Process stability requires control. Not only over what happens within each cycle, but also over the variation caused by the material, machine, and environment.
By making that variation visible, we can control the process more effectively. This enables targeted adjustments and creates the foundation for consistent output.
SPC (Statistical Process Control) shows how a process behaves over time. Not at a single measurement point, but across full production runs.
By identifying trends and deviations early, we can make targeted adjustments before they impact the final result. This keeps the process within the specified parameters.
Wherever possible, we integrate measurement directly into the process. Inline controllers and vision systems perform checks directly during the cycle.
Deviations are not identified after the fact; they are detected immediately. This reduces response time and prevents variation from accumulating.
Not everything can be measured inline. That is why metrology remains an integral part of process control. Measurements taken outside the cycle provide insight into what the process actually produces and where deviations occur.
It is not about relying on one type of measurement, but about finding the right balance. Depending on what needs to be measured, we focus on accuracy, speed, or reproducibility. That context determines which measurement strategy and instrument are best suited to the task.
At ENBI, we combine proven measurement tools with advanced, innovative measurement technology when product solutions require deeper insight, greater accuracy, or more measurement data. Examples include:
Used for contactless, automated measurements in serial production. Pre-set measurement programs check multiple dimensions simultaneously, with reproducible results and minimal operator influence. Measurement data is stored immediately and provides the basis for analyses such as MSA (Measurement System Analysis) and SPC (Statistical Process Control).
Used for 3D measurement, in which the entire product is scanned and converted into a digital mesh. This allows the product to be compared against the drawing and deviations to be visualized, for example through color mapping. This is especially valuable in development projects and for complex geometries or hard-to-reach measurement points.
We use the results of these measurements not only for inspection, but above all to better understand what is happening within the process. By turning those insights into process adjustments, we create a more stable process, cycle after cycle, production run after production run.
Process data provides insight into production stability. While SPC shows how product quality develops over time, process data shows how consistently the process itself continues to run.
Using systems such as ALS (Automated Logistics Solutions), we monitor process data during production. Examples include parameters such as cycle times, temperatures, pressure curves, reject rates, and machine status. That data helps us recognize patterns and better understand where variation occurs.
The next step is to connect product data and process data in smarter, more meaningful ways. This provides deeper insight into the relationship between process settings and product quality, enabling us to make well-informed decisions that support stable output. Not on instinct, but on data, experience, and process knowledge.
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