What is Process Data?
Process data is things like temperature, vibration, speed, current draw, flow rates, basically anything that can be pulled from a machine to tell how it’s running. Process data can be collected and compiled into manufacturing software, giving the manufacturer the ability to do a number of things like:
- Receive alerts
- Determine the root cause of a problem
- Check and monitor quality
- Alert maintenance of a problem.
1. Receive Alerts
Within Mingo, you can set upper and lower control limits on the data using control charts. If what you’re measuring gets close to the upper or lower limits, you can immediately notify someone about the problem. This is a very common scenario with our customers.
Think about the temperature of a machine. If it gets too hot or too cold, the product could be ruined and needs to be scrapped, thus increasing your scrap rate. This is a situation everyone wants to avoid. Using pre-set limits, if that temperature rises too high, an alert will be sent to the person who monitors that particular machine. They’re now able to control the temperature before it ruins the product.
2. Track Changes
With Mingo, there are pre-set settings, often determined and set by the administrator of the system. If someone is changing settings they’re not supposed to, you can track that and set alerts via the Mingo manufacturing app to notify you. Then, you’re able to stop any unwanted changes from occurring in the future and fix the ones that have been modified.
3. Determine the Root Cause of a Problem
Let’s say you produce bottles on a blow molding machine, and you find out right before they ship out that there’s a major problem. The bottles leak.
You can track those bottles back to the machine they were made on, look at the settings during production, analyze the different parameters, and correlate what caused the problem during production.
It gives you a very clear picture of how things were different than normal and why those bottles were bad. If you know that, you can take corrective action to ensure it doesn’t happen in the future.
4. Conduct Quality Checks
We have a customer that makes bottles, blow-molded bottles (just like in the example above). They continually conduct leak checks to make sure the bottle they’re shipping out to customers is of good quality. These various automated checks have to happen as soon as the bottle is produced to ensure it’s good quality and if it’s not, the bottle doesn’t make it any further in the process.
The machines don’t initially tell the manufacturer if a bottle is “pass or fail” which is why the data is fed into the Mingo software. The machines send the raw data to Mingo where it’s categorized using reason codes. If it is a “fail”, the data is translated into Mingo and alerts the manufacturer. The same applies to “pass”. All of this is done automatically.
Mingo gives the manufacturer the ability to look at that data on the leak test and know if it’s outside of the upper or lower control limits. So, you can automatically track good and bad parts based on that process data coming out of the PLCs in the machines.
Process Data Can Come From a PLC or Sensor
The thing that’s cool about process data is that it doesn’t have to come out of a PLC which opens so many more doors to accessibility and visibility. The data can come from other sensors.
You could have Banner temperature and humidity sensors, temperature and vibration sensors, basically any kind of sensor attached to a piece of machinery in the plant, and you can pull that data, too.
A great example of this in action is understanding how humidity and temperature really affect different processes based on what people are making. So, if you’re manufacturing products with rubber or plastics, temperature and humidity make a huge difference. These are two data points crucial to measure during production. Based on the ambient temperature and humidity in the plant, you have to change the settings on the machine to make sure your product is a quality product.
Let’s say, for example, you’re a manufacturer who produces rubber gaskets and seals in Dallas, Texas. The humidity and temperature in Dallas is going to be higher than in other parts of the country. If it was 100 degrees and 80% humidity, you’d need to change the settings on your machines to compensate for the higher temperature and humidity levels.
If the machines weren’t modified because of the conditions, and a bad product was made, you could go back and look at the settings to determine why it was a bad quality product. Using process data, you can conduct root cause analysis to find why the problem occurred.
In fact, we have customers who make rubber gaskets and seals, bottles, and coolers, all products with plastics and rubber so temperature and humidity monitoring is critical to their production. All of these customers have sensors in the plant that’s giving them the temperature and humidity information so they can look at it at any time and know if they have to change the settings on the machines. It’s a real life-saver.
At the end of the day, you can take all of these bits and pieces of process data that come out of a PLC or sensor, and turn it into meaningful information through our software, giving you the detailed context you need to make decisions and solve problems.
Using Process Data in Preventive Maintenance
Another use case for process data is preventive maintenance. We have a customer that measures the vibration and temperature of motors in their machines and monitors the coolant levels of the machines. When the vibration or temperature is too high or low, or the coolant levels get too low, an alert is sent to the maintenance team.
Another customer measures pressure on a machine so you can see when any of the pre-set parameters goes below a certain limit, an alert to the maintenance team is sent either via phone, email, or work order is created in the CMMS system.
The use cases of process data are vast, and it’s incredibly beneficial for manufacturers to monitor, especially if things like temperature and humidity make a big impact on the health of production.