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The industrial Internet of Things (IIoT) is producing a flood of data, but manufacturers are struggling to make sense of all that information. To stay ahead of the curve, manufacturers must be able to quickly analyze data and use it to improve processes. That’s where IoT analytics comes in. IoT analytics solutions can help manufacturers monitor production, catch anomalies and meet quality standards using process data. Read on to learn more about what IoT analytics can do for your manufacturing operation.

What is IIoT analytics?

IIoT analytics is the process of collecting data and using it to inform operational decisions. It’s based on the idea that your manufacturing data can give you a competitive edge. In a manufacturing environment, that data comes from sensors. It can also come from other systems, such as ERPs and business intelligence tools. All of this data is collected, stored and analyzed. That enables you to glean insights and make better decisions.

IIoT analytics benefits

The benefits of IIoT analytics are many. Let’s take a look at the top three. Better asset utilization – By analyzing data from sensors, you can improve asset utilization. You can schedule maintenance and repairs according to wear and tear. You can also ensure that machines aren’t running when they’re not needed. Better resource utilization means fewer losses due to overproduction and downtime. Faster response times – When you have access to real-time data, you can respond to problems more quickly. You can also detect process anomalies and respond to them before they become major issues. Improved customer service – You can use data to identify and solve problems before they lead to customer complaints. You can also use it to personalize customer service and improve retention.

IIoT data analysis tools

There are a number of tools that manufacturers can use to analyze their data. Let’s take a look at a few of them. Big data analytics tools – Many manufacturers start with big data. This is the process of storing data in a centralized location, then organizing and analyzing it. Big data analytics tools can help you store data in a centralized location. They can also help you organize and analyze it. – Many manufacturers start with big data. This is the process of storing data in a centralized location, then organizing and analyzing it. Big data analytics tools can help you store data in a centralized location. They can also help you organize and analyze it. Business intelligence tools – Once you have your data in one place, you can use business intelligence tools to make sense of it. BI tools can help you visualize data so you can identify patterns faster. They can also help you create reports based on your data. – Once you have your data in one place, you can use business intelligence tools to make sense of it. BI tools can help you visualize data so you can identify patterns faster. They can also help you create reports based on your data. Machine learning tools – Another option is to use machine learning tools. These are built to analyze data and find patterns. You can then take those patterns and create rules for your data. This enables you to automate some decision-making processes.

IIoT analytics use cases for manufacturing

Let’s look at a few use cases for IIoT analytics in manufacturing. Continuous improvement – The goal of continuous improvement is to reduce waste and optimize processes. To do that, you need data. IIoT analytics can help you track production. You can also use it to monitor quality control. If you identify gaps in the process, you can find ways to improve. – The goal of continuous improvement is to reduce waste and optimize processes. To do that, you need data. IIoT analytics can help you track production. You can also use it to monitor quality control. If you identify gaps in the process, you can find ways to improve. Supply chain management – To maximize efficiency, manufacturers are increasingly integrating their operations across the supply chain. You can use data from sensors, supply chain systems and other tools to make better decisions. For example, you can use data to reduce lead times or create more accurate demand forecasts. – To maximize efficiency, manufacturers are increasingly integrating their operations across the supply chain. You can use data from sensors, supply chain systems and other tools to make better decisions. For example, you can use data to reduce lead times or create more accurate demand forecasts. Human resources – IIoT data can also help you make better HR decisions. You can use it to find ways to improve employee engagement. You can also use it to hire better employees, train more effectively and retain talent.

Key takeaway

The industrial Internet of Things is creating a flood of data. That data can help manufacturers improve their processes. IoT analytics is the process of collecting and analyzing that data. It allows manufacturers to make better decisions. It can also help them catch anomalies and meet quality standards.