Planned applications in production.
PPI is being designed to fit the task: from a single, well-defined case to ongoing use with production data.
Investigate a problem. Check the impact.
PPI is intended to investigate a specific problem or a sound opportunity to improve performance. Once a measure has been implemented, it would use the same frame of reference to check whether the change had the intended effect.
Keep a regular pulse on production.
At agreed intervals, PPI would analyse production data, compare periods and flag new deviations or recurring patterns of loss.
Stay connected to production.
For ongoing use, PPI is intended to connect to production data so that operating states, anomalies and longer-term changes can be tracked.
Find the next capacity constraint.
PPI is designed to identify the part of a plant that currently limits output, then map which bottleneck would matter next if that constraint were eased.
Applications
Applications
Where PPI could add value.
The aim is to bring production data and operational expertise together to support decisions that can be tested.
Automotive
Complex production lines, short cycle times and many product variants call for a shared view of equipment condition, quality and flow.
PPI is intended to review performance regularly and help identify bottlenecks that limit line capacity.
- Link deviations with cycle-time, quality and process signals.
- Prioritise capacity constraints and recurring sources of loss for further investigation.
Mechanical engineering
Machine signals, order data and shop-floor experience can be brought together into a technical picture that can be traced back to its sources.
PPI is intended to investigate specific problems and later check whether the chosen measure worked.
- Compare how machines of the same type behave under different conditions.
- Ground service, maintenance and process-improvement recommendations in evidence.
Plant engineering
In interconnected production systems, the way equipment, measurement points and operating modes interact matters.
PPI is intended to assess possible improvements and map how bottlenecks could shift across the whole system.
- Show how changes in one process step affect another.
- Support commissioning, improvement work and knowledge transfer with findings that can be checked.
Recycling
Changing input materials make it harder to balance energy use, yield and consistent quality.
PPI is intended to examine changing operating conditions at regular intervals or continuously.
- Separate the effect of input materials from that of operating conditions.
- Look at losses, yield and energy demand together.
Aviation
Quality-critical process steps call for findings that can be traced and a clearly documented route to review.
PPI is intended to review performance repeatedly and use before-and-after comparisons to assess the effect of a measure.
- Put deviations in context using process, inspection and operating-state data.
- Keep a clear record of the evidence, alternative explanations and expert approvals.
Energy and gas
Changes in load and operating state affect efficiency, stability and equipment wear.
For continuous use, PPI is intended to compare operating states over time.
- Track operating states and performance indicators over time.
- Flag unusual patterns for a targeted technical review.
Chemicals
Material flows, recipes and process conditions need to be considered together to interpret deviations accurately.
PPI is intended to examine complex process data at regular intervals or continuously.
- Compare batches, operating modes and quality characteristics while keeping the evidence trail clear.
- Distinguish plausible causes from the checks needed to test them.
Pharmaceuticals
Every assessment needs a clear data context and a documented expert sign-off.
PPI is intended to work within a clearly defined scope and document any later assessment of a measure’s impact.
- Investigate batch-related deviations against approved versions of the data.
- Keep a traceable record of results, limitations and decisions made by people.