Operational dashboard
Production, quality and supplier health for the current shift.
Production system status
Shift A · 6 assets · illustrative valuesProductivity
Target 90%OEE
Target 75%Dial status uses the selected target: green at or above target, amber up to five percentage points below, red further below. Trends and values are fictional demo data.
OEE = availability × productivity × quality (96%).
In-process defects
Incoming & production defects
Counts by detection point; production is the same seven findings shown in WIP.
Supplier performance
Overall system RIO status
Risks · Issues · Opportunities
Availability
Machine runtime as a share of planned production time.
Needs a decision
TRACE / NW-204
One sample unit
A record link shows where to inspect; it is not proof of conformity.
Follow the handover
Process
Find a handover, inspect authority, and check objective evidence. Actual SOP methods are withheld.
No steps match. Clear the quick filter or select All Steps.
Evidence states respond to demo checkboxes in this browser session. They are not live verification results.
Controlled documents
Find the current identity and review state. Procedure text and signatures are masked.
Only document metadata is shown. Full SOP text, templates and approval signatures are not included.
Evidence trail
Unit NW-204 · fictional electromechanical assembly. Select a handover to inspect its record link.
The sequence shows relationships only. Underlying records and acceptance criteria are withheld.
Actions & approvals
See the owner, next decision and retained evidence for each sample item.
Signals for review
Illustrative measures point to records that need context. People validate the evidence and decide.
TREND / 06 MONTHS
Actions closed on time
REVIEW PROMPTS
Open the source
Open the related disposition record before judging trend.
Check effectiveness evidence and similar failures.
Confirm the owner and current revision.
The chart and prompts use fictional values. They do not report any buyer's performance.
SURIYAONE / OPERATIONS INTELLIGENCE
Turn machine loss
into an owned decision.
Follow one representative shift from machine signal to reason, quality outcome and financial context. Test a response before assigning the work.
Northstar Works · Sample shift
08:00–16:00 · 23 Oct 2026
- 01 / OBSERVEWhat happened?Machine states and part counts
- 02 / EXPLAINWhere was capacity lost?Reasons, speed and scrap
- 03 / MODELWhat would change?One bounded improvement
- 04 / ASSIGNWho checks the result?Owner and evidence to retain
The shift, accounted for.
An eight-hour shift less a 30-minute planned break. The remaining time is divided into good output and three distinct losses.
Reason evidence
Sample records · operator context neededChoose the loss to tackle.
Change one assumption at a time. The model holds the other shift factors constant so the comparison stays legible.
≈5.5additional good pieces / shift
63.6%modelled OEE · from 58.7%
Recovering alarm time adds runtime. Current speed and yield are held constant.
Verify the alarm code, root cause and restart record; compare stop minutes across the next five shifts.
What the shift carries.
A transparent cost basis links the quality and capacity result to a per-good-piece estimate. It is not a selling price.
Edit the illustrative cost basis
What this can support.
Availability × performance × quality. The 450-minute time bar reconciles to 264 good, 90 stopped, 72 speed-loss and 24 scrap-equivalent minutes.
Purchase value divided by useful life assumes zero residual value. This, upkeep, space/tooling, staffed time and runtime energy are divided by modelled annual good pieces. A recovered stop can add energy use.
Assign a cause, action owner and follow-up measure. Confirm machine and quality records before treating a modelled change as real.
All machine events, counts and amounts are fictional. No telemetry, ERP, QMS, operator log or buyer record feeds this demo. The scenario is a capacity and unit-cost illustration, not realised savings or a forecast.