managers dream in the era of Industry 4.0. A system that allows them to drill down on the assets in the production chain quickly and have immediate data on the throughput, results, and SPC data. This is all part of a goal to intelligently connect a company’s people, processes, places and assets to drive value across the whole organisation. That’s the goal of Industrial IoT (IIoT). And that’s what every manufacturer is striving for, having immediate, intelligent and critical data available on every process. This helps increase the efficiency of all manufacturing operations and allows plant-wide measuring and monitoring of machines’ quality, performance, and availability. Producers benefit from higher OEE and throughput while maintaining guaranteed levels of quality and cost.

The value of IIoT is that it immediately provides visibility of assets in a plant or in the field, and it transforms how a firm connects to the internet of things. The process of converting a factory to IIoT is to collect usage and performance data from existing systems and smart sensors, delivering advanced insights to unlock data-driven intelligence. Vision systems are an essential part of the manufacturing process. They have a significant impact on output and deliverables, so these are usually one of the first components connected to the factory information system. Companies are now establishing collaborative cultures in which engineers can make data-driven decisions that provide true economic benefit.

A fundamental part of machine vision inspection data is Statistical Process Control (SPC). Statistical Process Control (SPC) is a method for monitoring and controlling quality during the manufacturing process that is widely used in industry. During production, quality data in the form of Product or Process measurements are obtained in real-time. This information is then (at the very basic level) plotted on a graph with pre-set control limits. Control limits are set by the process’s capabilities, whereas the client’s requirements determine specification limits. Having this data connected to the IIoT system allows for more detailed analysis and alarms connected based on the moving data.

But how can I connect the vision system to the IIoT system?
There are many options. There are a large number of ways a vision system can send data to another system. This depends on the data (images, measurement data, settings, region of interest data etc.) required to be collected. Typically, the machine vision system will support a plug-in facility or a format convertor which allows the customisation of outputs to the IIoT system. But there are several immediate solutions that most vision systems will provide “out-of-the-box”, including
Digital I/O (small amount of data)
PLC standard comms (industrial ethernet)
SQL Databases (SQL Server, SQLite, MySQL)
XML output
TCP/IP (traditional TCP/IP versus Industrial Ethernet)
Reports (Excel, PDF, Word)
Web API’s
In addition, many systems now communicate on an industrial basis using:
Web Sockets
The vision system may have a role to play in closed-loop control with the production process, allowing for moving parameters of a process to be controlled by the information returned from the vision system. This could already directly connect to the PLC or line controller for the vision system, e.g. by industrial ethernet. In this case, pulling the data into the factory IIoT may be as simple as communicating the machine PLC data to the factory server. It can be collated with the overall factory statistics and information into the global IIoT information exchange and display.

So next time you get a call from the production manager asking for a status report on the shop floor vision system and production statistics, just refer them to the company wide IIoT system, they’ll have all the data they need!

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