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Monthly Archives: November 2026

How to clean an industrial ERP database before a SAP migration

Cleaning an industrial ERP database before a migration to SAP S/4HANA involves identifying, correcting, and validating critical data, including Part Numbers, Bills of Materials (BOMs), supplier and customer Master Data, and ECO/ECN statuses, before transferring it to the new system. Without this step, duplicates, coding errors, and obsolete data are carried over into the new environment, potentially disrupting production from day one of go-live. At Kleria, we structure this process into five methodological phases using our proprietary Zero-Backlog Engine™ approach, with an initial assessment delivered within 48 hours.

By |2026-11-04T10:25:26+00:00November 2nd, 2026|Data Cleansing, ERP migration|Comments Off on How to clean an industrial ERP database before a SAP migration
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The Hidden causes of non-conformities in industrial processes

A non-conformity detected at the end of the production line rarely originates on the line itself. In most industrial environments, its root cause can be traced back to an incorrect document, data record, or reference: a Bill of Materials (BOM) that was not updated following an ECO, a manufacturing routing that is out of sync between the PLM and ERP systems, or a supplier record containing an incorrect Part Number. According to the American Society for Quality (ASQ), the cost of poor quality accounts for 15–20% of a manufacturer's annual revenue in a typical organization, with most of these costs remaining invisible in standard performance dashboards.

By |2026-11-04T11:12:39+00:00November 2nd, 2026|ERP, Industrial Quality, News|Comments Off on The Hidden causes of non-conformities in industrial processes
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The 5 risks of poorly planned PLM and CAD data migration

You are migrating to Teamcenter, Windchill+, ENOVIA, or another PLM system. The project scope is defined, the timeline is set, and the licenses are signed. But one critical area has probably not yet been properly assessed: the actual condition of your technical data, CAD drawings, BOMs, routings, ECO histories, and revision relationships. 83% of data migration projects fail or significantly exceed their budgets and timelines (Gartner). In an industrial PLM environment, the consequences go beyond financial losses: inaccessible drawings, corrupted BOMs, broken traceability, and production downtime. This article identifies the 5 most critical risks, backed by real-world examples and sourced data, and explains how to prevent them before they materialize.

By |2026-11-05T08:42:33+00:00November 2nd, 2026|CAD, News, PLM|Comments Off on The 5 risks of poorly planned PLM and CAD data migration
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Why Do 80% of Industrial AI Projects Fail Before They Even Get Started (and How to Fix It)

You approved the budget. Hired a data team. Launched an AI proof of concept on your production line. Three months later, the model still won't scale, your experts are losing motivation, and your CIO is demanding answers. The problem isn't the algorithm. It's an invisible stock of data that no one has taken the time to qualify: your industrial backlog.

By |2026-11-05T08:43:36+00:00November 2nd, 2026|Artificial Intelligence (AI), News|Comments Off on Why Do 80% of Industrial AI Projects Fail Before They Even Get Started (and How to Fix It)
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