Comparative Analysis of Cloud Computing Adoption for an e-Commerce Platform in the Manufacturing Industry: A System-Dynamics Approach Using AWS

The manufacturing sector has undergone significant transformation with the advent of Industry 4.0 and the emerging principles of Industry 5.0, integrating advanced technologies such as Cloud Computing (CC) and Big Data to optimize processes, improve operational efficiency, and enhance customer experiences. This study presents a systematic, step-by-step process for implementing a CC solution from scratch within the automotive industry, focusing on the development of an e-commerce platform to expand market reach and improve vehicle sales. The architecture was designed using Amazon Web Services (AWS) as the cloud provider, considering multiple technical and economic attributes. Industry experts evaluated the proposed solutions using the Analytical Hierarchy Process (AHP), incorporating critical factors such as performance, cost-effectiveness, and scalability to select optimal architecture. A System Dynamics (SD) simulation model was employed to analyze and compare the selected implementations; it provided quantitative insights into their long-term impact. Results demonstrate substantial differences in performance and costs across the analyzed architectures, highlighting the importance of a structured evaluation process when adopting cloud technologies. The study offers a replicable methodology for manufacturers seeking to transition to cloud-based infrastructures, contributes to a better understanding of the economic and operational implications of CC adoption. The findings underscore the relevance of cloud solutions in aligning manufacturing operations with the objectives of Industry 4.0 and 5.0.