SMART standards - concept for the automated transfer of standard contents into a machine-actionable form

• Published in: Procedia CIRP Vol. 100; pp. 163 - 168
• Main Authors: Ehring, Dominik, Luttmer, Janosch, Pluhnau, Robin, Nagarajah, Arun
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2021
• Subjects: 3M model of Duisburg; automatic extraction; knowledge representation; SMART Standards; transfer; SMART Standards; transfer; knowledge representation; automatic extraction; 3M model of Duisburg
• ISSN: 2212-8271; 2212-8271
• DOI: 10.1016/j.procir.2021.05.025

Standards are - not directly visible to everyone – omnipresent in nearly every development process. In times of digitalization, where buzzwords such as "connectivity of machines", "artificial intelligence", “big data”, “cloud computing” or “smart factories” are often used, companies are still confronted with problems in handling standards throughout the entire product lifecycle. Today’s way of working with standards is characterized by manual viewing of documents, whereby a user searches for relevant information, such as formulas, and has to transfer this information to his process, method or tool. This manual process results in an increased time, loss of quality due to faulty manual transmission of information, a high adjustment effort for updates of standards and no guarantee for traceability. In order to reduce and minimize errors and needed time for work with information stored within standards, there is a need for a new form of knowledge representation for standards with sufficient data quality to ensure standard-compliant development activities. Consequently, there is a need for machine-actionable standards to ensure autonomous and efficient processes, whereby the effort for preparation is less than the benefit. The question arises how classified standards content can be represented in a machine-actionable way without loss of information. This paper shows a concept for the automatic extraction of standards content and their transfer into a machine-actionable knowledge representation. The concept, which is based on the “3M Framework of Duisburg” and thus answers questions of modularization, modeling and management, consists of six steps "extraction", "modeling", “modification”, "fusion and storage", "provision" and "application", to digitalize existing content, is presented and discussed.