Condition Monitoring: The Fitness Tracker for OT Networks

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Condition Monitoring: The Fitness Tracker for OT Networks

17.05.2021

Fitness trackers have become a staple of our times. Once deemed a useless fashion fad, they have grown to become the first analysts and indicators of people's health condition. Vital data are specifically checked, documented, and alarms are given if personal thresholds are exceeded or undercut.

Our machine networks are often called the aorta of automation. Preparation for digitalisation and Industry 4.0 are often mentioned. Reliability, stability, and safety are assumed, but hardly ever questioned. It is all the more important to record and assess events, communication relationships, and load situations.

Anyone who operates their machines and systems with Ethernet-based networks like PROFINET is aiming to use benefits such as real-time capability, high transfer rates, and uninterrupted communication in full and without interferences. The network condition, and as a result availability and outward perceptions, are derived repeatedly. That is generally possible, provided that they are homogeneous and enclosed systems. A closer look and assessment of the network structure already return a higher degree of networking than it initially seemed. Camera systems, scanners, and the new Smart Sensor generation will demand greater performance from the networks. Load peaks must be managed, and bottlenecks avoided.

This is exactly why the network experts of Indu-Sol have developed the intuitive condition monitoring solution „PROmanage^® NT V2“ that analyses, assesses, and monitors the network, and therefore communication, around the clock. The central software performs continuous queries of the statistics for switches, Wi-Fi Access Points, and routers, e.g. via the standard SNMP, to graphically illustrate them in the typical traffic light colours. The integrated scanning function maps the network 1:1 and indicates the event spectrum with precise connections and time stamps. Anomalies can be recognised, documented, and proactively removed in a targeted manner for each alarm without requiring any additional diagnosis hardware. This is also done, for example, by a fitness tracker with an automatic activity reminder.

A local data collector is installed in the respective fieldbuses for integration of the existing systems with PROFIBUS, CAN, Asi. It is queried proactively and cyclically via SNMP as well. It analyses the entire telegram traffic, localises error sources, and reports when any pre-set thresholds are exceeded.

This solution permits sensible and efficient implementation of a condition-oriented maintenance strategy. Expectations to a healthy future of the machine and system networks are good.