Influence of Edge Computing Adoption on Real-Time Data Processing Efficiency in Smart Manufacturing Systems in Brazil

Purpose: The purpose of this article was to analyze influence of edge computing adoption on real-time data processing efficiency in smart manufacturing systems. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The adoption of edge computing in smart manufacturing systems significantly enhances real-time data processing efficiency by reducing latency, improving data throughput, and enabling faster decision-making. Edge computing facilitates the processing of data closer to the source, minimizing reliance on centralized cloud systems and accelerating response times in mission-critical applications. As a result, manufacturing operations benefit from increased system reliability, optimized resource allocation, and enhanced operational agility. Unique Contribution to Theory, Practice and Policy: Technology-organization-environment (TOE) framework, diffusion of innovation (DOI) theory & socio-technical systems (STS) theory may be used to anchor future studies on the influence of edge computing adoption on real-time data processing efficiency in smart manufacturing systems. Practically, manufacturing firms should conduct comprehensive infrastructure readiness assessments to ensure compatibility between edge technologies and existing operational systems. From a policy standpoint, governments should offer targeted incentives such as tax credits, grants, or digital transformation subsidies to accelerate edge computing adoption in manufacturing sectors.