Industry 4.0: how does edge computing improve efficiency and increase the operating life of mobile assets ?

Whether in public transport, railways or public works or even defense, mobile assets (rolling stock, machinery, vehicles…) are the heart of the matter.

In the era of connected objects and industry 4.0, in a logic where competition and sustainable development must be harmonized, operators and manufacturers using or producing mobile assets have no choice but to combine savings with high-level service and security. They are therefore looking for smart digital solutions to maximize the use, profitability and operating life of their hardware investments. The challenge is clearly to maintain these assets as long as possible in operational conditions to ensure continuity of service while reducing operating and maintenance costs.

Continuity of service and safety, but also comfort and punctuality, rely on the efficiency of operations and maintenance. This depends to a large extent on the accuracy of the identification, characterization and localization of early defects as well as on the speed of detection and management of impacting events.

Get a fine-tuned and accurate knowledge

Managing the best use of mobile assets such as trains, trams, building machinery and other industrial vehicles requires a great deal of operational agility. This agility stems from the ability on the one hand to react to events in the field, to the right place, at the right time and in the right way, and on the other hand to be able to build knowledge, the closest to the reality, to anticipate maintenance and repair operations, which will lengthen the operating cycle.

This involves obtaining continuously and in real time, all the information needed to qualify the operating status of mobile assets and the conditions under which they perform their operations. This contextualized knowledge is based on the ability to collect and correlate real-time location, vibration, acceleration, shock or even noise and temperature data as close as possible to the critical organs, in order to identify, in real time, abnormal behavior, and anticipate possible failures.

Only a hardware and software solution able to unlock all the technological barriers can provide an answer. On mobile assets and equipment, these barriers are four in number: difficulty of access to measurement points to monitor critical organs, availability constraint for the system of a nearby power supply, need for measurement and embedded computing, robustness requirement of the hardware system and of communications needed to exchange data.

Getting value from the data, in the field of operations

Today, the advances of the IIoT paves the way for the design of connected, wireless, autonomous, reliable and robust systems, weakly intrusive and able to provide measurement and calculation capabilities deported on the mobile asset. The power of such Edge Computing Appliances lies in obtaining a wide variety of accurate data, from points considered inaccessible but critical and correlating them to obtain decisive information in real time.

These Edge Computing Appliances are installed in retrofit on the mobile asset, which facilitates even more the adoption of such systems. They capture and process data from their integrated sensors and remote wireless sensors, transmit the data to a storage, visualization and analysis platform in the cloud via a 3G network for example, and trigger actions on local PLCs (camera, etc …). With autonomy of functionning allowing to follow all the operations over their entire duration, these appliances supply the monitoring of operations, enrich the programming of actions of preventive maintenance and the study of the real conditions of operations. The addition of a GPS module to the system completes the information set (shocks, vibrations, etc.) with synchronized geolocation data. When the defined threshold is exceeded, the localized and time stamped information is transmitted following the same scheme for the triggering of alerts and automated actions and / or rapid informed interventions.

With these wireless Edge Computing solutions, it’s access to new knowledge and greater responsiveness that opens up to the industrial world. Data processing is done where the measurement is made. The information required for the action / reaction is immediately available. Operational management is brought to a new level with record-breaking, unprecedented, critical information that opens the door to unmatched agility.

Correlatively, remote processing in the field decreases data traffic and thus bandwidth by reducing the amount of data transmitted to the cloud to the sole information that contributes to a deeper analysis. Edge Computing is clearly the gateway that allows to take the real-time value of unprecedented and decisive data, and move the IIoT and industry 4.0 from big data to smart data.

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