THE CONVERGENCE OF COMPUTER-AIDED DRAUGHTING AND DISCRETE EVENT SIMULATION IN MANUFACTURING: A SYSTEMATIC STATE-OF-THE-ART REVIEW

Computer-Aided Draughting and Design (CAD) and Discrete Event Simulation (DES) grew out of engineering sciences related to manufacturing: CAD specifies the geometry of parts, tools and factory layouts, while DES analyses the behaviour of manufacturing systems over time. However, both fields are now becoming linked by the need for shorter commissioning cycles, product changes, and Industry 4.0 digital twins, with the geometric and logistical information already captured in a CAD model already being used to create a simulation study, but not built from scratch. This article is a systematic review of this convergence. According to PRISMA 2020, records from Scopus, Web of Science and IEEE Xplore were identified, screened and assessed for eligibility resulting in the synthesis of 55 peer-reviewed journal articles and conference papers from the period 2007–2025 (49 articles retrieved from the databases and 6 from backward and forward snowballing). Four thematic clusters of literature are presented to organize the literature: (A) automated/semi-automated generation of DES models from CAD and layout data, (B) CAD driven virtual commissioning and behavioural digital-twin simulation, (C) neutral data-exchange standards to link CAD and simulation tools, and (D) digital-twin taxonomies to situate the broader convergence. The review reveals consistent evidence that automated model generation reduces the time to simulation, and that it is easier to learn DES when it is automated, but that there is a loss of information at the CAD–simulation interface, that terminology can differ, and that there is insufficient industry-scale, longitudinal validation. It also considers the implications of the convergence for manufacturers in the developing industrial economies, where the use of simulation is not widely adopted despite the fact that many of the key inputs to the simulation are readily available. The article ends with a research agenda that draws on evidence to support the following points: (1) CAD–DES data exchange via standardised ontologies, (2) hybrid CAD-first vs. event-log-first model generation, (3) terminological precision, (4) human-centred Industry 5.0-oriented modelling, and (5) low-cost convergence pipelines for resource-constrained manufacturers.