Practical Q-Learning-Based Route-Guidance and Vehicle Assignment for OHT Systems in Semiconductor Fabs

Hong, Sangpyo; Hwang, Illhoe; Jang, Young Jae

doi:10.1109/tsm.2022.3168702

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…Since the OHT system has more than one Rx pickup structures on its MSWPT, a multi-load system is not the focus of this study, and, therefore, it is not discussed here. The energy harvesting capability is intuitively reflected by mutual inductance, as given by (21).…”

Section: Analysis Of Design Processmentioning

confidence: 99%

“…discussed here. The energy harvesting capability is intuitively reflected by mutual inductance, as given by (21).…”

Section: Analysis Of Design Processmentioning

confidence: 99%

“…In [18], the authors introduced a simulator with a Tx-end buried I-shaped magnetic core and a DQ-phase receiver (Rx) structure capable of accurately simulating and testing a wide range of driving speeds and investigating the resonant current stress on the receiver end. Most of the above WPT systems were studied with flat-plate magnetic coupling mechanisms, while the development of the orbital wireless power supply originated at the University of Auckland, New Zealand [19] and has gradually been further developed and diversified by scholars and companies in various countries [20,21]. These scholars have made pivotal contributions to the industrial and industrial aspects of WPT, but little has been said about the design thinking of magnetically coupled mechanisms.…”

Section: Introductionmentioning

confidence: 99%

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Design and Analysis of an H-Type Pickup for Multi-Segment Wireless Power Transfer Systems

Wang,

Hou,

Shi

et al. 2024

Electronics

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To tackle the complex wireless power supply requirements in the Automated Material Handling System (AMHS) of semiconductor wafer factories, this paper presents a design method for a magnetic coupling mechanism based on a Multi-Segment Wireless Power Transfer (MSWPT) system for dynamic wireless power supply in segmented track configurations. Firstly, the track is approached using Inductive Power Transfer (IPT) technology combined with an LCC-S resonant structure transmitter (Tx). Following this, the feasibility of the H-type pickup is assessed through magnetic and electrical circuit analyses, which leads to the preliminary determination of the pickup dimensions by means of finite element magnetic and thermal simulations. Furthermore, an analysis of the mutual inductance drop is conducted under various track structure parameters during track crossing and curve negotiation operation conditions. Secondly, a dual-coil winding method is proposed to reduce the insulation stress on the PCB board. Additionally, a method for calculating the wire length and a design process for the overall parameters of the pickup are derived. Finally, two Txs and a 1.5 kW power receiver (Rx) were designed to verify the mutual inductance fall under the aforementioned conditions. During low-speed full-load operations, a constant-voltage output was achieved through the proposed dual-loop PI control strategy, thereby meeting the requirements for a constant-voltage output in industrial applications.

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Section: Analysis Of Design Processmentioning

confidence: 99%

“…discussed here. The energy harvesting capability is intuitively reflected by mutual inductance, as given by (21).…”

Section: Analysis Of Design Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design and Analysis of an H-Type Pickup for Multi-Segment Wireless Power Transfer Systems

Wang,

Hou,

Shi

et al. 2024

Electronics

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A dual-critic DQN architecture for lifter assignment in multi-floor semiconductor FAB

Kim,

2024

International Journal of Production Research

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Machine learning in smart production logistics: a review of technological capabilities

Flores-García,

Hoon Kwak,

Jeong

et al. 2024

International Journal of Production Research

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Recent publications underscore the critical implications of adapting to dynamic environments for enhancing the performance of material and information flows. This study presents a systematic review of literature that explores the technological capabilities of smart production logistics (SPL) when applying machine learning (ML) to enhance logistics capabilities in dynamic environments. This study applies inductive theory building and extends existing knowledge about SPL in three ways. First, it describes the role of ML in advancing the logistics capabilities of SPL across various dimensions, such as time, quality, sustainability, and cost. Second, this study demonstrates the application of the component technologies of ML (i.e. scanning, storing, interpreting, executing, and learning) to attain superior performance in SPL. Third, it outlines how manufacturing companies can cultivate the technological capabilities of SPL to effectively apply ML. In particular, the study introduces a comprehensive framework that establishes the technological foundations of SPL, thus facilitating the successful integration of ML, and the improvement of logistics capabilities. Finally, the study outlines practical implications for managers and staff responsible for the planning and execution of tasks, including the movement of materials and information in factories.

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Practical Q-Learning-Based Route-Guidance and Vehicle Assignment for OHT Systems in Semiconductor Fabs

Cited by 5 publications

References 19 publications

Design and Analysis of an H-Type Pickup for Multi-Segment Wireless Power Transfer Systems

Design and Analysis of an H-Type Pickup for Multi-Segment Wireless Power Transfer Systems

A dual-critic DQN architecture for lifter assignment in multi-floor semiconductor FAB

Machine learning in smart production logistics: a review of technological capabilities

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