Amazon Web Services launches AWS IoT SiteWise
Amazon Web Services (AWS) announced the general availability of AWS IoT SiteWise, a managed service that collects data from the plant floor, structures and labels the data, and generates real-time key performance indicators (KPIs) and metrics to help industrial customers make data-driven decisions.
AWS noted that customers can use SiteWise to monitor operations across facilities, compute industrial performance metrics, create applications that analyze industrial equipment data to prevent costly equipment issues, and reduce gaps in production. This allows customers to collect data across devices, identify issues with remote monitoring more quickly, and improve multi-site processes with centralized data, the company said.
Industrial companies like manufacturers, energy utilities, and food processors want to utilize their equipment data to drive faster and better-informed decisions, but much of this data cannot easily be collected, processed, or monitored, Amazon said. According to the company, extracting data from thousands of sensors and equipment across different locations is time-consuming and expensive because sensor data is often stored locally in specialized servers that lack a common data format, and retrieving the data and placing it in a format useful for cross-site analysis requires significant developer resources and expertise.
AWS said that SiteWise helps customers overcome these challenges by making it easier to collect data from the plant floor, structure and label the data, and generate real-time metrics.
In SiteWise, Amazon said, customers begin by modeling their industrial equipment, processes, and facilities by adding context (e.g. equipment type and facility location) to the collected data, and defining common industrial performance metrics (e.g. overall equipment effectiveness and uptime) on top of the data using SiteWise’s built-in library of mathematical functions. Once a customer’s environment is modeled and their data ingested into AWS, the service automatically computes the metrics at the interval defined by the customer. All uploaded data and computed metrics are sent to a fully managed time series database, according to the vendor, which is designed to store and retrieve time-stamped data with low latency, making it significantly easier for customers to analyze equipment performance over time.
From within the SiteWise console, customers can also create custom web applications to visualize key metrics across end-user devices in near real-time.
“Industrial customers tell us that getting their data into the cloud and using it to understand their operational performance is the biggest opportunity they see when evaluating IoT solutions,” said Dirk Didascalou, VP of IoT at AWS. “With SiteWise, industrial customers can now use the power of AWS to collect, organize, and monitor their industrial equipment data at scale. SiteWise will help industrial customers move beyond data collection and enable them to visualize and monitor all their equipment, so they can focus on their main job of optimizing their operations.”
SiteWise is currently available in the U.S. East (N. Virginia), U.S. West (Oregon), Europe (Frankfurt), and Europe (Ireland) AWS regions. The company said it will add additional regions in the short time.
Volkswagen Group is developing the Volkswagen Industrial Cloud to further improve the efficiency of its manufacturing and logistics processes and using SiteWise, according to Amazon.
“Machine data generally has no context when extracted from a machine. To make the data useful, it requires the addition of context through enrichment with other data, labelling, filtering and transforming that data before analyzing”, said Dr. Roy Sauer, director for Enterprise & Platform Architecture with Volkswagen Group. “With SiteWise we are able to easily ingest manufacturing shop floor data into the cloud, model and organize those different machine assets within our plants, and then visualize operational data from our cylinder production line in a web application.”