Anforderungen an ein Daten-Backend-System zur Unterstützung industrieller Datenanalyse-Anwendungen in digitalen Engineering-Prozessen dynamischer Wertschöpfungsnetzwerke

Abstract

Industrial data analytics needs well-structured and linked data from different data sources. The increasing mass of data, scattered IT-structures and a lack of knowledge, especially in small and medium-sized companies (SMEs) are factors that hinder the usage of data analytics. The goal of the research project AKKORD is to build a toolkit for companies to facilitate distributed and integrated industrial data analytics inside valueadding networks. A core part of this toolkit is a data backend system, which collects and links data from different source systems together in a single meta-model. This paper describes the requirements analysis of the data backend system by conducting structured interviews and workshops.

Detection of Cause-Effect Relationships in Life Cycle Sustainability Assessment Based on an Engineering Graph

“…LifeCycleInitiative.org (2022)) were not considered. Other researchers have developed systems that integrate product data from different IT systems such as PLM, ERP, and Internet of Things (IoT) into storage for metadata (Bajaj et al, 2017;Eickhoff et al, 2020;Eiden et al, 2020). Their solution integrates product data from different IT systems within a company, but it does not include data from suppliers and other external sources.…”