Mukund Subramaniyan
Showing 22 publications
Realising the promises of artificial intelligence in manufacturing by enhancing CRISP-DM
Integrating Machine and Quality Data for Predictive Maintenance in Manufacturing System
Introduction to innovation analytics
Data-driven machine criticality assessment – maintenance decision support for increased productivity
An Enhanced Data-Driven Algorithm for Shifting Bottleneck Detection
Data-driven throughput bottleneck analysis in production systems
Artificial intelligence for throughput bottleneck analysis – State-of-the-art and future directions
Data-Driven Throughput Bottleneck Analysis in Production Systems
Balancing the role of domain experts and data scientists in an AI-powered factory
A generic hierarchical clustering approach for detecting bottlenecks in manufacturing
A data-driven approach to diagnosing throughput bottlenecks from a maintenance perspective
Adaptive Stream-based Shifting Bottleneck Detection in IoT-based Computing Architectures
A prognostic algorithm to prescribe improvement measures on throughput bottlenecks
Data Analytics in Maintenance Planning – DAIMP
Data-driven algorithm for throughput bottleneck analysis of production systems
Real-Time data-driven average active period method for bottleneck detection
Analysis of Critical Factors for Automatic Measurement of OEE
An algorithm for data-driven shifting bottleneck detection
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Showing 2 research projects
5G-Enabled Manufacturing II (5GEMII)
DAIMP - Data Analytics in Maintenance Planning