可维修性、再生材料含量和可回收性必须以可分析的产品数据形式存在于供应链中。DIN EN 18364 标准草案为此奠定了重要基础。企业和专业人士可在 2026 年 9 月 10 日之前，通过 DIN 标准草案门户对该草案发表评论。

How can materials and components be described in a standardized, transparent, and cross-industry manner in the future? In this interview, Detlev Raguse (ECLASS) and Stefan Willms (morphe*) provide insights into the joint development of the Material Dictionary by ECLASS and morphe*. They discuss the project's practical use cases, the added value the solution offers companies, and its growing relevance to digital supply chains, sustainability, and the Digital Product Passport.

ECLASS 17.0 Release 的 Alpha 版本现已完成，并正式向 ECLASS 社区开放测试。这标志着发布流程进入了下一个重要阶段：相关机构成员、专家组、IT 服务提供商以及开发者社区现可对该版本进行技术和内容层面的检查，并提交反馈意见。

The ECLASS association has finished the initial version of an innovative, AI-driven mapping between the two leading standards, ETIM and ECLASS. In this interview, Thorsten Kroke discusses the project’s background, its underlying technology and how artificial intelligence is transforming the work of subject matter experts.

Unambiguous, machine-readable product information is essential for interoperability and automated processes. A new technical article from the DKE explains how the COMDO project involves ISO, IEC, and ECLASS working together on a common semantic foundation.

D&TS and complement are joining forces to help companies build usable digital twins. They are focusing on combining master data quality, ECLASS-compliant classification, and AAS technology.

Many companies are not yet sufficiently prepared for the Digital Product Passport. In an interview with QRNow, Thorsten Kroke explains why companies should not wait for the EU to release all of its detailed requirements, and he discusses the role of clear semantic standards in the implementation process.

Material master data is the foundation of countless business processes – yet it often remains one of the biggest challenges for organizations. Inconsistent descriptions, duplicate records, and missing classifications create significant manual effort and reduce data quality. With the eptos™ AI Classification Engine, Paradine brings artificial intelligence to master data management, transforming fragmented data into a reliable, company-wide source of truth.