Development of an Integrated CNC Technology Assessment Framework (ICTAF) for Smart CNC Technology Evaluation in Modern Manufacturing
DOI:
https://doi.org/10.71229/0y7zbp97Keywords:
Computer Numerical Control, Smart CNC Technology, Decision Support Framework, Technology Assessment, (ICTAF), Intelligent Manufacturing, Industry 4.0, Sustainable ManufacturingAbstract
Computer Numerical Control (CNC) technology has become a fundamental component of modern manufacturing systems due to its capability to provide high accuracy, enhanced productivity, and flexible production performance. The continuous evolution of CNC systems has been driven by advances in motion control strategies, servo drive technologies, precision machining methods, sensing systems, and intelligent manufacturing solutions. This study develops an integrated decision-support framework for evaluating smart CNC technologies by considering multiple technical and industrial factors. A comprehensive analysis of recent CNC advancements is conducted to identify the key assessment dimensions influencing technology evaluation, including performance capability, economic feasibility, risk and reliability, sustainability considerations, and industrial readiness. Based on these requirements, the Integrated CNC Technology Assessment Framework (ICTAF) is proposed as a systematic methodology for supporting technology evaluation and adoption decisions in smart manufacturing environments. The proposed framework integrates technological characteristics with strategic assessment criteria to address the limitations of fragmented evaluation approaches commonly applied to CNC technology selection and implementation. The study demonstrates that effective evaluation of modern CNC systems requires a multidisciplinary perspective combining mechanical performance, control capabilities, digital integration, operational requirements, and sustainability considerations. The developed framework provides a structured approach for assessing smart CNC technologies and supports manufacturers in making informed decisions toward reliable, efficient, and sustainable manufacturing systems.
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