One OEE dashboard that shows where your losses hide
Overall Equipment Effectiveness turns a shift into a single honest number, then splits it into Availability, Performance, and Quality. Brilliqs builds the dashboard that calculates it from your own data, so you stop guessing and start fixing the loss that costs you the most.
- One score built from three clear parts
- The six big losses ranked by impact
- Availability, Performance, and Quality side by side
- Years in delivery
- 20+Years in delivery
- Enterprise clients
- 135+Enterprise clients
- Data projects
- 500+Data projects
- Split every score
- 3 lossesSplit every score
Give every asset one score you can actually improve
Plenty of plants track output, uptime, and scrap in three separate places. Each number looks fine on its own, yet the shift still misses target and nobody can say why. The problem is that these figures never meet, so the real loss stays split across reports that no single person reads together.
An OEE dashboard fixes that by rolling those three ideas into one measure. It multiplies Availability by Performance by Quality and gives you a single percentage for each machine, line, and shift. When the score drops, the dashboard shows which of the three parts caused it, so the conversation moves from blame to action.
Brilliqs builds this around the way your plant already runs. We define your planned production time, your ideal cycle time, and your quality rules with your team, then wire the calculation to your live data. The result is an OEE number your operators trust and your Plant Director can defend.
Why your current OEE number does not add up
Most plants measure OEE at some point, but the way it is captured leaves the score soft. These are the gaps a proper OEE dashboard closes.
The score is calculated by hand
Availability, Performance, and Quality get pulled from three spreadsheets once a week. By the time the math is done, the shift it describes is long gone.
Nobody agrees on ideal cycle time
Performance depends on a target speed for each part. When that target is a guess or years out of date, the Performance factor is meaningless.
One number, no breakdown
A single OEE figure with no split hides the cause. You know the score fell, but not whether stops, slow running, or rejects pulled it down.
The six big losses stay uncounted
Breakdowns, setups, minor stops, speed loss, startup rejects, and process defects all drag OEE down. Without a loss waterfall, you cannot see which one to attack first.
What your OEE dashboard actually does
Every view exists to answer one question about your score. Here is what sits at the heart of the OEE dashboard Brilliqs builds.
The full OEE calculation, done live
The dashboard captures run time, part counts, and rejects from your assets, then computes Availability, Performance, and Quality and multiplies them into one OEE score. It updates as the shift runs, so the number is never stale.
- Availability from planned production time and actual run time
- Performance from ideal cycle time against real output
- Quality from good parts against total parts made
- OEE as the product of all three, per machine and line
The six big losses, ranked as a waterfall
OEE only helps when you can see what eats it. The dashboard maps every loss to one of the six standard categories and stacks them in a waterfall, so the biggest drain sits at the top of your list.
- Breakdowns and planned stops under Availability loss
- Minor stops and reduced speed under Performance loss
- Startup rejects and process defects under Quality loss
- Losses sorted by size so improvement effort goes where it counts
Benchmarks, targets, and TEEP in one place
The dashboard sets your current score against your own target and the widely used world class mark of around 85 percent. It also shows TEEP, so you can see effectiveness across all calendar hours, not just scheduled ones.
- Live score against your OEE target for each asset
- The world class OEE benchmark near 85 percent as a reference line
- TEEP to reveal capacity hidden in unscheduled time
- Trend of the score over shifts, days, and weeks
Features that keep your OEE score honest
Practical capabilities that make the OEE dashboard a tool your team leans on, not a report that gathers dust.
Live OEE score
A single percentage per machine and line that recalculates through the shift as parts and stops are recorded.
Three factor split
Availability, Performance, and Quality shown next to the headline score so the cause of any drop is clear.
Loss waterfall
The six big losses stacked from largest to smallest, turning planned production time into good output step by step.
Ideal cycle time engine
A managed library of target speeds per part so the Performance factor always compares against the right ideal.
Target and benchmark lines
Your OEE goal and the world class benchmark near 85 percent drawn on every chart for instant context.
OEE trend history
Score and factor trends over time so you can prove whether an improvement actually moved the number.
What a real OEE dashboard changes
The score is not the point. The point is knowing which loss to fight next and being able to prove the fight worked.
A number everyone shares
Availability, Performance, and Quality meet in one figure, so meetings start from one agreed measure instead of three.
Loss you can see
The waterfall shows exactly which of the six big losses drags your score, so effort lands where the loss is largest.
Focused improvement
Teams stop chasing every problem at once and work the loss with the biggest return on the OEE number.
A score you can defend
Because the math is consistent and live, the OEE you report holds up to scrutiny from the floor to the board.
How Brilliqs sets up your OEE dashboard
A clear path from first talk to a live OEE score your team trusts. No long study, no ripping out what you own.
Define the score
We agree your planned production time, ideal cycle time per part, and quality rules with your team, so the OEE calculation reflects how you really run.
Wire the inputs
We connect run states, part counts, and reject data from your machines and add simple operator inputs for reasons where sensors cannot see them.
Build the views
We design the score card, the three factor split, and the loss waterfall around your assets, then tune them with your supervisors.
Roll out and refine
We launch on one line first, train your crews to read the score, then extend across the plant and keep the targets current.
The three factors your OEE dashboard tracks
OEE is only as trustworthy as the measures behind each factor. These are the signals we surface under Availability, Performance, and Quality.
Availability
- Planned production time set for the shift
- Actual run time against unplanned stop time
- Breakdown and setup loss captured with reasons
- Availability factor as run time over planned time
Performance
- Ideal cycle time for each part number
- Actual output against the ideal running speed
- Minor stops and reduced speed loss made visible
- Performance factor as real pace over ideal pace
Quality
- Good parts against total parts produced
- Startup rejects separated from steady state defects
- Rework and scrap counted at the source
- Quality factor as good parts over all parts
Where an OEE dashboard proves its worth
The same OEE score supports very different jobs across the plant. A few of the ways teams put it to work.
Daily improvement stand ups
Teams open the loss waterfall each morning, pick the largest loss dragging OEE, and assign an owner. The next day the same screen shows whether the number moved.
- Biggest loss chosen from the ranked waterfall
- Actions tied to a specific OEE factor
- Yesterday's score compared against today
Bottleneck and capacity decisions
Operations leaders compare OEE and TEEP across assets to find the true constraint. A low score on the bottleneck matters far more than a high score elsewhere.
- OEE compared across lines and cells
- TEEP to reveal spare capacity in idle hours
- Investment aimed at the constraining asset
Setup and changeover reduction
When Availability loss is dominated by setups, the dashboard proves it. Teams run changeover projects and watch the Availability factor and the overall score climb.
- Setup loss isolated inside Availability
- Changeover time tracked run to run
- Score gains linked to each project
Quality and speed trade offs
Running a machine faster can lift Performance but hurt Quality. The dashboard shows both factors together, so the team finds the speed that gives the best OEE, not just the best count.
- Performance and Quality read side by side
- Startup rejects flagged after each changeover
- Best sustainable pace chosen by the score
Spreadsheet OEE versus a live OEE dashboard
The gap is not only speed. It changes whether your score can be trusted and acted on at all.
| OEE by spreadsheet today | With an OEE dashboard | |
|---|---|---|
| When the score appears | Weekly, once counts are keyed in by hand | Live, recalculated as the shift runs |
| The three factors | Blended into one figure with no split | Availability, Performance, and Quality shown apart |
| Finding the loss | Guesswork from a single low number | The six big losses ranked in a waterfall |
| Ideal cycle time | An old target buried in a workbook | A managed library kept current per part |
| Proving improvement | Hard to tie a change to the score | Trend lines link each action to the number |
Built to read the plant you already run
You do not need new machines to measure OEE well. Brilliqs pulls run states, counts, and rejects from what you already own, from modern controllers to older assets that only offer a basic signal, and fills the gaps with light operator inputs for stop and reject reasons.
We bring those inputs together, apply your OEE rules, and compute the score in one reliable place. Because our roots are in data engineering, the calculation behind your dashboard stays accurate and consistent as you add assets, lines, and sites.
A 62 percent score, explained in one screen
A short example of how the same shift reads with and without a proper OEE breakdown.
Say a line finishes a shift at an OEE of 62 percent. On a spreadsheet that is just a low number, and the morning meeting turns into a debate about whether the machine, the crew, or the material was at fault. Everyone has a theory and nobody has proof.
On the OEE dashboard the same 62 percent splits open at once. Availability sits high, Quality is fine, but Performance is low because a string of minor stops kept dropping the running speed. The loss waterfall puts those small stops at the very top, ahead of every other cause.
Nothing about the machine changed. What changed is that the team could see the score was a Performance problem, not a breakdown or a scrap problem, and could send the right people to the right cause the same day. Chase that one loss across a month and the score climbs toward the world class mark near 85 percent.
Why manufacturers choose Brilliqs for OEE
Plenty of tools print an OEE number. We build a score that matches your process and holds up as you grow.
Your rules, not a template
We define planned time, ideal cycle time, and quality with your team, so the OEE reflects your plant rather than a generic default.
Serious data engineering
Our background is data pipelines, so the calculation behind your OEE stays accurate and stable across every asset and site.
Vendor neutral
We read the machines and systems you already own and stay independent of any single equipment or software brand.
Support that stays
We teach your teams to read the score and keep the targets and rules current long after the launch shift.
Made for the people who own the score
An OEE dashboard gives each leader the view they need, from the machine to the boardroom.
Plant Directors
Hold every line to one consistent OEE measure and see at a glance which assets are pulling the plant down.
Production Managers
Read the three factor split each shift and send effort at the loss that is hurting the score right now.
Continuous Improvement Managers
Work the loss waterfall to pick high return projects and prove each one moved the OEE number.
Industrial Engineering Managers
Keep ideal cycle times honest and use Performance data to set realistic targets for every part.
Operations Managers
Compare OEE and TEEP across lines and sites to find the true constraint and guide capacity.
Manufacturing Heads
Track the effectiveness of the whole operation on one trusted score to steer investment and priorities.
OEE dashboard questions
Straight answers to what manufacturing teams ask before they measure OEE properly.
What is an OEE dashboard?
It is a live screen that calculates Overall Equipment Effectiveness for your machines and lines. It measures Availability, Performance, and Quality, multiplies them into a single OEE score, and shows the losses behind that score, so your team can see how well an asset really runs and where it is losing time or output.
How is OEE calculated?
OEE is Availability times Performance times Quality. Availability is actual run time divided by planned production time. Performance is real output divided by what ideal cycle time says the asset should have made in that run time. Quality is good parts divided by total parts. Multiply the three together and you get one OEE percentage.
What are the six big losses?
They are the six standard reasons OEE falls. Breakdowns and setup or adjustment losses sit under Availability. Minor stops and reduced speed sit under Performance. Startup rejects and steady state process defects sit under Quality. The dashboard maps every loss to one of these and ranks them so you know what to fix first.
What is a good OEE score?
The widely used world class benchmark for discrete manufacturing is around 85 percent, which comes from roughly 90 percent Availability, 95 percent Performance, and 99 percent Quality. Many plants start well below that. The useful target is steady improvement on your own baseline rather than chasing a single fixed figure.
How is OEE different from TEEP?
OEE measures effectiveness during planned production time only. TEEP, Total Effective Equipment Performance, measures it against all calendar hours, including unscheduled time. TEEP shows the extra capacity you could gain by running more hours, while OEE shows how well you run the hours you already schedule.
Do we need new machines to measure OEE?
No. Brilliqs reads run states, counts, and rejects from the equipment you already have, from modern controllers to older assets with a basic signal. Where a stop or reject reason needs a human, we add a quick operator input, so nothing is left out of the calculation.
How does an OEE dashboard help us improve?
It splits your score into Availability, Performance, and Quality and ranks the six big losses in a waterfall. That tells your team exactly which loss to attack for the biggest gain, and the trend lines then prove whether each action actually moved the OEE number.
Explore more efficiency and OEE tools
Explore the rest of the Brilliqs manufacturing suite and the services behind it.
Production monitoring dashboard
See live output, pace, and order progress across every line as the shift runs.
Machine performance dashboard
Track how each machine runs and spot the assets that need attention first.
Machine downtime monitoring
Capture every stop and its reason so you can cut Availability loss at the source.
Data analytics services
See how we turn raw plant data into decisions across the wider business.
See your real OEE, split three ways
Book a short demo and we will show you an OEE dashboard built around one of your own machines, with the loss waterfall behind the score.