Highlights:
- The maintenance tool will gather the data from the customer’s industrial equipment and provide the details before the machine failure happens.
- The predictive factory maintenance could reach a value of $12.3 billion by 2025.
Introduction:
The company launched its preview last year during Amazon Web Services re:Invent 2020. Lookout for Equipment ingest sensor data from customers industrial equipment and develops and trains a model to provide early warning signs of machine failure or suboptimal performance.
Predictive maintenance technologies have been present since decades with jet engines and gas turbines. Companies like GE Digital’s Predix and Petasense offer Wi-Fi-enabled cloud and AI driven sensors. According to a statement from a recent report by analysts at Markets and Markets, predictive factory maintenance could be worth $12.3 billion by 2025.
Startups like Augury are looking to take up a slice of the segment beyond Amazon.
How Lookout for Equipment functions:
With Lookout for Equipment, industrial customers can develop a predictive maintenance solution for a single or multiple facilities. To begin with, the company uploads their sensor data to Amazon Simple Storage Service and provides the relevant S3 bucket location to Lookout for Equipment. The service then automatically will shift through the data, determine the patterns and develop a model that is tailor-made for the customer’s operational environment.
Lookout for Equipment then uses the model to analyse incoming sensor data. Through this, it identifies early warning signs for machine failure or malfunction. For every alert, Lookout for Equipment will define which sensors are indicating a problem. It measures the magnitude of its impact on the detected event. If Lookout for Equipment spots a problem on a pump with 50 sensors, the service shows five sensors. These sensors indicate an issue on a specific motor. It relates that issue to the motor power current and temperature.
Statement from VP of Machine Learning at AWS:
“Many industrial and manufacturing companies have heavily invested in physical sensors and other technology with the aim of improving the maintenance of their equipment. But even with this gear in place, companies are not in a position to deploy machine learning models on top of the reams of data due to a lack of resources and the scarcity of data scientists,” VP of machine learning at AWS Swami Sivasubramanian said in a press release. “Today, we’re excited to announce the general availability of Amazon Lookout for Equipment, a new service that enables customers to benefit from custom machine learning models that are built for their specific environment to quickly and easily identify abnormal machine behavior — so that they can take action to avoid the impact and expense of equipment downtime.”
Lookout for Equipment is available for use via the AWS console. It is also available through supporting pad partners in the AWS Partner Network. It will be launched today in US East, EU, and Asia Pacific server regions. This will also be available in other regions within coming months.
The launch of Lookout for Equipment will follow the general availability of Lookout for Metrics. It is a fully manageable service that uses machine learning to track key factors that impact the health of enterprises. Both products are complemented by Amazon Monitron. It is an end to end equipment monitoring system. It enables predictive maintenance by using a sensor, a gateway, an AWS cloud instance and a mobile app.
