More machine original equipment manufacturers (OEMs) are offering predictive maintenance as a service to differentiate themselves from their competition. By offering IIoT-enabled maintenance services, OEMs unlock an ongoing revenue stream that ensures maximum uptime for customers. To streamline and aggregate the high volume of sensor-fed, real-time data, OEMs need cloud services. According to Smart Industry, some of the key benefits related to a cloud infrastructure include:
To derive usable insights from multiple machines, OEMs must first normalize the data before moving it to the cloud.
Cloud transactional costs. OEMs offering machine monitoring and predictive maintenance as a service need to control their cloud-related costs as they publish more data to the Cloud.
Disparate data sources. As OEMs expand through mergers or acquisitions, they often find themselves managing a larger portfolio of machines and legacy equipment. As a result, an OEM may need to manage a wide variety of control system models with unique standards and datasets for new and legacy equipment across greenfield and brownfield sites. This creates challenges around data uniformity in the Cloud.
Aggregate and curate data in a single payload. Manufacturers who deploy HighByte Intelligence Hub can collect, contextualize, and combine data from disparate sources into payloads purpose-built for target systems. This approach delivers a uniform data structure for every machine to the cloud.
Native connections. The HighByte Intelligence Hub securely connects devices and applications via open standards and native connections. This eliminates the need for custom-coded integrations.
Templatized projects. To address scalability requirements, data models, connections, flows, and other project components in the Intelligence Hub can be templatized for easy adaptation and reuse. OEMs can leverage external metadata sources to streamline configuration and scale deployments.
Lower costs. Uniform data delivered to a cloud machine service platform reduces data transaction costs and delivers a significant annual ROI with short time to value for HighByte customers.
Legacy system integration. The Intelligence Hub can normalize data streaming from different types of equipment without the need for additional hardware or retrofitting.
A food and beverage OEM offered a machine monitoring and predictive maintenance service to their customers by streaming machine data to Azure IoT Hub. While providing a valuable service for their customers, this service platform was a technical and commercial challenge for the OEM to manage.
One of the largest challenges the OEM faced was the large and diverse portfolio of machines they supported. The variety of control system vendors and the volume of legacy machines still operating in the field made it challenging for the machine builder to provide a uniform and standardized set of data to the Azure cloud. This limited the data available to their cloud-based predictive maintenance models. Furthermore, the high cost of pushing machine data to the cloud increased the builder’s operating costs.
The machine builder selected the Intelligence Hub to streamline and standardize their data publishing to the Azure cloud. The Intelligence Hub was able to normalize the variety of source equipment and publish data to Azure IoT Hub while limiting extraneous detail, delivering a 45% reduction in cloud data transactions per machine. The OEM’s future implementations aim to further reduce the impact of data acquisition by buffering time series machine data to a Parquet file for greater cost savings.
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