OEE and availability
Compare availability, performance and quality by shift, line and product. Separate planned stops from losses that need attention.
View the example view
Manufacturing and production analytics
See where production capacity goes.
Most factories can report last month's output. Fewer can show which line, shift or changeover cost the most margin this week. Griffith's Digital Insights Ltd. builds production efficiency dashboards for UK manufacturers that make those losses visible.
Bring OEE, throughput, downtime, scrap, quality, inventory and workforce performance into one clear operating view.
Based in Batley, West Yorkshire. Working on site across the region and remotely with manufacturers throughout the UK.
Production view / Line 02
Illustrative shift view
Overall equipment effectiveness
Current shift · illustrative figures
68.4% OEE
Availability78%
Performance91%
Quality96%
Recorded production losses
Changeover overrun42 min
Unplanned stoppage31 min
Material wait18 min
Quality adjustment12 min
Example layout only. Measures, values and downtime codes are configured to your production data.
Production efficiency dashboards
The measures a production dashboard should actually show
A useful OEE dashboard lets a manager move from a plant-wide figure to the line, product, shift or changeover behind it. It also puts the cost of a loss in view.
Start with the decisions your team makes.
Throughput and takt
Track output against plan and expected cycle time. Spot the bottleneck before it holds up the next job.
View the example viewDowntime by reason
Turn operator-entered reason codes into analysis by duration, asset and recurrence. Keep the categories practical on the shop floor.
View the example viewScrap and rework
See rejected units, rework and their cost by defect type, product and production run.
View the example viewQuality and inventory
Bring inspection outcomes and material availability alongside production. Find recurring shortages and quality patterns.
View the example viewWorkforce performance
Review labour efficiency and shift coverage in context, with reporting that helps teams plan rather than single out individuals.
View the example viewCritical asset watchlist
Illustrative risk ranking · review with maintenance planning
Press line motor 04Vibration trend · run hours · service history
Review soonHigher risk
Compressor BTemperature drift · cycle count
Plan checkWatch
Filler drive 02Stable cycles · recent maintenance
RoutineLower risk
Predictive maintenance
Act before a critical asset stops the line.
Failure scores are useful when they point to a real maintenance decision. We combine available machine and maintenance signals, rank assets by risk and show when an intervention could fit around planned work.
Good inputs matter more than a clever model.
- Assess cycle counts, run hours, temperature, vibration, maintenance history and quality drift.
- Connect recommended checks with your maintenance system and shutdown calendar.
- Confirm data history and sensor coverage before deciding whether predictive modelling is justified.
Production quality analytics
Connect process conditions to quality outcomes.
Link process parameters and batch records to inspection results. The view can show which conditions tend to appear before a defect, then track the pattern by product, line, shift or supplier batch.
Catch drift while there is time to act.
Process conditionsTemperature, speed, pressure and operating ranges
Batch and inspection recordsProduction context matched to checks and results
Quality drift to reviewEarly indication when a measure moves outside its normal band
Defect rate by batch
Illustrative trend view · hover a bar for a batch reference
Within normal range
Review condition
Batch 2401Batch 2408
For food and beverage producers, reporting can include batch traceability, shelf-life checks and specification compliance.
Built around your production setting
Useful views for engineering firms and food producers
Production teams use different terms, shift patterns and checks. We configure the measures and reporting cadence around the work your people already do.
Context makes the numbers useful.
Engineering and fabrication
See job progress beside machine use and delivery commitments.
- Machine utilisation and job status
- Rework and first-pass quality
- On-time delivery against plan
See an example use case
Compare planned and actual machine time across a fabrication cell, then trace late work to queue time, setup overruns or rework.
Food and beverage
Keep yield, changeovers and batch checks in the same view.
- Batch yield and material variance
- Changeover and hygiene-related downtime
- Specification and traceability checks
See an example use case
Review yield by product and batch, then compare quality checks with process conditions and supplier batch details.
General manufacturing SMEs
Give site and shift leads a consistent operational picture.
- Multi-site and shift comparison
- Material consumption variance
- Output and labour efficiency
See an example use case
Compare like-for-like lines across shifts or sites, with local targets and definitions visible beside the measures.
Shift patterns, product terms and reporting cadence are agreed with the people who use the dashboard.
What the system makes easier to see
Useful outcomes start with evidence.
Every plant has different constraints. We report what your production data supports, then give your team a clear place to focus its next improvement.
Stoppages to plan around
Use asset risk signals to help maintenance teams schedule an intervention before a failure disrupts production.
OEE losses with a cause
Find recurring availability, setup and changeover losses by line, product and shift.
Quality drift in context
Review process conditions and batch records before a small shift becomes a larger rejection issue.
Cleaner shift handovers
Bring production, downtime and quality information into one view for daily team discussions.
These are areas a well-grounded dashboard can help a team examine. Results depend on data quality, process changes and how measures are used on site.
Start with the production problem
Walk through your production data with us.
Tell us which loss is hardest to explain: repeated changeover overruns, an unreliable asset or quality variation between batches. We'll begin by assessing the machine, MES, ERP and spreadsheet data you already have.
Bring the question your team is asking.
- Map the available sources and agree which production measures matter first.
- Review practical data gaps, ownership and reporting needs with your team.
- Arrange an on-site discussion in West Yorkshire or a remote session elsewhere in the UK.