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How can manufacturers avoid drowning in data?

# : MANUFACTURING | SMART OPERATIONS

Thu, 25 Jun 2020

3 to 5 mins read

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Manufacturing industry applications utilize the Industrial Internet of Things (IIoT) despite its disruptiveness because it promises to collect streams of data from equipment, analyze data, and provide opportunities for production that's more efficient. However, there are still misconceptions clouding the topic.


One of these misconceptions about the potential for manufacturers drowning in data. The belief is that there is no measurable benefit from this information collection. However, this situation doesn't have to occur.

Using IIoT edge

What does edge mean?

"Edge" is a cloud computing paradigm where rather than sending data to the central network for analytics performance, each device processes it locally.

Data processing

Information is selectively forwarded to the central hub including exceptions, highlighting trends, and summary data. These efforts reduce the need for computing and bandwidth power, as well as other IT infrastructure.

25% of the audience uses edge computing technology

According to Lauren Horwitz, the managing editor of Cisco, a major network devices supplier.

More than 50% plan to implement it within two years

According to Gartner conference on edge technology

Benefits of optimized analytics

It's possible for manufacturers to receive all the benefits of optimized analytics with accessibility in a centralized location without the need to sift through endless amounts of data aggregated at every site. 


Under most circumstances, this data indicates that the process is running as they would expect. The data collection is also something manufacturers can worry less about because it travels with them from site to site, thus allowing them to make decisions no matter their location.

What kind of data is good candidate for edge processing?

The best data for IoT Edge processing is those "must-process" pieces of information that can occur locally.

Every other piece of intelligible high-level data, like uptime and production counts, for example, should pass directly through the cloud.

It's possible for users to work with data in the cloud, as well as edge-analyzed data.

Faster decision making

Efficiency is achieved by ONLY focusing on the changing trends leading to faster decision making

Avoids getting inundated with data

As low-utility, high-frequency data is processed locally and only specific trends or insights collected from cleaned and de-duped data is sent to the cloud for deeper analysis.

Gain control over your manufacturing execution

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