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AWS: driving industrial industry data driven decision making

AWS announces the general availability of AWS IoT SiteWise, to drive data driven decision making in the industrial industry.

|Jul 14|magazine8 min read

AWS IoT SiteWise

A managed service that collects data from the plant floor, AWS IoT SiteWise structures and labels data as well as generates real-time key performance indicators and metrics providing the industrial industry with improved data-driven decisions. 

SiteWise has the capabilities to:

  • Monitor operations across facilities 
  • Quickly compute industrial performance metrics 
  • Develop applications to analyse industrial equipment data 
  • Reduce gaps in production

“This allows customers to collect data consistently across devices, identify issues with remote monitoring more quickly, and improve multi-site processes with centralized data,” commented AWS is a company statement. 

Industrial organisations such as manufacturers, energy utilities and food processors looking to better utilise their equipment data to drive faster and more informed decisions, often face challenges when it comes to extracting data from sensors and equipment across different locations, due to being stored locally in specialised servers that also lack a common data format. As a result, retrieving the data and placing it in a format useful for cross-site analysis requires significant developer resources and expertise, which is a time-consuming and expensive process. 

SiteWise can help organisations overcome these challenges via its capabilities to make data collection from the plant floor, structure and label the data, and generate real-time metrics easier.

“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 (e.g. report uptime every hour). All uploaded data and computed metrics are sent to a fully managed time series database, which is uniquely designed to store and retrieve time-stamped data with low latency, making it significantly easier for customers to analyse equipment performance over time,” noted AWS. In addition, users can create custom web applications to visualise key metrics across end-user devices in almost real time as well as monitor equipment performance to help reduce waste, make faster decisions, and optimise plant performance.

“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,” commented Dirk Didascalou, Vice President of IoT, 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 - in addition to using edge software - provides interfaces for collecting data via MQ Telemetry Transport (MQTT) messages or its Application Programming Interface (APIs). 

“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 Enterprise & Platform Architecture, 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."

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