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 MaintenanceThe aim of predictive maintenance is first to predict when equipment failure might occur, and secondly, to prevent the occurrence of the failure by performing maintenance. Monitoring for future failure allows maintenance to be planned before the failure occurs. Ideally, predictive maintenance allows the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance, without incurring costs associated with doing too much preventive maintenance.Predictive maintenance uses condition-monitoring equipment to evaluate an asset’s performance in real-time. A key element in this process is the Internet of Things (IoT). IoT allows for different assets and systems to connect, work together, and share, analyze and action data.Process Control & Optimization (PCO)Process 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 optimizationThe 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 proceduresOperating 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 optimizationIn 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.Shipment TrackingUtilizing IoT and digital supply chain management platforms have moved far beyond looking at only ocean carrier milestones. With this new level of end-to-end shipment visibility, shippers can instantly access transit times from every carrier along the route to create efficiencies and increase communication within their organizations – ultimately providing the highest level of customer satisfaction.Digitized data comes in many formats, including feeds from the Internet of Things (IoT). Global supply chains are ideal candidates for IoT applications because there are so many moving parts and multiple parties. IoT applications capture and share immense amounts of data that equip logistics managers with a level of visibility not previously achievable. Specifically, for shippers and the carriers moving their products, advances in cellular devices and networks have made it possible for less-than-truckload (LTL) and other over-the-road truckers to provide tracking data.These connected tracking devices feed into transportation management and supply chain platforms to provide critical information at the pallet and package level. When connected with the ocean, air, and rail shipment tracking, these last mile data systems give shippers a competitive edge. To alleviate the pressure on your supply chain, the most important component is a technology platform with one big view of everything across your multimodal transportation ecosystem.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.