The following is the Amazon cloud technology launches predictive maintenance service for industrial equipment based on machine learning recommended by recordtrend.com. And this article belongs to the classification: Industry information.
Amazon lookout for equipment enables industrial customers to make full use of their existing equipment sensors and carry out predictive maintenance on a large scale in all their industrial sites through machine learning
Currently, customers and partners using lookout for equipment include siemens energy, petrospain, rovisys, tensoriot, etc
Recently, Amazon cloud technology announced that Amazon lookout for equipment is officially available. The service uses the machine learning model developed by Amazon cloud technology to help customers carry out predictive maintenance on the devices in their facilities. Amazon lookout for equipment obtains sensor data (such as pressure, flow, speed, temperature and power) from customers’ industrial equipment, trains a proprietary machine learning model, and then accurately predicts early warning signals of machine failure or poor performance based on the real-time data flow of customers’ equipment. With Amazon lookout for equipment, customers can quickly and accurately detect equipment abnormalities, quickly diagnose problems, reduce false alarms, and take action before machine failure to avoid expensive downtime losses. Amazon lookout for equipment has no prepaid fee or minimum commitment fee. Users only need to pay according to the amount of data consumed, the calculation time and reasoning time required to train the customized model. To start using Amazon lookout for equipment, visit: https://aws.amazon.com/cn/lookout-for-equipment/ . To learn more about Amazon cloud technology’s AI / ml innovation initiatives and many customers’ best practices in business innovation and enterprise transformation, please pay attention to the 2021 Amazon cloud technology AI online conference to be held on April 22.
Industrial enterprises have been trying to improve operation efficiency and avoid unexpected downtime caused by equipment failure. These enterprises continue to invest in physical sensors, data connection, data storage and dashboard to monitor the operation and performance of equipment. In order to analyze data on devices, most enterprises usually use simple rules or modeling methods to identify problems based on past performance. However, these methods often lead customers to find problems have no time to take measures, or receive false alarms and unnecessary checks. In fact, customers want to detect conventional operating conditions or fault types (such as high temperature due to friction) and complex equipment faults (such as pump faults indicated by high vibration and speed but low flow), which can only be obtained by modeling the unique relationship between sensors. Thanks to the progress of machine learning technology, people can quickly identify anomalies and understand the unique relationship between each device’s historical data. However, most enterprises lack the professional knowledge to build and expand customized machine learning models on different industrial equipment, which leads to that they often can not make full use of their investment in sensors and data infrastructure, and often miss the insight to better manage the normal operation and performance of key equipment.
With Amazon lookout for equipment, industrial and manufacturing customers can now quickly and easily build predictive maintenance solutions for entire or disparate facilities. First, customers upload their sensor data (such as pressure, flow, speed, temperature and power) to Amazon Simple Storage Service (Amazon S3), and provide Amazon lookout for equipment with relevant Amazon S3 bucket locations. The service will automatically analyze data, evaluate normal or healthy patterns, and tailor a machine learning model based on customer data. Amazon lookout for equipment will then use this customized machine learning model to analyze incoming sensor data and identify machine failures or early warning signals of failures. For each alert, the service can indicate which sensors are showing the alert problem and measure its impact on the detected event. For example, if Amazon lookout for equipment detects a problem with a pump with 50 sensors, the service can display which five sensors indicate a problem with a particular motor and relate the problem to the high current and temperature of the motor. This means that customers can identify problems, diagnose problems, determine the priority of required operations, and carry out accurate maintenance before problems occur, which avoids downtime, saves customer costs and improves production efficiency. Amazon lookout for equipment enables customers to get more value from existing sensors and help them make decisions in a timely manner, thus greatly improving operational efficiency. Customers can obtain Amazon lookout for equipment directly through Amazon cloud technology console or support partners in Amazon cloud technology partner network. The service has been officially launched in western United States (Oregon), Europe (Ireland) and Asia Pacific region (Seoul), and other regions will soon be launched.
In addition to Amazon lookout for equipment, Amazon cloud technology also provides the widest range of cloud to edge industrial machine learning services for industrial and manufacturing customers, including Amazon monitron (end-to-end solution composed of sensors, gateways and machine learning services for predictive maintenance), Amazon monitor (end-to-end solution composed of sensors, gateways and machine learning services), Amazon monitor (end-to-end solution composed of sensors, gateways and machine learning services for predictive maintenance), Amazon Amazon lookout for vision, and Amazon Panorama (for visual inspection, giving the ability of computer vision model to local camera through hardware device and software development kit).
“Many industries and manufacturing enterprises have invested a lot of money in physical sensors and other technologies to improve the maintenance level of equipment. But even with these devices, due to the lack of resources and data scientists, enterprises can not deploy machine learning models on a large amount of data. As a result, they miss out on key insights and operational discoveries that can help them better manage their operations. ” Swami sivasubramanian, vice president of global machine learning at Amazon cloud technology, said, “we are very happy to launch Amazon lookout for equipment. This new service, a customized machine learning model based on customers’ specific environment, will benefit customers, help customers quickly and easily identify abnormal machine behaviors and take actions in advance, The impact and loss caused by equipment shutdown are avoided. “
Siemens energy provides products, solutions and services throughout the energy value chain to support its customers towards a sustainable future“ Siemens energy works with our customers to empower existing lines of business with digital service solutions to improve performance, reliability and security. Digitalization is a key driver for a sustainable energy future. ” Amogh bhonde, senior vice president of siemens energy digital solutions, said, “through Amazon look out for equipment, Amazon cloud technology machine learning is combined with siemens energy industry knowledge to help customers improve the visibility of systems and equipment in the whole operation process. Amazon lookout for equipment’s automated machine learning workflow enables customers to easily build and deploy models of various asset types even without data science knowledge. Amazon cloud technology is our trusted partner, accelerating our continuous development of omnivis digital solution suite. “
Cepsa is a global energy and chemical company, operating end-to-end in all aspects of the oil and gas value chain. Cepsa also uses plants as raw materials to produce products, and promotes new strategies to become a model for energy transformation“ At cepsa, the focus of digital transformation is people. In this respect, our professionals are the engine behind us. Through Amazon lookout for equipment, we bring machine learning insights to those experts who know the most about equipment – reliability and maintenance engineers, so that they can make more intelligent decisions, improve uptime and reduce operating costs. ” Alberto GASC, senior head of analysis, cepsa ó “Solutions such as predictive maintenance of devices have traditionally involved manual and complex data science, such as choosing the right algorithms and parameters, but Amazon lookout for equipment automates these processes so that engineers can focus on solving key challenges that affect their business,” n said
Rovisys is a global operational technology system integrator and a leading independent provider of comprehensive process automation solutions and services“ Machine learning is one of the most promising technologies for industrial customers and has the potential to provide higher value by reducing maintenance and operating costs. ” Bryan DeBois, director of industrial artificial intelligence of rovisys, said, “rovisys is cooperating with Amazon cloud technology to integrate Amazon lookout for equipment with data of field devices and infrastructure by using Amazon cloud technology IOT service, so as to realize large-scale advanced machine learning and maintenance solutions. This technology allows our customers to make the most of their existing infrastructure while unlocking more value from this data quickly and easily. “
Tensoriot is a senior consulting partner of Amazon cloud technology, providing complete end-to-end products and solutions in the fields of Internet of things, data engineering, machine learning and artificial intelligence“ Tensoriot uses Amazon cloud technology services to build solutions to accelerate the integration of machine learning in industrial operation products and processes. ” “Amazon lookout for equipment can reduce the heavy workload of machine learning and support the continuous improvement of automated machine learning development, management and anomaly detection models,” said Charles burden, vice president of tensoriot consulting. This greatly reduces the human effort required, allowing engineers to focus on translating insights into operational improvements. In short, lookout for equipment enables enterprises to innovate faster. ” Read more: AWS releases five machine learning services for industry. Amazon and red hat announce the launch of red hat openshift container platform hosting service based on Amazon cloud technology. Amazon cloud technology announces to provide low-cost storage level for Amazon EFS. AWS releases Amazon Devops guru machine learning driven new operation service. Industry equipment and component industry analysis from January to June 2016 Amazon cloud technology’s self-developed cloud native processor provides cost-effective computing power for graffiti intelligence. Amazon cloud technology in China is rich in ecological diversity. Amazon EC2 x2gd with self-developed processor Amazon graviton2 is fully available to Amazon Personalize personalized recommendation launched in Amazon cloud technology China Amazon cloud service (AWS) expands the circle of machine learning and touches every AI worker Amazon cloud service (AWS) launched in Ningxia and Beijing Sagemaker Amazon cloud technology releases China business strategy Zhang Wenyi announces Troika to accelerate customers’ global business expansion new F1 insight supported by Amazon cloud technology helps racing fans understand the instant decision on the track AWS Zhang Xia: tensorflow 85% of the world’s load is on AWS platform, development cost can reduce 54% of the impact of machine learning on SaaS industry
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