CASE STUDY
IMPROVING MASTER DATA MANAGEMENT for national oil company in the middle east
Location: Middle East
Partner: DIGATEX
Year: 2022
Project Type: Data Extraction & Data Analytics
Background
& Challenge
In-house engineering updates held in the clients Document Management Systems were not reflected in their maintenance system. Consequently, when maintenance tasks were generated, there were inconsistencies and errors between the two data sources. This resulted in added cost and schedule delays during maintenance (wrong drawings, missing parts, design changes not noted) along with added risk due to incorrect inspection and maintenance procedures being applied. DIGATEX was engaged to extract the data from the data sources using their AIML platform and to provide advanced mapping analytics to link the Tags and engineering drawings to the equipment in the field.
DIGATEX’s
Solution
DIGATEX processed the data held in both SAP and the clients Document Management System, identifying disparities between Master Materials at a FLOC (functional Location) level and the engineering tags in the documents. All this information was made available to the users through our web portal and inconsistencies identified. The client then had a clear view of data quality and consistently and could confidently target their resources to where they were needed to resolve the issues.
Implementation
& Outcome
Product Utilised: DaaS & Knowledge Hub
Major Benefits
Time Efficiency
Over 3.5 million validated tags were extracted and consolidated in 9 months.
Cost Savings
Across all the different document sets the extraction accuracy exceeded 92% and for key documents was hitting >99%. The project could not have been done cost effectively without the DIGATEX solution.
Operational Continuity
More than 1 million documents were processed which equated to over 5 million sheets of engineering drawings; P&ID’s, Piping General Arrangement (GA’s), Single Line Diagrams and manuals and vendor data books.
Conclusion
This project proved that it is possible to quickly and cost effectively identify and validate Tags extracted from millions of legacy documents. This enables key data to be instantly accessed in the context of solving numerous business problems, in this case mapping and verifying engineering data with physical equipment in the field.
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