The planning system has a rate for every SKU on every line. It was entered when the line was installed, or when the product launched, or by someone who divided the nameplate by a factor that seemed reasonable at the time. It has not been checked against the line since.
It is not the rate the line runs at. In our experience the standard often sits 5 to 15% above what machine data shows, changeovers are planned at a time nobody measured, and every plan built on them is over-committed before Monday starts. The planner finds out on Tuesday, the gap becomes overtime by Thursday, and the next capacity review concludes the plant is at its limit.
The OEE audit article was about the OEE number being wrong. This one is about what the planner does with the wrong number, and what changes when the plan is built on the rate the line actually delivers.
Ask a planner where a planning rate came from and the answer is usually one of four.
Nameplate times a factor. The vendor said 200 units a minute; somebody applied 70%, the OEE the plant believed it ran at, and entered 140. The factor was a guess about losses, made before anyone had measured them.
The launch trial. The SKU ran for two hours under supervision on a Tuesday afternoon with the engineering team watching, and the rate from that run became the standard. It has never been achieved since.
Copied from a similar SKU. The new format looked like an existing one, so it inherited the rate. The two run differently on the labeler, and nobody has compared them.
Nobody knows. The number has been in the system for six years. The person who entered it has left. It is now the standard because it is the standard.
Each of these is a belief about the line. A demonstrated rate is a measurement of it. The difference between the two is the difference between a plan that holds and one that does not.
Over-committed. The standard is above the demonstrated rate, which is the common case. The plan promises output the line cannot make in the hours available, and the shortfall appears as orders slipping, then as overtime, then, as the overtime article describes, as a Saturday shift that becomes permanent. The plant believes it is capacity-constrained because the plan is always short; the plan is always short because the rate is wrong.
Under-committed. The standard is below the demonstrated rate. Less common, but it happens on lines where the loss work has been done and the planning rate was never raised, or where a cautious planner set a safe number. The line finishes early, idles or runs slow to fill the shift, and the capacity is invisible. A plant looking for a new line sometimes already owns one in the gap between its conservative standards and what its lines can do.
Both are fixed by the same change: plan at the rate the line has demonstrated, and keep the standard as the target it was meant to be.
A demonstrated rate is the output rate a line actually sustains on a given SKU, measured from machine data over enough runs to be representative. Five rules make it usable for planning.
Per SKU, per line. Not a line average. The series line runs its six formats at six different rates, and the slowest is 25% below the fastest. A line average plans the slow format too tight and the fast one too loose, and both show up as misses.
From machine data. The count from the PLC or a sensor, not the shift report and not the ERP confirmation. The reasons are the same as in the OEE article: self-reported numbers drift toward the standard.
Over enough runs. Every crew, several runs per SKU, at least four weeks. One run is a trial; a month is a rate.
As a distribution, not a single number. Plan at the median or a stated percentile and keep the spread visible. A format that runs at 138 on nights and 120 on days has a planning rate and a problem, and the plan should know about both.
Exclude what is planned separately, include what the line does. Changeovers and planned downtime are scheduled as their own blocks, so they come out of the rate. Micro-stops, speed loss, unplanned stops and waiting on bulk are what the line does in the time it is meant to run, so they stay in. A demonstrated rate that strips out micro-stops is a standard with a new name.
Refresh it monthly. As the loss work lands, the demonstrated rate should rise, and the plan should tighten with it. A demonstrated rate that is not refreshed becomes the next six-year-old standard.
This is the paragraph the VP Operations needs, because the objection is predictable: planning at the demonstrated rate sounds like lowering the bar.
It is not. The rated speed stays as the target the CI team works toward. The plan uses the demonstrated rate, because the plan is a commitment to customers and crews, and commitments should be made on what the line will do. The gap between the two contains the recoverable capacity from the hidden capacity method, along with losses only equipment will remove. Planning this way keeps that gap visible as a number, per line and per week, instead of hiding it as padding smeared across every run time.
When the loss work closes part of the gap, the demonstrated rate rises, the plan tightens, and the plant makes more with the same hours. The ambition is unchanged. What changes is that the plant stops paying for the ambition in overtime every week while it waits for the improvements to arrive.
A practical note for plants that are starting from nothing. The first demonstrated rates take four weeks of measurement to exist. In the meantime the plan runs on the estimates the plant already has, corrected as the data comes in. Starting with estimated times is not a compromise; it is how every plant starts, and the point is that the estimates get replaced by measurements rather than staying estimates for six years.
The capacity statement that goes up to S&OP is usually built on standards, which means the commercial team is being told the plant can make more than it can. When the plant then misses, operations is blamed for a number planning produced from a rate nobody checked.
Replace it with two lines per line and SKU family: demonstrated capacity, which is what the plant will make in the hours available, and the recoverable gap, which is what it could make if the loss program is funded and delivers. The commercial team then sees both numbers and can commit to the first while the plant works on the second. Both are honest, both are measured, and the conversation about whether to fund the recovery program happens with the value of the gap on the table.
The series line, six SKUs, 120 planned hours a week, 58% OEE on an honest basis, rated at 200 units a minute. The planning system carries 140 units a minute for every SKU, the rated speed times the 70% OEE the plant believed it ran at, and plans changeovers at the 25-minute standard. Four weeks of machine data gave the demonstrated medians below: good output per hour the line was meant to run, with changeovers planned separately.
| SKU | Standard (u/min) | Demonstrated median (u/min) | Gap | Note |
|---|---|---|---|---|
| A | 140 | 138 | 1% | |
| B | 140 | 132 | 6% | |
| C | 140 | 126 | 10% | Speed loss; line turned down after a jam in 2022 |
| D | 140 | 142 | −1% | Slightly under-committed |
| E | 140 | 106 | 24% | The labeler format from the micro-stops article |
| F | 140 | 136 | 3% |
A representative week’s orders needed 118 hours at the standard rates and changeover times. At the demonstrated rates and measured changeovers, the same orders needed 134 hours, against 120 available: about 8 hours more from the rates and 8 from the changeovers. The plan was 14 hours over-committed before it was issued, which is about what the 16-hour Saturday shift in the overtime article delivers at weekend productivity. The plant had been buying its planning error back at time-and-a-half for eighteen months.
Two changes. The week was replanned at demonstrated rates and measured changeovers, which made the over-commitment visible as a number rather than as a Thursday surprise. And SKU E, running at 106 here, was moved to line 4, where the same format demonstrated 130 on a labeler without the guide problem and the line had spare hours. The requirement on this line came to about 115 hours against 120 available, and the five hours left are the contingency the planner holds, visibly. SKU E on this line is now a named CI project with a value attached, and when the labeler fix from the micro-stops article lands and its demonstrated rate rises, the plan will tighten by itself.
Nothing on the floor changed in week one. The plan simply stopped promising fourteen hours the line did not have. The figures are illustrative; the shape, one or two SKUs far below standard carrying most of the over-commitment, is what we see on most high-mix lines.
A demonstrated rate needs the measurement and the plan in the same place: the rate has to come from the floor and go straight into the schedule, and refresh without anyone re-keying it. That is what Fabrico’s manufacturing performance platform (MES, OEE, CMMS & AI) is built for, and it is designed to work for a plant that has never measured a rate as well as one that has.
Start with what the plant has. The scheduling module runs on the planning times the plant already uses, entered as estimates, from day one. A traditional manufacturer does not need machine-verified rates to produce a finite schedule on the first morning; it needs its current standards in the system, and it has those. Estimated times are a fully supported way to operate the scheduler, not a fallback.
Replace estimates with measurements as they arrive. As the OEE module captures runs, it builds the demonstrated rate per SKU per line as a distribution. The planner sees the estimate and the measurement side by side, chooses when to switch each SKU over, and from then on the rate refreshes automatically. A plant moves from estimated to demonstrated one SKU at a time, at its own pace, with the gap between the two shown throughout.
The gap is the contingency. The scheduler plans at the chosen percentile of the demonstrated rate and shows the standard-versus-demonstrated gap as a visible number per line and per week, which is the contingency available to the replanning ladder when something stops.
Routing uses the per-line rates. Because the rate is per SKU per line, the scheduler sends each format to the line where it demonstrably runs best, which is how SKU E in the example moved to line 4 without anyone looking it up.
The financial impact module values the gap. With the selling price and margin entered once per SKU, the gap between standard and demonstrated is priced per SKU, which is how the CI backlog is ranked. SKU E’s 24% gap is the largest, but E is the line’s lowest-margin format, so a smaller gap on a premium format can rank above it. The AI actionable insights propose the fix and track whether the demonstrated rate moves after it.
The S&OP statement comes from the same numbers. Demonstrated capacity and the recoverable gap, by line and SKU family, are generated from the data the scheduler plans on, so the number given to the commercial team is the number the plant is running to.
Drift is flagged early. When a SKU’s demonstrated rate starts falling with no change in crew or material, the insights flag it before it reaches the attainment report. A falling rate is usually the earliest visible sign of a new loss on the line.
The plant keeps its standards as targets. The plan runs on what the line has shown it can do, and gets tighter as the line gets better.
What is demonstrated capacity? The output a line actually sustains on a given SKU, measured from machine data over enough runs to be representative, including the stops, micro-stops and speed losses the line routinely has and excluding changeovers and planned downtime, which are scheduled separately. It is a measurement; a standard is a belief.
Should you plan at standard or actual rates? Plan at the demonstrated rate and keep the standard as the improvement target. Planning at a standard the line does not achieve produces a plan that is over-committed before it is issued, and the shortfall becomes overtime. Planning at demonstrated does not lower the target; it stops paying for the gap every week.
How do you calculate a planning rate? Per SKU per line, from machine counts over at least four weeks and every crew, as a distribution; plan at the median or a stated percentile. Exclude changeovers and planned downtime; include stops, micro-stops and speed loss. Refresh monthly.
Why is my production plan always over-committed? Most often because the planning rates sit above what the lines demonstrate and changeovers are planned at the standard rather than the measured time, so the plan needs more hours than exist. One or two SKUs with a large gap usually carry most of the over-commitment, and they are the same SKUs the loss analysis will identify.
How often should planning rates be updated? Monthly from measured data, so that improvements on the line tighten the plan and new losses show up as a falling rate. A planning rate that is not refreshed becomes a standard again within a year.
If the planning system has one rate per SKU and nobody can say where it came from, four weeks of machine data will show how far it is from the truth, and how many hours a week the plan is promising that the lines do not have.
The fixed-scope pilot does that on one line: six weeks, machine-verified output per SKU per run with an industrial sensor and hub installed with your team, the demonstrated rate per SKU as a distribution next to the standard the plan currently uses, the over-commitment in hours for a representative week, and the three highest-value interventions, one of which is usually a routing change the planner can make the following week. The fee is fixed and credited in full against a first-year subscription if you roll out. The pilot runs on Fabrico’s manufacturing performance platform (MES, OEE, CMMS & AI), which connects machine data, OEE and loss analysis, production scheduling, SKU-level output value and maintenance in one system, so the rates the plan uses are the rates the lines deliver.
Request a demo or read how the scheduling module plans at demonstrated rates.
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