Molicel FSSF00058AK User Manual

White Paper

Improving Data Integrity
with Auto Sync

White Paper

Improving Data Integrity with Auto Sync

“Less than 50 percent of companies claim to be very
confident in the quality of their data.”

Marsh, Drowning in dirty data?, 2005

Organizations rely heavily on the records they keep in their asset management
databases. In many plants, systems like AMS Device Manager are online all the time,
allowing maintenance and operations personnel a constant, critical window into the

health of intelligent eld devices.

However, even with the ever-expanding reach of the Industrial Internet of Things (IIoT),
there are still stranded devices, due to their age, location, or criticality rating. Moreover,
even for critical, connected devices, there will always be situations where a technician
needs to make repairs or run a diagnostic at the device, even in fully connected systems.

For many organizations, this collection of data at the device means a buildup of critical
information that never makes it into the asset database. Because current handhelds have
no method of enforcing authorization requirements—any technician with the handheld

can make necessary changes to a eld device—there is no guarantee that changes made
in the eld are reected in the master information store. The only way to be sure this

data is kept up-to-date is to perform a manual synchronization after every use. Yet, in the

busy plant environment, it is easy for this synchronization to be overlooked indenitely.

Over time, this failure to keep the master database updated leads to conguration
drift, in which the congurations of an organization’s assets become more and more

divergent due to manual, ad-hoc changes and updates made by technicians operating

on devices in the eld.

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Improving Data Integrity with Auto Sync

Pre-Digital Smart Devices Asset Management

As device maintenance grew more sophisticated, data became more and more disconnected.

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The Problem with Missing Data

Operators and technicians rely on critical device status data to perform their jobs. As

more and more device health and conguration data fails to make its way back to the
asset database, it becomes difcult to take full advantage of the system. A technician
heading into the eld to work on a device cannot be sure that the records in the
database accurately reect what will be seen at the device. On the other hand, operators
who don’t know the accurate status of plant devices cannot properly manage the

processes they are responsible for. Further complicating plant operations, when asset
management database information is unreliable, records required for compliance or

internal troubleshooting take longer to nd and compile, potentially resulting in nes or

production outages.

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