A large amount of machine data is already available at field level. The problem: "Often the data cannot be analyzed," says Daniel Walldorf, Manager IoT Business Development at TE in Darmstadt. Pilot projects at TE have shown that there are hurdles during implementation that need to be overcome not only in the company's own production, but more or less in all factories. Walldorf is specific: "Larger plants are connected to a network and therefore also to an MES or SCADA system, but many peripheral machines are not. In addition, only a fraction of the information available in the machines is actually available for evaluation."

In order to access the remaining data, a great deal of effort is required, ranging from reprogramming control systems to expanding the capacity of the network. Furthermore, the data models of the machines are usually not standardized, which is why they have to be individually adapted. "As a result, more than 60% of the costs incurred in the pilot projects went on manpower to interpret the data and store it in structures. In addition to the enormous costs, the number of employees with the necessary skillset of production and IT expertise also limits the roll-out of such solutions," says Walldorf.

So what can be done to connect participants to a network and collect, transfer and analyze a large amount of data without the costs exploding? According to Walldorf, one option is to install additional sensors in the machines that are intended solely for applications that have nothing to do with control tasks. Alternatively, gateways can be installed. However, only the data offered by the control systems would then normally be available. The third - and in Daniel Walldorf's opinion the most promising - option is to equip machines with smart field devices whose data can be mapped in detail in IT systems and whose performance can be precisely analyzed using methods such as Statistical Process Control (SPC).

Visitors to the SPS IPC Drives trade fair were able to see an example of this at TE's stand in the form of a prototype of the smart 'IoT Omnigate I/O module', into which a mini-computer has been integrated. Walldorf explains: "Traditional I/O modules record data from sensors and actuators and forward it to the controllers via a higher-level bus system. With the smart I/O module, which acts as a so-called edge computer, a further path can be set up in addition to this real-time communication path, via which data for intelligent applications in the sense of Industry 4.0 and the IoT can be aggregated in the machine and then transferred to IT systems." Another advantage: classic I/O modules, which are often found in machines today, can simply be replaced with IoT omnigate modules without having to change the architecture and interfaces.

A cloud-based software tool is available to configure the smart I/O module. Among other things, it can be used to configure the interfaces via which the recorded data can be forwarded in structured form to other applications such as databases or ERP systems. "This means that it is no longer necessary to retrieve the data from different locations; on the other hand, the data always has the same format, which makes integration into IT systems much easier," concludes Walldorf.