A Digital Ecosystem for Improving Product Design

Digitization is reaching to every corner of the industry. The industry 4.0 (I4.0) movement initiated a move towards a stronger reliance on data in the manufacturing domain in order to improve processes and product quality. Multiple works highlight the potential benefits of deploying artificial intelligence or big data management platforms for industrial companies to improve their processes and provide a better understanding of their production tools. Many I4.0 work often assume the existence of interconnected machinery, sensors, and Manufacturing Execution System (MES) in the company and assume that most data is already available from these interconnected systems on the production line. Unfortunately, this does not reflect the state of many companies whose production systems are not interconnected due to historical reasons or security and normative issues. This report describes a big data architecture for the collection, storage and analysis of industrial prototype data. We provide details on how such an architecture can be structured and how it supports the engineering cycle in a partner company through a case study.