A pipette can comprise as many as 50 individual molded parts. For Sartorius, that translates into producing around six million individual parts each year—plus 600 million pipette tips—to extremely exacting specifications and standards. Making sure that happens consistently is the responsibility of Tomi Villilä, Development Manager Injection Molding at Sartorius’ facility in Helsinki. He recently got a helping hand from the ComoNeo process monitoring system and ComoNeoPREDICT function developed by Kistler (Winterthur, Switzerland). It has been a game changer, he said.
Founded in 1870 and headquartered in Göttingen, Germany, Sartorius supplies laboratories and research facilities with specialized equipment such as high-precision balances, filtration units and centrifuges. It develops and manufactures mechanical and electronic pipettes in Helsinki. Manufacturing products for the medical technology sector requires precise, repeatable and stable processes, noted Sartorius in a press release. Kistler’s ComoNeo system is a tool that uses predictive technology to achieve those goals.
As a confidence building measure of sorts, Sartorius began by using ComoNeo in molding a non-critical fixture. That allowed technicians to begin “to understand the system, practice using it and improve our own process,” said Villilä.
Online quality prediction allows forecasting of part quality during the injection molding process, based on numerous learned process parameters and related part-specific quality criteria, said Sartorius in the press release. The first step is to use the associated Stasa QC software to generate a testing plan, known as design of experiments (DoE), that includes all the parameters needed to determine the process. For example:
- Which dimensions are to be achieved?
- How must the machine be set to achieve them?
- Is it possible to reduce the cycle time?
Comprehensive, precise answers to these and other questions are generated by the Stasa QC PC software and ComoNeoPREDICT process monitoring feature. For convenience, the DoE can be generated on a PC and implemented digitally in ComoNeo at a later stage.
The Kistler sensor technology installed in the mold supplies the basis for transparent process management of all material-related and part-specific attributes. Based on the measured cavity pressure and part characteristics, Kistler's system delivers a prediction of part quality while the injection molding process is in progress.
It took Sartorius only two or three days' work with ComoNeo to set up the specific DoE for modeling of the injection molding process for the fixture. Then, following optimization with Stasa QC and ComoNeoPREDICT, precise results were obtained. Because such large numbers of machine parameters are considered, users gain a clear understanding of the limits of the injection molding process and the relevant part characteristics, paving the way for intelligent process monitoring. It takes very little time to understand what is happening in the injection mold, and to gain knowledge about the entire process, said Sartorius.
Based on the generated prediction model, ComoNeo can significantly reduce the percentage of bad parts, which can be segregated automatically, if desired.
A key feature of the system is its simple operation and integration. “This system is really simple to handle—almost like a smartphone,” said Villilä. “You only need five or 10 minutes to understand how it works. And setting up a DoE poses no problems, either, thanks to the software that comes with the product. You don't have to be a mathematician to understand the whole system. Once you've generated the DoE, you can simply upload it into ComoNeo and then you already get accurate feedback for process optimization in the test phase," Villilä explained.
Sartorius is so pleased with the results that it is planning to deploy six to eight additional ComoNeo units to monitor the production of critical components. “If it were up to me, all Sartorius' technical parts that require high precision would be produced with the Kistler system in the future,” said Villilä. He will soon have an opportunity to make his case: A workshop is scheduled to take place in Helsinki with a practical demonstration of ComoNeo, ComoNeoPREDICT and the online quality prediction feature for interested staff members from the entire Sartorius group.