Advancing intelligent toolpath generation: A systematic review of CAD–CAM integration in Industry 4.0 and 5.0

Simonič, Marko (author), Palčič, Iztok (author), Klančnik, Simon (author)

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

• Language: English
• Keywords: CAD–CAM integration, Industry 4.0, Industry 5.0, toolpath optimization, AI, theory–context–characteristics–methodology (TCCM)
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FS - Faculty of Mechanical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2025
• Number of pages: 9 str.
• Numbering: Vol. 71, no. 9/10
• PID: 20.500.12556/RUL-177381
• UDC: 658.5:004.8
• ISSN on article: 2536-3948
• DOI: 10.5545/sv-jme.2025.1370
• COBISS.SI-ID: 260345347
• Publication date in RUL: 22.12.2025

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

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)

Projects

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