Making our reserves last longer
Making our reserves last longer

Making our reserves last longer

Modern mining practices can help us optimise consumption of scarce raw materials, says Bhanu Bhatnagar of Adani Cementation Ltd.

Scientific mining and optimal exploitation of limestone stands on four pillars viz., effective mine planning, optimisation of deposit with judicious blending of various grades, regular monitoring and effective improvements in mining operations. This ultimately results in to effective mineral conservation, enhanced life of deposits, sustainable mining operation and low cost of limestone production.

This article will cover the optimisation of deposit as a part of effective mine planning. To think of optimisation as "informed mine planning with maximising the geological resources safely throughout the life of mine operation" would not be amiss. We will elaborate on the steps involved in optimisation and the significant role IT plays in optimisation exercise.

There exist several state-of-the-art software solutions for optimisation of mineral resources, both available commercially and developed by companies in house. In the current scenario, IT-enabled services coupled with state-of-the-art mining software are used to monitor quarry operations and to take key decisions for regular operation of mining.

Introduction
The optimisation of deposit is essential for maximum utilisation of resources at lowered cost of mining production. Given the limited quantity of available raw material resources and increasing mining constraints, quality and cost competitive requirements become quite strict for cement making, making a good and well designed resource optimisation desirable.

Every deposit of limestone in India is not homogeneous in nature with varying quality in terms of CaO, SiO2, MgO, etc. content. This directly affects the cement making process, where a consistent quality of run-of-mine is required. Most deposits with variable quality contain both lower and higher range, needing a proper blend plan for proper utilisation. This has to be taken into account during the optimisation exercise of mine planning to prepare extraction plans with proper blending of all chemical constituents available in resource.

Benefits of effective optimisation
Following are the benefits at large for effective optimisation of resource available:
  • Improves the understanding of geological resource, managing variation in structure and quality available.
  • Maximises the resource recovery
  • Optimise the waste removal
  • Enable product planning to achieve proper blend plan
  • Allows allocation of effective resources like man, machine and material
  • Controls of CapEx and OpEx of mining operations
  • Allows for effective reclamation planning of mine
  • Effective pit design, with access and ramp planning for life of mine.

    A basic requirement of optimisation for a limestone deposit is extensive knowledge of the deposit and its possible extraction plans. Lack of proper extraction plan can lead to various risks like complexity of deposit, variation in quality, resource sterilisation, proper benching, maintaining slopes, stripping ratios, etc.

    Steps involved in effective optimisation in mine planning
    Basic requirements of optimisation of resource in a deposit are as follows, which depends on stages of mining operations:
  • Case 1: New mine to be opened:
  • Prospecting details: Comprises of topographical plan, survey details, geological plan, exploration work details, etc.
  • Plant requirements: Quality inputs required from process of cement plant, to know the desired LSF, SR, AR ratios and other process parameters and the production quantity required. The quality and quantity of additives plays a significant role in defining the desired quality of ROM.
  • Case 2: Existing mine area:
  • Updated mine plans, blast hole quality data, location plan and feedback on quality parameters.
  • Quality control data such as additives available for mixing in process, samples from various sources being used.
  • Plant requirements, as detailed above.

    In both above cases, resource optimisation depends on site visits and analysis of factors affecting the optimisation planning of a mine, such as surface constraints (like wetland, transmission lines, private land, access etc.), overburden depths, limestone quality, hydrogeological constraints, relative cost ranking, geotechnical issues, etc.

  • Know the deposit: In this step, a construction of deposit block model is done using an updated version of the 3D topographical survey of the deposit. This model is prepared based on actual exploration done in the field area and analysis of sample data, and is a digital representation of the deposit and its inventory (Fig 2). Thus, the overall exercise of optimisation and mine planning depends primarily on authenticity and accuracy of said sample data and its interpretation. Using the above deposit block model is imperative for understanding the inventory in terms of quality and quantity available in the deposit. To do so, one prepares Grade-Tonnage curves from these block models, which provide details of deposit inventory at various cut-off grades. This helps to understand the deposit better for planning purposes. One may also use such models as a basis for mine scheduling with alternative choices.
  • To optimise and schedule: This step puts various constraints on the above Block model (like mining constraints, raw mix design, resources and equipment availability, water table, habitants, applicable laws for mining, etc.). This is essential for preparation of mine scheduling and optimisation model, which should remain workable for the complete lifetime of the mine. Such optimisation of the deposit helps in understanding potentiality of deposit, where after putting constraints and quality variations together, the reserves are maximised (as much as possible) and wastage is minimised. Extensive and versatile sensitivity analysis is also done during optimisation for deciding in favour of a sustainable strategy.
  • To divide optimisation in various schedules: Optimisation model is divided in short term and long term schedules. Short term planning may for be yearly to monthly to weekly, etc. In terms of long-term strategy, one requires action to be delivered in a phase wise manner, and the development of a sustainable production plan with desired quality and quantity. Such plans should consider various options so as to build in flexibility in the optimisation process, to correspond with the changing market scenario, latest industry practices for limestone working and current expert knowledge on technology. One should also undertake medium level planning on a yearly basis (important for yearly business plans). This also becomes essential for adjusting mining parameters and plant requirements with regards to resource optimisation demands. Preparation of multiple plans based on seasonal variations is a must for all such medium level planning. During optimisation process, the success lies when planning is also done continuously on a weekly basis (i.e. short term basis), for this is the actual phase where the objective of the plan is converted into actual production with desired qualities. The short term optimisation of resource should always be flexible enough to take care of micro mining constraints like lead distances variation, equipment scheduling and other problems encountered on a day to day basis.
  • To prepare operation strategy and extract plans of short-term planning, based on optimisation of model: An extract plan comprises of:
  • 1.Map (2D or 3D) with location of ramps, haul roads, benches, stockpiles, sumps, crusher, conveyors, etc. 2.Quality and quantity of production and final ROM parameters. 3.Phasing sequence of extraction of mineral 4.Blending schedule for each extraction phase - Blended stockpile management. 5.Benches pit slopes and Mine limits 6.Identification for new area for exploration 7.Progressive and final mine closure areas 8.Any other information which management would like to add. 9.Updating of extract plans with Blast hole quality data, on regular basis.

    To update the optimisation model: To update block model with the regular quality and quantity inputs from production data, blast hole data and with additional exploration data. This will ultimately update the optimisation model for deposit.

    Effectiveness of optimisation plan for a mine
    The effectiveness of an optimisation plan of a mine depend on several parameters. The main parameters in this are listed below:
  • Minimise the human interventions and non-judicious adjustments or modifications
  • Savings in mining costs
  • Flexibility in mining operation
  • Good mechanism for monitoring and effective updates in plan
  • Most effective in extending the life by optimal use of all material available in resource.
  • Outcome of effective optimisation and mine plan
    Production scheduling (as a result of mine planning and optimisation) is the preparation of a sequence in which the limestone deposit is extracted and moved in order to maximise the NPV encompassing the effect of mining, economic and processing constraints.
    Application of IT for optimisation of resources
    In today's age, IT has become essential to use tools of IT for the optimisation detailed above, underlying its importance in the framework of any mining initiative. In general, the major reason for the success of IT tools in multiple fields is the ability of such tools to continuously monitor, collect and assess various kinds of data. This eliminates the possibly erroneous and definitely discrete step of manual data collection, and allows for continuous and accurate data collection with minimal expenditure. To credit of these IT tools is also their ability to process large quantities of collected data in very short times, and their ability to provide this to the users in a comprehensible and easy to use format.

    In the context of the above resource optimisation resources in mines, the following benefits of using IT tools emerge:

  • Efficiency, flexibility and accuracy through ease-of-use, powerful 3D graphics and workflow automation
  • Creating digital inventory of mineral deposit through proper 3D geological resource modelling for long-term to short-term scheduling
  • Mine layout design and site assessments, which comply with all geographical and environmental constraints with accurate volumetric calculations (can be validated by multiple methods)
  • Understanding the potential value of a deposit and determining target areas for future drilling
  • Establishing the economic viability of the deposit and the options for capital investment and development strategies
  • Enabling fulfilment of corporate economic objectives by ensuring the mine plans are robust enough to stand up to changing physical and economic factors
  • Reducing variation and increasing productivity through a faster consideration of a large number of "what-if" scenarios and deliver executable mining plans accordingly While the information collection and representation aspects of such IT tools are the main interfaces for the operations of a mine, the powerhouse of these IT tools are the various mathematical algorithms developed to analyse the collected data. The foremost of these algorithms was the Lerchs-Grossman algorithm, which makes use of the deposit block models to generate a optimisation problem on a weighted graph, which can be solved. A major factor in this generation is the floating cone method, which requires the removal of overlying ore blocks if one wishes to mine the block underneath. Multiple modifications to this algorithm use different methods to solve the same problem, or extend it to consider other constraints (such as economic data, engineering feasibility, etc.). Other methods move away from the floating cone method, and instead consider other possible mine layouts - a major one here being the split shell concept. Yet another method is of dynamic programming, which takes an iterative or sequential approach to the optimisation problem. Current IT tools depend on multiple algorithms depend on various algorithm not unlike the one discussed above, and have added contemporary techniques from other fields into the mix. This has led to stochastic variations of these methods, heuristics such as genetic algorithms, Langrangian approaches for large scale problems and introduction of machine learning approaches such as artificial neural networks. It is, however, not useful for someone in the mining industry to be a master of all such algorithms (for an apt review on these algorithms, refer to Newman et al (2010)). Rather, one would be better off understanding the different software solutions offered for the optimisation without looking "under their hoods". Multiple such software solutions exist and are used in digital enabled mine designing and optimisation. All these software solutions consider survey, mine planning and scheduling (both strategic and tactical) while generating a optimisation plan. Thus, it would be now fruitful to turn to first the desired general specifications for such a software, and then a brief description of the mining software solutions available in India. Desired technical specifications for mine planning and optimisation software This is a general list of specifications which any mining software must fulfil for it to be viable as a solution for mining optimisation. Each company, individual etc. will require to either modify or add to these while selecting their own software solution, but as such this would serve as basic guidelines for this selection. Generally, a mining software solution must satisfy the following:
  • Single integrated software for long term, medium term and very short term scheduling, avoiding to invoke different software for long term and short term schedules.
  • Creation of wireframe of pushback shell by using output block model from pit optimisation software.
  • Easy in creating pit string (road, toe and crest) for each pushback.
  • Pit, Pushback and bench definition which provides, much simpler visualisation, edition, block model interrogation.
  • Easy in trimming pit/pushback design with the topography.
  • Quick pit/pushback reserve calculation (block model interrogation).
  • Quick mining block creation (regular grid or irregular mining shape)
  • Quick mining block interrogation with geological block model
  • Easy in creating mining sequence (manual and/or user rules and/or optimal sequence) from pit optimisation software.
  • Variable time units for mid to short term scheduling (combination of hourly, daily, weekly, monthly and yearly schedule).
  • Easy in assigning of truck speed (uphill, downhill, empty and loaded) on road segments.
  • Quick/automatic dump and stockpile design tools.
  • Quick/automatic dump and stockpile units (dumping blocks and stockpiling blocks) creation.
  • Update schedule based on actual mined tonnage and grade.
  • Report customisation
  • Blending capability using linear programming A few cement companies like ACC and Ambuja have started mine planning and optimisation with their own created software like QSO (Quarry Scheduler and Optimiser) for long-term planning and Quarry Master for short term planning from Holcim. However, majority still use commercial solutions from other vendors. The mining software solutions commonly used in India for limestone mines planning and optimisation are described below:
    Gemcom (Surpac) - Now GEOVIA (3DExperience mine solution for limestone mine):
  • This software has presence in India for quite long and integration of end to end solution for mine i.e. from Exploration activities, resource modelling, planning for life of mine, medium term plans, short term plans, production management.
  • GEOVIA has presence in Iron ore, Coal, Uranium and Lignite mine planning.
  • Clients: For limestone in Grasim, L&T Awarpur, Holtec, Lafarge, Prism, ACC, Birla, Ambuja etc.
  • Brief details - The software uses Surpac software for surveying, geology inputs, pit optimisation, scheduling and grade controls as a tools for mine planning & optimisation.
  • Following features make Geovia stand out among the rest of the mine planning software available for Limestone Mining:
  • 1.The software has recently been updated with point cloud technology for better data management. 2.For strategic mine planning, the GEOVIA works on principle of mine optimisation to match with business objectives of life of mine maximisation (resources/reserves), Optimised cash flow, and better plan for how to mine and where to mine. 3.This gives idea of proper blend plan to optimise the resources of mine on short term and long term basis.
    >Datamine Studio RM Software:
  • This software is also popular for limestone mine deposits.
  • Clients in India: Grasim, Chettinad Cement, NCCBM, Binani, Shree Cement, etc.
  • Following IT and functionality features of the Datamine software make it have an edge over other competitors:
  • 1.Data validation through HOLES3D output files, which generates table of drillholes 2.Export current view to pdf format. 3.Graphics using 64bits, which can handle large data set 4.Advantageous in working with 2 or 3 monitors, Data/Model/solids can be viewed separately. 5.Dynamic checking of data using mouse and curser on screen 6.It handles complex data filtering 7.Drillhole samples assay values, lithologs and geology is easy to compare. 8.Advanced geostatistics is possible.
    Maptek (Vulcan) software:
  • This software is currently not very popular in India.
  • Indian Clients: Coal India, Thiess, JSW. No client in limestone as far details available.
  • This is a 3D Mining software solution, allows user to validate and transform raw mining data into dynamic 3D models, accurate mine designs and operating plans.
  • The Maptek (Vulcan) has following benefits, separate from the features offered by other software solutions:
  • 1.Scheduling (optimisation) based on commodity pricing. 2.Integrate modelling with I-Site laser survey data. 3.This is also available in 64bit graphics
    Mining software by CMC:
    Concept of remote quarry management
    A recent technique which accentuates the importance of application of IT to mine optimisation is the "Remote Quarry Management". It uses IT solutions to analyse and support actual mining activity in field from a remotely located center. This technique does not add onto the previous IT solutions for mine optimisation. Rather, the core of this technique lies in the battery of IT tools used to share data and for management purposes, which in turn enables the remote center to effectively convert the optimisation plans to operations on the field without requiring a separate local management team. This not only reduces manpower requirements, but also coordinates the operations with the planning stage, enabling corrective inputs to be incorporated easily and earlier. Such a remote center also can integrate expert help, multiple knowledge bases and potential leaderships easily to provide quick alternative solutions, detailed analysis, evaluation of multiple scenarios and ultimately better operation management, deposit use and streamlined quarry output. Conclusion
    This article has discussed about the mine optimisation in limestone mine, which is major commodity for cement manufacturing. This is quite a critical exercise for maximising the resources and optimising the NPV of gains. Mining of limestone is a dynamic scenario, in which any changes in Cement markets directly affect mining operations. The optimisation exercise helps in updating and timely managing the above two objectives. Despite extensive use of optimisation techniques, challenges still exist in this field, such as various demands from stakeholders, environmental demands, etc.

    Software solutions available for mine planning and optimisation help in expediting the analysis and obtaining alternative results for management to take suitable decision. Various software available in India were discussed in brief with their capabilities. Continuous improvement in this field is on the card, which is something the IT world is working on constantly and continuously. It is fluid and dynamic situation, and each new day brings a new solution or software to light for the ever present challenges of this field.

    References
  • Cox, F.C., Bridge, D. McC., Hull, J.H., 1977. Procedure for the assessment of limestone resources. Miner. Assess. Rep. Inst. Geol. Sci., No. 30.
  • Schneider, P., Oswald, K. D., Riedel, W., Meyer, A., Schiller, G., Bimesmeier, T., ... & Khac, L. N. (2018). Engineering Perspectives and Environmental Life Cycle Optimization to Enhance Aggregate Mining in Vietnam. Sustainability, 10(2), 525.
  • Runge, I. C. (1998). Mining economics and strategy. SME.
  • W.A. Hustrulid and M. Kuchta, Open pit mine planning and design, two volume set, Taylor & Francis, 1995.
  • IBM, Envisioning the Future of Mining (White Paper). URL: https://www-935.ibm.com/services/multimedia/wp_envisioning_mining.pdf
  • Kwiri, Joseph & Genc, Bekir. (2017). Mine planning and optimization techniques used in surface mining - Position Paper.
  • Chadwick, John "On Screen Planning" International Mining Feb 2016. Print. ?Newman, Alexandra M., et al. "A review of operations research in mine planning." Interfaces 40.3 (2010): 222-245.
  • Anon, 2016, Planning and Optimisation of Surface Mines Course lecture notes, University of the Witwatersrand, Johannesburg, South Africa, August 2016
  • Gallagher, M.S and Kear, R.M, 2001, Split shell open pit design concept applied at De Beers Venetia Mine South Africa using the Whittle and Gemcom software, The Journal of the South African Institute of Mining and Metallurgy, Volume 101, Number 8, page 401- 410
  • Onur, A.H and Dowd, P.A, 1993, Open-pit optimization. Part 2. Production scheduling and inclusion of roadways, Transactions of the Institution of Mining and Metallurgy Section A: Mining Technology, Volume 102
  • Smit, A and Lane, G, 2010, Mine optimization and its application using the Anglo Platinum Mine Optimization Tool, The 4th International Platinum Conference, Platinum in transition 'Boom or Bust, The Southern African Institute of Mining and Metallurgy, page 317 - 328
  • Lane K.F, 1997 The Economic Definition of Ore - Cut-off grades in Theory and Practice, 3rd Edition, COMET Strategy Pty Ltd Queensland, Australia
  • Frimpong, S., E. Asa, J. Szymanski. 2002. Intelligent modeling: Advances in open pit mine design and optimization research. Internat. J. Surface Mining Reclamation Environ. 16(2) 134-143.
  • Hochbaum, D. S., A. Chen. 2000. Performance analysis and best implementations of old and new algorithms for the open-pit mining problem. Oper. Res. 48(6) 894-914
  • Osanloo, M., J. Gholamnejad, B. Karimi. 2008. Long-term open pit mine production planning: A review of models and algorithms. Internat. J. Mining Reclamation Environ. 22(1) 3-35.
  • Tan, S., R. Ramani. 1992. Optimization models for scheduling ore and waste production in open pit mines. Proc. 23rd Internat. Appl. Comput. Oper. Res. Mineral Indust. (APCOM) Sympos., SME, Littleton, CO, 781-791.
  • Topuz, E., C. Duan. 1989. A survey of operations research applications in the mining industry. CIM Bull. 82(925) 48-50
  • Yun, Q., J. Liu, Y. Chen, G. Huang. 1990. Optimization of planning and design in underground mines. Proc. 22nd Internat. Appl. Comput. Oper. Res. Mineral Indust. (APCOM) Sympos., Technische Universität Berlin, Berlin, 255
  • Maptek Vulcan. Maptek Software Pty Ltd. Vulcan Chronos. Sydney, Australia. http://maptek.com/
  • Geovia. Dassault Systèmes® Vélizy-Villacoublay, France. https://www.3ds.com/products-services/geovia/ & http://blogs.3ds.com/geovia/
  • Studio RM. Datamine International, Wells, United Kingdom. http://www.dataminesoftware.com/resource-modelling/

  • benefits of effective optimisation:
    Affected partiesBenefits Operation Staff1.Flexibility in operation 2.No human interventions 3.Avoid Human biasness 4.Alternatives available 5.Efficient operation Management1.Evaluation of alternatives 2.Optimal use of deposit 3.Better controls over resource 4.Regular updating of mine faces Company 1.Savings in Operating Cost 2.Minimal inventories 3.Increased deposit life 4.Consistent production Customer1.Consistent quality product 2.Effective Cost to product

    Author: Bhanu Prakash Bhatnagar, Head Mining and Raw materials, Adani Cementation Ltd, Ahmedabad.

    No stories found.
    Indian Cement Review
    www.indiancementreview.com