Data-driven process optimization strategies in
engineering: integrating machine learning, lean
principles, and real-time analytics systems
Engineering systems across manufacturing, energy, and
infrastructure are under increasing pressure to deliver
higher productivity, quality, and sustainability under
volatile demand and constrained resources. From a broad
perspective, process optimization has evolved from
static, experience-driven improvement efforts toward
data- driven strategies that exploit advances in
sensing, analytics, and computation.
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