Noticeable Trends Transforming Industrial Maintenance

Reliable data collection of assets and equipment is a prerequisite for the provision of maintenance insights and knowledge. In many other cases, maintenance data is collected from multiple sources, including different sensor types.

Fremont, CA: The ongoing collaboration of IT (Information Technology) with OT (Operational Technology) is completely transforming industrial processes. Besides, it is gradually transforming industrial organizations to digital enterprises.

Technologies like BigData, cloud computing, and the (Industrial) Internet-of-Things (IoT) are being integrated to improve the scalability, efficiency, quality, and cost-efficiency of processes in major industries such as oil and gas, energy, manufacturing, and aerospace.

These industries are also the source of completely new technological capabilities and business models. This is apparent in the scope of equipment maintenance processes, which are largely supported by IT technologies.

Additive Manufacturing

In the past few years, there has been an increased focus on 3D printers to produce parts for various applications. Additive manufacturing has similarities with 3D printing, which is becoming mainstream in both the industrial and consumer sectors.

In the field of maintenance of industrial equipment, 3D printing can provide obvious advantages when used for the production of spare parts. There are numerous cases where equipment malfunction occurs unless the component is replaced. In such cases, the required part can be rapidly produced by additive manufacturing. This speeds up maintenance times and reduces inventory costs.

Wireless Sensor Networks, Internet of Things, and Automated Data Collection

Reliable data collection of assets and equipment is a prerequisite for the provision of maintenance insights and knowledge. In many other cases, maintenance data is collected from multiple sources, including different sensor types. These data can then be analyzed by expert systems and sophisticated algorithms.

Data collection was a manual task only a few years ago, requiring trained personnel to physically access the equipment. With the emergence of wireless sensor networks and IoT, this process is gradually changing.

Companies now have increased access to low-cost, multi-purpose sensors and sensor networks that can be connected to industrial equipment in a number of ways. As a consequence, modern plants often employ hundreds of sensors that are utilized to collect maintenance data. Simultaneously, IoT enables the creation of smart networks for such sensors to facilitate the automated collection of sensor data.

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