See change over time
Compare shifts, periods and machines instead of relying on a single current OEE number.
MANUFACTURING ANALYTICS
Move from production data to loss analysis.
ClearRivet manufacturing analytics are designed to show where time and output are being lost, how performance changes over time and which losses deserve attention first.
WHY IT MATTERS
Analytics should answer operational questions.
Useful manufacturing analytics help a team decide what to work on next: which machine, which loss, which shift, which product and whether an improvement actually held.
Prioritise repeated losses
Group downtime and event reasons so teams can separate recurring losses from isolated events.
Keep the operating story
Analyse production alongside machine, order, shift and reason context rather than looking at disconnected KPI totals.
CLEARRIVET APPROACH
Analytics should answer operational questions.
Useful manufacturing analytics help a team decide what to work on next: which machine, which loss, which shift, which product and whether an improvement actually held.
OEE and component trends
Downtime Pareto analysis
Production output trends
Shift comparison
Machine comparison
Historical period selection
Order/product context
Multi-site roll-up views
TURN HISTORY INTO PRIORITIES
Manufacturing analytics should tell the team where to investigate next.
More data does not automatically create better decisions. Useful analysis starts with reliable production events and asks practical questions: which machine is losing the most time, which downtime reason repeats, which shift changed, which product runs below target, and whether an improvement actually reduced the loss.
Rank production losses
Group downtime reasons by duration and frequency so teams can distinguish the few large events from the repeated smaller losses consuming capacity.
Compare machines, shifts and periods
Use historical views to see whether performance is stable or whether one machine, shift or period is behaving differently from the normal pattern.
Measure before and after improvement work
When a recurring loss is addressed, compare the same production context afterwards to check whether downtime, rate or OEE actually improved.
ANALYSIS NEEDS CONTEXT
Keep machine, order, shift and reason data together.
A production loss can mean different things depending on what product was running, which shift was operating and whether the machine was changing over, starved, blocked or waiting for maintenance. ClearRivet keeps that operating context beside the event history so trend analysis does not reduce the plant to disconnected totals.
For Australian manufacturers starting with one or a few machines, the same approach can scale from a focused pilot to plant-level and multi-site comparison once the underlying data has been validated.
COMMON QUESTIONS
Questions manufacturing teams ask.
Is ClearRivet an AI analytics platform?
ClearRivet is first and foremost a production-data and manufacturing-visibility platform. Any advanced analysis should be grounded in validated operational data rather than replace it.
Can managers compare machines?
Yes. The platform is designed to support plant-level views and historical comparisons across machines within the authorised scope.
Can data be exported?
Production/event data can be made available for analysis workflows where supported by the product configuration and user permissions.
EXPLORE CLEARRIVET
Related production monitoring capabilities.
FROM DATA TO PRIORITY
Manufacturing analytics should rank losses so the team knows where to start.
Averages can hide the events that consume the most production time. Pareto analysis, downtime trends and machine or shift comparisons help separate the few recurring losses that deserve attention from one-off events that may not justify the same effort.
ClearRivet keeps the analysis connected to production context so teams can move from a plant-level trend into the machine, shift, order or downtime reason behind it.
See it. Then prove it.