From Pilot to Robust Industrial Production
Many processes that work in pilot struggle when scaled up. Variation that was manageable at small scale becomes costly in full production.
We help you understand what drives the variation — and build processes that deliver consistent quality at full scale.
Consulting
Process Mapping · DFMEA · MSA · SPC · Variation Analysis · Design of Experiments
We map the process, identify sources of variation and help you establish control — so you can scale with confidence.
Understanding Variation
Statistical Process Control (SPC) · Measurement System Analysis (MSA)
Learn to use SPC to determine capability and build robust processes. Learn to use MSA to ensure reliable measurements.
Determining Optimal Settings
Design of Experiments (DOE)
Learn to design efficient experiments that deliver maximum information with a minimum number of runs — and determine optimal settings.
What will you get out of the consulting?
- A clear picture of which process steps and factors drive variation in quality — based on data, not assumptions.
- A measurement system you can trust — MSA ensures your measurements reflect what is actually happening in the process.
- SPC that makes it possible to detect deviations early and respond correctly — without overreacting to normal variation.
- Optimal process settings based on designed experiments — so you scale with documented conditions, not trial and error.
- A team that understands the process and owns the improvements when the engagement is complete.
Robust Processes
When a process is scaled up, controlling variation is critical. Understanding where the variation comes from is the first step towards a robust process.
We use process mapping to identify possible sources of variation, combined with:
- SPC (Statistical Process Control): determine normal variation, stability and capability — essential for choosing the right strategy to make your process more robust.
- MSA (Measurement System Analysis): ensures your measurements are reliable and able to detect real differences in what you are measuring.
- Variation Analysis (Components of Variation): quantifies how much different sources — process steps, operators, machines or batches — contribute to the total variation.
Design FMEA
When developing new processes or products, we use Design FMEA to identify potential failure modes early — before they become costly problems in production.
Capability Analysis
We assess whether the process is able to deliver within customer specifications — and what it takes to achieve sufficient capability.
Relevant courses: SPC online course · MSA online course
Design of Experiment (DOE)
Design of Experiment (DOE) gives you maximum information with a minimum number of runs. Instead of testing one variable at a time — which is time-consuming and gives limited information — you test multiple factors simultaneously and see how they interact.
We use:
- Factor Relationship Diagram (FRD): plans the experiment so you understand the relationship between factors and noise variables before you start.
- Full and fractional factorial design: depending on the number of factors and available resources.
- Optimisation: determines which factor values give the best possible result.
Lean Tech has analysed 1,100 experiments at one company — where 150 runs would have given the same information. Well-planned experiments save time and resources.
We assist with design, execution and analysis of experiments — and offer courses for those who want to learn to do it themselves.
Course: Design of Experiment (DOE)
Productivity (OEE)
OEE (Overall Equipment Effectiveness) is a productivity indicator that reveals losses in production time and capacity. It helps you identify bottlenecks and prioritise improvement actions.
- We define available production time and stop causes in a way that gives actionable information.
- We analyse stop causes and calculate the effect of investing in buffer capacity or other measures to increase uptime.
- We help establish good routines for recording stop causes — so the data actually says something about the cause.
Lean Tech has helped companies increase capacity by 33% — a net gain of NOK 700 million in fish feed production.
What are typical challenges you help with?
Variation in quality that increases when scaling up, processes that are difficult to reproduce, uncertainty about which factors matter most for quality, and product development that takes too long because experiments are not efficiently planned.
Which industries do you work with?
We have worked with environmental technology scale-ups, food and beverage, chemical, pharmaceutical, diagnostic, metallurgical production and the defence industry. The methods are industry-neutral — it is about processes and variation, not products. They have the greatest impact where variation is costly and cause-and-effect relationships are not obvious.
What is the difference between consulting and training?
In consulting, we work with your processes and your data. In training, you learn the methods — and can apply them yourselves afterwards.
Where do we start?
With a conversation about the challenge. We are honest about whether we think we can help and what the right approach is. Get in touch for a no-obligation meeting.
Assignments
Contact info
Lean Tech AS | Kristoffer Robins vei 13
0047 481 23 070
Oslo, Norway
Lean
L - Look for solutions
E – Enthusiastic
A – Analytical
N - Never give up