Sensor technology plays a decisive role in the digitalization of industrial production. Today, many machines are already equipped with online interfaces that can be used to communicate sensor data to higher-level systems. Older machines that do not have this capability can usually be retrofitted with appropriate sensors. As sensors have become much cheaper in recent years, this retrofitting is now also economically viable.

Among other things, this offers manufacturing companies a great opportunity to catch up on automation in quality assurance. While their production processes are now usually highly automated, manual work is often still the order of the day in quality assurance. Samples are often simply taken on the basis of statistical procedures after certain quantities and the parts are checked for compliance with specifications. If only the umpteenth part is tested and it is defective due to an incorrect machine setting or a malfunction, all parts produced up to that point in the series may also have quality defects. In extreme cases, an entire batch may even have to be recorded as a reject.

As a result, manufacturing companies can hardly meet the stricter quality assurance requirements. In order to meet the increasing demands of customers and remain competitive, companies must produce ever smaller batch sizes and more diverse variants, deal with shorter product life cycles and bring new products to market faster. Traditional, cumbersome quality assurance processes cannot support the necessary flexibility and speed. In future, the aim of manufacturing companies must be to carry out quality inspections not only at the end of the manufacturing process but also during production.

The basis for this is provided by the sensor technology. For example, it makes it possible to measure and monitor the pressure exerted by a press and to intervene immediately if defined limit values are exceeded or not reached. Destructive measurements are therefore largely obsolete, as it is possible to trace whether a pressing operation has been carried out correctly or which specific parts are faulty.

Bernd Jost is Managing Director of DiIT in Krailling near Munich. © DiIT

However, sensors can also be used to record more complex information about the machines and their environment, for example conditions such as vibration, noise, lux or_CO2. This enables manufacturing companies to recognize and anticipate malfunction scenarios at an early stage. For example, they can determine that whenever a defined vibration pattern occurs at a certain ambient temperature, a type X malfunction can be expected within the next hour. On this basis, predictive quality applications can be implemented that avoid quality defects from the outset by bringing forward the maintenance of a machine or tool. In addition, such data can also be used to "tune" machines and make them run faster without compromising quality.

However, the sensors alone are of course only half the battle for these applications. In order to be able to evaluate them in real time, all systems involved must be networked with each other without media discontinuity. This networking and evaluation is the task of manufacturing execution systems (MES). They are located below the ERP systems and are directly connected to the distributed process automation systems in order to control, monitor and document production in real time. This also makes the MES the central data hub for digitalized quality assurance. If they also receive quality-relevant data from the machines, they can use algorithms to calculate whether there are any quality deviations.

However, the prerequisite for this is that they have the necessary interfaces to connect the machines or their sensor data. This is the only way to ensure that the systems can exchange data with each other without media discontinuity. If data has to be read manually from one system and entered into another by operating personnel, real-time evaluation is of course not possible.

The combination of sensors and a suitable MES enables manufacturing companies to digitalize their quality assurance - and there is no alternative, as Industry 4.0 will only work with Quality 4.0 in the long term. Digital quality assurance is the only way to ensure that the requirements of digitalization, such as small batch sizes, short product life cycles or short time-to-market, are not met at the expense of quality. There is therefore no way around manufacturing companies investing in their systems. B. Jost/as