This Is How Medium-Sized Businesses Get Started With Industrial IoT

It’s time for Industry 4.0 and Industrial IoT: To establish digital business models, medium-sized mechanical engineering companies are concerned with the scalable digitization of their products and manufacturing companies and IoT pilot projects to digitize their processes. Digital solutions such as edge computing enable the machine “as-a-service.” Demand-dependent as-a-service models also help manufacturing companies keep costs and expenses down.

Industrial IoT (IIoT) has arrived on the market – and among medium-sized companies: According to a current study by market researchers, more than a quarter of the surveyed companies from industry and industry-related sectors have already implemented IoT projects. Another 15 percent are in the pilot phase, and 47 percent are in the planning and evaluation phase.

 “Large companies have currently implemented IoT projects more frequently than medium-sized companies, but the medium-sized industrial companies that are important will not be left behind in the future: here, pilot projects are currently being carried out much more often, and new initiatives are being evaluated and planned.”

IIoT Solutions Suitable For Medium-Sized Companies

But how do medium-sized companies get into the Industrial IoT? In principle, only a few IT resources and corresponding know-how are required for an IIoT solution suitable for medium-sized companies. Typical industrial IoT use cases include monitoring and analyzing measurement data, for example, evaluating usage data.

An example: A manufacturer of stamped parts wants to monitor its automatic stamping presses and hydraulic presses and evaluate the measurement data centrally. A simplified setup consists of sensors, an edge computer, and an analytics application in the cloud. The sensors determine machine and production data such as temperature, vibration, pressure, or the quantity produced and send them to the cloud via the intermediate station, an edge computer, via the cellular network.

Similarly, processes can be automated and made more efficient in all industries, or new digital products and services can be developed. For example, if such IIoT solutions are implemented as “Machine as a Service (MaaS),” the initial investment is close to zero. Thanks to demand-based billing models, the running costs also remain manageable.

Retrofitting Of Machines With IT Interfaces

Companies cannot and do not want to reinvent their machinery if they’re going to implement IIoT solutions – in most cases, “retrofitting” with edge computing and a remote station should take place in the cloud. Older machines without IoT capabilities have to be converted or upgraded. Sensors for machine data are usually already available and are connected to an additional IT interface and queried. 

If the sensors support IO-Link, the global standard for communication with sensors and actuators, they can easily be connected to an IO-Link master. The amounts of data generated by sensors are enormous. A high-speed camera, for example, produces a terabyte per hour. Edge computing, which can be directly connected to an IO-Link master, is used to collect, temporarily store, and, if necessary, preprocess such masses of data.

Edge Computing Is The Core Element For IIoT

As the name suggests, edge computing is located on the edge of an IT network. The central cloud determines which data is kept for how long and with which preprocessing. Because the data should not be sent to the cloud unfiltered, edge devices must therefore have sufficient on-site computing capacity and preprocess and filter the data according to the specifications of the cloud platform.

Measurement data from sensors are often only of interest when values ​​change. To not overload the networks and guarantee constant high-performance data transmission, only these changes should be transferred to the cloud from the edge. For this purpose, the edge device establishes a secure, encrypted data connection via Ethernet, cellular network, WLAN, or other wireless technologies. 

Since the machines and their sensors themselves are not connected to the IT network, the edge device also offers protection against cyber attacks. The current study also shows the relevance of edge computing for the industrial sector: According to this, 24 percent of those surveyed are already processing data at the edge, and a further 60 percent are currently examining the added value in pilot projects or are planning to do so.

Take A Close Look At Providers Of IoT Platforms

From the edge to the cloud: Companies obtain the applications for their machines from IoT platforms in the public cloud. There they are made available as apps, i.e., as Software as a Service (SaaS). There are currently several hundred providers of IoT platforms, from small IT companies to large cloud providers. 

Your solutions can usually be implemented in the pilot project without any problems, but they have significant differences in terms of scalability and pricing. Therefore, Medium-sized companies should always pay attention to scalability, price transparency, and the portability of data and algorithms to not become dependent on one provider (“lock-in effect”). To avoid unpleasant surprises, we recommend a price model based on the number of devices installed – regardless of the amount of data transferred or the storage space used.

Data Sovereignty And Data Security

Another important selection criterion is data sovereignty. Companies should contractually ensure that they can only use the data. The GDPR does not provide a regulatory basis for this because it only protects personal and no-machine data. Without special agreements, a provider can legally use a customer’s IIoT data to improve machine learning. But maybe the machine builder would like to do that himself.

In addition, it is essential to achieve the best possible data security for the entire system consisting of sensor, edge, and cloud. Identities and encryption are decisive factors for this. The precise identification of a machine is fundamental for the further processing of the data. In this way, valid analyzes are only possible if the individual data can be assigned to a machine or sensor identity.

In addition, the entire system should offer end-to-end encryption. The data in the edge device is encrypted before being sent to the cloud and only decrypted again before further processing in an analysis application.

Quick Entry Into IIoT With Proof Of Concept

The changes will not succeed overnight – a proof of concept is an excellent choice to make digitization easier for medium-sized industrial companies. With the Q-loud Proof-of-Concept, you receive a functioning demonstrator for your specific application with hardware, connectivity, and IoT platform at a fixed price within 100 days. This gives companies maximum investment security on their way to new digital business models.

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