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Menampilkan 1–2 dari 2 artikel
Energy Aware Reinforcement Learning Approach for Dynamic Production Scheduling Optimization in Sustainable Smart Manufacturing Environments
Yogiek Indra Kurniawan
; Krisna Widi Nugraha
; Rosyid Ridlo Al-Hakim
; Erick Fernando
; Rian Ardianto
; Genrawan Hoendarto
; Mursalim Mursalim
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 2
, No 4
(2025)
Background: The development of modern manufacturing systems requires production scheduling strategies that not only improve productivity but also optimize energy utilization. Multi-machine production systems with job-shop configurations exhibit high complexity due to dynamic interactions between machines, job queues, and varying processing times, making conventional scheduling methods less effective in handling changing operational conditions. Objective: This study aims to develop and evaluate a...
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Integrated Digital Twin and Physics Informed Machine Learning Model for Real Time Performance Prediction of Industrial Mechanical Systems
Irlon Irlon
; Siti Shofiah
; Helmi Wibowo
; Erick Fernando
; Genrawan Hoendarto
; Mursalim Mursalim
International Journal of Mechanical, Industrial and Control Systems Engineering
Vol 2
, No 2
(2025)
Background: The rapid advancement of digital technologies in the Industry 4.0 era has transformed industrial mechanical systems into highly interconnected and data driven environments through the integration of sensors, the Internet of Things (IoT), data analytics, and cyber physical systems. This increasing complexity requires more adaptive and accurate monitoring and prediction methods than conventional simulation approaches, which often face limitations in capturing real time dynamic system b...
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DOI