It's not easy to stay at the top of the pack in manufacturing anymore. Shifts especially in digitalization are quickly weeding out those enterprises that are failing to adapt as Industry 4.0 drives new standards. Manufacturers need to accelerate everything from their shop floor protocols to their delivery turn-around time in order to achieve the value realization that meets company goals and, most crucially, customer demand.
If you've been following along with our digital transformation strategies series, you'll know that there are four key drivers for manufacturing success. First, manufacturers must CONNECT everything in their facilities: machines, materials, edge devices and other equipment, personnel, and business software. IIoT connections enable the capture, presentation, and analysis of essential data... and data drives profitable decision-making.
Second, manufacturers must use that data to better MANAGE their people and processes. Inefficiencies and errors cost time and money that no manufacturer can afford in today's market.
We come now to the third digital transformation (DX) key which is VALIDATE. This is where the data really starts to go to work.
Wouldn't you rather know that your product passes spec and meets quality standards from the get-go instead of hoping for the best or finding out the worst at the 11th hour?
With PlantStar 4.0 manufacturing execution system (MES), you get real-time data from every cycle. You set the parameters on tolerance limits. You indicate the conditions that trigger alerts. You get a heads-up even before there's a problem, not after a shift or after you've missed a deadline.
Do you know when your equipment and machinery is about to go down? In unexpected down-time a liability you can afford? If not, implementing PlantStar 4.0 MES is a way you can enable predictive maintenance with machine learning.
Automation World has a recent article on the role of MES in the manufacturing space. The article cites Tom Hechtman, President and CEO of Sepasoft, on the particular benefit of MES with regard to data's role in shop floor error correction and reducing unplanned down-time.
"As much as 80% of the effort in machine learning is spent preprocessing the data to clean it up" before manufacturers can use it to streamline and increase productivity, says Hechtman. With a smart technology MES solution in place, you can skip that step and go straight to validation of results. He explains that "machine learning ...must be trained against known valid answers" which is where MES proves particularly valuable.
Key performance indicators
Here's an example.
At PlantStar, we frequently encounter push back from new customers about the perceived accuracy of our system's KPIs. Directors of manufacturing operations tend to take seriously their OEE numbers and have a good idea of where those hover. When they start using our software and the numbers come in lower than anticipated, they balk and assume the system is faulty.
However, our OEE tech team is able every single time to validate the accuracy of the data collected and demonstrate that prior to having all that data, the ops managers were basing KPIs on little more than hunches. They didn't know what they didn't know, because without connections they were relying on bad data, out-of-date data, or no data.
Data validation with MES holds enormous potential for cost-savings and increased efficiency.
Here's another consideration.
How industrious is your work force? You can walk your shop floor and get an idea. Or you can implement PlantStar 4.0 MES and know for certain who your top performers are and who might benefit from additional training or incentivizing.
Our system features end-to-end track and trace for user actions: every keystroke, every machine action, every tool adjustment is logged in a read-only database that's viewable in real-time or usable as an historian. You can see shift data per operator across any time span. Reward your top performers. Incentivize others by turning performance goals into a contest. The event logs give you insight into exactly how long every employee takes to do everything, so you know exactly where inefficiencies arise and how to address them. This is a great way for managers to take concrete action toward goals like increased rate of production.
The AW article praises MES's capability to "streamline the application of technologies ...to deliver predictive analysis and prescriptive planning and scheduling."
If you're ready to leverage data to save money from one end of your plant to the other, then contact SYSCON PlantStar today! We're ready to make a difference for YOU.