Written by Olena Shepelyuk Industrial data projects rarely fail because of poor software. They fail because technology is applied without the engineering logic to make it meaningful. The gap between AI and industrial reality AI in predictable, repeatable processes can reduce operational costs by 20% to 50%. If you are part of the green energy, oil & gas, chemicals, or pharma […]
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Delivering SAP BOM, Data Governance, and Materials Management Excellence We are proud to announce that our team has received the Focused Recognition Award following the successful completion of the Spare Part Cataloguing & BOM Development project supporting the PRefChem BOM Team. This recognition highlights not only the successful delivery but also the strong focus on BOM creation accuracy, data governance, and materials management best practices demonstrated throughout the project lifecycle. A Milestone Achievement in […]
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Written by Igor Pyl In asset-intensive industries, digital transformation is not simply a question of installing new systems – it’s about unlocking and structuring the enormous volume of existing technical and operational information that organizations already have. Much of this data, however, remains trapped in unstructured and semi-structured formats: scanned PDF documents, technical drawings, vendor […]
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By Vitalii Yeliashevskyi “Everything should be made as simple as possible, but no simpler”. Albert Einstein. Unfortunately, due to unpredictable obstacles during asset life, the data stored in EAM becomes obsolete or, in the worst case, is not relevant at all. Such data discrepancies cause financial losses and wasted personnel time. From the vast Keel […]
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By Blake Livermore, Machine Learning Engineer As the world continues to become more data-centric and businesses become more data-driven, the importance of maintaining quality, scalable data systems, and the cost of using poor data and poor data management systems has never been higher. How much can you really be losing due to bad data? The annual […]
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