33% more production with the same equipment

The company had committed to 33% more volume. Management thought the capacity was there. The plant disagreed.

Background

A manufacturing company had signed an agreement to deliver 33% more volume to its customers.

An increase of 55,000 tonnes.

Management was calm. The capacity should be there. Sales had done the maths.

The plant was less calm.

In short

Situation: Sales had sold 33% more than current production volume. Deadline: the following year.

Problem: Management and the plant used different assumptions in the OEE calculation and arrived at entirely different numbers. Management: OEE 56%, target 75%. The plant: OEE 67%, target 90%. Both described a 33% increase, but they were solving two entirely different problems.

Action: Build a shared understanding of OEE. Break the target down into sub targets for availability, performance and quality. Set concrete limits for changeover time, process stops, technical stops and cleaning. Weekly root cause analysis and follow up.

Result: 55,000 tonnes of additional production delivered on time. The company's revenue grew by NOK 1.6 billion that year, against NOK 900 million in increased costs (source: proff.no).

The challenge: two sets of numbers, two realities

The first meeting revealed something important.

Management had calculated OEE at 56% and set the target at 75%. In their world, this was about using existing capacity slightly better.

The plant had calculated OEE at 67% and knew they had to reach 90% to deliver the volume that had been sold. In their world, this was a demanding lift that would require systematic work over time.

Neither of them had done the maths wrong. They had simply used different assumptions, and nobody had sat down to sort it out.

The result was that they lived in two completely different realities.

In management's numbers, the task looked manageable. The plant knew it was not that simple.

And as long as they disagreed on the numbers, they were never going to agree on the solutions.

What we actually did

We did not start with actions. We started with the measurement.

Together we went through how OEE should be calculated, step by step, so that everyone had the same numbers in front of them. Management, production and maintenance.

Once we finally agreed on what OEE was, and what drove it, it became much easier to align the organisation around what actually had to be done.

OEE breaks down into three components:

- Availability: is the equipment available and running when it should be?
- Performance: is it producing at the right speed?
- Quality: is it producing the right product first time?

We quickly saw that availability was where we had the most to gain. It averaged around 70%. The target was 93%.

That is where we put the effort.

Four concrete sub targets for availability

Availability is too big a number to work with. So we split it into four sub targets, each with a clear owner and a threshold for what was acceptable.

• Changeover between product variants: a maximum time per day per line was set. The number of changeovers was reduced, and where possible they introduced running transitions instead of a full stop.

• Process stops: maximum time per day per line. Weekly meetings with the shift leaders, root cause analysis of every stop, actions along the way.

• Technical stops: maximum time per day per line. Weekly meetings with maintenance, review of causes and closer follow up of critical equipment.

• Cleaning: maximum time per day per line. The tasks were mapped, described and organised into fixed rounds.

The thresholds were not the same for every line. They were set based on what was actually achievable on each line, not on what someone wished for.

It sounds simple. It was not.

Behind every sub target were concrete causes that had to be understood before they could be solved. Equipment that failed again and again. A fault in a heating process. Communication failures between two systems that were supposed to talk to each other. Intermediate storage filling up because production and dispatch were not coordinated.

None of them could be fixed in a single meeting.

Week after week. Stop by stop.

What actually turned it around

It was not one single action that made the difference.

It was that everyone worked towards the same target, with the same numbers, and that we followed up weekly.

Management stopped assuming the capacity "was there". The plant stopped explaining problems that management did not understand. And when something went wrong, we went to root causes, not to blame.

We also saw that the products were seasonal. That required building stock during parts of the year to use full capacity through the whole season. It became part of the production plan.

The solutions stuck because everyone had been part of understanding the problem.

Does this sound familiar?

Maybe you recognise the dynamic:

- Management and production disagree on what the numbers mean, but nobody sits down to sort it out.
- Actions are decided before everyone agrees on what the problem is.
- The capacity "should" be there, in theory, but in practice it is not.
- Root causes stay unsolved because daily operations always win over analysis.
- Results swing from week to week and nobody quite knows why.

If one of these hits home, you are probably solving symptoms.

Not what is actually driving them.

What this taught me

A shared understanding of the current situation is not a soft warm up step at the start of a project.

It is the condition for the solutions to work at all.

In this project we spent a lot of time establishing an OEE calculation the whole organisation could stand behind. It felt slow. It felt like we were postponing "the real work".

But that was the real work.

And once it was done, everything else went much faster than it otherwise would have.

Frequently asked questions

What is OEE?
OEE (Overall Equipment Effectiveness) measures how effectively production equipment is used. It is calculated as availability multiplied by performance multiplied by quality. An OEE of 100% means the equipment produces the right product, at the right speed, without stops.

Why is it common for management and production to have different OEE numbers?
Because OEE can be calculated in several ways, and the assumptions are rarely discussed openly. What counts as planned downtime? What is included in available time? These choices give different numbers, and without a shared definition people work towards different targets.

What are typical causes of low availability?
Long changeover times, frequent product changes, technical stops that are not followed up systematically, process stops handled reactively, and cleaning routines that are not coordinated with operations.

Can you increase capacity without investing in new equipment?
Yes, in most cases. Availability on existing equipment is rarely optimised. A systematic review of stops, changeovers and maintenance often gives considerable capacity improvement before any investment is needed.

Want more stories about problem solving?

This story is from our weekly newsletter, where we share experiences. Short stories for those who want to solve problems at the root, and achieve measurable, lasting value.

Want to learn more about the topics in this post?

- Understand what OEE really measures, and how to calculate it consistently

- Map and improve production processes from start to finish

- Shared focus first: how to build the same understanding of the problem

- Tell noise from signal with statistical process control