A Lean Scheduling Framework for Underground Mines Based on Short Interval Control

Loading...
Thumbnail Image
File version

Version of Record (VoR)

Author(s)
Wang, Hao
Zhang, Xiaoxia
Yuan, Hui
Wu, Zhiguang
Zhou, Ming
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2023
Size
File type(s)
Location
Abstract

Production scheduling management is crucial for optimizing mine productivity. With the trend towards intelligent mines, a lean scheduling management mode is required to align with intelligent conditions. This paper proposes a lean scheduling framework, based on short interval control as an effective tool to adapt intelligent scheduling in underground mines. The framework shortens the production monitoring and adjustment cycle to near-real-time, enabling timely corrective measures to minimize schedule deviations and improve overall production efficiency. An intelligent scheduling platform is implemented by adopting the digital twin platform framework, the intelligent scheduling mobile terminal module, and the integrated scheduling control cockpit module. The results indicate that the platform is effective in promoting mine intelligence by providing benefits in information transparency, flexible scheduling, lean production, and scientific decision-making. The proposed framework provides a practical solution for implementing intelligent scheduling in underground mines, contributing to the overall improvement of mine productivity. Overall, this paper provides insights for implementing intelligent scheduling in underground mines.

Journal Title

Sustainability

Conference Title
Book Title
Edition
Volume

15

Issue

12

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Item Access Status
Note
Access the data
Related item(s)
Subject

Mining engineering

Science & Technology

Life Sciences & Biomedicine

Green & Sustainable Science & Technology

Environmental Sciences

Environmental Studies

Persistent link to this record
Citation

Wang, H; Zhang, X; Yuan, H; Wu, Z; Zhou, M, A Lean Scheduling Framework for Underground Mines Based on Short Interval Control, Sustainability, 2023, 15 (12), pp. 9195

Collections