Example: Wire Machinery
What is the maximized speed of a wire machine? While the machine runs, it’s hard to determine how fast it can go before the quality deteriorates.
If the quality of a product declines, easily detectable anomalies show up in the HFIM-depiction. Additionally, the measurement system is able to evaluate other process parameters, like the degree of wear of a drawing die.
Move the controller: On the left side you see the HFIM-depiction of a wire machinery process with a drawing speed of 6 meters per second with a consistently high quality of the wire. The right side shows the HFIM-depiction of a wire machinery process with a drawing speed of 12 meters per second. The depiction shows neither signals of cracks nor anomalies which implies that the wire quality is still high.
Maximized production speed with the QASS Optimizer4D. Anomalies of production show up in the HFIM-depiction.
Example: Plastic Injection Molding
The maintenance costs of plastic injection tools are considerable. Normally, these tools are maintained periodically, for example after manufacturing x products. But it’s possible that the maintenance is conducted too early. It’s impossible to determine the actual condition of a tool in-process and in real-time with todays predominant monitoring technology.
It is not necessary to service all of the different parts of a plastic injection molding tool at the same time. For example, if chatter sounds appear while the tool is closing itself, it’s sufficient to grease the corresponding parts. Optimizer4D is able to relate acoustic emission to each single phase of an injection process. Standard acoustic emission evaluation devices analyze only the oscillation of an object. Optimizer4D takes this an essential step further by detecting the impulses that cause the oscillation. This opens up new possibilities for the user. Example plastic injection molding: When a tool closes itself, it emits many different acoustic emissions at the same time. They overlap and result in sounds like squeaking, chattering etc. Optimizer4D detects the actual source of each sound utilising its high sampling rate, frequency analysis and pattern recognition.
Optimizer4D is able to monitor several parts of a plastic injection molding tool and merge the acoustic emissions (Amplitude & Frequency) into an energy signature graph. The higher and rougher this graph, the more worn-out the corresponding part of the tool. For example, the blue line in the diagram to the right shows an ejector. The right half of the diagram shows the line getting rougher. This indicates an ejector that’s getting more and more sluggish. This evalutation is based on the unique features of Optimizer4D:
- 50 Mio. samplings per second
- Spectral analysis of the acoustic emission in real-time
- Cognitive Big-Data-Analysis, consisting of selective frequency filters, pattern recognition and other software-tools.