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Manufacturers are accelerating the use of cloud technologies throughout their operations. While manufacturers have always been among the earliest adopters of technology, they’re moving faster than decades past. To stay competitive, investing in digital technologies has become the highest priority.

Many manufacturers add line of business applications in the cloud. Starting with common industry solutions such as customer relationship management or human resource management. Customer Relationship Management (CRM) and Human Resource Management (HRM) solutions can be less-integrated with process and products making them easier to implement. Moving line of business applications, IT infrastructure, or other common services to the cloud removes the overhead of monthly maintenance and regular replacement. Setting the stage to explore additional opportunities for cost savings or productivity enhancements.

Moving to the cloud quickly spreads to other departments such as Engineering, Manufacturing, and Services. Where most software vendors now provide cloud-based or cloud-enhanced solutions. Solutions for Computer Aided Design (CAD), Computer Aided Engineering (CAE), Enterprise Resource Planning (ERP), Manufacturing Execution System (MES), or Internet of Things (IoT) on a subscription-based model are common and can provide more value to manufacturers versus on-premise solutions.

To stay competitive, manufacturers need to integrate investments in Artificial Intelligence technologies such as Machine Learning or other technologies like IoT, or High-Performance Computing (HPC). These technology investments lead to increases in production outputs, decreases in production inputs, and new ways to capture value throughout the process.

What tech investments offer the most for Manufacturers?

Like all companies reducing the overhead of managing technology, maintaining servers, and upgrading code is beneficial for manufacturers as well. Manufacturers find more value by focusing on technologies such as IoT, Machine Learning, Large-Scale Computing, Hybrid Clouds, and Blockchain.

Internet of Things

IoT Implementations without a cloud offering is prohibitively difficult in most scenarios. Managing potentially thousands of devices from around the globe, streaming large quantities of data and then storing and processing the data in real or near-real-time is a task the cloud was specifically designed to perform. And Azure is designed to perform them in both Platform as a Service (PaaS) and Software as a Service (SaaS), making Azure the choice for Manufacturers.

At the PaaS level, we have the Azure IoT Hub, the Azure IoT Hub Device Provisioning Service, the IoT Edge, Azure Stream Analytics, and the Azure IoT Suite.

  • The Azure IoT Hub enables you to simply and securely connect and ingest data from IoT assets.
  • The Azure IoT Hub Device Provisioning Service allows you to provision millions of devices in a secure and scalable manner.
  • The IoT Edge gives you the power to run advanced analytics, machine learning, and artificial intelligence at the device level.
  • Azure Stream Analytics integrates with Azure IoT Hub to enable real-time analytics on data from IoT devices and applications.
  • The Azure IoT Suite provides a set of preconfigured IoT solutions for workloads such as Remote Monitoring, Predictive Maintenance, and Connected Factory.

At the SaaS level, we have the Microsoft IoT Central, a fully managed IoT SaaS solution. IoT Central makes it easy to connect, monitor and manage IoT assets at scale. And then create deep insights from IoT data to take informed action.

Artificial Intelligence and Machine Learning

These are major areas of investment for both Microsoft and Manufacturers, limited only by our imaginations. We continue to improve old tools and build new ones to simplify the process of integrating these technologies with your business.

  • Azure Machine Learning services are an integrated, end-to-end, data science and advanced analytics solution that enables data scientists to prepare data, develop experiments, and deploy models at cloud scale.
  •  The Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data
  • The Azure Bot Service is an integrated environment that is purpose-built for bot development, enabling you to build, connect, test, deploy, and manage intelligent bots.
  • Cognitive Services are intelligent algorithms to see, hear, speak, understand, and interpret user needs through natural methods of communication.

Large-scale computing

For computationally-intensive engineering workloads, large-scale computing is a building block for working with large datasets. Manufacturers use technologies such as rendering and simulation, with Azure Batch to run large-scale parallel and HPC batch jobs, high performance VMsLinux RDMA cluster to run Message Passing Interface (MPI) applications, and Microsoft HPC Pack, which allows you to deploy an on-premises Windows compute cluster and dynamically extend to Azure when you need additional capacity.

Hybrid clouds

The most popular choices for companies who aren’t ready to make a full conversion to the cloud. Or for those who want to keep some data and systems in-house. The Microsoft Azure Stack is designed for this type of scenario. The stack is a hybrid cloud platform that lets you deliver Azure services from your organization’s datacenter. The two common scenarios in Manufacturing that make hybrid cloud deployments particularly interesting.

  • Edge and disconnected environments Often IoT implementations include devices that are intermittently connected, or not connected at all to the Internet.
  • Security and compliance requirements Highly secure devices often are unable to connect directly to the internet and must use a local service. This is more common in the manufacture of goods for the military and defense sectors.

Blockchain technologies

Cryptocurrencies such as Bitcoin rely on blockchain technologies. However, Blockchain as a technology has much broader application. Microsoft provides easy-to-deploy templates that run on Azure for the most popular ledgers, including our own Azure Blockchain Service. Using tools like these in the cloud, Blockchain is gaining attention in Manufacturing. It has potential to address several important manufacturing scenarios including Supply Chain management, Digital Thread traceability, Counterfeit prevention, IoT tracking and identification, and Asset Management to name a few.

Azure’s key value proposition is the deep integration of all these services, whether they are from Microsoft or Open Source, with on-premises systems, rich operational analytics, strong SLAs, and compliance certifications that you can trust.

Diego TamburiniDiego Tamburini currently works as the Principal Industry Lead for Azure Manufacturing, where he focuses on ensuring that Azure delivers the best cloud platform for Manufacturing, and on sharing Microsoft’s cloud story with decision makers and influencers in the industry.

Before Microsoft, Diego worked as the Manufacturing Industry Strategist for Autodesk, where he helped define the vision for Autodesk in manufacturing and was an evangelist of Autodesk’s thought leadership in the industry by delivering talks, writing, and engaging with the media and industry analysts.