maji Tool

Speed-Downtime Trade-off

Interactive calculator for sales-constrained environments. Find the optimal line speed where UPLH (Units Per Labour Hour) peaks, accounting for speed-induced reliability and quality degradation.

This page was created by maji, majaco's AI operational excellence tool. maji is in active development, so occasional inaccuracies may appear as the system continues to learn.

Understanding the Speed-Downtime Trade-off

In sales-constrained environments, labour efficiency (UPLH — Units Per Labour Hour) drives profitability. When demand exceeds capacity, every unit your line can produce has full margin value.

Increasing line speed boosts throughput, but typically degrades availability and quality. Run too fast and downtime eats the gains. Use the calculator below to find your optimal operating point.

UPLH = Speed × Availability × Quality ÷ Operators

Calculator

Baseline Parameters

100 units/hr
85%
98%
4 people
8 hours

Speed Increase Scenario

+0%

Degradation Sensitivity

5% per 10%
2% per 10%

Results

Baseline UPLH
Your Scenario UPLH
Change
Optimal Speed
Optimal Increase
Optimal UPLH

Your Position vs Optimal

Your Scenario
--
units/labour-hr
vs
Optimal
--
units/labour-hr

UPLH vs Speed Curve

Hover over the chart to see UPLH at each speed increase level.

This only finds the local optimum

What this calculator does is find the best speed to run at given your current conditions, without any problem solving. It takes the trade-off between speed, availability and quality as a given, and works out where UPLH peaks within that trade-off. That’s useful, but it’s worth being honest about what it doesn’t do.

Most manufacturers run their lines too “safe”. The reason is straightforward: if the line is running 10% below its capability, nobody notices. Speed loss is invisible. But if you speed up and breakdowns increase or waste spikes, those are very visible problems — people get calls, managers ask questions. So the natural tendency is to drift toward a comfortable speed that avoids those visible problems, even if it quietly leaves a lot of UPLH on the table.

This tool helps you use data to determine the actual optimal at current conditions, rather than relying on the “it runs fine at this speed” default.

The real gains come from changing the curve, not riding it

The much bigger opportunity is to actually solve the problems that appear as you speed up, rather than just accepting them as the cost of going faster. If you can work out why availability drops at higher speeds and fix the root causes, you don’t have to compromise at all — the whole curve shifts upward and the jump in UPLH is far more significant than anything you get from optimising within the existing trade-off.

That kind of work needs a systematic, rigorous and logical approach to problem solving. In our experience, tools like 5 Whys and fishbone diagrams tend to produce educated guesswork — they’re familiar and comfortable, but they rarely get to root cause on the kinds of speed-related reliability and quality problems that actually constrain throughput.

If you want to see what this looks like in practice, take a look at how we helped Proper Snacks break through their line speed constraints. And if you want to explore how problems decompose into solvable parts, try the Split Solve tool.

majaco can help you break through these constraints

We have a method for systematically identifying and solving the problems that limit line speed — structured root cause analysis that follows the evidence rather than the opinions in the room. If you want to move beyond optimising within the trade-off and actually shift the curve, get in touch.

Talk to majaco