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Title:Advancing intelligent toolpath generation: A systematic review of CAD–CAM integration in Industry 4.0 and 5.0
Authors:ID Simonič, Marko (Author)
ID Palčič, Iztok (Author)
ID Klančnik, Simon (Author)
Files:.pdf 68f221b891c43.pdf (636,16 KB)
MD5: 930C746BEF4B30D2E3B67493294F1404
 
URL https://www.sv-jme.eu/sl/article/advancing-intelligent-toolpath-generation-a-systematic-review-of-cad-cam-integration-in-industry-4-0-and-5-0/
 
Language:English
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Abstract:This systematic literature review investigates advancements in intelligent computer-aided design and computer-aided manufacturing (CAD–CAM) integration and toolpath generation, analyzing their evolution across Industry 4.0 and emerging Industry 5.0 (I5.0) paradigms. Using the theory–contextcharacteristics–methodology framework, the study synthesizes 51 peer-reviewed studies (from 2000 to 2025) to map theoretical foundations, industrial applications, technical innovations, and methodological trends. Findings reveal that artificial intelligence (AI) and machine learning dominate research, driving breakthroughs in feature recognition, adaptive toolpath optimization, and predictive maintenance. However, human-centric frameworks central to I5.0, such as socio-technical collaboration, remain underexplored. High-precision sectors (aerospace, biomedical) lead adoption, while small and medium enterprises (SMEs) lag due to resource constraints. Technologically, AI-driven automation and STEP-NC standards show promise, yet interoperability gaps persist due to fragmented data models and legacy systems. Methodologically, AI-based modeling prevails (49 % of studies), but experimental validation and socio-technical frameworks are sparse. Key gaps include limited real-time adaptability, insufficient AI training datasets, and slow adoption of sustainable practices. The review highlights the urgent need for standardized data exchange protocols, scalable solutions for SMEs, and human-AI collaboration models to align CAD–CAM integration with I5.0’s
Keywords:CAD–CAM integration, Industry 4.0, Industry 5.0, toolpath optimization, AI, theory–context–characteristics–methodology (TCCM)
Publication status:Published
Publication version:Version of Record
Submitted for review:24.04.2025
Article acceptance date:22.09.2025
Publisher:Univerza v Ljubljani, Fakulteta za strojništvo
Year of publishing:2025
Number of pages:str. 328-336
Numbering:Vol. 71, no. 9/10
PID:20.500.12556/DKUM-96187 New window
UDC:658.5:004.8
ISSN on article:2536-3948
COBISS.SI-ID:260345347 New window
DOI:10.5545/sv-jme.2025.1370 New window
Publication date in DKUM:09.12.2025
Views:193
Downloads:16
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Strojniški vestnik
Shortened title:Stroj. vestn.
Publisher:Fakulteta za strojništvo
ISSN:2536-3948
COBISS.SI-ID:294943232 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0157-2020
Name:Tehnološki sistemi za pametno proizvodnjo

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Abstract:Pregled literature raziskuje napredek na področju integracije računalniško podprtega konstruiranja in računalniško podprte proizvodnje (CAD–CAM) ter generiranja poti orodja, pri čemer analizira razvoj v okviru Industrije 4.0 in Industrije 5.0 (I5.0). S pomočjo pristopa po teoriji–kontekstuznačilnostih–metodologiji (TCCM) študija sintetizira 51 recenziranih raziskav (v obdobju 2000–2025) ter analizira teoretične osnove, industrijske aplikacije, tehnične inovacije in metodološke trende. Ugotovitve razkrivajo, da raziskave močno zaznamujejo umetna inteligenca (UI) in strojno učenje, ki poganjata preboje na področju prepoznavanja značilnosti, adaptivne optimizacije poti orodja in napovednega vzdrževanja. Vendar pa človeškousmerjene rešitve, ki so osrednjega pomena za I5.0, kot je sociotehnično sodelovanje, ostajajo premalo raziskana. Panoge z visoko natančnostjo (letalska in vesoljska, biomedicinska) vodijo pri uvajanju, medtem ko mala in srednja podjetja (MSP) zaostajajo zaradi omejenih virov. S tehnološkega vidika obetajo avtomatizacija, ki temelji na UI in standardi STEP-NC, a vrzeli v interoperabilnosti ostajajo zaradi razdrobljenih podatkovnih modelov in zastarelih sistemov. Metodološko prevladuje modeliranje na osnovi UI (49 % raziskav), eksperimentalna validacija in sociotehnična ogrodja pa ostajata redka. Ključne vrzeli, ki so bile zaznane v študiji, vključujejo omejeno sprotno prilagodljivost, pomanjkanje zadostnih učnih podatkovnih zbirk za učenje modelov UI, ter počasno uvajanje trajnostnih praks. Pregled poudarja nujnost standardiziranih protokolov za izmenjavo podatkov, razširljivih rešitev za malo serijsko proizvodnjo ter razvoj modelov sodelovanja med človekom in UI, ki bi CAD–CAM integracijo uskladili s trajnostnimi in odpornimi cilji I5.0. Z odpravljanjem teh vrzeli prispeva pregled k oblikovanju na
Keywords:CAD–CAM integracija, Industrija 4.0, Industrija 5.0, optimizacija poti orodja, umetna inteligenca (UI), teorija–kontekstznačilnosti–metodologija (TCCM)


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