Key Performance Indicators
Overview
KPI Index
- Efficiency
- Target Efficiency
- Lifetime Efficiency
- 1 hour Efficiency
- 24 hour Efficiency
- 1 week Efficiency
- Cycle Time
- Target Cycle time
- Lifetime Cycle Average
- 1 hour Cycle Average
- 1 week Cycle Average
- Last Cycle Interval
- OEE
- Target OEE
- 1 hour OEE
- 1 week OEE
- Temperature
- Baseline Temperature
- Lifetime Max Temperature
- 1 hour Max Temperatore
- 24 hour Max Temperature
- 1 week Max Temperature
Rules
- Hourly KPIs are exactly 1 hour long and start at the top of every hour. Therefore there are 24 hourly KPI buckets in a day.
- Time-based KPI analysis (e.g., 1-hour, 24-hour, 1-week) are performed on the current period. This means that in a 1 hour bucket, if you are 15 minutes into an hour, your 1-hour OEE will show the OEE for that 15 minute period going back to the top of the current hour.
- If a tool had no cycles in a bucketed period, the value will be empty for that period. This means that the 1 hour efficiency column will be empty in a report if the tool has not run within the current hour.
KPI Evaluation Process
- Every cycle we get has a timestamp.
- Based on that timestamp, identify what specific kpi interval of type
DAY
, HOUR
and SHIFT
it falls into. Each "kpi interval" has a start and end date. For example, DAY
kpis start when the plant day starts and end when the next day starts.
- If there is no KPI entry for that interval, create a new one
- Apply changes to the metrics in the KPI interval (e.g., increment the
downtime
).
- Save the updated KPI back into the database.
Example: Computing Hourly Statistics
- Look in the saved KPI data for the asset, for the entry of type hour that "started" in the last hour. For example, if it's now 10:33, is there a KPI entry that started after 09:33.
- The system finds the next possible hourly bucket, which is the 10:00 bucket.
- Compute the statistics using the data in that horuly bucket.