Dr.-Ing. Abdelhakim Laghmouchi

Fraunhofer Institute for Production Systems and Design Technology (IPK)

Dr.-Ing. Abdelhakim Laghmouchi is a research fellow at the Fraunhofer Institute for Production Systems and Design Technology (IPK). He holds a Diploma (Dipl.- Ing.) and Ph.D. (Dr.-Ing.) in Computational Engineering Sciences from with the Technical University Berlin and a M.A. in Sustainability and Quality Management from Berlin School of Economics and Law. His research fields are process, condition and production systems monitoring, data analytics and IoT applications for Predictive Maintenance in the context of Industry 4.0.

Digital twin for industrial applications. CONTACT Elements for IoT opens up new perspectives.

Abstract

The digital transformation in production industry opens promising and enormous challenging prospects. According to recent studies, companies tend to see Internet-of-Things as a high priority task to improve customer relations rather than just being a short-lived hype.

So farPreviously, isolated devices are will bea parts of comprehensive system architectures on in the internet.: iIn the future, the skillful utilization of software will be steadily growing in importance rather than the hardware. This trend will apply to products themselves as well as to production systems and processes.

CONTACT Elements for IoT presents a comprehensive software platform for enterprises in order to enable them for the reliable implementation of their business idea with a high-performance Closed Loop Product Lifecycle Management. CONTACT Elements supports the configuration and development of solutions for management of digitalized products and production systems. Focus is on the efficient Design-to-IoT of cybertronic product concepts and management of digital twins „as built“ and „as used“.

Through monitoring of devices and analysis of raw data, discrepancies in the digital twin can be detected in early stage with the digital twin and necessary measures for maintenance actions can be taken. Machine down-time can be therefore reduced and acquired data can be used in the future for product engineering process.