All machines have minor lags because of unpredictable performance variations. The moment a machine lags, it makes all the neighboring machines wait, because they have nothing to work on.
In a serial line, different machines become the weakest link at different times. Resultantly, the impact of each lag compounds with the delays caused by previous lags, leading to a snowballing effect on overall production efficiency.
Most manufacturers fail to recognize this compounding bottleneck effect and in turn, stay unaware of the real potential of the output their lines could be producing.The worst part? The shifting nature of bottlenecks makes them tricky to pinpoint with manual observations.
Unlike conventional IIoT solutions that focus on individual machines, our algorithm understands the intricate web of interactions between the machines. These interactions paint the true picture of wait times along the line to identify the most important limiting factor, i.e., bottlenecks.
Implement targeted improvement initiatives with auto-identified bottlenecks
Answer questions about lost capacity with classified loss occurrences of each asset.
Prioritize maintenance efforts by learning about assets tampering the line productivity.
Identify the most significant loss types and trends on your line.
Customize conditions, receive real-time alerts, & proactively address critical events.
Track OEE for each station and identify areas of improvement.
Effortlessly manage daily production targets versus actual output.
Kick-start your part and process parameter compliance.
Easy-to-build reports to track key stats – JPH, downtime, MTTR, MTBF and more.