Citation:

Srujana Manigonda ,2021. "Empowering Data-Driven Decision Making In Manufacturing ", ESP Journal of Engineering & Technology Advancements 1(1): 239-244.

Abstract:

In the manufacturing sector, the increasing complexity of operations and competitive pressures demand a shift toward data-driven decision-making (DDDM). By integrating advanced analytics, real-time data monitoring, and predictive modeling, manufacturers can significantly enhance productivity, reduce costs, and improve product quality. This paper explores the transformative impact of DDDM on manufacturing, highlighting its applications in predictive maintenance, supply chain optimization, and quality control. It also examines challenges such as data silos, lack of governance, and workforce adaptability, offering practical solutions and a roadmap for successful implementation. Ultimately, data-driven strategies empower manufacturers to achieve greater agility, innovation, and long-term competitiveness in the Industry 4.0 era.

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Keywords:

Data-Driven Decision Making, Smart Manufacturing, Predictive Maintenance, Industry 4.0, Manufacturing Analytics, Big Data in Manufacturing, Supply Chain Optimization, Digital Transformation, Quality Control, Real-Time Data Monitoring, Prescriptive Analytics, Operational Efficiency, IoT in Manufacturing, Manufacturing Data Governance.