Research on Key Success Factors of Building Sensor-based MES System in Intelligent Manufacturing Environment

The global manufacturing sector urgently needs digital transformation, yet a significant number of enterprises, especially small and medium-sized ones, remain trapped in traditional production models. Data collection largely relies on manual operations and paper-based records, leading to inefficiencies across procurement, production, and warehousing. Production staff depend on manual statistics and daily data compilation, resulting in substantial productivity losses. To address this challenge, this study investigates the key success factors for transitioning to sensor-based Manufacturing Execution Systems (MES) to enable smart manufacturing. Methodologically, a mixed approach is adopted, including questionnaire design and SPSS-based data analysis, incorporating reliability and statistical analyses to validate research hypotheses. Findings indicate that sensor-based MES significantly improves data collection efficiency and reduces response times, offering a viable transformation pathway for traditional manufacturers. Beyond technological feasibility, the study highlights broader implications: supporting national smart manufacturing strategies, bridging the digital divide between developed and developing economies, and proposing policy measures such as sensor subsidies to promote industry-wide adoption. The research underscores the transformative potential of sensor-based MES in driving economic growth, creating employment opportunities, and advancing environmental sustainability, marking a pivotal direction for the future of manufacturing.