Realtime Scoring for Felss Systems GmbH

Felss Systems GmbH is a machine building and process engineering company and part of the Felss Group. Felss Systems is an automotive supplier as well as a specialist in cold forming processes of tubes applying rotary swaging, axial forming, bending, autofrettage and tube end forming.

To stay ahead of the pack in this highly competitive industry, internal processes need to be integrated into interconnected systems. Felss Systems chose X-INTEGRATE’s specialized, custom-made solution to their challenge. Predictive scoring and automation were the keys to significantly increasing the efficiency of industrial machines who use highly precise forming-process technology.

The predictive analysis method that was put in place starts with sensors placed on the machines in the production line. They constantly measure and monitor the quality of the machines and the parts they make. The goal of this is to continuously collect valuable, meaningful data which enables accurate predictions when it comes to the quality of the manufactured parts. On top of that, the solution also facilitates reacting with flexibility if there are any occurrences and it makes the process of changing machine components much more efficient.

The pressure to increase efficiency when building and running production line machines is enormous these days. Companies can get ahead of the competition if they streamline their internal processes and convert to industry 4.0.

The more they rely on predictive planning and automated processes, the more efficient their production capabilities become. Especially areas like maintenance and quality control use a lot of personnel and thus hold a lot of optimization potential. Both take up a lot of time and resources: at set, regular intervals parts have to be retrieved from the production line and checked in a time-consuming process.

The need for checks and the sensible choice of intervals are challenging: if the intervals are too short, unnecessary and expensive delays in production are the result; if the intervals are too long, deteriorated components are only discovered once there are malfunctions.

This is where the predictive analytics method which X-INTEGRATE’s experts developed for Felss Systems comes in. In its capacity, among other things, as an automotive supplier, Felss uses machines that form metal for transmission shafts, steering shafts, propulsion components and many more highly specialized parts.

The first step was to install sensors on the machines. Their data is collected in an edge gateway that supports industry connectivity standards. The predictive analytics software by X-INTEGRATE then reads out the relevant information and compares the sensors’ data with the standards the machine should be running on, for instance correct pressure or temperature. It’s programmed to only check components where there is a known risk of deterioration over time. Then, a prediction is made as to the possible condition of the deficient component. The results are sent back to the machine via an integration component and they show up for the machinist in charge.

Dynamic, realtime performance in crucial here, since production lines operate on a second-by-second basis and so the answer time of the predictive process – from measuring over the SPSS’ prediction to the sending of a notification to the machine – needs to lie within that timeframe as well. This method is a true paradigm shift within the billion-dollar automotive and forming-process industry.

Thanks to continuous, precise checks production managers can more reliably predict when certain machines in a production line will need maintenance or adjustment and plan accordingly. Customers of Felss Systems can switch off, repair affected machines, or change worn down tools long before a critical point is ever reached.

Within the production line, that translates to fewer wasted products and much smaller chances of suffering an unexpected machine failure. Quality control of the parts produced also becomes exponentially more efficient because of the predictive analytics method used.

Quality control processes requiring a lot of man-power are now made more efficient and automated by logging and saving everything in a database –  from the tracing of data over the predictions made by the SPSS model to the ensuing reports. That also contributes to the continuous improvement of the predictive model.

Felss Systems can now tap into a new field of business with a managed services package of its industry 4.0 machines. The scalability of the solution paves the way to an intelligent factory, for Felss Systems and all of its customers, past, present and future.