• 3 min read

The Value of IoT-Enabled Intelligent Manufacturing

As the manufacturing industry tackles some significant challenges including an aging workforce, compliance issues, and declining revenue, the Internet of Things (IoT) is helping reinvent factories and key processes.

As the manufacturing industry tackles some significant challenges including an aging workforce, compliance issues, and declining revenue, the Internet of Things (IoT) is helping reinvent factories and key processes. At the heart of this transformation journey is the design and use of IoT-enabled machines that help lead to reduced downtime, increased productivity, and optimized equipment performance.

Learn how you can apply insights from real-world use cases of IoT-enabled intelligent manufacturing when you attend the Manufacturing IoT webinar on March 28th. For additional hands-on, actionable insights around intelligent edge and intelligent cloud IoT solutions, join us on April 19th for the Houston Solution Builder Conference.

IoT in action webinar series: From Reaction to Prediction - IoT in Manufacturing March 28th, 2019.

Using IoT solutions to move from a reactive to predictive model

In the past, factory managers often had no way of knowing when a machine might begin to perform poorly or completely shut down. When something went wrong, getting the equipment back up and running was often time consuming and based on trial-and-error troubleshooting. And for the company, any unplanned downtime meant slowed or halted production, resulting in lower productivity and higher costs.

The development of IoT-enabled machines with sensors allows companies to improve overall efficiency, performance, and profitability. Rockwell Automation found it time consuming and challenging to monitor its equipment in remote locations. Using Microsoft Azure to connect them, Rockwell Automation now sees real-time performance information and can proactively maintain equipment before an incident occurs.

Kontron S&T, a Microsoft partner, also recently developed the SUSiEtec platform, an end-to-end IoT solution that enables companies to build scalable edge computing solutions using Microsoft Azure IoT Edge integration and customization services. With SUSiEtec, companies can dynamically decide where data analysis will take place and manage distributed IoT devices regardless of where they’re located or how many devices are used. Join the Manufacturing IoT webinar to learn more about SUSiEtec and how to develop secure, manageable IoT solutions for manufacturing.

Keeping IoT data secure with Azure Sphere

Using IoT to create the factory of the future also means additional access points into the factory network and systems, so creating a secure network is top priority. Factory managers typically access IoT data using mobile devices, which creates even more access points. For a true connected IoT experience and factory, security is foundational.

Azure Sphere provides a foundation of security and connectivity that starts in the silicon and extends to the cloud. Together, Azure Sphere microcontrollers (MCUs), secured OS, and turnkey cloud security service guard every Azure Sphere device accessing IoT data, IoT sensors, and IoT-enabled machines. By adding useful software to Edge hardware, factories are protected with IT-proven standards as well as new Operational Technology (OT) network security.

Getting ready to develop IoT solutions

Moving to a factory of the future starts with determining what you want to achieve through the IoT-enabled machine. If predictive maintenance is the end goal, start by conducting an inventory of data sources. Identify all potential sources and types of relevant data to determine what is most essential. Then you’ll need to lay the groundwork for a robust predictive model by pulling in data that includes both expected behavior and failure logs.

With the initial logistics determined, the next step is to create a model and test and iterate to figure out which model is best at forecasting the timing of unit failures. By moving to a live operational setting, you can apply the model to live, streaming data to observe how it works in real-world conditions. After adjusting your maintenance processes, systems, and resources to act on the new insights, the final step is to integrate the model with Azure IoT Central into operations.

Of course, not all companies have the skillset or resources to develop an IoT solution from scratch. To accelerate the design, development, and implementation process, partners can utilize the Microsoft Accelerator program. By using open-source code or leveraging proven architectures, companies can create a fully customizable solution and quickly connect devices to existing systems in minutes. For instance, the Predictive Maintenance solution accelerator combines key Azure IoT services like IoT Hub and Stream analytics to proactively optimize maintenance and create automatic alerts and actions for remote diagnostics, maintenance requests, and other workflows.

Digitally transforming your own business and building or deploying IoT solutions that are highly scalable and economical to manage takes partnerships. Join Microsoft and Kontron S&T on March 28th for the webinar, Go from Reaction to Prediction – IoT in Manufacturing, and discover new approaches for achieving your business goals.