CASE STUDY

Enhancing Maintenance Engineering for AN EPC

Location: United States of America
Partner: DIGATEX
Year: 2020
Project Type: Data Extraction and Maintenance Hierarchy Build

Background
& Challenge

Hundreds of thousands of engineering tags for every maintainable item must be manually pulled from un-structured sources, documented and linked together, before being populated into the selected maintenance database. In order to remain competitive and provide a better quality and faster service our client partnered with DIGATEX to optimise and automate this process.

DIGATEX’s
Solution

Using our AIML Platform, DIGATEX created a set of digitally intelligent documents to build most of the data required to populate the maintenance hierarchy. Once in a digital format the data was made available in the DIGATEX Knowledge Hub where automated rule based utilities and drag and drop capabilities meant the engineers could very quickly create and verify the maintenance hierarchy build process.

Implementation
& Outcome

Product Utilised: DaaS &  Knowledge Hub

Major Benefits

Time Efficiency

Data extraction – 70% faster than traditional  processes and saved 30%-50% of time spent in building the asset hierarchy

Cost Savings

Data extraction and building the asset hierarchy delivered cost savings of 50%.  Revising the hierarchies with as-built changes saved 80% of the cost

Operational Continuity

All the data is captured and can be visually shown on the documents, which significantly increases quality and reduces the amount of time checking

Conclusion

A key task at the beginning of such contracts is to create a Maintenance Hierarchy, essentially a list of all the maintainable items of equipment and materials in an organised hierarchy, where each item is a child of another item or system, allowing maintenance tasks to be optimised across logical groups of equipment items.

Used on several projects to assist in the asset hierarchy build. DIGATEX have now processed over 500,000 documents.

  • Data extraction – 50% cheaper and 70% faster than “high value centres” manual processes with higher quality
  • Asset hierarchy build – saved 30%-50% of time spent in building the asset hierarchy.
  • Because all the data is captured and can be visually shown on the documents this increases the quality and reduces the amount of checking.
  • Revising the hierarchies with as-built documents was 80% faster and cheaper than doing it manually using the compare and update features.

start THE conversation

Inspired by this Maintenance Hierarchy Build success story?

Don’t let maintenance hierarchy build challenges impact your operations. Connect with us today to explore how our Data as a Service and Knowledge Hub can streamline your asset management, reduce downtime, and drive cost savings.