Angelina Anani
- Associate Professor, Mining and Geological Engineering
- Member of the Graduate Faculty
- (520) 621-6063
- Mines And Metallurgy, Rm. 141
- Tucson, AZ 85721
- angelinaanani@arizona.edu
Biography
Dr. Angelina Anani is currently an associate professor at the University of Arizona. She holds a BS (Summa cum laude) and PhD from the Missouri University of Science and Technology. She has over 11 years of research and teaching experience. Dr. Anani has extensive experience in the modeling and optimization of mining systems. Her current research interests include modeling and optimization of mining systems, mine planning and production scheduling, design and management of sustainable mining systems, mine equipment reliability studies, tunneling and underground works, energy and water efficiency, ethnographic research in mining, application of machine learning in the mining, 3D mining planning, mining supply chain, etc.
She has a diverse teaching background in three universities in two countries. In her current role, she teaches graduate and undergraduate mining engineering courses. Dr. Anani is an active member of the Society of Mining, Metallurgy and Exploration (SME), the Society of Mining Professors, and the Women In Mining (WIM).
Degrees
- Ph.D. Mining Engineering
- Missouri University of Science and Technology, Rolla, Missouri, United States
- Applications of simulation and optimization techniques in optimizing room and pillar mining systems
- B.S. Mining Engineering
- Missouri University of Science and Technology, Rolla, Missouri, United States Minor Outlying Islands
Work Experience
- University of Arizona, Tucson, Arizona (2022 - Ongoing)
- Pontificia Universidad Católica de Chile (2017 - 2021)
- Missouri University of Science and Technology (2016 - 2017)
- Missouri University of Science and Technology (2016 - 2017)
- Missouri University of Science and Technology (2012 - 2015)
- Victor Diamond Mine (2010)
- Morupule Colliery Ltd (2008)
Awards
- 2022 Freeport-McMoRan, Inc. Career Development Grant
- Society for Mining, Metallurgy and Exploration, Fall 2022
Licensure & Certification
- Engineering Project Management, Rice University (2019)
- Machine learning, Stanford University (2019)
- Diploma in Teaching, Pontificia Universidad Católica de Chile (2018)
Interests
Teaching
- MNE 442/542 - Application of discrete event simulation mining- Surface Mine Planning Design- Underground Mine Design
Research
Mine planning optimization for transition mines; Production schedule optimization; Automation & Equipment reliability studies; ML/AL applications in mine planning and safety; Application of operations research in mining; Supply chain management in the mining industry; 2D - 4D/ VR in mine planning; ethnography
Courses
2024-25 Courses
-
Application of DES in Mining
MNE 542 (Fall 2024) -
Dissertation
MNE 920 (Fall 2024) -
Independent Study
MNE 599 (Fall 2024) -
Independent Study
MNE 699 (Fall 2024) -
Thesis
MNE 910 (Fall 2024)
2023-24 Courses
-
Thesis
MNE 910 (Summer I 2024) -
Dissertation
MNE 920 (Spring 2024) -
Research
MNE 900 (Spring 2024) -
Surface Mine Planning & Design
MNE 436 (Spring 2024) -
Surface Mine Planning & Design
MNE 536 (Spring 2024) -
Thesis
MNE 910 (Spring 2024) -
Application of DES in Mining
MNE 542 (Fall 2023) -
Dissertation
MNE 920 (Fall 2023) -
Research
MNE 900 (Fall 2023)
2022-23 Courses
-
Surface Mine Planning & Design
MNE 436 (Spring 2023) -
Surface Mine Planning & Design
MNE 536 (Spring 2023) -
Application of DES in Mining
MNE 542 (Fall 2022) -
Thesis
MNE 910 (Fall 2022)
Scholarly Contributions
Journals/Publications
- Adewuyi, S. O., Anani, A., & Luxbacher, K. (2024). Advancing sustainable and circular mining through solid-liquid recovery of mine tailings. Process Safety and Environmental Protection, 189, 31--46.
- Anani, A., Adewuyi, S. O., Risso, N., & Nyaaba, W. (2024). Advancements in machine learning techniques for coal and gas outburst prediction in underground mines. International Journal of Coal Geology, 104471.
- Rojas, C., Anani, A., Cordova, E., Nyaaba, W., Wellman, E., & Adewuyi, S. O. (2024). Analysis of Raise Boring with Grouting as an Optimal Method for Ore Pass Construction in Incompetent Rock Mass—A Case Study. Mining, Metallurgy & Exploration, 1--15.
- Velasquez, N., Anani, A., Munoz-Gama, J., & Pascual, R. (2023). Towards the Application of Process Mining in the Mining Industry—An LHD Maintenance Process Optimization Case Study. Sustainability, 15(10), 7974.
- ANANI, A., Nyaaba, W., Risso, N., & Tenorio, V. (2022).
Application of Machine Learning in Mine Safety: A State-of-The-Art Review
. Social Science Research Network. doi:10.2139/ssrn.4314075 - Anani, A., Nyaaba, W., & Cordova, E. (2022). An integrated approach to panel width, fleet size, and change-out time optimization in room-and-pillar mines. Journal of the Southern African Institute of Mining and Metallurgy, 122(4), 181--190.
- Ayawah, P. E., Sebbeh-Newton, S., Azure, J. W., Kaba, A. G., Anani, A., Bansah, S., & Zabidi, H. (2022). A review and case study of Artificial intelligence and Machine learning methods used for ground condition prediction ahead of tunnel boring Machines. Tunnelling and Underground Space Technology, 125, 104497.
- Soto, I., Anani, A., & Cordova, E. (2022). A discrete event simulation approach for mine development planning at Codelco's New Mine Level. Journal of the Southern African Institute of Mining and Metallurgy, 122(10), 549--560.
- Anani, A. (2021). Blasting and preconditioning modelling in underground cave mines under high stress conditions. Journal of the Southern African Institute of Mining and Metallurgy.More infoSYNOPSIS Cave mining is an underground mass mining technique. The largest projects, which are known as 'super caves', produce hundreds of thousands of tons of ore per day, which involves large footprints with considerable column height, and have a life of mine of over 20-40 years. These operations are typically located deep, under high stresses and in competent rock masses, making initiation and propagation of the caving process harder to manage. These challenges must be confronted by optimizing the fragmentation of the orebody to achieve smaller size blocks that will result in consistent caving and improved flow of the ore from the drawpoints. To achieve better performance from the drawpoints, preconditioning is applied to fragment and damage the material required to cave. We present a proposed design for preconditioning in underground mines, considering the challenges that these large-scale mines are already facing, based on a comprehensive analysis of current design parameters, case studies, and sensitivity analyses using numerical models. Keywords: fragmentation, preconditioning, caving, blasting, structures, stresses, explosives.
- Anani, A. (2020). Optimization of level intervals in steeply-dipping vein deposits: A two-step approach. Resources Policy.
- Anani, A. (2019). Fatigue damage investigation of ultra-large tire components.
- Anani, A. (2019). Optimizing cut-out distance for maximum coal productivity.
- Anani, A. (2018). An assetmanagement oriented methodology for mine haul-fleet usage scheduling.. Reliability Engineering & System Safety.
- Anani, A. (2017). Application of discrete event simulation in optimizing coal room and pillar panel width: A case study.
- Anani, A. (2017). Optimization of Shuttle Car-Continuous Miner Matching Using Discrete Event Simulation: A Case Study.
- Anani, A. (2016). Effect of Input Correlation on Discrete Event Simulation of Truck-Loader Production Operations.
- Que, S., Anani, A., & Awuah-offei, K. (2016).
Effect of Ignoring Input Correlation on Truck-Shovel Simulation
. International Journal of Mining, Reclamation and Environment, 30(5), 405-421. doi:10.1080/17480930.2015.1099188More infoAbstractThis paper presents an approach for handling correlated input variables in discrete event simulation (DES) modelling of truck–shovel systems using commercial DES software and uses a case study to investigate the effect of ignoring correlation between input variables. Multivariate random vectors, instead of independent probability distributions, are used for variables found to be correlated. The authors prove that correlations do exist in truck–shovel haulage systems. The model with multivariate random vectors performs better than the original model. The significance of modelling correlation in input variables depends on the strength of the correlation and the output’s sensitivity to the input variables.
Proceedings Publications
- Akbulut, N. B., Anani, A., Brown, L. D., & Wellman, E. C. (2023).
Innovative Approach for Monitoring Underground Excavations at San Xavier Underground Mine Laboratory
. In 57th US Rock Mechanics / Geomechanics Symposium. - Tenorio Gutierrez, V. O., Anani, A., Riley, D., Risso, M. ., Heath, G., Akbulut, N. B., & Werner, J. D. (2024, Spring). Preprint 24-069 Outlining a Roadmap for the Deployment of a DIgital Twin System for the San Xavier Mine Laboratory. In 2024 SME MineXchange. SME Annual Meeting, Feb. 25 – Feb 28, 2024, Phoenix, AZ, 4.More infoImplementing a Digital Twin at the San Xavier Mine Laboratory (Sahuarita, AZ), requires a network redesign with a robust architecture. The goal is to create an ecosystem in where all personnel and equipment can be monitored in real-time from the University of Arizona campus, visualizing the site in a digital terrain model. A wireless mesh will help to test robots with autonomous features. Expected outcomes include data retrieval and analytics, the evolution of communications and safety protocols, tele-operation, and an innovated approach for managing the site with new supervision challenges. A timeline with expected commissioning benchmarks is also included. Keywords: Autonomous Equipment, Data Collection, Digital Twin, Internet of Things, Network-based, Systems Integration, Wireless Mesh
- Flores, I., Anani, A., & Li, H. (2022, September). Optimizing the Production Schedule for Transition Mines . In Mines 32nd SOMP annual meeting and conference.
- Anani, A. (2018). CM cut-sequence optimization in room and pillar coal mines, Desafíos en Planificación Minera workshop.
- Anani, A. (2018). Optimization of coal production rate as a function of cut-out distance.
- Anani, A. (2017). Optimizing Room & Pillar Recovery and Production Rates as a Function of Panel Dimensions.
- Anani, A. (2016). Effect of Changing Duty Cycles with A Panel in CM-Shuttle Car Matching: A Case Study.
- Anani, A. (2016). Mine production optimization using cutting plane method.
- Anani, A. (2015). Modeling Mining Risk in Room and Pillar Mine Sequencing Using Mixed Integer Linear Programming.
- Anani, A. (2014). Cost Saving Approach using Solution Algorithms.
- Anani, A. (2013). Incorporating Cycle Time Dependency in Truck- Shovel Modeling.
- Anani, A. (2013). Modeling Room and Pillar Operation with Pillar Retrieval as Mixed Integer Linear Programming.
Others
- Anani, A. (2019). Optimization of coal recovery and production rate as a function of panel dimensions.