Cyber-Physical Systems for High-Performance Machining of Difficult to Cut Materials in I5.0 Era-A Review

The fifth Industrial revolution (I5.0) prioritizes resilience and sustainability, integrating cognitive cyber-physical systems and advanced technologies to enhance machining processes. Numerous research studies have been conducted to optimize machining operations by identifying and reducing sources of uncertainty and estimating the optimal cutting parameters. Virtual modeling and Tool Condition Monitoring (TCM) methodologies have been developed to assess the cutting states during machining processes. With a precise estimation of cutting states, the safety margin necessary to deal with uncertainties can be reduced, resulting in improved process productivity. This paper reviews the recent advances in high-performance machining systems, with a focus on cyber-physical models developed for the cutting operation of difficult-to-cut materials using cemented carbide tools. An overview of the literature and background on the advances in offline and online process optimization approaches are presented. Process optimization objectives such as tool life utilization, dynamic stability, enhanced productivity, improved machined part quality, reduced energy consumption, and carbon emissions are independently investigated for these offline and online optimization methods. Addressing the critical objectives and constraints prevalent in industrial applications, this paper explores the challenges and opportunities inherent to developing a robust cyber-physical optimization system.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:24

Enthalten in:

Sensors (Basel, Switzerland) - 24(2024), 7 vom: 05. Apr.

Sprache:

Englisch

Beteiligte Personen:

Gohari, Hossein [VerfasserIn]
Hassan, Mahmoud [VerfasserIn]
Shi, Bin [VerfasserIn]
Sadek, Ahmad [VerfasserIn]
Attia, Helmi [VerfasserIn]
M'Saoubi, Rachid [VerfasserIn]

Links:

Volltext

Themen:

Adaptive control
Cyber–physical systems
Finite element analysis
Industry 5.0
Journal Article
Process optimization
Review

Anmerkungen:

Date Revised 15.04.2024

published: Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.3390/s24072324

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM370998464