Measures for a successful digital transformation of SMEs

V Stich, V Zeller, J Hicking, A Kraut - Procedia Cirp, 2020 - Elsevier
Since 2016, the “Digital in NRW” Competence Centre has been supporting SMEs in the
manufacturing industry in designing their individual digital transformation. With an Industry …

Self-optimizing machining systems

HC Möhring, P Wiederkehr, K Erkorkmaz, Y Kakinuma - CIRP Annals, 2020 - Elsevier
In this paper the idea of Self-Optimizing Machining Systems (SOMS) is introduced and
discussed. Against the background of Industry 4.0, here the focus is the technological level …

[PDF][PDF] Capability Indices for Digitized Industries: A Review and Outlook of Machine Learning Applications for Predictive Process Control.

J Mayer, R Jochem - Processes, 2024 - depositonce.tu-berlin.de
Leveraging machine learning applications for predictive process control signifies a decisive
advancement in manufacturing quality management, transitioning from traditional …

[HTML][HTML] Develo** a framework to analyse the effect of sustainable manufacturing adoption in Indian textile industries

R Chourasiya, S Pandey, RK Malviya - Cleaner Logistics and Supply …, 2022 - Elsevier
This study aims to develop a framework to understand the effect of sustainable
manufacturing (SM) adoption in Indian textile industries. The survey-based methodology has …

[PDF][PDF] Overall Equipment Effectiveness (OEE) complexity for semi-automatic automotive assembly lines

P Dobra, J Jósvai - Acta Polytechnica Hungarica, 2023 - epa.niif.hu
In industrial practice, measuring and monitoring production performance is an essential task.
The production plan performance is monitored by middle and top management of …

Visual analysis of fatigue in Industry 4.0

D Alfavo-Viquez, MA Zamora-Hernandez… - … International Journal of …, 2024 - Springer
The performance of manufacturing operations relies heavily on the operators' performance.
When operators begin to exhibit signs of fatigue, both their individual performance and the …

Enhance of OEE by hybrid analysis at the automotive semi-automatic assembly lines

P Dobra, J Jósvai - Procedia Manufacturing, 2021 - Elsevier
Nowadays, industrial companies are constantly improving their processes and increasing
their efficiency in order to achieve higher profits. One of the most common measures of …

Machine learning tools in production engineering

M Rom, M Brockmann, M Herty, E Iacomini - The International Journal of …, 2022 - Springer
Abstract Machine learning methods have shown potential for the optimization of production
processes. Due to the complex relationships often inherent in those processes, the success …

Optimization model for production scheduling taking into account preventive maintenance in an uncertainty-based production system

P Penchev, P Vitliemov, I Georgiev - Heliyon, 2023 - cell.com
In the dynamic yet uncertain environment of Industry 4.0, industrial companies are utilizing
the benefits of contemporary technologies in manufacturing by striving to implement …

Self-description of cyber-physical production modules for a product-driven manufacturing system

J Hermann, P Rübel, M Birtel, F Mohr, A Wagner… - Procedia …, 2019 - Elsevier
The shift in customer demand from low cost to customized products has a strong influence
on production concepts. To combine the advantages of mass production such as economies …