Reliability Dashboard
Monitor key reliability KPIs — MTBF, MTTR, and Availability — computed from your live asset and work order data to identify failure trends and improve maintenance strategy.
Overview
The Reliability Dashboard is a read-only analytics screen that aggregates data from the Asset Registry and Work Orders to surface equipment reliability metrics. It requires no manual data entry — all figures are computed automatically from your existing maintenance records each time the screen is loaded.
Computed from Live Data
All metrics are derived on the fly from your asset and work order records. There is no separate data store for reliability data. The more complete your work order history, the more accurate the metrics.
📈 MTBF
Mean Time Between Failures — average operating time between corrective work orders per asset. Higher is better.
🔧 MTTR
Mean Time To Repair — average hours spent on corrective work orders. Lower means faster repairs.
⚡ Availability %
Calculated as MTBF / (MTBF + MTTR) × 100. Represents the percentage of time equipment is operational.
🏭 Asset Breakdown
Assets grouped by criticality (Critical / High / Medium / Low) with per-asset failure count and health score trends.
AI Assistant
A chat panel on the right edge reads the fleet-wide MTBF/MTTR/Availability KPIs plus the worst-MTBF and highest-MTTR asset rankings to generate executive summaries, root-cause explanations, and quantified recommendations — it explains the numbers already on screen rather than editing any assets or work orders.
Key Metrics Explained
MTBF — Mean Time Between Failures
MTBF measures how long an asset operates on average before requiring a corrective repair. It is computed per asset from the time gaps between consecutive corrective work orders. The fleet-wide MTBF is the average across all assets that have at least two corrective work orders.
Formula: Total operating time ÷ number of failures. Where operating time is approximated from the date range of work orders for that asset.
A rising MTBF means your preventive maintenance program is working. A falling MTBF signals an asset under increasing stress.
MTTR — Mean Time To Repair
MTTR is the average labour time per corrective repair, derived from the Estimated Hours field on Corrective work orders that are in Completed status.
Formula: Sum of estimated hours on completed corrective WOs ÷ count of completed corrective WOs.
A low MTTR means your team responds and resolves faults quickly. A high MTTR may indicate skill gaps, spare parts unavailability, or poor fault diagnosis procedures.
Availability %
Availability expresses what fraction of planned operating time an asset is actually available for production.
Formula: MTBF ÷ (MTBF + MTTR) × 100
An asset with MTBF = 240h and MTTR = 8h has Availability = 240 / (240 + 8) × 100 = 96.8%. World-class availability targets are typically 95%+.
| Metric | Source data | What improves it |
|---|---|---|
| MTBF | Corrective work order dates | Consistent preventive maintenance, replacing wear-prone parts proactively |
| MTTR | Estimated Hours on completed corrective WOs | Spare parts stocked on-site, skilled technicians, clear repair procedures |
| Availability % | Derived from MTBF + MTTR | Increasing MTBF and/or decreasing MTTR simultaneously |
Dashboard Layout
The Reliability Dashboard is organised into three rows of information:
Row 1 — Fleet KPI Tiles
Four summary tiles across the top of the screen showing the fleet-wide values for MTBF (hours), MTTR (hours), Availability (%), and total open corrective work orders.
Row 2 — Asset Criticality Breakdown
Assets grouped into four criticality bands (Critical, High, Medium, Low) with a count in each. This comes directly from the criticality field on the Asset Registry.
Row 3 — Per-Asset Reliability Table
A sortable table showing each asset with its individual MTBF, MTTR, Availability %, failure count (number of corrective work orders), and current health score from the Asset Registry. Sort any column to find the worst-performing assets.
Focus on Low Availability Assets
Sort the per-asset table by Availability % ascending to immediately identify your most problematic assets. These are candidates for root cause analysis, design improvements, or replacement.
Data Requirements for Accurate Metrics
The dashboard metrics are only as accurate as the underlying data. For reliable numbers:
- All corrective repairs must be logged as Work Orders with type set to Corrective.
- Work orders must be moved to Completed status when the repair is finished — open work orders are excluded from MTTR calculation.
- The Estimated Hours field on each work order must be filled in accurately — it is used directly in MTTR.
- Assets must be registered in the Asset Registry before their work orders contribute to per-asset metrics.
New Installations
If you have fewer than 2 corrective work orders for an asset, MTBF cannot be calculated and the asset is excluded from the fleet-wide average. Allow 2–3 months of normal operation before treating the metrics as statistically significant.
Work Order Completion Rate
A secondary KPI shown on the dashboard is the Work Order Completion Rate: the percentage of all work orders (across all types) that are in Completed status. This measures your team's throughput and backlog health.
A completion rate below 70% usually indicates an understaffed maintenance team or an excessive volume of open work orders accumulating in the Open column without being processed.
AI Assistant
Click the vertical AI Assistant tab on the right edge of the screen (or the Sparkles toggle) to open a chat panel over the dashboard. Because the Reliability Dashboard is a chart/KPI screen rather than a record list, the assistant is scoped to dashboard-style capabilities only — it narrates and explains the aggregate numbers already rendered on screen, it does not edit any assets or work orders:
- Executive summary — a plain-language readout of the plant's current reliability standing, calling out the best and worst performing assets by name (e.g. "Average MTBF is 575h, above target, but CNC Machine A1 is the weakest at 397h").
- Root cause & anomaly detection — when MTBF has dropped or MTTR has spiked for a specific asset, the assistant explains which asset is driving the plant-wide trend and by how much.
- Recommendations — turns an observed weak spot into a concrete, quantified suggestion (e.g. shortening a preventive maintenance interval for a specific asset), grounded in the actual numbers shown on the dashboard.
Every reply can be saved with the Save as Report button, which stores it in My Reports under a title derived from your question and the current month/year. The panel respects the currently applied date range and criticality filter, and the Writer Engine selected in Settings → Agentic (Local CLI, Hosted API, Local LLM, or Ollama) — Ollama and other local/in-browser engines run entirely on your own machine and never proxy through the server.