The next step in Industry 4.0: rule-based analysis of production data
At our factory in Homburg, Industry 4.0 is a very important topic – which is why we have a wide range of exciting projects running to help make this vision a reality. I’d like to briefly introduce one of these projects: rule-based analysis and processing of production data with help from software designed especially for manufacturing experts. The idea is to reduce the effort and expense that goes into monitoring relevant process data. To do this, we have implemented a tool to oversee our processes, which means we can respond to deviations and faults more quickly. We are currently using it in injector assembly and in throttle plate production.
Before we could correctly deploy the software in a production line, we first needed to precisely analyze the manufacturing process and conduct a range of interviews with our experts in the plant. For throttle plate production, we spoke with production planners, setters, and team leaders to support the manufacturing process of the Electrical Discharge Machines (EDMs) with a rules model. The experts explained, for example, which parameters influence the size of the hole being eroded. We evaluated this information and then created a rule model. Now this model keeps an eye on the eroding process for a hole and we can set various early warning limits for the defined parameters in order to guarantee consistent process quality.
How the software works in daily operation:
- Data is transferred from the machines and existing systems to the software
- The rules monitor process data from multiple machines in the parts production’s manufacturing process
- The software promptly recognizes when defined early warning limits are reached for deviations from target values for features on the individual part
- Automated notifications are sent to the line worker responsible
- Machines can be promptly readjusted
- Our manufacturing experts can work on and optimize the rule model themselves
To sum up, we can now detect deviations in the manufacturing process at an early stage. Whoever is responsible will be immediately notified so they can take the appropriate steps to prevent production downtime or loss of quality.
Implementing this project showed me once again how crucial it is to have our associates’ expert knowledge in the factory so we can continue to improve quality standards. The software allows us to put a tool in our associates’ hands that increases manufacturing transparency. Furthermore, the employees can flexibly adjust the rules at any time, and thus precisely apply their knowledge and experience.
What is your experience in production data analysis?