Friedrichshafen, Germany — Winterthur, Switzerland-based sensor producer Kistler Group has developed new sensors and software solutions, as the company demonstrated on its booth at Fakuma 2023 in Friedrichshafen.
The 2.5-millimeter diameter sensor front piezoelectric 9239B miniature piezoelectric-electric pressure sensor is smaller and more sensitive than its predecessors, Thomas Michael Koch, Kistler application specialist for plastics business area told Plastics News.
He explained that this new sensor has been designed to be placed just under the mold surface, so that it doesn't leave marks on molding on critical items such cosmetics packaging.
It detects pressure not from direct contact with the melt, but from deformation during the molding process of the mold wall within which it is integrated.
Claimed by Kistler to be a worldwide unique type of sensor, the new 4004A piezoelectric combined melt pressure and temperature sensor has a 3-mm sensor front and is aimed at applications involving relatively long periods of pressure. It can determine melt quality in hot runner and 3D printing channels and nozzles. The 4004A sensor additionally recognizes valve gates and is capable of identifying leakage and wear.
The new ComoScout process monitoring system is a relatively simple and quick way for newcomers to become involved in process monitoring, also as it can be retrofitted to "digitalize" older existing injection molding machines, Koch said. It also provides an interface to overall production management via OPC UA (Open Platform Communications Unified Architecture).
Koch said it functions by measuring the melt path, clamping force, injection speed and temperatures. It is less expensive than the established Como Neo system, but offers less performance, Koch added.
AkvisIO IME (injection molding edition) is, according to Koch, a further development of the Como Data Center, "rather like a MES manufacturing execution system, but less expensive." This modular statistical data analysis software is based on artificial intelligence (AI) and can be integrated with existing MES.
STASA QC Optimizer uses algorithms for machine learning to generate data how injection molding machines should ideally run by establishing the most stable production parameters. It can automatically correlate internal mold pressure curves with quality tolerance data, thereby improving staff process knowledge. Similarly, the new Kistler Plastics Academy offers staff training in factories, for example at processors and mold makers.
As head of global sales and integrated solutions, Oliver Schnerr showed Plastics News, a new Kistler KVC 821 system line running live on the booth uses a SmartRay laser light to measure parts by triangulation and to check surface quality with eight cameras. With the aid of KeyVisio software, the line analyzes the data and presents it visually on the line's display screen. The line would normally inspect parts at 750 parts per minute, but Schnerr said it can just as easily run at 4,000 parts/minute for inspection of, for example, electronic connectors, with no compromise on precision.
Schnerr said the company recently bought a Chinese firm that enables Kistler to bring that company's part-handling capability to Europe.
The acquisition fits well, as Kistler has worked with the Rapperswil, Switzerland-based IWK materials and plastic processing institute at OST Eastern Switzerland university on automating the task of checking produced components. This involves robots moving through production halls, picking up components from a number of injection molding machines and bringing them to measurement points and to the storage area.