Engineering design is a multidisciplinary concept employed across various industries to develop innovative solutions for complex challenges. Industry 4.0 has profoundly impacted engineering design by incorporating cutting-edge technologies such as the Internet of Things (IoT), big data analytics, virtual reality, artificial intelligence (AI), and robotics. Small and Medium Enterprises(SMEs) are unaware of the design approaches they are currently using and their potential benefits, leading to failure in leveraging design approaches for process alignment. In this light, the study seeks to analyse key engineering design methodologies by highlighting the gaps and challenges regarding the potential cutting-edge technologies. A comprehensive review was conducted to identify technological alignments with advanced manufacturing practices, and relevant attributes for each design approach were extracted from the literature. The Pugh Weighted Decision Matrix was applied to evaluate the most effective design methodology. Findings indicate that, when assessing attributes against design methodologies, the Circular Design approach achieved the highest weighted score of 162, followed closely by the Data-Driven Design approach. Similarly, when evaluating technologies against design methodologies, the Data-Driven Design approach ranked highest, with the Circular Design approach in second place. Based on these findings, the research concludes that integrating the Data-Driven Design approach with the Circular Design approach establishes a robust framework for developing sustainable and highly efficient manufacturing systems. Future work will focus on integrating or merging the design approaches to develop the most effective strategy that suits current manufacturing needs.