Why Arc Flash Projects Get So Complicated Before the Study Even Begins

For many electrical engineering teams, the hardest part of an arc flash project is not necessarily running the study.

It is getting the data ready to run it.

A recent conversation with an engineering team working on a large industrial arc flash project made that challenge very clear. The project involved nearly 12,000 electrical assets and roughly 90 motor control centers, along with panels and other equipment requiring review. The team was performing the familiar combination of arc flash, short-circuit, and protective device coordination studies.

The engineering itself was only part of the challenge.

The bigger problem was everything happening before the model was ready.

Three Sources of Information, None of Them Complete

The team described a workflow that will probably sound familiar to anyone who has worked on a large electrical study.

They had existing one-line diagrams.

They had field data collection forms.

They had equipment photos.

The problem was that no single source contained everything they needed.

Some of the one-lines were approximately 20 years old. The field forms were incomplete. The photos varied in quality. Engineers had to manually compare all three sources to determine what information was correct before updating the electrical model.

That creates an enormous amount of engineering work that does not necessarily feel like engineering.

It becomes detective work.

Which breaker is this?

Does this field tag match the one-line?

Was the equipment replaced?

Did the person collecting the data capture the frame size, trip rating, and settings?

Is the model correct, or is the field documentation correct?

And what changed since the last version?

These questions happen on almost every large arc flash project. The bigger the facility, the harder they become to manage.

When One MCC Takes 12 Hours

One of the most striking examples from the discussion involved a single MCC with approximately 65 loads.

Reviewing the available documentation and preparing updates took several hours. The information then still needed to be entered into the model and checked again by another engineer.

The estimated total effort was approximately 12 hours per MCC.

Multiply that by dozens of MCCs and hundreds or thousands of assets, and the scale of the problem becomes obvious.

This is not simply a labor problem.

It is also a workflow problem.

Experienced engineers are spending valuable hours comparing PDFs, spreadsheets, photos, and model data. Junior engineers need additional guidance and review. Every handoff creates another opportunity for information to be missed or entered incorrectly.

And once a model is updated, tracking exactly what changed can become difficult.

Better Field Collection Changes Everything

One of the simplest ways to improve an arc flash project is to improve how information is collected in the field.

Instead of handing someone a generic spreadsheet or paper form, a digital field workflow can guide the data collector through the information required for each asset.

For example, a circuit breaker record may require specific engineering attributes before the asset is considered complete. Photos can be attached directly to the equipment being inspected rather than stored separately in a folder and matched later.

A readiness indicator can then identify assets that still lack the information necessary for the study.

That changes the question from:

“Did we collect everything?”

to:

“Which specific assets are still missing information?”

In Egalvanic, Arc Flash Data Collection work orders are designed around that approach. Field users can move through assets, capture photos, enter required information, and see which equipment records are complete before leaving the facility.

That matters because discovering missing information after the field team has already left the site is one of the most expensive problems in an arc flash project.

AI Can Help With the Data Review

Photos are becoming increasingly important in electrical documentation.

They also create another problem.

Someone eventually has to review them.

On a large project, engineers may be sorting through hundreds or thousands of equipment photos to identify manufacturers, breaker frames, settings, and other details.

That is an area where AI can reduce some of the repetitive work.

Egalvanic can analyze equipment photos, identify useful images, and extract equipment information that can then be associated with engineering data and SKM library information.

AI does not eliminate the need for engineering review.

Poor photos are still poor photos.

A blurry image from an old camera cannot magically reveal information that was never captured. In those situations, structured required fields become even more important.

But when high-quality photos are available, automated extraction can significantly reduce the amount of manual transcription engineers have traditionally performed.

The One-Line Should Not Be a Static Deliverable

Another challenge emerges after the arc flash study is finished.

The facility changes.

A breaker is replaced.

A panel is added.

A transformer is changed.

A new production line is installed.

Someone updates the equipment, but nobody updates the electrical model.

A few years later, the next engineering team arrives and begins the same process again.

That is why the idea of a model custodian came up during the discussion.

Instead of treating the SKM or EasyPower model as something that exists only during a study, contractors and engineering firms can help customers maintain the electrical system record continuously.

Egalvanic supports importing and exporting SKM XML data, so existing models can move into the platform, be updated through fieldwork, and then be synchronized back into SKM for engineering analysis.

The engineering software still performs the study.

The difference is that the facility data does not have to be lost in the engineering model between studies.

From Arc Flash Study to Electrical System of Record

This is ultimately a much larger opportunity than simply speeding up an arc flash study.

Once the electrical assets are organized, the same information can support other electrical safety and maintenance programs.

The asset record can include equipment condition, maintenance findings, issues, inspection history, panel schedules, photos, and other documentation.

Condition of Maintenance assessments can also support NFPA 70B planning by helping teams evaluate asset condition and build longer-term maintenance plans.

Instead of creating another collection of PDFs that may become outdated within months, contractors can provide customers with a living electrical system record.

The record helps determine the work.

The work then updates the record.

That creates a continuous cycle instead of another one-time project.

The Bigger Opportunity for Electrical Contractors and Engineers

There is a practical business opportunity here as well.

Many contractors and engineering firms are already performing the difficult work required to understand a customer's electrical distribution system.

They collect the equipment data.

They build or update the one-line.

They perform the arc flash study.

They identify maintenance problems.

Then the project ends.

A digital system of record enables contractors to maintain that relationship.

Customers can continue updating the facility information. Contractors can help maintain the model. Maintenance teams can track upcoming work. Engineers can return to a much cleaner dataset the next time a study is required.

Instead of starting over every few years, everyone starts from the same record.

For an industry facing limited engineering resources and increasingly complex electrical systems, reducing repetitive work matters.

The goal is not to replace engineers.

It is to make sure engineers spend their time engineering rather than searching through spreadsheets, PDFs, and photo folders to figure out what happened in the field.

That is the problem Egalvanic was built to help solve.