Acerta LinePulse
Predictive quality software with machine learning analyzes shop floor data in real time to predict defects and automate root cause analysis.
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With LinePulse, quality engineers can start a root cause analysis investigation of a test failure with a list of the most likely causal factors—generated in seconds.
Manufacturing engineers get alerted when the algorithm detects that process conditions could lead to an upcoming failure.
Managers can instantly generate capability reports and dive deeply into the data to optimize their process and increase efficiency.
LinePulse helps quality teams reduce scrap and rework by monitoring quality data in real time and alerting them of issues before they have a chance to impact production.
Automated root cause analysis allows corrective action to be applied quickly and precisely, meaning fewer production delays and more on-time shipment to customers.
Real time alerts and on-demand reporting allow manufacturers to spot previously unknown process inefficiencies and optimize their process.
On-demand data analytics designed for the shop floor.
LinePulse leverages data that manufacturers are already collecting to provide them with advanced insights to help them reduce their scrap and rework, eliminate process bottlenecks, and increase operational efficiency.
Acerta LinePulse reduces scrap and rework
LinePulse is a predictive quality analytics software that uses machine learning to analyze manufacturing and test data from the shop floor in real time. Features of LinePulse include:
01
Real-time data ingestion
Critical data such as machine signals, part attributes, process data, test results, and environmental data are ingested in real time, enabling on-demand machine learning analysis.
02
Automated root cause analysis
When a part fails a test, LinePulse generates a list of the most likely contributors to the failure, making root cause analysis investigations faster.
03
Quality event prediction
Machine learning algorithms monitor machine sensor data for any patterns that might indicate a defect, allowing engineers to intervene much earlier in the process.
04
Capability reporting
Use a traditional-looking SPC dashboard to run capability studies on certain signals, part numbers, op-counts, part groups, or data ranges.
05
Part history
Isolate and view the data history for any part on the line.
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