IoT

How IoT Analytics Can Optimize Productivity

How IoT Analytics Can Optimize Productivity - Mining Shoving working at night - Parker Voice of the MachineFrom our personal devices to medical systems and online shopping, it’s clear we live in a digital world—and the rapid progress of that world is driven by data. The collection and application of data are everywhere. It’s why there’s been substantial investment in the Internet of Things (IoT) across all major industries. But collecting data is not enough. A precise analytics strategy is necessary to fully understand the data.  Because real value can only be obtained from data when it can be analyzed, interpreted and used to generate the insights that improve productivity.
 
 
 
How IoT Analytics Can Optimize Productivity - White Paper Download - Parker Voice of the Machine
Learn more by downloading our latest white paper: Using Analytics to Build Customer Solutions 
 
How IoT Analytics Can Optimize Productivity  - Taking IoT to the last mile infographic - Parker Voice of the Machine

 

The Parker approach: Discrete IoT

Generally, the Industrial IoT is employed to monitor the relative health and productivity of equipment. Insights are required at the machine level so that machines can self-report the difference between optimum and actual performance. But the machines, of course, are made up of components, so generating insights at the machine or system level requires visibility at the component level. This is where Parker expertise applies. Parker has over a century of experience in motion and control technologies. Through its platform called Voice of the Machine™, Parker’s efforts in IoT are concentrated at the component- and subsystem-level, or what we refer to as Discrete IoT. Parker Discrete IoT produces distinct component insights that become the basis for machine, higher-level system and even fleet-level productivity improvements.
 
 

Generating insights from digital twins

To realize the most value from IoT, Parker focuses on contextualizing the data collected from machines. Models of the overall system and the individual components are created and leveraged to generate insights. Not unlike the way their actual counterparts are assembled, digital twins of components are connected to build digital twins of systems. The insights identified from these models reveal opportunities for customers who can then make improvements to existing processes and systems. With model-validated insights from Voice of the Machine™, decision-making, planning, and management of operations are more precise and more productive.
 
How IoT Analytics Can Optimize Productivity - Digital Twins infographic - Parker Voice of the Machine
 
 

Discrete IoT informs decision making

When precise machine data is analyzed in the context of higher-level operational goals, sound decisions can be made. For example, think of all the factors that go into deciding when to schedule maintenance on a factory machine. What is the production schedule? Is planned downtime coming up? How much will it cost to replace a component? What is the loss of performance cost compared to the cost of replacement? How long will the machine be down?  How much will a worn component affect performance? Answering these questions is key. But just as critical is analyzing the right data that generates actionable insights about the machine itself.
 
To learn more about how to empower your operations with Parker’s Voice of the Machine™, visit our IoT website 
 
 
 
 
How IoT Analytics Can Optimize Productivity  - Tim Franke. solutions architect, Internet of Things Parker HannifinThis blog was contributed by Timothy Franke, solutions architect, Internet of Things, Parker Hannifin Corporation
 
 
 
 
 
 
 
 
 

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