What exactly does the process assurance at ZERO defects look like?

We don’t follow the classic process model with years of IT projects that end up with a large amount of personnel anda money at best delivering what was originally planned. Our process model is based on small, iterative cycles that can be realized with little expenditure of personal and money.

To this end, we select the process and the specific process step whose safeguarding promises the greatest benefit for the company. Be it because it has the highest error rate to date, manufactures the most expensive products or for other reasons. Next, we define which concrete requirements there are for the process, which parameters are known, which influencing variables have played a role in the process so far and which errors are known that need to be avoided. We collect the live data for these parameters etc. from the entire IoS/IoT landscape.  It does not matter which system (Planning Solution, Lean Solutions, databases, other systems) the data comes from. The collaboration of different applications ensures a more comprehensive view. An important advantage here is that not only internal, program data is used. In principle, all external systems with the associated data can be brought into the system via the open interface and displayed/used.

The complete safeguarding of the process results in zero-defect production. This process safeguarding can be approached as a quick solution, since only individual processes or process steps in which there is a particularly obvious need for action are initially iteratively safeguarded here. This means that you can start the validation process with little money and effort. The initial safeguarding of the process steps with the highest error potential results in directly measurable success.

As the process is thus secured and monitored more and more in detail and filigree, the logical consequence is a zero-defect production.

Iterative process protection

The following approach is used to ensure iterative process protection and feedback:

All data monitored in a process step are actively stored in our system. This data is assigned to the concrete product and process. As a waste product, we thus obtain complete traceability of all parts through the entire production process. Our dashboard can be used to view this data live in prepared form.

If the previously defined values are violated, one or more reactions can be triggered. This can be concrete information to the responsible worker/process representative/QMB/etc., a warning signal (optical/acoustic/etc.), up to a stop of a machine or even an entire production line.

Making unknown mistakes to known ones

The information to the responsible employee contains all known data on the specific product or process. If one of the already monitored characteristics has been violated, we speak of a known error. After an analysis of the cause of the error, the corresponding characteristic is adapted and the error can easily be avoided in the future.

We speak of unknown errors when an error occurs but none of the monitored characteristics has been violated. Here, too, an analysis of the cause of the error must be performed. The result of the analysis then leads to either adapting existing characteristics or adding completely new characteristics for monitoring. As a result, unknown errors become known errors and can also be prevented in the future.

Since this feedback runs continuously, all errors are discovered, known, and ultimately prevented step by step.

**automatically translated**