Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.
Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment.
Amazon Web ServicesAmazon Web Services has developed the managed cloud platform AWS IoT to let connected devices easily and securely interact with cloud applications and other devices. AWS IoT can support billions of devices and trillions of messages, and can process and route those messages to AWS endpoints and to other devices reliably and securely. With AWS IoT, your applications can keep track of and communicate with all your devices, all the time, even when they aren’t connected.
- Application Industries
Chemicals Construction & Buildings Equipment & Machinery Other Transportation
- Application Functions
Logistics & Warehousing Maintenance Product Development
- USE CASES
Predictive MaintenancePredictive maintenance is a technique that uses condition-monitoring sensors and machine learning or rules based algorithms to track the performance of equipment during normal operation and detect possible defects before they result in failure. Predictive maintenance enables the reduction of both schedule-based maintenance and unplanned reactive maintenance by triggering maintenance calls based on the actual status of the equipment. IoT relies on predictive maintenance sensors to capture information, make sense of it, and identify any areas that need attention. Some examples of using predictive maintenance and predictive maintenance sensors include vibration analysis, oil analysis, thermal imaging, and equipment observation. Visit our condition-based maintenance page to learn more about these methods.Process Control & OptimizationProcess control and optimization (PCO) is the discipline of adjusting a process to maintain or optimize a specified set of parameters without violating process constraints. The PCO market is being driven by rising demand for energy-efficient production processes, safety and security concerns, and the development of IoT systems that can reliably predict process deviations. Fundamentally, there are three parameters that can be adjusted to affect optimal performance. - Equipment optimization: The first step is to verify that the existing equipment is being used to its fullest advantage by examining operating data to identify equipment bottlenecks. - Operating procedures: Operating procedures may vary widely from person-to-person or from shift-to-shift. Automation of the plant can help significantly. But automation will be of no help if the operators take control and run the plant in manual. - Control optimization: In a typical processing plant, such as a chemical plant or oil refinery, there are hundreds or even thousands of control loops. Each control loop is responsible for controlling one part of the process, such as maintaining a temperature, level, or flow. If the control loop is not properly designed and tuned, the process runs below its optimum. The process will be more expensive to operate, and equipment will wear out prematurely. For each control loop to run optimally, identification of sensor, valve, and tuning problems is important. It has been well documented that over 35% of control loops typically have problems. The process of continuously monitoring and optimizing the entire plant is sometimes called performance supervision.Supply Chain VisibilitySupply chain visibility solutions provide visibility into the movement of raw materials, components, and finished goods from suppliers to manufacturers to the final buyer. Solutions are typically built on a centralized cloud-based platform that integrates data from multiple systems, including those those of partners. Technologies such as smart sensors, RFID, and digital ledger protocols can enable additional functionality. For example, digital ledger technology can keep logs of all transactions occurring on the network in a secure way, while providing supply chain partners with access to specific data. Visibility solutions can enhance the efficiency and transparency of supply chains, record the quantity and transfer of products as they change hands between supply chain nodes, track change orders and buy orders, process shipment notifications, manage trade documents and receipts, link physical products to bar codes, and share information about processing or manufacturing processes with suppliers, logistics providers, and customers.Fog ComputingFog computing refers to a decentralized computing structure, where resources, including the data and applications, get placed in logical locations between the data source and the cloud; it also is known by the terms fogging and fog networking. The goal of this is to bring basic analytic services to the network edge, improving performance by positioning computing resources closer to where they are needed, thereby reducing the distance that data needs to be transported on the network, improving overall network efficiency and performance. Fog computing can also be deployed for security reasons, as it has the ability to segment bandwidth traffic and introduce additional firewalls to a network for higher security.Factory Operations Visibility & IntelligenceVisualizing factory operations data is a challenge for many manufacturers today. One of the IIoT initiatives some manufacturers are pursuing today is providing real-time visibility in factory operations and the health of machines. The goal is to improve manufacturing efficiency. The challenge is in combining and correlating diverse data sources that greatly vary in nature, origin, and life cycle. Factory Operations Visibility and Intelligence (FOVI) is designed to collect sensor data generated on the factory floor, production-equipment logs, production plans and statistics, operator information, and to integrate all this and other related information in the cloud. In this way, it can be used to bring visibility to production facilities, analyze and predict outcomes, and support better decisions for improvements.