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Applications of Simulation and Optimization Techniques in Optimizing Room and Pillar Mining Systems

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Applications of Simulation and Optimization Techniques in Optimizing Room and Pillar Mining Systems Scholars' Mine Doctoral Dissertations Student Theses and Dissertations Spring 2016 Applications of simulation and optimization techniques in optimizing room and pillar mining systems Angelina Konadu Anani Follow this and additional works at: https://scholarsmine.mst.edu/doctoral_dissertations Part of the Mining Engineering Commons, and the Operations Research, Systems Engineering and Industrial Engineering Commons Department: Mining Engineering Recommended Citation Anani, Angelina Konadu, "Applications of simulation and optimization techniques in optimizing room and pillar mining systems" (2016). Doctoral Dissertations. 2467. https://scholarsmine.mst.edu/doctoral_dissertations/2467 This thesis is brought to you by Scholars' Mine, a service of the Missouri S&T Library and Learning Resources. This work is protected by U. S. Copyright Law. Unauthorized use including reproduction for redistribution requires the permission of the copyright holder. For more information, please contact [email protected]. APPLICATIONS OF SIMULATION AND OPTIMIZATION TECHNIQUES IN OPTIMIZING ROOM AND PILLAR MINING SYSTEMS by ANGELINA KONADU ANANI A DISSERTATION Presented to the Faculty of the Graduate School of the MISSOURI UNIVERSITY OF SCIENCE AND TECHNOLOGY In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY in MINING ENGINEERING 2016 Approved by: Kwame Awuah-Offei, Advisor Samuel Frimpong Grzegorz Galecki Nassib Aouad Yanzhi Zhang 2016 Angelina Konadu Anani All Rights Reserved iii ABSTRACT The goal of this research was to apply simulation and optimization techniques in solving mine design and production sequencing problems in room and pillar mines (R&P). The specific objectives were to: (1) apply Discrete Event Simulation (DES) to determine the optimal width of coal R&P panels under specific mining conditions; (2) investigate if the shuttle car fleet size used to mine a particular panel width is optimal in different segments of the panel; (3) test the hypothesis that binary integer linear programming (BILP) can be used to account for mining risk in R&P long range mine production sequencing; and (4) test the hypothesis that heuristic pre-processing can be used to increase the computational efficiency of branch and cut solutions to the BILP problem of R&P mine sequencing. A DES model of an existing R&P mine was built, that is capable of evaluating the effect of variable panel width on the unit cost and productivity of the mining system. For the system and operating conditions evaluated, the result showed that a 17-entry panel is optimal. The result also showed that, for the 17-entry panel studied, four shuttle cars per continuous miner is optimal for 80% of the defined mining segments with three shuttle cars optimal for the other 20%. The research successfully incorporated risk management into the R&P production sequencing problem, modeling the problem as BILP with block aggregation to minimize computational complexity. Three pre-processing algorithms based on generating problem-specific cutting planes were developed and used to investigate whether heuristic pre-processing can increase computational efficiency. Although, in some instances, the implemented pre-processing algorithms improved computational efficiency, the overall computational times were higher due to the high cost of generating the cutting planes. iv ACKNOWLEDGMENTS I will like to express my deepest gratitude to Dr. Kwame Awuah-Offei for his support and guidance. He has been a great teacher and mentor and I will be forever grateful to him for giving me the opportunity to pursue my PhD. I will also like to thank my graduate committee members: Drs. Samuel Frimpong, Aouad Nassib, Yanzhi Zhang, and Grzegorz Galecki for their guidance and support towards my research. I will like to thank my research group members Dr. Sisi Que and Mark Boateng for their assistance with some of the data preparation, and the Illinois Clean Coal Institute for funding my research. I will also like to say a special thank you to Dr. Joseph C. Hirschi for his time and contribution toward my research, the engineers at Lively Groove Mine, and the Department of Mining administrative staff for their support throughout my graduate studies. My special gratitude goes to my late father Emmanuel Godson Anani for instilling in me the value of education and the encouragement to succeed. I will also like to thank my dear mother Lucy Gameti, my sisters, brother, and guardians for their prayers and support. Last but not least, I will like to thank my husband Brandon Lee Radford for his unwavering support, love, and encouragement. v TABLE OF CONTENTS Page ABSTRACT ....................................................................................................................... iii ACKNOWLEDGMENTS ................................................................................................. iv LIST OF ILLUSTRATIONS ............................................................................................. ix LIST OF TABLES ............................................................................................................. xi NOMENCLATURE ......................................................................................................... xii SECTION 1. INTRODUCTION ........................................................................................................ 1 1.1. BACKGROUND .................................................................................................. 1 1.2. STATEMENT OF RESEARCH PROBLEM ...................................................... 5 1.3. OBJECTIVES AND SCOPE OF STUDY ........................................................... 8 1.4. RESEARCH METHODOLOGY ......................................................................... 9 1.5. SCIENTIFIC AND INDUSTRIAL CONTRIBUTION ..................................... 11 1.5.1. Contribution to Literature. ....................................................................... 11 1.5.1.1. Panel width optimization. ........................................................... 11 1.5.1.2. Effect of changing duty cycle on CM-shuttle car matching. ...... 12 1.5.1.3. Production sequencing. .............................................................. 13 1.5.2. Contribution to the Mining Industry. ....................................................... 14 1.6. STRUCTURE OF DISSERTATION ................................................................. 16 2. LITERATURE REVIEW ........................................................................................... 17 2.1. SIMULATION OPTIMIZATION ..................................................................... 18 2.1.1. Discrete Event Simulation. ...................................................................... 20 2.1.2. DES Application in Mining. .................................................................... 25 2.1.3. DES for Optimizing Design Parameters. ................................................. 27 2.2. EQUIPMENT FLEET SIZING .......................................................................... 30 2.2.1. Techniques for Fleet Size Optimization. ................................................. 30 2.2.2. DES for Fleet Size Optimization. ............................................................ 33 2.2.3. Incorporating Duty Cycles in Fleet Sizing. ............................................. 36 2.3. PRODUCTION SEQUENCE OPTIMIZATION IN MINING ......................... 37 2.3.1. Mine Production Sequencing Models. ..................................................... 38 2.3.1.1. Linear programming (LP) models. ............................................. 38 vi 2.3.1.2. Other models. ............................................................................. 43 2.3.2. Production Sequencing in Underground Mines. ...................................... 44 2.3.3. Accounting for Risk in Production Sequencing. ..................................... 49 2.3.4. Solutions to Integer LP-based Mine Production Sequence Optimization Problems. ............................................................................ 53 2.4. THE BRANCH AND CUT METHOD FOR SOLVING COMBINATORIAL PROBLEMS....................................................................................................... 56 2.4.1. The Branch and Cut Algorithm. .............................................................. 56 2.4.1.1. Branch and bound algorithm. ..................................................... 56 2.4.1.2. Branch and cut algorithm. .......................................................... 61 2.4.2. Generating Valid Cutting Planes. ............................................................ 67 2.4.3. Role of Pre-Processing in Efficiency of Branch-and-Cut Algorithm. ..... 69 3. APPLICATION OF DISCRETE EVENT SIMULATION IN OPTIMIZATION COAL MINE ROOM AND PILLAR PANEL ............................................................ 72 3.1. INTRODUCTION .............................................................................................. 72 3.2. FRAMEWORK FOR PANEL WIDTH OPTIMIZATION USING DES ......... 73 3.3. CASE STUDY ................................................................................................... 77 3.3.1. Step 1: Build Valid DES Model. ............................................................. 77 3.3.1.1. Problem formulation. ................................................................. 77 3.3.1.2. System and simulation specification. ......................................... 77 3.3.1.3. Model formulation: CM and
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