No Industry 4.0 without digital quality assurance
Digitalization enables manufacturing companies to ensure quality already during the ongoing production processes. However, many of them have not yet seized this opportunity. This should change, because otherwise quality assurance will become a stumbling block for Industry 4.0.
While production processes in the manufacturing industry are now highly automated, manual work is still the order of the day in quality assurance. Often, for example, samples are taken on the basis of statistical procedures after certain numbers of pieces and the parts are checked for compliance with specifications. If only the umpteenth part is inspected and it is defective due to an incorrect machine setting or a malfunction, all parts produced in the series up to that point may also have quality defects. In extreme cases, a complete batch may even have to be booked as rejects. Digitalization is further increasing the demands on quality assurance. 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 more quickly. Conventional, cumbersome quality assurance processes cannot support the required flexibility and speed. On the contrary, they usually stand in the way. For this reason, a concept based on "Industry 4.0" has emerged that describes the demands of digitalized production on quality assurance processes under the name "Quality 4.0". The central objective is that quality inspections should no longer be carried out ex post - i.e. only after the end of the manufacturing process - but already during ongoing production.
Acquire and evaluate machine data in real time
This can be achieved by recording and evaluating machine data in real time. However, this is only possible if the machines have the corresponding sensors and all systems are networked with each other without media disruption. Many machines are already equipped with online interfaces via which they can also communicate quality-relevant data to higher-level systems. Older machines that do not have this capability can usually be retrofitted with the appropriate sensors. Since the sensors have become massively cheaper in recent years, this retrofitting is also economically feasible.
Manufacturing Execution Systems (MES) play a decisive role in the networking of systems and the evaluation of machine data. Located below the ERP systems and directly connected to the distributed process automation systems, their task is 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. To do this, however, they must have interfaces for connecting the machines or their sensor data: This is the only way to ensure that the systems can exchange data without media breaks. If the manual reading of data from one system and the input into another system by operating personnel is required, it is of course not possible to implement a real-time evaluation.
Monitoring the pressure of a press in the running process
If, on the other hand, the necessary sensors and networking are available through an MES, quality-relevant characteristic data can already be recorded during the running process and evaluated in real time on the basis of algorithms - as required by the "Quality 4.0" concept. For example, the pressure exerted by a press can be monitored and immediate intervention is possible if defined limit values are exceeded or not reached. Destructive measurements are thus largely obsolete, as it is possible to determine whether a pressing has been carried out correctly or which specific parts are defective.
By recording more complex information from the machines, but also from their environment, manufacturing companies can also detect and anticipate malfunction scenarios at an early stage. This information includes conditions such as vibration, noise, lux or CO2. On the basis of such data, it is then possible to determine, for example: If a defined vibration pattern occurs at a certain ambient temperature, a type X malfunction is to be expected in the next hour. Quality losses can thus be avoided from the outset, for example by giving priority to machine or tool maintenance. In addition, such data can also be used for tuning measures to make machines run faster without compromising quality.
Last but not least, an MES also enables the tracing of batches. Finished cable harnesses, for example, often consist of thousands of components - and a suitable MES can keep a complete history of each component. It knows on which machine by which employee and with which tools the components were produced. This makes it easy to check retrospectively in which end products, be they cars, washing machines or refrigerators, cable harnesses with a cable from a particular batch were installed. Any repair measures or even recalls can then be narrowed down in this way.
There is no way around investment
Quickly detect incorrect settings, prevent possible faults before they occur, trace back batches without gaps: The advantages of a comprehensively digitalized quality assurance speak for themselves. However, the manufacturing industry is still far from being ready. Therefore, there is no way around investing in the digitalization of their plants, because without Quality 4.0, Industry 4.0 will not work in the long run. The requirements of digitization, such as small batch sizes, short product life cycles or tight time-to-market, should not be met at the expense of quality.