What does the data say about process stability? What are the causes of process variations and quality issues? And which data are relevant? Data scientists are trained to answer these questions but in-house data experts may not always be available. Following the inclusion of the new 'analytics' package in its performance.boost process optimisation service, ENGEL now offers this expertise as a service.
"We have specifically built up personnel resources for the new offering," reported Dr Johannes Kilian, Head of Process Technologies and inject 4.0 at ENGEL's headquarters in Schwertberg, Austria. "Our data scientists have years of injection moulding experience on top of well-founded data analytics training. They understand the injection moulding machine and the processing technologies, and that is precisely the major advantage of performance.boost analytics compared with other service offerings on the market."
ENGEL's data scientists systematically analyse the available data for each specific application, visually process the results and develop recommendations for action. For example, to increase production efficiency or reduce the reject rate.
If rejects are identified too late and the root cause of the rejects is not found, data collected over a longer period of time is analysed. This is where data scientists are deployed in addition to processing engineers. Depending on the application and customer requirements, production and process data as well as data from quality assurance provide the raw data. The analysis allows insights into the root causes of rejects, reveals gradual quality changes and enables long-term trend statements. In doing so, the analytics service package goes one step further than the previously available performance.boost packages.