Machine data acquisition refers to the collection of data produced by machines and equipment to monitor and optimise their performance and condition.

That involves using sensors and measuring devices that record data on various machine conditions, such as power, temperature or utilisation. This data is then transmitted and analysed by specialised software tools to identify patterns and deviations that may indicate problems.

By collecting machine data, companies can optimise their production processes by improving machine performance, reducing downtime and scheduling maintenance. It also enables the prediction of future problems and the development of measures to prevent failures.

Machine data acquisition is a key component of industrial automation and the Internet of Things (IoT), enabling communication and collaboration between machines and systems to improve efficiency and productivity.

However, networking systems results in an increased risk, which should be carefully considered right from the start. The use of specialised technologies and proven middleware can counteract the risk.

Importance for industrial production

Machine data acquisition has several important meanings for industrial production:

1. Optimising production processes: By acquiring data on the performance and condition of machinery and equipment, companies can optimise processes by improving machine performance, reducing downtime, and scheduling maintenance.
2. Preventive maintenance: By monitoring machine conditions in real time, companies can identify potential problems early for appropriate action before they lead to downtime.
3. Increasing efficiency and productivity: By optimising processes and avoiding downtime, increased efficiency and productivity is possible, which leads to higher profitability and competitiveness.
4. Decision support: By analysing the acquired data, companies can make essential decisions, such as selecting suppliers, allocating resources, and identifying new business opportunities.
5. Flexibility and adaptability: By capturing machine data and allowing monitoring it in real time, companies can respond more quickly to changes in production and adapt their processes to respond rapidly to market demands.

Data acquisition technologies

In machine data acquisition, OPC UA and MQTT play a significant role by enabling the transmission of data from sensors and measuring devices connected to machines and plants to central controllers or cloud systems. As a result, companies can monitor and analyse their machine data in real-time to optimise processes and detect potential problems in advance.

OPC UA

OPC UA (OPC Unified Architecture) is an open standard for the communication of devices and applications in industrial automation. It enables real-time data transfer between machines, controllers and software systems, regardless of manufacturer and protocol.

During the development of the OPC UA standard maximum security was ensured from the beginning. OPC UA, in contrast to OPC Classic, has been developed as “firewall-friendly”, which means that it can be controlled and managed via standard network techniques.

Several protocols have been made available at the transport layer. For example, a binary protocol directly on TCP/IP is used for fast applications or cross-platform SOAP with HTTPS.

Encryption of 128 or 256 bits secures the data during transmission, as well as message signing, packet sequencing and user authentication.

For additional security, OPC UA uses a certificate exchange so that each client has to authenticate itself with a certificate. In this way, it is possible to control which client has permission to connect to the server.

MQTT

MQTT (Message Queuing Telemetry Transport) is a protocol for transmitting data in real-time over wireless and wired networks. It is an easily manageable and energy-efficient protocol optimised for use in limited resource environments such as sensors and Internet of Things (IoT) devices.

This transmission uses on the publisher/subscriber principle. The communication runs via an MQTT broker, which takes over a central task, receives all messages, and distributes them to the recipients. Since the message type is defined by the sender, the connection is energy-efficient, but without a structure definition.

Methods of securing machine data

Once a machine is networked for machine data acquisition, IT security must be considered right from the start. Because with networking, a machine is more vulnerable in any case than without networking. However, there are many ways to reduce the risks to a minimum by using common security mechanisms.

Network separation

The most basic security against unauthorised access is strict network separation. It is necessary to clearly distinguish which network areas exist, how they are connected and what communication is allowed between the networks. A firewall is a solution for this.

For production networks, solutions are also available that segment the production network as such and separate individual production islands. Only the paths required for machine data acquisition are opened for defined clients.

Certificates

There are also built-in mechanisms in the standardised communication protocols to guarantee the security of data acquisition. Thus, in the concept of OPC UA, security is implemented as a standard requirement. In addition to encrypted transmission, OPC UA provides certificate exchange between client and server.

Unfortunately, many other protocols originate from a time when the focus was not yet on security, so integrated mechanisms are missing here and must always be additionally configured. Therefore, OPC UA is also a viable choice regarding “security”.

Access control

Finally, user authentication is also necessary for machine data acquisition to restrict access to the data according to roles. These functionalities are standard for modern systems for storing data (databases/cloud) and only need to be actively used.

Further use of the machine data acquisition

As soon as the machine data can be made available, it must be forwarded to the respective higher-level systems and applications within the company to use the benefits effectively. The middleware takes on the central distribution role here and enables the creation of a complete IoT network.  

Middleware is an elementary software that connects two separate applications. In the industrial environment, the field level (OT), consisting of machines, devices and controls, is connected to higher-level IT systems, such as databases, ERP or cloud systems. This connection is bidirectional and can therefore start at the field level and end at the IT level, as well as vice versa from the IT to the OT.

This way, the machine data from OT is sent to higher-level systems in IT, where it is evaluated to optimise production processes.