When setting up and converting vehicle production lines, everything is focused on the system ramp-up, but the critical phase before this is often underestimated.
The following applies:
The ramp-up is only the consequence.
The pre-ramp-up is the cause.
The pre-ramp-up is often seen as a "test phase". This falls short.
In reality, it is a systematic preparation for instability.
Because it is precisely this instability that awaits you in the ramp-up. Whether it's incomplete data, unstable processes, high dynamics or increasing pressure - there are many challenges to overcome during ramp-up.
The pre-ramp-up therefore has a clear goal:
👉 To make risks visible before they take effect
Research and practice show that ramp-ups consist of three clear phases:
And it is precisely the first phase that is often underestimated.
At the same time:
The less experience there is in the system, the higher the error rate in the system ramp-up.
This means
If you don't work cleanly in the pre-ramp-up, you are simply postponing the uncertainty.
The pre-ramp-up is not a checklist. It is a process for reducing uncertainty.
Typical questions:
The goal is not perfection, the goal is controllability.
Many projects test individual systems, processes and functions in the pre-ramp-up, but the decisive factor is overlooked: The system as a whole has never been tested.
This creates the following problem:
Simulations show that local changes in production systems often have an impact on the overall system that is difficult to predict without a system-wide view (see Simulation in Manufacturing Systems).
👉 This is precisely where the problems arise later in the ramp-up.
Simulations are a key lever in pre-ramp-up.
Why?
Because they make it possible to identify bottlenecks early on, analyze material flows, understand system behavior and test decisions in advance.
Simulation helps with one question in particular: What happens when everything runs simultaneously?
And that is precisely the reality of ramp-up.
Many projects focus on production and forget about the supply chain.
Research clearly shows that the performance of ramp-ups depends to a large extent on the integration of suppliers and project partners (see Terwiesch et al.).
Typical problems in the supply chain include missing parts, fluctuating quality and unstable delivery times.
👉 These problems do not arise during ramp-up. They only become visible there.
One crucial point is:
👉 Pre-ramp-up = learning process
Studies show that successful ramp-ups depend heavily on continuous improvement, integration and close collaboration (see Procedia CIRP).
This means
👉 Not once - but iteratively.
Now it's getting specific. The following five levers of the pre-ramp-up contribute significantly to its success.
The question should not be: "Does the system work?"
But rather:
👉 "Does the overall system work under real conditions?"
Through the targeted use of simulations, for example for bottleneck analyses, running through various scenarios and testing load situations, assumptions can be replaced by findings.
Without a stable supply chain, there is no stable ramp-up. It is therefore important to involve suppliers early on in the pre-ramp-up, to test material availability and to take fluctuations into account.
This can minimize risks at an early stage and make the ramp-up more reliable.
A strong database is created through uniform information, up-to-date data and clear transparency. The earlier the project's database is consolidated, the more clearly the project can be managed.
Always reacting to challenges and risks means always being at least one step behind. By identifying risks at an early stage, understanding the effects and defining measures, the project can be optimally prepared.
Many try to shorten the pre-ramp-up - because it brings "no direct output".
This is a mistake.
Because: the pre-ramp-up determines the costs of the ramp-up.
More preparation = less chaos
The biggest mistake in project management:
The ramp-up starts with production.
The reality:
👉 It starts in the pre-ramp-up.
This is where it is decided how stable processes are, how transparent the project is and how well risks are understood.