Sample Assessment Deliverable
What the 10-Day Throughput Reliability Assessment actually produces. Based on a real facility. Numbers are real.
The following sections represent the core deliverables of a Throughput Reliability Assessment on a food manufacturing facility with four production lines over 83 days of MES data.
Data Trust Audit
Before any analysis, we validate data quality. Reason codes, planned vs. unplanned classifications, target rates, and shift boundaries are checked for consistency. Issues are flagged before they corrupt the diagnosis.
| Check | Status | Notes |
|---|---|---|
| Target rates validated | ✓ Pass | Nameplate rates confirmed against validated speeds for all SKUs |
| Planned downtime classification | ⚠ Flag | Sanitation coded as “planned” on Lines A/B but “unplanned” on C/D. Inconsistency inflates availability on two lines. |
| Reason code coverage | ⚠ Flag | 37% of downtime events on Delta coded as “Other” — reason code discipline needs improvement before root cause analysis is reliable. |
| Shift boundary alignment | ✓ Pass | MES shift cutoffs match production schedule. No orphan events. |
| Short stop capture | ✓ Pass | Events ≥30 seconds captured. Sufficient for pattern analysis. |
Data trust issues don’t stop the assessment — they become part of the deliverable. If your reason codes are unreliable, that’s diagnostic information.
TRI Baseline — OEE vs. TRI Comparison
The core output: every line classified by operating state with reliability and direction scores alongside traditional OEE.
| Line | OEE | OEE Rank | CV | TRI | TRI Rank | Operating State |
|---|---|---|---|---|---|---|
| Charlie | 31.1% | #2 | 0.118 | 0.380 | #1 | Strong but Unstable |
| Bravo | 31.7% | #1 | 0.248 | 0.299 | #2 | Strong but Unstable |
| Alpha | 19.3% | #3 | 0.285 | 0.168 | #3 | Weak & Deteriorating |
| Delta | 18.2% | #4 | 0.721 | 0.067 | #4 | Weak & Deteriorating (Critical) |
Key finding: Bravo and Charlie both report ~31% OEE. OEE says they’re equivalent. TRI reveals Charlie is 27% more reliable (CV 0.118 vs. 0.248). A planner treating them as equivalent will be wrong more often than right.
Variance Decomposition
Where the instability lives for each line — and who owns the fix.
Alpha — primarily schedule-induced
Within-shift (equipment) 25% · Between-crew 20% · Schedule-induced 45% · Special cause 10%
Bravo — primarily between-crew
Within-shift 20% · Between-crew 50% · Schedule-induced 20% · Special cause 10%
Charlie — low variance across all categories
Within-shift 40% · Between-crew 25% · Schedule-induced 25% · Special cause 10%
Delta — extreme variance, primarily equipment + crew
Within-shift (equipment) 40% · Between-crew 35% · Schedule-induced 15% · Special cause 10%
What this means: Bravo’s instability is 50% crew-driven. The fix is standard work and training, not maintenance. Alpha’s instability is 45% schedule-driven. The fix is changeover optimization and product sequencing, not equipment. The Pareto chart can’t tell you this.
Financial Exposure by Line (EVAR)
The dollar cost of throughput instability. Seven categories, computed from actual plant economics.
| Line | Lost Throughput | Excess Labor | Expediting | Safety Stock | Maint. / Quality / Service | Total EVAR |
|---|---|---|---|---|---|---|
| Delta | $145K | $98K | $87K | $72K | $108K | $510K |
| Alpha | $142K | $95K | $52K | $41K | $50K | $380K |
| Bravo | $68K | $54K | $72K | $58K | $38K | $290K |
| Charlie | $88K | $45K | $32K | $28K | $27K | $220K |
| Total | $443K | $292K | $243K | $199K | $223K | $1.4M |
Delta accounts for 36% of total plant exposure despite second-lowest volume. Its extreme variance (CV = 0.721) creates cascading costs across every category. This is the line OEE treats as “about the same” as Alpha.
Prioritized Intervention Plan (Ranked by Return)
| # | Line | Intervention | Primary Driver | Est. Cost | Annual Recovery | Return |
|---|---|---|---|---|---|---|
| 1 | Delta | Stabilization sprint: reduce CV from 0.721 to 0.400 | Equipment + crew variance | $15–25K | ~$280K | 11–19x |
| 2 | Bravo | Standard work + crew training program | Between-crew variance (50%) | $8–12K | ~$145K | 12–18x |
| 3 | Alpha | Schedule optimization + SMED on top changeovers | Schedule-induced variance (45%) | $10–18K | ~$170K | 9–17x |
Interventions ranked by return on investment, not by severity. A traditional Pareto would send CI to Alpha (worst OEE). VOI analysis sends it to Delta (highest return per dollar invested).
What the full report also includes
- Weekly TRI trajectory — week-by-week progression showing where reliability improved, declined, or broke (see the timeline)
- Shift-level and crew-level breakdowns behind the variance bars above
- Short-stop pattern analysis — clusters that precede major faults
- 30/60/90-day recurrence checkpoints for each intervention
- Data quality improvement roadmap for flagged issues
Want this for your plant?
$3,000–$5,000 · 10 business days · 90 days of shift-level OEE data
If it doesn’t surface at least one decision your current reporting missed, you pay nothing.
Based on an actual assessment. Line names anonymized. Numbers are real.
Throughput Reliability Index is proprietary methodology of Crusoe Advisory LLC.