Microsoft Azure enables the world’s applications to become intelligent using the next-generation infrastructure, data and developer services.
Some cloud providers make you choose between your datacenter and the cloud. Not Azure, which easily integrates with your existing IT environment through the largest network of secure private connections, hybrid database and storage solutions, and data residency and encryption features — so your assets stay right where you need them. And with Azure Stack, you can bring the Azure model of application development and deployment to your datacenter. Azure hybrid cloud solutions give you the best of both worlds: more IT options, less complexity and cost. It’s why it’s one of the best cloud computing services available.
Microsoft Azure (Microsoft)Microsoft Azure is a cloud computing platform and infrastructure created by Microsoft for building, deploying, and managing applications and services through a global network of Microsoft-managed data centers. It provides both PaaS and IaaS services and supports many different programming languages, tools and frameworks, including both Microsoft-specific and third-party software and systems. Azure was announced in October 2008 and released on 1 February 2010 as Windows Azure, before being renamed to Microsoft Azure on 25 March 2014.
- Application Industries
Automotive Construction & Buildings Energy Equipment & Machinery Other
- Application Functions
Logistics & Warehousing Maintenance Process Manufacturing Product Development Quality Assurance
- USE CASES
Fleet ManagementFleet management is an administrative approach that allows companies to organize and coordinate work vehicles to improve efficiency, reduce costs, and provide compliance with government regulations. While most commonly used for vehicle tracking, fleet management includes other use cases such as mechanical diagnostics and driver behavior. Automated fleet management solutionsto connect vehicles and monitor driver activities, allowing managers to gain insight into fleet performance and driver behavior. This enables managers to know where vehicles and drivers are at all times, identify potential problems and mitigate risks before they become larger issues that can jeopardize client satisfaction, impact driver safety, or increase costs.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.Structural Health MonitoringStructural health monitoring solutions ensure the safety and soundness of engineering structures such as a buildings and bridges. Structural health monitoring uses an assortment of sensors to collect and analyze data pertaining to any damage or deterioration that a structure may receive over the course of its life. The data that structural health monitoring systems acquire can help its users avoid structural failures and changes to the material and/or geometric properties of a structural system, including changes to the boundary conditions and system connectivity, which adversely affect the system's performance. The structural health monitoring process involves the observation of a system over time using periodically sampled response measurements from an array of sensors (often inertial accelerometers), the extraction of damage-sensitive features from these measurements, and the statistical analysis of these features to determine the current state of system health. For long term solutions, the output of this process is periodically updated information regarding the ability of the structure to perform its intended function in light of the inevitable aging and degradation resulting from operational environments. After extreme events, such as earthquakes or blast loading, health monitoring is used for rapid condition screening and aims to provide, in near real time, reliable information regarding the integrity of the structure.Warehouse AutomationWarehouse automation is the application of specialized equipment and storage and retrieval systems to automate warehousing tasks previously handled by manual labor. Warehouse automation takes many forms, including machines and robots that aid workers with processes related to inventory handling, sensors that track goods, and software that automates record keeping. Leveraging warehouse automation solutions can help warehouses increase productivity, improve the accuracy of inventory records, reduce labor costs, and improve safety.Inventory ManagementInventory management solutions aim to automate the inventory management process and increase accuracy and reliability. Every individual inventory item that is to be tracked receives an RFID tag or other similar tracking technology. Each tag has a unique identification number that contains encoded digital data about an inventory item, for example the model and batch number. Tags are scanned by RFID or other readers. Upon scanning, a reader extracts the tag's ID and transmits it to the cloud for processing. Along with the tag's ID, the cloud receives data about the reader’s location and the time of the reading. Based on this data, an application states the location of the item with the corresponding ID, visualizes the findings and displays real-time updates about inventory items’ movements to the solution users, allowing them to monitor the inventory using a smartphone or a laptop from anywhere, in real time. There are also secondary benefits of inventory management. For example, machine learning can forecast the amount of raw materials needed for the upcoming production cycle based on the data about the inventory quantity and location, and reorder them as needed. It can also help in matching demand with supply more accurately as inventory movement is also a representation of demand.Asset Health Management (AHM)Asset Health Management refers to the process of analyzing the health of an asset as determined by operational requirements. The health of an asset in itself relates to the asset's utility, its need to be replaced, and its need for maintenance. It can be broken down into three key components: 1) Monitoring: Tracking the current operating status of the asset. 2) Diagnostic Analysis: Comparing real-time data to historical data in order to detect anomalies. 3) Prognostic Analysis: Identifying and prioritizing specific actions to maximize the remaining useful life of the asset based on analysis of real-time and historical data.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.Smart City OperationsSmart city operations include the range of solutions required to enable smart city concepts by integrating information and communication technology with senors and connected devices to optimize the efficiency of city operations and services. Smart city technology allows city officials to interact with both community members and city infrastructure and to monitor situation in the city in real time. Benefits for city managers include tracking events in the city in real time, managing congestion, improving operational efficiency, reducing emergency response times, and enabling remote management. Modern solutions will aim to integrate all city data into a single dashboard. Both historical and current KPIs are measured to conduct performance reviews and gap analysis, and to plan future infrastucture and service investments.