REHAU and KraussMaffei together on the course for 4.0
Digital Cooperation

Fifty years of product reliability - for example, for underfloor heating. If you want to establish yourself as a premium supplier, you need to have manufacturing with complete transparency and partners highly skilled at it. Because of this, REHAU AG + Co, and KraussMaffei have been involved in a development cooperation with the common course of Industry 4.0 for a year already.

Text Petra Rehmet  Photos Rehau

The spring board for this was the DataXplorer, a high-resolution data acquisition tool by KraussMaffei. After the presentation at the K 2016, REHAU commissioned the very first customer system in its Plant 5 in Viechtach, Bavaria. This location manufactures, by the millions, a product that is technically advanced and, thanks to comprehensive 100% online testing, is ideally monitored: sliding sleeves and connecting pieces (fittings) for pipes made of cured polyethylene (PE-Xa) with the brand name Rautitan. The complete systems are usually installed at places that are difficult to access at a later point in time, such as underfloor heating systems and water lines, and they have to function for 50 years under pressure, with fluctuating temperatures and sometimes with aggressive mediums. The specific perspective for use of the DataXplorer is clear: to reduce the monitoring effort by "predictive quality" after thorough validation of production..

Fully automated and cycled through
Fully automated and cycled through
During production of the Rautitan components, only the material feed and parts removal are carried out by people.

Two technological leaders

The REHAU Group has Automotive (Tier 1), Construction and Industry company divisions and is active in all segments of plastics processing: injection molding, extrusion and reaction technology. The KraussMaffei Group, in turn, is the only supplier in the world to deliver machines for these very different technologies—thus, it is not difficult to imagine cooperating in an even more fundamental way, for example regarding digital opportunities. The DataXplorer is currently running as a pilot on a CX machine with MC6 control system. The machine produces Rautitan articles in imperial sizes for the United States market. The DataXplorer records up to 500 signals as continuous curves and allows for a unique view into the depth of process and hardware thanks to its extremely high resolution of 5 ms. In this way, default parameters such as injection time and pressure can be collected but also special signals such as mold cavity pressure. For each signal and cycle, one file is created that can be called up on the machine for up to seven days. It is converted into a global date format for transfer or further processing. Klaus Klement, Head of Smart Production at REHAU, is enthusiastic: "I am not aware of any other high-resolution interface, and we want to start using DataXplorer as quickly as possible on our other machines with the MC5 control system, too." The data acquisition tool as a kind of 4.0 springboard for injection molding triggered a wide variety of developments in the area of Smart Production at REHAU—also accelerated by upper management. By now, Klaus Klement even has his own data lab with five employees. Smart Production, like Smart Products and Smart Services, is part of REHAU's Smart Offensive by which the company is advancing digitalization of its product range across all divisions.

The goal: an autonomous system

Now the Viechtach 5 lighthouse project has to validate all irregularities that occur in production even within the tolerances. Then DataXplorer can be used, for example, to superimpose the melt-pressure curves from up to 10,000 cycles and track whether there are outliers. Or to analyze the height of the melt pressure at defined times in the cycle. If unusual values appear, the component can be submitted to precise measurement or even destructive testing. The first step just concerns visualization of anomalies. Once these have been made transparent and evaluated, an alarm function (alerting) should follow if a curve becomes conspicuous. Some kind of assisting system could then suggest remedial measures to the machine operators or initiate them on its own. In the end, an autonomous, self-optimizing system would be the result. The goal is clear, and the prerequisites have been created. Because of this, Klaus Klement evaluates the year "since we began with DataXplorer as absolutely positive."


Dr. Stefan Kruppa

Head of Machine Technology