The field of engineering is moving towards increased digitalization, with a focus on creating modular, reusable, and machine-interpretable models of processes and products. This shift is driven by the need for improved reproducibility, efficiency, and sustainability in engineering design and production. Recent work has centered on the development of ontology design patterns, product-process-resource asset networks, and digital twins to support the entire product life cycle, from design to end-of-life phases. Notably, these approaches enable automated validation, semantic reasoning, and executable design rules, facilitating the transition to digitized smart standards.

Some noteworthy papers include: The paper on Semantic Representation of Processes with Ontology Design Patterns, which proposes a method for automatic extraction of design patterns from existing ontologies. The paper on Product-oriented Product-Process-Resource Asset Network, which introduces a modeling approach that incorporates the end-of-life phase of the product life cycle into the engineering phase. The paper on Machine-interpretable Engineering Design Standards for Valve Specification, which demonstrates how to transform engineering design standards into modular, reusable, and machine-interpretable ontologies. The paper on Product Digital Twin Supporting End-of-life Phase of Electric Vehicle Batteries, which proposes the use of digital twin technology to optimize disassembly processes and enhance sustainability.