The Eureka Mine An Example of How to Identify and Solve Problems in a Flotation Plant

Transcription

1 CHAPTER 1 The Eureka Mine An Example of How to Identify and Solve Problems in a Flotation Plant Christopher Greet MAusIMM, Manager Metallurgy Minerals Processing Research, Magotteaux Australia Pty Ltd, 31 Cormack Road, Wingfield SA christopher.greet@magotteaux.com Chris commenced his working life as a Trainee Metallurgist at Bradken s Adelaide steel foundry in He subsequently worked in a number of foundries, before becoming a shift foreman at Seltrust s Teutonic Bore Mine in In 1985 he decided to formalise his knowledge by studying for a Bachelor of Engineering in Metallurgical Engineering at the South Australian Institute of Technology. Upon graduating, he worked as a Plant Metallurgist at Ok Tedi Mining Limited and Bradken Adelaide, before undertaking a PhD at the Ian Wark Research Institute in Since leaving the Wark, Chris has held applied research positions at Mount Isa Mines Limited, Pasminco, AMDEL, and now with Magotteaux Australia, where he leads the technical group identifying the impact of grinding chemistry on downstream processing. Abstract Introduction The Eureka Mine Data Acquisition Problem Definition Solution Development and Testing The Cycle Begins Again Communication Conclusions References Appendix 1 The Down-the-Bank Survey Appendix 2 Estimated Mineral Assays from Elemental Data ABSTRACT As the title implies, this chapter will provide, by way of example, a methodology for identifying and solving problems in a flotation plant. To do this a mythical concentrator (The Eureka Mine) will be described and used to demonstrate to the reader how to go about the process of identifying where the losses of valuable mineral occur, and what gangue species are diluting the concentrate. It is intended that this chapter be used in parallel with subsequent chapters to guide the reader through the steps involved in the process of optimising the plant. INTRODUCTION Many of us have, at one time or another, flicked through the newspaper or searched online for a job, and stumbled upon an ad not unlike the one that appears below. Whether we are jaded with our current role, looking for a step up to the next level, or wanting a new challenge, we prepare our resume and send it off in the vain hope that we may be the successful candidate. With the interview process out of the way, the waiting and self doubt start. And, after what seems an eternity you receive a phone call or letter telling you that you have got the job. Congratulations! Now what? You re new, you have ambition, you have drive, and you want to make your mark! But, there s a rightwayandawrongwaytodothis.thefirstthingtoremember is that this place has a history, and the people you are going to work with have been here much longer than you have. So, communication and respect are keys to your success. You need to discover the history of the concentrator, and discuss its operation with other members of staff (operators, metallurgical technicians, shift foremen, plant metallurgists, the chemist, mechanical and electrical maintenance, the mine (ie geologists and mining engineers) and supply). They will all give you their perspective, Flotation Plant Optimisation Spectrum Series 16 1

2 SENIOR PROJECT METALLURGIST The key objectives of this position are to: identify opportunities for improvement within the process, develop, test, evaluate and implement process improvements, identify and evaluate new technologies that will improve our process, and be actively involved in our future ores testing program. Operating in a climate of continuous improvement, you will be required to actively participate in the promotion of safe work practices, have good interpersonal skills and a professional work ethic. Skills and experience The successful applicant candidate will have the following attributes: Bachelor of Engineering Metallurgy or equivalent, five years or more process experience, a working knowledge of grinding and flotation processes, good communication skills, proven problem solving skills, good time management skills, and have sound leadership qualities and management skills. Employment conditions Eureka Mining Limited is a wholly owned subsidiary of Stockade Resources Limited, an Australian based mining and exploration company with interests in Australia, New Guinea, Zambia and Peru. Reporting to the Metallurgy Manager, the successful candidate will work closely with production to maintain and improve plant performance. This is a residential position, with an attractive renumeration package commensurate with your qualifications and experience. To apply Please submit your application including a cover letter and current copy of your resume via to... and you need to respect their point of view. You will also work out who among these people hold the knowledge, the history; the real story of your concentrator. While you are establishing relationships you need to determine what (if any) data exists that will help you to develop a technical perspective of how your concentrator performs. The focusing questions in any process improvement strategy are: Where and how do the losses of valuable mineral occur? What gangue minerals are diluting the concentrate and how did they get there? The intention of this book is to provide you with a sequence of logical steps to follow so that you can collect the necessary data to be able to define the problem(s) within your operation. Once the problems are defined, you can then prioritise them and develop experimental strategies that may lead to solutions that can be implemented in the plant. To assist you in this journey the performance of the Eureka Mine will be scrutinised and used as an example. The Eureka Mine treats a complex polymetallic sulfide ore supplied from an underground mine, producing three saleable concentrates. This chapter provides a description of the Eureka Concentrator, and its metallurgical performance since commissioning. Then provides, by example, the methodology used to collect plant data, analyse and interpret it to determine where the metallurgical problems lie. THE EUREKA MINE Location and history Extensive geological surveying of the region north of Laylor River by Stockade Resources Limited resulted in the discovery of the Eureka deposit in Throughout 1991 and 1992, drilling continued to delineate the deposit. Preproduction geological studies indicated probable reserves of approximately 25 million tonnes of greater than 15 per cent zinc plus lead, with economically significant copper, silver and gold grades. A one million tonnes per annum processing plant was commissioned by Stockade in 1995 to treat ore with an average head grade of 0.4 per cent copper; three per cent lead; 12 per cent zinc; 130 g/t silver; and 2.0 g/t gold. Geology The Eureka volcanogenic massive sulfide deposit occurs within the Laylor-Eureka Volcanic sequence of the Mount Rush Volcanics. The deposit was formed when hot mineralised solutions were spewed out on to the ocean floor and were rapidly quenched by the surrounding seawater. Hence, the sulfide minerals that were precipitated from solution formed very fine crystals and intricate mineral textures. Subsequent geological changes to the orebody were few; therefore many of the original fine grain textures remained intact. Deposit mineralogy To fully appreciate the complexity of flotation at Eureka it is necessary to have a rudimentary understanding of the mineralogy of the orebody. Eureka is unusually sulfide rich, and contains a relatively simple mineral suite: 58 per cent pyrite, 20 per cent sphalerite, four per cent galena, two per cent arsenopyrite, one per cent chalcopyrite, with minor amounts of tetrahedrite. The remaining 15 per cent of the ore consists of: quartz, barite, calcite, chlorite, sericite and siderite. Macroscopically the mineral textures are diverse, however, the orebody can be divided into two distinct metal zones. The demarcation between the two zones is set, arbitrarily, at 100 g/t of silver, and represents a continuous horizon across the deposit. Above this level is the hanging wall enrichment zone characterised by higher lead, zinc, silver, gold, and arsenic grades. Macroscopically the sulfides within the enrichment zone tend to be banded and very fine grained. The footwall-depleted zone occurs below the 100 g/t silver horizon. Pyrite and chalcopyrite are the dominant minerals within this part of the orebody, with reduced lead, zinc, silver, gold, and arsenic grades. The footwall-depleted zone is highly recrystallised, therefore the grain structure is comparatively coarse when compared with those observed in the hanging wall enrichment zone. It is important to note that the Eureka orebody is relatively free of non-sulfide gangue mineralisation. So, pyrite is the dominant gangue mineral, and is associated with all other minerals within the deposit. Therefore, the properties of pyrite will influence greatly the behaviour of all other minerals during processing. 2 Spectrum Series 16 Flotation Plant Optimisation

3 CHAPTER 1 THE EUREKA MINE AN EXAMPLE OF HOW TO IDENTIFY AND SOLVE PROBLEMS IN A FLOTATION PLANT The pyrite textures vary markedly across the deposit from coarse recrystallised grains in the footwall-depleted zone to compact microcrystalline masses, spongy and colliform clots, such as melnokovite (an amorphous pyrite of colloidal origin). Ultra-fine intergrowths of pyrite with other sulfides are common, particularly with galena and arsenopyrite (Figure 1). The association of auriferous arsenopyrite with pyrite is also of significance. Process description Laboratory testing of the Eureka ore clearly demonstrated that it was possible to produce saleable copper, lead and zinc concentrates. The flow sheet developed in the laboratory was tested at pilot scale to prove that the process route selected was robust, and to produce sufficient quantities of concentrate for smelter testing. The final Eureka process flow sheet is presented in Figure 2. As the ore is mined the mine geologists classify it into three broad ore types based on texture (ie enrichment zone ore (banded), or footwall depleted zone ore (coarse grained)), and estimated pyrite content. Each ore type is crushed in batches to nominally 100 per cent passing 100 mm, in the underground jaw crusher before being trucked to the surface in 50 tonne dump trucks. Upon delivery to the run-of-mine (ROM) pad each ore type is stockpiled separately. The ore is fed onto a conveyor belt that leads to an open stockpile in specific ratios of each ore type. Apron feeders, underneath the open stockpile, feed the blended ore onto the primary mill feed conveyor at nominally 120 t/h. The primary mill is a low aspect ratio semi-autogenous grinding (SAG) mill in open circuit. The SAG mill product discharges into a common sump shared with the ball mill. The pulp is pumped from the mill discharge sump to cyclones in closed circuit with a secondary ball mill. The cyclone underflow feeds the secondary ball mill, and the cyclone overflow reports to flotation feed. The cyclone configuration is designed to produce a P80 of 75 microns. The secondary cyclone overflow feeds a sequential copper/ lead/zinc flotation circuit. Each flotation section consists of a rougher/scavenger, with the rougher concentrate reporting to the cleaner circuit. The copper cleaning is achieved without regrinding, and with only one stage of cleaning. The lead rougher concentrate feeds the first of three stages of cleaning. The lead scavenger concentrate and lead first cleaner tailing are reground and recycled back to the head of the lead rougher. The lead scavenger tailing reports to the zinc circuit feed. The zinc rougher concentrate reports to two stages of cleaning. The zinc scavenger concentrate and the zinc first cleaner tailing are reground and recycle back to the zinc rougher feed. The concentrates produced from the copper, lead and zinc flotation circuits are pumped to thickeners. The thickened concentrate is filtered. The filter cake is stockpiled before loading into rail cars for shipment to the smelter. The flotation tailing is dewatered, and used as paste backfill in the underground workings. Metallurgical performance The Eureka concentrator was commissioned in December 1995, reaching name plate throughput by July A further 18 months were required to achieve the design concentrate grades and recoveries. Typical metallurgical performance since 1998 is summarised in Table 1. FIG 1 - Photomicrographs of various galena ore textures: (A) galena replacement in pyrite matrix, like melnokovite (magnification 10); (B) galena blebs in pyrite matrix (magnification 20); (C) galena in crystal voids around pyrite (magnification 5); and (D) galena replacement in melnokovite colloform (magnification 40). (Note: The blue/grey areas are galena and the golden areas are pyrite.) Flotation Plant Optimisation Spectrum Series 16 3

4 Feed Copper Circuit Lead Circuit Zinc Circuit Cu Ro Pb Ro Pb Scav Zn Ro Zn Scav Zn Scavenger Tailing Grinding P80 = 75 microns Zn 1 st Cl Copper Cleaner Concentrate Cu Cl Pb 1 st Cl Zn 2 nd Cl Zinc 2nd Cleaner Concentrate Pb 2 nd Cl Lead Regrinding P80 = 38 microns Zinc Regrinding P80 = 38 microns Pb 3 rd Cl Lead 3rd Cleaner Concentrate FIG 2 - The Eureka Concentrator flow sheet. TABLE 1 Typical metallurgical performance of the Eureka Concentrator since Stream Wt % Grade (%) Recovery (%) Ag (ppm) Cu Pb Zn Ag Cu Pb Zn Flotation feed Cu concentrate Pb concentrate Zn concentrate Final tailing DATA ACQUISITION The first step towards a better understanding of how your plant is performing is being able to measure the plant s performance. In today s modern concentrator the process can be monitored using a multitude of sensors, however the data collected from inventory samples on a shift, daily, weekly and monthly basis, coupled with well executed metallurgical surveys can be invaluable in defining where valuable mineral losses occur and what gangue minerals are diluting the concentrate. In the first instance, as the new metallurgist you should acquaint yourself with the existing plant data. That is, review the shift mass balance data, interrogate the monthly composite data, and examine any plant surveys that have been conducted in the past. This analysis should provide some indication of where the metallurgical weaknesses lie in the concentrator. However, do not be surprised if the only data that is up-to-date and readily available are the shift mass balances. Therefore, it should be considered good practice to organise for a plant survey to be completed reasonably early in the piece so that you can quantify the metallurgical performance of each section of the plant. The shift data for the copper, lead and zinc circuits of the Eureka Concentrator appear in Figure 3 for the first half of An examination of these data suggest that with the exception of the lead and zinc concentrate grades the plant performance is somewhat unstable. The copper concentrate grade and recovery tend to fluctuate wildly, lead recoveries are highly varied, with greater than ten per cent zinc grade in the lead concentrate, and zinc recoveries are more often than not in the low to middle 80s. Your gut feeling when you look more closely at the copper, lead and zinc recoveries should tell you that they appear lower than you would expect, therefore it should be possible to improve the plant performance. But you don t know what the limiting factors are so completing a comprehensive plant survey is in order. The next item to decide is what level of detail does the survey have to go? This will obviously depend on what work has been completed previously. In this example it will be assumed that the available data is scattered and incomplete. Therefore, the objective of the survey will be to collect as much data as possible to provide you with sufficient information to describe the pulp chemistry and metallurgical performance of the plant. Ideally both sets of data can be collected in tandem, and complement each other. To add further value to your survey the collection of gas hold-up, superficial gas velocity and bubble size data will provide information about the hydrodynamics of the flotation cells. 4 Spectrum Series 16 Flotation Plant Optimisation

5 (a) Cu recovery, % (b) Pb recovery, % (c) Zn recovery, % The metallurgical survey (Chapter 2) Why don t metallurgists do surveys? The author has visited many plants around the world, and it is apparent that there is a wide spectrum of knowledge and experience. However, plants that conduct frequent, well focused surveys and have a clear understanding of their metallurgical performance, its strengths and weaknesses, are few and far between. The reasons for this are many and varied, but generally boil down to not knowing how to conduct a survey, and the fear of mass balancing! What do I have to do? Time, days Cu recovery Cu grade Time, days Pb recovery Pb grade Zn grade in Pb con The objectives of the survey(s) are to provide information about rougher/scavenger flotation performance in each of the flotation circuits, and to examine how the concentrates up grade during cleaning. In the first instance block surveys of each of the flotation sections (roughers, scavengers and cleaners) for each 1/01/98 15/01/98 29/01/98 12/02/98 26/02/98 12/03/98 26/03/98 9/04/98 23/04/98 7/05/98 21/05/98 4/06/98 18/06/98 1/01/98 15/01/98 29/01/98 12/02/98 26/02/98 12/03/98 26/03/98 9/04/98 23/04/98 7/05/98 21/05/98 4/06/98 18/06/98 1/01/98 15/01/98 29/01/98 12/02/98 26/02/98 12/03/98 26/03/98 9/04/98 23/04/98 7/05/98 21/05/98 4/06/98 18/06/98 Time, days Zn recovery Zn grade Fe grade in Zn con FIG 3 - Time series data for: (A) copper; (B) lead; and (C) zinc circuits. Cu grade, % Pb and Zn grade, % Zn and Fe grade, % product should be conducted. Ideally, a more detailed down-the-bank survey of the rougher/scavenger sections would also be included. An example of a down-the-bank survey is provided in Appendix 1. Further, to gain greater appreciation of how the circuit operates, more than one plant survey should be completed over a number of days. In fact, a good strategy to follow would be one detailed survey and several less detailed block surveys be completed to give a more balanced view of the metallurgical performance of the plant. Organisation and communication are the key to successfully completing surveys in a concentrator. In the first instance, decide on the sampling points and the type of sample to be taken. A list of samples for the Eureka concentrator is given in Table 2. It is important to note that all tailing samples are taken in duplicate to ensure sampling consistency, and are used as internal checks (note: the recovery calculation is dependent on the tailing assay). TABLE 2 The sampling points and sample type for the metallurgical survey of the Eureka flotation circuit. Sample number Process stream 1 Flotation feed (ball mill cyclone overflow) Sample type Half moon cutter 2 Copper rougher concentrate Lip sample 3 Copper rougher tailing A Dip sample 4 Copper rougher tailing B Dip sample 5 Copper cleaner concentrate Lip sample or OSA 6 Copper cleaner tailing A Dip sample 7 Copper cleaner tailing B Dip sample 8 Lead rougher concentrate Lip sample 9 Lead rougher tailing A Dip sample 10 Lead rougher tailing B Dip sample 11 Lead scavenger concentrate Lip sample 12 Lead scavenger tailing A Dip sample 13 Lead scavenger tailing B Dip sample 14 Lead first cleaner concentrate Lip sample 15 Lead first cleaner tailing A Dip sample 16 Lead first cleaner tailing B Dip sample 17 Lead second cleaner concentrate Lip sample 18 Lead second cleaner tailing A Dip sample 19 Lead second cleaner tailing B Dip sample 20 Lead third cleaner concentrate Lip sample or OSA 21 Lead third cleaner tailing A Dip sample 22 Lead third cleaner tailing B Dip sample 23 Zinc rougher concentrate Lip sample 24 Zinc rougher tailing A Dip sample 25 Zinc rougher tailing B Dip sample 26 Zinc scavenger concentrate Lip sample 27 Zinc scavenger tailing A Dip sample or OSA 28 Zinc scavenger tailing B Dip sample or OSA 29 Zinc first cleaner concentrate Lip sample 30 Zinc first cleaner tailing A Dip sample 31 Zinc first cleaner tailing B Dip sample 32 Zinc second cleaner concentrate Lip sample or OSA 33 Zinc second cleaner tailing A Dip sample 34 Zinc second cleaner tailing B Dip sample Flotation Plant Optimisation Spectrum Series 16 5

6 There are other process streams that you may consider collecting. For example, the copper rougher feed, lead rougher feed, and zinc rougher feed, just to name a few, that are redundant samples in the mass balance, but do provide valuable data for checking assays, and ensuring that the mass balanced data makes sense. With the sample list decided upon it is necessary to brief the team conducting the survey, prepare the equipment, and ensure that the plant is running in a fashion that will allow it to be surveyed. During this briefing, delegate tasks to each person taking part in the survey so that: sufficient sample buckets with lids are cleaned, weighed and labelled; the sampling equipment is checked, clean and ready for use; each person taking part in the survey knows what is expected of them; and set the ground rules for the survey (ie number of rounds over what time interval). Further, it is wise at this point to inform operations of your intentions to conduct a plant survey(s). Give then the reasons for conducting the surveys and check that the plant will be available at the time you anticipate the survey(s) will be completed. You also need to inform the chemical laboratory that you intend to submit a large number of samples from a plant survey, and you would like to have them assayed for a range of elements. The day before conducting the survey it is wise to visit the plant and inspect the flotation circuit to make sure that all those participating in the survey know where the sampling points are that they are responsible for. It is also a time when flotation cell lips can be checked for build-up and cleaned in readiness for the survey. Of equal importance during the plant inspection is to ensure that the work area is free of hazards, and is safe to work in. On the day of the survey, attend the morning production meeting to establish how the plant has been operating overnight and inform operations of your intentions to survey the plant. Once you have the all clear commence setting up for the survey, set out the buckets in the correct positions, station the sampling equipment accordingly, check the flotation cell lips and clean them again. Check again that your team is familiar with the task ahead of them. Now that you are ready, go to the control room and check on the status of the concentrator. Ensure that the feed tonnage is steady, the feed grades are steady, and the circuit has not experienced a major disturbance in the last few hours. Once you are satisfied that the plant is running smoothly you can start the survey. It is suggested that a survey of this type be conducted over a number of hours, whereby multiple rounds of samples are collected to form a composite of the sampling period. In this particular case, the survey was conducted over a three hour period, during which time four cuts from each sampling point were collected randomly. Once the metallurgical survey is completed, the samples are gathered together and taken to the laboratory. What data do I need? In the laboratory the samples are weighed (to determine the wet weight), filtered, dried, weighed, prepped and submitted for assay. A summary of this data is given in Table 3. The wet and dry weights are used to determine the per cent solids of each sample, and calculate a water balance. In terms of assays, apart from those pertaining to the valuable minerals you are separating from the gangue (in Eureka s case copper, lead, zinc, silver and gold), it is also wise to assay for other elements. For example, iron and sulfur, to aid in performing mineral conversions so that information about the sulfide gangue can be extracted from the elemental assays, and deleterious trace elements like arsenic, antimony, bismuth, mercury and/or cadmium. Knowing how these penalty elements deport to the concentrate can lead to a way of minimising their recovery, which translates to a potential decrease in smelter penalties. Other data that can be useful when analysing the plant survey mass balance are: the throughput at the time of the survey, reagent additions and other plant operating parameters (ie air flow rates and pulp levels), OSA readings, and information about the ore being treated. In the context of a one off survey some of these pieces of information may not be of great value. However, when the analysis is extended to include other surveys on other ore blends, circuit configurations, reagent suites, these data provide a vital link in the comparison. How do I analyse the data collected (Chapter 3)? Once the assays have returned from the chemical laboratory the fun starts! You will be confronted with a list of numbers not unlike that presented in Table 4. Initially, this may be a little daunting, but once you have organised the data into a logical format, and brought order to the chaos you will be in a position to mass balance this survey. At the beginning of the mass balancing process it is necessary to make sure that you have received all the assays and that they are in good order. That is, do the tailing assays match? Do the concentrate assays follow a logical trend (for example, the rougher concentrate grade is higher than the scavenger concentrate, the cleaner concentrate grades increase as you pass from the first to the third cleaner)? Once you have satisfied yourself that the assays are good you can start the mass balancing process. Remember, if a water balance of the flotation circuit is required this can be achieved using the per cent solid values for each process stream. That is, you treat the per cent solids as an assay, and include it in your mass balance calculations. There are numerous mass balancing packages available, but the basic steps involved in completing the mass balance are the same for all. Unfortunately, it is not a case of plugging the numbers in and pressing GO, as invariably this leads to process streams having zero flow! The basic steps to following when mass balancing a survey are given below. A more detailed explanation is given in Chapter 3: Mass Balancing Flotation Data by Rob Morrison. Step 1 Determine what the plant throughput was when the survey was completed. If the feed tonnage is not available, assign the fresh flotation feed a value of 100 per cent. It is further assumed that you have a high level of confidence in this value. Step 2 Balance the outer circuit. That is, complete a mass balance of the feed, final concentrate and tailing for the copper, lead and zinc circuits (Figure 4). This balance will provide estimates of the tonnes of copper, lead and zinc concentrates produced. These values can be used in subsequent balances to estimate tonnages of the internal process streams within rougher, scavenger and cleaner circuits. Assign each process stream a number, and identify each of the nodes. So, the process streams are: 1. flotation feed, 6 Spectrum Series 16 Flotation Plant Optimisation

7 TABLE 3 Raw data from the metallurgical survey of the Eureka Concentrator. Sample Process stream Sample weight (g) % Solids number Gross wet Bucket Cutter Net wet Dry 1 Flotation feed Copper rougher concentrate Copper rougher tailing A Copper rougher tailing B Copper cleaner concentrate Copper cleaner tailing A Copper cleaner tailing B Lead rougher concentrate Lead rougher tailing A Lead rougher tailing B Lead scavenger concentrate Lead scavenger tailing A Lead scavenger tailing B Lead first cleaner concentrate Lead first cleaner tailing A Lead first cleaner tailing B Lead second cleaner concentrate Lead second cleaner tailing A Lead second cleaner tailing B Lead third cleaner concentrate Lead third cleaner tailing A Lead third cleaner tailing B Zinc rougher concentrate Zinc rougher tailing A Zinc rougher tailing B Zinc scavenger concentrate Zinc scavenger tailing A Zinc scavenger tailing B Zinc first cleaner concentrate Zinc first cleaner tailing A Zinc first cleaner tailing B Zinc second cleaner concentrate Zinc second cleaner tailing A Zinc second cleaner tailing B Cu scav tailing 5. Pb scav tailing 1. Flotation feed Cu Circuit Pb Circuit Zn Circuit (1) (2) (3) 7. Zn Scan Tail (Final Tail) 2. Cu Clnr Con (Final Cu Con) 4. Pb 3rd Clnr Con 6. Zn 2nd Clnr Con (Final Lead Con) (Final Zn Con) FIG 4 - The outer circuit. 2. copper cleaner concentrate, 3. copper rougher tailing, 4. lead third cleaner concentrate, 5. lead scavenger tailing, 6. zinc second cleaner concentrate, and 7. zinc scavenger tailing. Flotation Plant Optimisation Spectrum Series 16 7

8 The nodes are: 1. flotation feed = Cu cleaner concentrate + Cu rougher tailing (or,1=2+3); 2. Cu rougher tailing = Pb third cleaner concentrate + Pb scavenger tailing (or, 3 = 4 + 5); and 3. Pb scavenger tailing = Zn second cleaner concentrate + Zn scavenger tailing (or, 5 = 6 + 7). In this case, at the time of surveying the plant, throughput was 120 t/h. An examination of the tailing assays reveals that the assays are reasonably similar and in the expected range (indicating that the sampling was of a good standard). Therefore, taking an average of the two tailing sample assays is acceptable. However, if one assay was considerably higher than the other (for example, the copper cleaner tailing A, in Table 4), one suspects that this dip sample has been contaminated with froth during collection, and this assay would be rejected from the data set. It is likely that having this sample reassayed would only confirm that the sample was contaminated during collection. However, care must be taken when rejecting assays because it may not always the case. This sample has a similar assay to that obtained for the copper rougher concentrate, so another possibility may be that samples have been wrongly labelled. Having sorted the data, identified the process streams, nodes and feed tonnage, the numbers can be plugged into your mass balancing program. In this case MATBAL, using a Monte Carlo simulation, was employed. The resultant mass balance is provided in Table 5, which includes a sigma value. If sigma is less than five per cent, then the data are considered to be good. Step 3 The next step in the mass balance is to balance the internal, or inner circuits within the copper, lead and zinc flotation circuits. TABLE 4 Raw assay data from the metallurgical survey of the Eureka Concentrator. Sample Process stream % Solids Raw assays number Ag (ppm) Cu (%) Pb (%) Zn (%) Fe (%) 1 Flotation Feed Copper rougher concentrate Copper rougher tailing A Copper rougher tailing B Copper cleaner concentrate Copper cleaner tailing A Copper cleaner tailing B Lead rougher concentrate Lead rougher tailing A Lead rougher tailing B Lead scavenger concentrate Lead scavenger tailing A Lead scavenger tailing B Lead first cleaner concentrate Lead first cleaner tailing A Lead first cleaner tailing B Lead second cleaner concentrate Lead second cleaner tailing A Lead second cleaner tailing B Lead third cleaner concentrate Lead third cleaner tailing A Lead third cleaner tailing B Zinc rougher concentrate Zinc rougher tailing A Zinc rougher tailing B Zinc scavenger concentrate Zinc scavenger tailing A Zinc scavenger tailing B Zinc first cleaner concentrate Zinc first cleaner tailing A Zinc first cleaner tailing B Zinc second cleaner concentrate Zinc second cleaner tailing A Zinc second cleaner tailing B Spectrum Series 16 Flotation Plant Optimisation

9 TABLE 5 Adjusted assays for the outer circuit mass balance. No Stream t/h Adjusted assays (%) Ag (ppm) Cu Pb Zn Fe 1 Flotation feed Cu cleaner concentrate Cu rougher tailing Pb 3rd cleaner concentrate Pb scavenger tailing Zn 2nd cleaner concentrate Zn scavenger tailing Flotation feed Cu rougher (1) 3. Cu rougher tailing 5. Cu cleaner tailing 2. Cu rougher concentrate Cu cleaner (2) 4. Cu cleaner concentrate (Final Cu Con) FIG 5 - The copper circuit inner mass balance. These internal balances are broken down into bite size pieces to simplify the balancing process, and generate estimates of tonnages that can be used in subsequent inner circuit balances. The copper circuit (Figure 5) is comparatively easy to balance using the tonnage estimates for the flotation feed and copper cleaner concentrate generated in the outer circuit mass balance. In this case the process streams are: 1. flotation feed ( t/h), 2. copper rougher concentrate, 3. copper rougher tailing, 4. copper cleaner concentrate (1.21 t/h), and 5. copper cleaner tailing. The nodes are: 1. flotation feed + Cu cleaner tailing = Cu rougher concentrate + Cu rougher tailing (or, = 2 + 3); and 2. Cu rougher concentrate = Cu cleaner concentrate + Cu cleaner tailing (or, 2 = 4 + 5). The resultant mass balance assays are provided in Table 6. A similar approach is adopted for the lead circuit (Figure 6) where the circuit is balanced in four parts: 1. the lead second and third cleaners, 2. the lead first cleaner, 3. the lead scavenger, and 4. the lead rougher/cleaner circuit. While this arrangement may appear to be counter intuitive, the reasons for moving backwards through the lead circuit are driven by the need to estimate tonnage figures for the recycle streams. In Balance 1 (the lead second and third cleaners), by using the third cleaner concentrate estimated tonnage generated in the outer mass balance in Step 2 it is possible to estimate the tonnage for the lead first cleaner concentrate and the lead second cleaner tailing. Using these two values, it is then possible to mass balance the lead first cleaner. This will give tonnage estimates for the lead rougher concentrate and the lead first cleaner tailing. Balance 3 uses the tonnage estimate for the lead scavenger tailing determined in the outer balance in Step 2. The mass balance of the lead scavengers yields an estimate of the tonnage for the lead scavenger concentrate. Once these three inner mass balances are complete it is possible to fix certain tonnages (ie copper rougher tailing, lead scavenger tailing, lead first, second and third cleaner concentrates), and complete a mass balance of the lead circuit. The process streams used for this balance are: 1. copper rougher tailing, 2. lead rougher concentrate, 3. lead rougher tailing, 4. lead scavenger concentrate, 5. lead scavenger tailing, 6. lead first cleaner concentrate, 7. lead first cleaner tailing, 8. lead second cleaner concentrate, 9. lead second cleaner tailing, 10. lead third cleaner concentrate, and 11. lead third cleaner tailing. Flotation Plant Optimisation Spectrum Series 16 9

10 TABLE 6 Adjusted assays for the copper circuit inner mass balance. No Stream t/h Adjusted assays (%) Ag (ppm) Cu Pb Zn Fe 1 Flotation feed Cu cleaner con Cu rougher tailing Cu cleaner con Cu cleaner tailing Pb rougher feed Balance 3 1. Cu rougher tailing Pb rougher (1) 3. Pb rougher tailing Pb scavenger (2) 5. Pb scavenger tailing Balance 2 Pb 1 st cleaner feed 2. Pb rougher concentrate Pb 1 st cleaner (3) 7. Pb 1 st cleaner tailing 4. Pb scavenger concentrate 6. Pb 1 st cleaner concentrate Pb 2 nd cleaner feed Pb 2 nd cleaner (4) 9. Pb 2 nd cleaner tailing 8. Pb 2 nd cleaner concentrate Balance 1 Pb 3rd cleaner feed Pb 3 rd cleaner (5) 11.Pb3 rd cleaner tailing 10. Pb 3 rd cleaner concentrate (Pb final con) FIG 6 - The inner mass balances for the lead circuit. And, the nodes are: 1. Cu rougher tailing + Pb scavenger concentrate + Pb first cleaner tailing = Pb rougher concentrate + Pb rougher tailing (or, = 3 + 3); 2. Pb rougher tailing = Pb scavenger concentrate + Pb scavenger tailing (or, 3 = 4 + 5); 3. Pb rougher concentrate + Pb second cleaner tailing = Pb first cleaner concentrate + Pb first cleaner tailing (or, =6+7); 4. Pb first cleaner concentrate + Pb third cleaner tailing = Pb second cleaner concentrate + Pb second cleaner tailing (or, 6+11=8+9);and 5. Pb second cleaner concentrate = Pb third cleaner concentrate + Pb third cleaner tailing (or, 8 = ). The mass balanced assays for the lead circuit are given in Table 7. The same approach is employed when mass balancing the inner circuits for zinc flotation (Figure 7). The first balance (Balance 1) examines the zinc first and second cleaner, while the second mass balancing (Balance 2) step involves the zinc scavenger circuit. When these two internal mass balances are complete, it is possible to mass balance the zinc circuit while fixing certain flows. The process streams used for this balance are: 1. lead scavenger tailing, 2. zinc rougher concentrate, 3. zinc rougher tailing, 4. zinc scavenger concentrate, 5. zinc scavenger tailing, 6. zinc first cleaner concentrate, 7. zinc first cleaner tailing, 8. zinc second cleaner concentrate, and 9. zinc second cleaner tailing. And, the nodes are: 1. Pb scavenger tailing + Zn scavenger concentrate + Zn first cleaner tailing = Zn rougher concentrate + Zn rougher tailing (or, = 3 + 3); 10 Spectrum Series 16 Flotation Plant Optimisation

11 TABLE 7 Adjusted assays for the inner lead circuit mass balance. No Stream t/h Adjusted assays (%) Ag Cu Pb Zn Fe 1 Cu rougher tailing Pb rougher con Pb rougher tailing Pb scavenger con Pb scavenger tailing Pb 1 st cleaner con Pb 1 st cleaner tailing Pb 2 nd cleaner con Pb 2 nd cleaner tailing Pb 3 rd cleaner con Pb 3 rd cleaner tailing Zn rougher feed Balance 2 1. Pb rougher tailing Zn rougher (1) 3. Zn rougher tailing Zn scavenger (2) 5. Zn scavenger tailing 2. Zn rougher concentrate 4. Zn scavenger concentrate Zn 1 st cleaner feed Zn 1 st cleaner (3) 7. Zn 1 st cleaner tailing 6. Zn 1 st cleaner concentrate Zn 2 nd cleaner feed Zn 2 nd cleaner (4) 9. Zn 2 nd cleaner tailing Balance 1 8. Zn 2 nd cleaner concentrate (Zn final con) FIG 7 - The inner mass balances for the zinc circuit. 2. Zn rougher tailing = Zn scavenger concentrate + Zn scavenger tailing (or, 3 = 4 + 5); 3. Zn rougher concentrate + Zn second cleaner tailing = Zn first cleaner concentrate + Zn first cleaner tailing (or, =6+7);and 4. Zn first cleaner concentrate = Zn second cleaner concentrate + Zn second cleaner tailing (or, 6 = 8 + 9). The adjusted assays for the zinc circuit are provided in Table 8. Step 4 With the inner mass balances complete it is now possible to mass balance the whole circuit. The resultant mass balance is given in Table 9. When reviewing your mass balance it is always a good idea to check that the internal workings of the circuit are balanced. For example, in the copper circuit, the feed to the copper rougher is actually the fresh flotation feed plus the copper cleaner tailing. The sum of these recovery values should be the same as the copper rougher concentrate plus the tailing. That is, for copper: R flotation feed + R Cu cleaner tailing = R Cu rougher con + R Cu rougher tailing = = The balance holds, so we can have confidence that the mass balancing calculations have been completed correctly. What does it mean? (Chapter 2) With the mass balance completed it is time to analyse the data and determine what it means. From this analysis it is possible to establish what and where the weaknesses are in the circuit, and Flotation Plant Optimisation Spectrum Series 16 11

12 TABLE 8 Adjusted assays for the inner zinc circuit mass balance. No Stream t/h Adjusted assays (%) Ag Cu Pb Zn Fe 1 Pb scavenger tailing Zn rougher con Zn rougher tailing Zn scavenger con Zn scavenger tailing Zn 1st cleaner con Zn 1st cleaner tailing Zn 2nd cleaner con Zn 2nd cleaner tailing TABLE 9 Mass balance of copper, lead and zinc circuits of the Eureka Concentrator. No Stream t/h Cu (%) Pb (%) Zn (%) Fe (%) Grade Recovery Grade Recovery Grade Recovery Grade Recovery 1 Flotation feed Cu rougher con Cu rougher tailing Cu cleaner con Cu cleaner tailing Pb rougher con Pb rougher tailing Pb scav con Pb scav tailing Pb 1st cleaner con Pb 1st cleaner tailing Pb 2nd cleaner con Pb 2nd cleaner tailing Pb 3rd cleaner con Pb 3rd cleaner tailing Zn rougher con Zn rougher tailing Zn scav con Zn scav tailing Zn 1st cleaner con Zn 1st cleaner tailing Zn 2nd cleaner con Zn 2nd cleaner tailing determine what additional tests are required to give more definition to the data. As the mass balance was completed using elemental assays it is now possible to use this data to calculate what is happening on a mineral basis. That is, the mass balanced elemental assays can be converted to minerals by making certain assumptions about the elemental composition of the various minerals of interest within your system. Appendix 2 provides an example of these element to mineral calculations. The conversion to minerals allows you to examine the flotation behaviour of the iron sulfide and non-sulfide gangue species. Combining the calculated non-sulfide gangue mass balanced data with the water recovery data it is possible to gain an appreciation of how these minerals are being recovered (ie entrainment). Chapter 2: Existing Methods for Process Analysis by Bill Johnson provides a detailed description of how to analyse and interpret your plant survey data. The copper grade/recovery curve for the copper circuit appears in Figure 8. This data, in conjunction with Table 9, indicates that there is a small circulating load (about 12 per cent) of copper returning to the rougher feed via the copper cleaner tailing. This is not a major concern. However, the poor selectivity for chalcopyrite against galena and sphalerite during copper roughing (ie the high lead and zinc grades) is an issue, and requires further investigation. Figure 9 contains the lead grade/recovery curve for the Eureka circuit. It is immediately obvious that there is a large circulating load of galena within the lead circuit centred around the lead first 12 Spectrum Series 16 Flotation Plant Optimisation

13 Cu cleaner concentrate Cu grade, % Cu rougher concentrate Cu rougher feed 5.0 Flotation feed Cu recovery, % FIG 8 - The copper grade/recovery curve for the copper circuit within the Eureka Concentrator. 7 6 Pb 3 rd cleaner concentrate 5 Pb 2 nd cleaner concentrate Pb 2 nd cleaner feed Pb grade, % Pb 1 st cleaner concentrate Pb rougher concentrate Pb 1 st cleaner feed 1 Cu rougher tailing Pb rougher feed Flotation feed Pb recovery, % FIG 9 - The lead grade/recovery curve for the lead circuit within the Eureka Concentrator. 7 6 nd st 5 Zn grade, % 4 3 Zn rougher concentrate st 2 1 Pb rougher tailing Zn rougher feed Cu rougher tailing Flotation feed Zn recovery, % FIG 10 - The zinc grade/recovery curve for the zinc circuit within the Eureka Concentrator. cleaner bank. A closer examination of the lead circuit mass balanced data in Table 9 reveals that accompanying the very large circulating loads of galena is a large circulating load of sphalerite. This would suggest that there may be liberation issues within this part of the circuit. Again, this warrants further investigation. The zinc grade/recovery curve (Figure 10) also reveals that there are circulating loads of zinc around the zinc first cleaner. While these loads are not as severe as those noted in the lead circuit, undoubtedly they are having an impact on the zinc metallurgy. Consulting Table 9, it was noted that there may be an issue with iron, particularly around the rougher/scavenger/first cleaner circuit. Further investigation is again needed to define the problem. It is apparent that there are opportunities for improvement in all three circuits. Equally, it is obvious that making improvements in Flotation Plant Optimisation Spectrum Series 16 13

14 the copper circuit will have ramifications on both the lead and zinc circuits. And this makes for a good rule of thumb: start at the front of the circuit and work downstream. The test programs need to be prioritised so that resources can be focused on the project that has the greatest potential metallurgical (and financial) benefit to the plant. The survey data indicates that the lead circuit is very unstable with high circulating loads, and could be impeding both the lead and zinc circuit performance. It is recommended that further work be completed to determine the recovery-by-size and liberation characteristics through the lead circuit to see where improvements may be made. Sample identification and storage At the risk of stating the obvious, having a workable sample identification and storage system will make life easier. A lack of attention to detail in this area will lead to mistakes in the assay laboratory with poor labelling, and can jeopardise the ability to locate samples for check assaying or for further testing (for example, sizing or mineralogical examination). Therefore, it is necessary to set up a system of identification that is both simple and effective. For example, all surveys are labelled with an S and numbered consecutively, with each sample in that survey given a number. So, if the survey described in this chapter is the tenth survey completed in the Eureka Concentrator its identification code would be S10/1 to S10/34, where the sample numbers 1 to 34 correspond to the sample numbers listed in Table 2. The next survey would be S11, and so on. Flotation tests could be identified according to the operator s initials, for example, CG351/1 to CG351/5, which would be read as flotation test 351 completed by CG with five test products. Once a numbering system has been put in place it makes it easy to develop a storage system. In developing your storage system you must set some rules regarding the length of time you are going to keep a sample, and then allow the laboratory technicians time, periodically, to maintain the storage facility. For example, it is wise to keep flotation test produces for nominally three months and plant surveys for up to 12 months. It is also wise have a clean up every three months to dispose of samples that have passed their storage date. The pulp chemistry survey (Chapter 6) Concurrent to the metallurgical survey, pulp chemical data was collected from the plant to determine the pulp chemical conditions. What do I have to do? The pulp chemical survey involves collecting Eh, ph, dissolved oxygen, and temperature data from the following process streams: SAG mill discharge, cyclone underflow, ball mill discharge, cyclone overflow, copper circuit feed, lead circuit feed, zinc circuit feed, and final tailings. To complete a pulp chemical survey, a sample of slurry is cut from the process stream of interest, and poured into a small beaker. The sample is then stirred gently with the probes for nominally two minutes until equilibrium readings are obtained. The Eh, ph, dissolved oxygen, and temperature data are logged on a data logger. The logged data can then be downloaded from the data logger to a laptop computer where it is able to be manipulated. All of the probes should be checked to ensure they are clean and in good working order, and it is imperative that they are calibrated before use. The ph probe should be calibrated using ph buffer solutions seven and ten, if this is the range expected in the plant. Alternative buffer solutions should be used if the pulp ph is outside this range. The Eh probe should be calibrated, for example, using Zobell solution (1:1 solution of Part A and B = 231 mv at 24 C), the dissolved oxygen probe calibrated in a 0.2 g/l solution of sodium sulfite for the zero calibration, and air. The temperature probe can be calibrated with the aid of a thermometer, using iced and heated water to give a two point calibration. To complete the data set, EDTA extractions should be completed on the same process streams as the pulp chemistry. For the Eureka survey, each stream was cut and the sample poured into a small wide mouth, screw top sample bottle. The samples were taken back to the laboratory, and the wet weight recorded. The EDTA extraction procedure used was: stir the pulp sample with a 25 ml syringe to produce homogeneous slurry; syringe a 25 ml aliquot of slurry from the sample bottle and weigh; inject the contents of the syringe into a 400 ml beaker containing 250 ml of three per cent (by weight) EDTA solution, ph modified to 7.5 with sodium hydroxide; thoroughly mix the slurry and EDTA solution using a magnetic stirrer, for five minutes; filter the slurry using a 0.2 micron millipore filter; and submit the filtered EDTA solution for assay. The remainder of the pulp sample was pressure filtered, and the solids dried. The dry solids were weighed and submitted for assay. What data do I need? The pulp chemical data (ph, Eh, dissolved oxygen and temperature) are stored on a data logger. These data now need to be downloaded into Excel, massaged and put into a logical format for analysis and interpretation. The samples for EDTA extraction (solids and liquids) are prepared and submitted for assay. Usually these samples are assayed for the base metals of interest; in the case of the Eureka Concentrator, the solids and liquids were assayed for copper, lead, zinc and iron. As with the metallurgical surveys, other data that can be useful when analysing the EDTA survey are: the throughput at the time of the survey, reagent additions and other plant operating parameters (ie air flow rates and pulp levels), OSA readings, and information about the ore being treated. In the context of a one off survey some of these pieces of information may not be of great value. However, when the analysis is extended to include other surveys on other ore blends, circuit configurations and reagent suites, these data provide a vital link in the comparison. It can be beneficial to collect process water samples routinely to determine the free ions in solution (ie base metal ions (copper, lead, zinc, iron), calcium, magnesium, sulfate and chloride). 14 Spectrum Series 16 Flotation Plant Optimisation

15 How do I analyse the data? With the exception of the Eh data the other pulp chemical measurements can be read directly from the measured data. The Eh should be adjusted so that it is referenced against the standard hydrogen electrode (SHE). Chapter 6: Chemical Measurements During Plant Surveys and Their Interpretation by Stephen Grano provides an explanation of how to manipulate and analyse the data you have collected. One method of analysing the EDTA data is given by Rumball and Richmond (1996), who developed a simple relationship for calculating the percentage of oxidised mineral present in a pulp from EDTA extraction data (Equation 1): Mass of M in EDTA solution % EDTA extractable M = 100 (1) Mass of M in solids where: M is the metal ion under investigation The data is generally presented graphically with the pulp chemical parameter on the y-axis and the circuit position on the x-axis. The process streams are set to mimic the normal flow of the slurry through the circuit. In this case: 1. SAG mill discharge, 2. cyclone underflow, 3. ball mill discharge, 4. cyclone overflow, 5. copper rougher feed, 6. lead rougher feed, 7. zinc rougher feed, and 8. final tailing. When investigating the pulp chemistry within your circuit often the urge is to sample every stream in the concentrator. While this may be a good idea initially to get an idea of the variations between process streams, it soon becomes apparent that some of this data is redundant. For example, concentrate streams usually have high dissolved oxygen contents and very oxidising pulp potentials because the froth in the concentrate contains significant amounts of air. Therefore, when conducting a pulp chemistry survey of the primary grinding/rougher flotation circuit measuring the pulp chemistry of the rougher concentrate can produce numbers that skew the analysis. However, if you are examining the pulp chemistry of a regrind/cleaner circuit, it is normal to collect a sample of the fresh concentrate that feeds the regrinding section. It is also good policy when completing surface analysis comparing pairs of streams (ie rougher concentrate and rougher tailing), to collect the pulp chemistry of the two process streams of interest. What does it mean? The ph, Eh, dissolved oxygen, and temperature data should be plotted in such a way to represent the pulp flow profile through the circuit to assist with the analysis and interpretation of the data. The profiles through the Eureka circuit are displayed in Figures 11 to 14, respectively. The ph profile (Figure 11) indicated that grinding occurs at natural ph (in the range 8.0 to 8.5). The slight reduction in ph in the ball mill discharge maybe attributed to pyrite oxidation. Sodium metabisulfite (SMBS) was added to the copper rougher feed, to depress galena during copper flotation. The addition of SMBS resulted in the ph being reduced to approximately 6.0. The ph was then increased to 8.0 for galena flotation and 11.5 sphalerite flotation thought the addition of lime. Figure 12 contains the Eh profile through the circuit. The Eh shifted to slightly less oxidising pulp potentials as the pulp flowed from the SAG mill through the ball mill, and became more oxidising during flotation where air is used as the flotation gas. The dissolved oxygen profile (Figure 6) through the circuit indicated that the oxygen content of the pulp was negligible during both grinding and flotation, registering zero on the meter. It was not until the zinc flotation stage that the dissolved oxygen content of the pulp was increased to 4.5 ppm in the final tailing. These data suggest that the ore is very reactive and continues to consume oxygen throughout the process. The pulp temperature ranged 33 to 35 C across most of the circuit (Figure 14). The spike in the pulp temperature in the ball mill discharge can be attributed to part of the addition grinding energy being dissipated as heat. The Eh-pH data for the grinding and flotation circuits of the Eureka Concentrator have been plotted in Figure 15 to determine where the reactions are occurring. From the Nernst Equation 2 there is a dependence of redox potential on ph: E = E + log n 10 α α Reactants Products (2) ph SAG mill discharge Cyclone underflow Ball mill discharge Cyclone overflow Cu rougher feed Pb rougher feed Circuit position Zn rougher feed Zn rougher tailing FIG 11 - The ph profile through the grinding and flotation circuits of the Eureka Concentrator. Flotation Plant Optimisation Spectrum Series 16 15

16 20 16 Eh, mv (SHE) SAG mill discharge Cyclone underflow Ball mill discharge Cyclone overflow Cu rougher feed Pb rougher feed Circuit position Zn rougher feed Zn rougher tailing FIG 12 - The Eh profile through the grinding and flotation circuits of the Eureka Concentrator DO, ppm SAG mill discharge Cyclone underflow Ball mill discharge Cyclone overflow Cu rougher feed Pb rougher feed Circuit position Zn rougher feed Zn rougher tailing FIG 13 - Dissolved oxygen profile through the grinding and flotation circuits of the Eureka Concentrator Temperature, o C SAG mill discharge Cyclone underflow Ball mill discharge Cyclone overflow Cu rougher feed Pb rougher feed Circuit position Zn rougher feed Zn rougher tailing FIG 14 - Temperature profile through the grinding and flotation circuits of the Eureka Concentrator. Applying the Nernst equation to water results in a Pourbaix diagram that describes three domains, separated by lines of equilibria. The upper most of these is the water-oxygen line (Equation 3), above which water decomposes and oxygen is evolved, and below which water is stable: E = log p pH (3) 0 10 o 2 2 This can be simplified further (Johnson, 1988; Natarajan and Iwasaki, 1973) for an oxygenated aqueous solution with no well defined redox couples to (Equation 4): 16 Spectrum Series 16 Flotation Plant Optimisation

17 E0 2 = ph (4) In broad terms, if the changes in Eh and ph result in a line parallel to the water-oxygen line this means that water equilibria is being maintained. That is, any change in Eh is directly proportional to a change in ph with a similar relationship to that expressed in Equation 4. If the changes in Eh and ph result in a line that is perpendicular to the water-oxygen line then the evidence suggests that oxidative reactions are occurring. Figure 15 shows that the Eh-pH lines between points 1 to 4 are perpendicular to the water-oxygen line. This indicates that oxidative reactions are occurring in the grinding circuit. It is likely that these oxidative reactions are corrosion of the grinding media and oxidation of the sulfide minerals. As the ph is decreased across the ball mill it is suggested that pyrite oxidation (an acidic reaction) may be one of the dominant reactions. The changes in the Eh-pH curve between Points 4 and 5, 5 and 6, and 6 and 7 can be attributed to the addition of reagents that alter the ph of the system. During copper flotation it is the addition of SMBS, while in the lead and zinc circuits it is the addition of lime. The EDTA extractable copper, lead, zinc and iron data are presented in Figure 16. The EDTA extractable copper profile (Figure 9) suggested that the percentage of oxidised chalcopyrite remained negligible throughout the grinding circuit. The per cent EDTA extractable copper increased during the copper flotation step to approximately 2.5 per cent and this increases to 17 per cent in the zinc rougher feed, which can be attributed to the addition of copper sulfate for sphalerite activation. The first observation to be made is that the percentage of EDTA extractable lead is at least an order of magnitude greater than the values reported for zinc and iron. The percentage of EDTA extractable lead is higher as galena is a reactive mineral when in contact with other sulfide minerals, particularly pyrite. The EDTA extractable lead profile shows that the percentage of oxidised galena remained approximately constant through the grinding circuit, with values of around 1.0 per cent. The per cent EDTA extractable lead increased in the cyclone overflow, and remains reasonably constant through the copper circuit. After the lead flotation stage the lead scavenger tailing per cent EDTA extractable lead was 17 per cent, and then increased to almost 40 per cent after zinc flotation. These data suggest that the lead species that remain in the lead scavenger tailing are more heavily oxidised. The EDTA extractable zinc profile exhibits a very similar trend to that observed for lead. That is, through the grinding circuit the percentage EDTA extractable zinc remained approximately constant, with values of around 0.1 per cent. This indicated that sphalerite oxidation was largely unchanged through this circuit Eh, mv (SHE) SAG mill discharge; 2 2. Cyclone underflow; Ball mill discharge; 4. Cyclone overflow; 7 5. Cu rougher feed; Pb rougher feed; 7. Zn rougher feed; and 8. Final tailing ph 4 FIG 15 - The Eh-pH curve for the grinding and flotation circuits of the Eureka Concentrator. EDTA extractable Cu and Pb, % SAG mill discharge Cyclone underflow Ball mill discharge Cyclone overflow Cu rougher feed Pb rougher feed Circuit position Cu Pb Zn Fe Zn rougher feed Final tailing EDTA extractable Zn and Fe, % FIG 16 - The EDTA extractable copper, lead, zinc and iron profiles through the grinding and flotation circuits of the Eureka Concentrator. Flotation Plant Optimisation Spectrum Series 16 17

18 There was an increase in the per cent EDTA extractable zinc during the copper and lead flotation circuits (ie from 0.13 to 0.37 per cent) and then a significant increase after the zinc flotation circuit (to 1.0 per cent). This increase indicated that the zinc species that remained in the zinc scavenger tailing were more heavily oxidised. The EDTA extractable iron profile gives the best indication of the impact of grinding media corrosion on the system. The EDTA extractable iron through primary grinding ranged from 5 to 0.16 per cent, and then increased to 0.30 per cent in the cyclone overflow. That is, the pulp entering the flotation circuit contains elevated levels of EDTA extractable iron, presumably after contact with the forged grinding media. Interestingly, the levels of EDTA extractable iron decrease through the flotation circuit. This is probably due to the continuing oxidation of the iron species to higher level iron oxides, which are not soluble in EDTA. Summary of data acquisition The metallurgical survey suggests that there are a number of opportunities for improving the metallurgical performance of the Eureka Concentrator. It is suspected that these may be liberation related, and further data is required to identify exactly what the liberation characteristics are. The data strongly suggests that the first priority should be improving the lead flotation circuit. The pulp chemistry suggests that the ore is reasonably reactive, particularly during grinding, and consideration should be given to improve this aspect of plant performance. However, this should not be rectified until the liberation issues have been resolved. PROBLEM DEFINITION From the metallurgical survey the circulating load observed in the lead rougher/lead first cleaner circuit were observed to be extremely high (Table 10), for both lead and zinc. In fact, the copper scavenger tailing contributed only 15.4 and 28.6 per cent of the lead and zinc units, respectively, to the lead rougher feed. The recycle from the lead first cleaner tailing contributed by far the most lead and zinc to the lead rougher feed (81.9 and 64.7 per cent, respectively). Recovery by size (Chapter 2) The mass balanced data gives you information about the grades and recoveries in the circuit. The data also provides information about the circulating loads. However, to gain a greater appreciation for where problems occur and their magnitude, it is advisable that samples from selected process streams be sized, and each size fraction assayed. By mass balancing the size fractions, the performance of each size fraction can be assessed. An examination of Table 9 and Figure 9 indicates that the lead rougher/first cleaner section of the plant has a large circulating load of galena and sphalerite. It is likely that this large circulating load produces instability within the circuit, and is probably due to composite particles. However, at this stage you are only guessing. You need to gather solid data that tells you which size fractions are being rejected from the circuit, and what their mineralogical characteristic is. Therefore, the first step in this analysis is to examine the recovery-by-size around the lead rougher feed. What do I have to do? When you conducted the plant survey you may have had every intention to have the samples sized so that you can complete a recovery-by-size analysis. However, before having your metallurgical technicians launch into a large body of work sizing every sample collected during the survey it is best to mass balance the plant survey. Sizing samples prior to completing the mass balance may waste time, resources and money if the survey does not mass balance easily (ie poor sampling). Once you have established that the mass balance is good, you need to decide if completing a recovery-by-size analysis is warranted, and if it is, what samples you would like to have sized. It is not always necessary to size every sample in the survey. The sample selection will depend on what the survey reveals about plant performance. For example, sizing the concentrate and tailing from a section will show which size fractions of the valuable species are misbehaving (ie not being recovered efficiently), and which size fractions of the gangue species are being recovered. Sometimes completing recovery-by-size analysis on a downthe-bank survey can add value because it allows you to determine where size fractions are recovered in the circuit, and can be used to determine the kinetics of various species on a size basis. With these decisions made you need to retrieve the samples from storage, ensure that you have sufficient sample to complete a sizing (generally 200 grams is sufficient), and determine what sizes you require. If you need to obtain size fractions below 38 microns you will need to use a cyclosizer, which will give you six more size fractions. However, if cyclosizer is used in concert with a precyclone and a centrifuge the number of size fractions obtained can be extended to seven. What data do I need? With the sizing completed you will require the mass collected in each size fraction. If the sizing has been restricted to a simple sieve analysis, then you will need to determine how much mass you have in each size fraction to ensure that you have sufficient for assay (usually 5 grams is more than enough). If you do not have enough sample in each size fraction for an assay you need to either complete another sizing on this sample, or you combine size fractions to yield enough mass. However, if you do combine size fractions you must apply this across all of the samples within this data set. Not to do so will make it impossible to complete the analysis. That is, if you were required to combine the +300, +212 and +150 micron fractions in the feed sample, then you will need to do the same for all other samples in the suite of samples for this survey. When it comes to sizing the subsieve fractions using a precyclone/cyclosizer/centrifuge combination, you will need to know the water temperature, the elutriation time, the water flow TABLE 10 Mass balanced data for the lead rougher feed, with respect to flotation feed. Note: Both the lead scavenger concentrate and the lead first cleaner tailing are recycled back to the head of the lead rougher. Stream t/h Grade (%) Recovery (%) Cu Pb Zn Fe Cu Pb Zn Fe Cu scav tailing Pb 1st cleaner tailing Pb scav concentrate Pb rougher feed Spectrum Series 16 Flotation Plant Optimisation

19 rate and the specific gravity of the mineral being separated. With these variables known using the cyclosizer manual (Warman International Limited, 1991) the cut size for each cyclone can be calculated. That is, for quartz the cyclone cut sizes for the cyclosizer are: C1 = 44 microns, C2 = 33 microns, C3 = 23 microns, C4 = 15 microns, and C5 = 11 microns. The precyclone generally cuts at about 7 microns. To convert these cut sizes to values that are more representative of minerals such as chalcopyrite, galena, sphalerite and pyrite, then the cut size for quartz must be multiplied by the overall correction factor: f = f T f SG f FM f ET (5) where: f T is the temperature correction factor f SG is the mineral specific gravity correction factor f FM is the flow meter reading correction factor f ET is the elutriation time correction factor It is important to note that you should correct for each mineral in the system as each mineral has a different specific gravity. The cyclone cut sizes for each of the cyclosizer cones are given in Table 11. Further, it must be realised that sizing the -38 micron material using the precyclone, cyclosizer and/or the centrifuge represents a change in the way the particles are sized. When using sieves the sizing is achieved by passing the particles over a nest of sieves. Particles that are larger than the screen aperture are retained on the screen and those that are smaller fall through. However, when sizing using the precyclone, cyclosizer and/or centrifuge sizing is completed hydraulically based on size and mineral specific gravity. When the two sizing methods are used together, the transition point from one technique to the other can lead to some unusual shaped curves which are purely due to the change in the sizing method. To overcome this it is usual to combine the -53 micron to +C2 size fractions. This smooths the curves and effectively removed the transition between sizing methods. If you are considering completing a mineralogical analysis it is at this point that you would split out a small representative portion from the samples of interest prior to pulverising the samples for assay. Once you have reviewed the weights in each size fraction for each of the samples you have had sized, and decided which size fractions to combine, and ensured that there is enough sample for assay in each size fraction, the samples can be prepared and submitted of assay. How do I analyse the data collected? When the assays return it is important to check that the assays are in good order. This can be done by calculating the head assay from the size fraction assays and comparing it with the actual head assay. If they are in good agreement, then you can assume that both the sizing and the assays were completed properly. To construct a graph similar to that presented in Figure 17 the size and assay data for the copper rougher tailing, the lead first cleaner tailing, the lead scavenger concentrate and the lead rougher feed are required. To simplify the analysis only the lead assay data will be considered in this example. The starting point for determining the recovery-by-size behaviour in this part of the circuit is the mass balanced data from the plant survey given in Table 9, and for this section of the plant Table 10. Using the mass balanced tonnages for each of the process streams given in Table 10 the size distribution data determined from the sizing process (ie the weight per cent data) for each of these sample points were applied to yield the tonnes of ore in each size fraction (Table 12). The weight per cent and the assay for each size fraction are used to calculate the head grade: Head grade = n i = 1 ( mi ai) m i where: m is the weight per cent is size fraction i a is the assay for that size fraction This calculated head grade is then compared with the assay of the head sample to determine how well the sizing and assay procedures have been completed. Unfortunately, in this instance the mass and assay of the -5.6 micron fraction was calculated by difference. That is: (6) TABLE 11 Cyclosizer cyclone cut sizes for quartz, chalcopyrite, galena, sphalerite and pyrite. Correction factor Mineral Quartz Chalcopyrite Galena Sphalerite Pyrite f T f SG f FM f ET f Cyclone cut size C C C C C Flotation Plant Optimisation Spectrum Series 16 19

20 Pb distribution, % Pb rougher feed 1 Pb 1st cleaner tail Total Particle size, microns Pb scav con Cu scav tail FIG 17 - Lead distribution by size in the process streams contributing to the lead rougher feed. TABLE 12 The lead recovery-by-size data for the lead rougher feed calculated from the copper rougher tailing, lead first cleaner tailing and the lead scavenger concentrate. Stream/size Wt % Wt (t/h) Pb parameter (%) Grade Distribution Recovery to Pb Ro feed Cu scavenger tailing μm μm μm μm μm μm Head Pb First cleaner tailing μm μm μm μm μm μm Head Pb scavenger con μm μm μm μm μm μm Head Pb rougher feed μm μm μm μm μm μm Head Spectrum Series 16 Flotation Plant Optimisation

21 n 1 m 56. μ m mh m1 (7) and a 56. μm = i 1 n 1 mh ah m1 ai i 1 = m 56. μm where: m H and a H are the weight per cent and assay for the head By calculating the weight per cent and assay for the finest size fraction all the errors associated with the sizing, assaying and sampling are accumulated to this size fraction. In an ideal world as sample of this material would be collected. Having worked out the tonnes of ore and the assay for each size fraction the distribution-by-size within each process stream, and the recovery-by-size against a particular process stream can be calculated. The distribution within a process stream is given by: Distribution a (8) ( mi ai) = 100 (9) ( m a ) H H The distribution of lead within each process stream is provided in Table 12. In this case the recovery-by-size is calculated for the lead rougher feed because the copper scavenger tailing, the lead first cleaner tailing and the lead scavenger concentrate all combine to form the lead rougher feed. So, the recovery for each size fraction, i, is given by: n ( mp ap) P Recovery i, a = = (10) ( mh ah) where: P are the process streams of interest A similar approach is adopted for the more traditional recovery-by-size curves presented in Figure 18 and 20. What does it mean? Figure 17 contains the distribution by size, for galena, for the three process streams contributing to the lead rougher feed. The vast majority of the galena in the lead rougher feed is in the coarse (+20 micron) lead recycled back from the lead first cleaner tailing (80 per cent of the total lead in the lead rougher feed). Thus, the flotation characteristics of the lead rougher/scavenger unit are dominated by the behaviour of this material. The recoveries versus size data for the lead final concentrate are provided in Figure 18. These data show clearly that the lead final concentrate consists predominantly of fine (-20 micron) galena, with greater than 90 per cent lead recovery for the intermediate size fractions (+5/-20 microns). Either side of this size range the recoveries decrease. The recoveries of gangue minerals (sphalerite, iron sulfides and non-sulfide gangue) are low across all size fractions. The galena distribution, by size, of the lead scavenger tailing, with respect to flotation feed, is provided in Figure 19. Clearly the losses of galena from the lead circuit are bimodal, with significant losses in the fine (-5 microns) fraction (5.6 per cent) and coarse (+20 microns) fractions (19.9 per cent). Of greatest concern however are the losses in the coarse fractions. It is presumed that these coarse particles occur as galena deficient/sphalerite rich composites. Figure 20 shows the recovery by size data for the zinc final concentrate. These data show the peculiar behaviour of the coarse (+20 microns) galena, which exhibits recoveries as high as 60 per cent. It is presumed that this behaviour is related to the composition of these galena particles (ie galena deficient/ sphalerite rich composites). Mineralogy (Chapter 4) Once the recovery-by-size data has been analysed and a theory formed, select streams should be examined mineralogically. As this is a relatively expensive process, it is wise to complete the work already discussed, prior to obtaining mineralogical analysis. The recovery-by-size analysis indicates that a significant amount Recovery, % Geometric mean particle size, microns Lead Zinc Copper Iron Silica FIG 18 - Recovery-by-size data for the lead final concentrate, with respect to flotation feed for the Eureka Concentrator. Flotation Plant Optimisation Spectrum Series 16 21

22 Distribution (with respect to flotation feed), % Geometric mean particle size, microns FIG 19 - The galena distribution by size, with respect to flotation feed, in the lead scavenger tailing for the Eureka Concentrator Recovery, % Geometric mean particle size, microns Lead Zinc Copper Iron Silica FIG 20 - Recovery-by-size data for the zinc final concentrate, with respect to flotation feed for the Eureka Concentrator. of material is recycled back to the lead rougher feed from the lead first cleaner tailing, and that the vast majority of this material occurs in the +20 micron size fraction. It is highly likely that these particles are galena/sphalerite composites. However, in order to prove this it is necessary to complete a mineralogical examination. What do I have to do? To complete a mineralogical analysis of samples from you plant you need to provide the company completing the examination for you with a representative sample of the process stream that has not been pulverised. For liberation analysis, the sample provided will be of a number of closely sized size fractions. If you have completed a recovery-by-size analysis you should have prepared the samples for mineralogical examination at the same time. With the samples available for analysis it is then necessary to choose the method by which the mineralogical data will be collected. These methods range from optical microscopy through to automated methods such as QEMSCAN and MLA. Chapter 4: A Practical Guide to Some Aspects of Mineralogy that Effect Flotation, by Alan Butcher, describes the methods available. What data do I need? When shipping samples off to a laboratory for mineralogical analysis it is wise to provide the mineralogist with a scope of work, and assays of the samples that will be examined. The scope of work will inform the mineralogist of the questions you would like answered. For example, at Eureka you are interested in the locking and liberation characteristics of galena and sphalerite around the lead rougher/first cleaner circuit. It is then clear to the mineralogist that the examination should provide information about the degree of liberation of these minerals, and how they are locked with other minerals. Supplying the assays for the samples you have supplied for examination allows the mineralogist to reconcile his calculated head grade based on the minerals present back to the assays. It is a check that the mineralogist uses to ensure the quality of the data that is provided. How do I analyse the data collected? The mineralogical report provided will depend on the technique employed by the mineralogist to examine your samples. Essentially, the data provided should provide nominally the same information. That is, the percentage of liberated mineral within 22 Spectrum Series 16 Flotation Plant Optimisation

23 the sample, the percentage of binary particles present and what the two minerals are, and the percentage of more complex composite particles measured. Table 13 provides a simplified list of the liberation data for galena in the lead rougher feed of the Eureka Concentrator. What this data means is that of the lead in the +28 micron size fraction 66 per cent occurs as liberated particles of galena and 28 per cent are present as binary composites with sphalerite. Minor amounts of galena are associated with pyrite and occur in ternary particles. What does it mean? Mineralogical examination of strategic process streams feeding into the lead rougher feed showed that about one third of the galena in the lead rougher feed occurs as coarse (+20 micron) galena/sphalerite composite particles (Figure 21), and the majority of this material emanates from the lead first cleaner tailing. Thus, two thirds of the galena in the lead rougher feed is liberated, which infers that the maximum lead recovery to the final lead concentrate, at grade, would be approximately 70 per cent. Therefore, galena liberation was considered to be the limiting factor impinging of improved metallurgical performance. Problem definition summary The metallurgical survey suggested that the lead circuit was potentially unstable with large circulating loads of galena and sphalerite around the lead rougher/first cleaner circuit. The use of recovery-by-size and liberation analysis has clearly indicated that the recovery of +20 micron galena within the lead circuit is limited. The liberation analysis clearly shows that the galena in the +20 micron fraction is locked with sphalerite. Thus, the problem is: poor liberation of galena in the +20 micron size fractions. SOLUTION DEVELOPMENT AND TESTING It is apparent that to improve liberation one needs to grind finer. The first step in proving that improved regrinding is required in the lead circuit is to complete a series of laboratory tests examining the impact of regrinding the main feed source to the lead rougher, the lead first cleaner tailing. Laboratory investigation (Chapter 9) What do I have to do? As the lead first cleaner tailing contributed the highest flow of material to the lead rougher feed, and this process stream contains a significant percentage of galena/sphalerite composite particles greater than 20 microns, it was decided that this process stream would be the best one to complete laboratory tests examining the impact of regrinding on lead rougher flotation. It is your job to design a series of laboratory flotation tests that would identify what changes would occur as the lead first cleaner tailing was reground to progressively finer sizes. TABLE 13 Galena liberation by size and mineral class for the lead rougher feed of the Eureka Concentrator. Size (μm) Liberation class (%) Total (%) Liberated Binary with Ternary Sphalerite Pyrite Gangue Head Distribution Head Size, microns Liberated Ga-Sp Ga-Py Ga-Gn Liberation class Ternary FIG 21 - Size by liberation class data for the lead rougher feed. Ga = galena; Sp = sphalerite; Py = pyrite; and Gn = gangue. Flotation Plant Optimisation Spectrum Series 16 23

24 With the laboratory test program designed, sufficient pulp was collected from the lead first cleaner tailing. In addition to the lead first cleaner tailing pulp, a bulk sample of process water was also collected. The pulp was filtered and cut into 1000 gram lots. The test program called for one test to be completed without regrinding, and then tests completed on ore ground for five, ten, 15 and 20 minutes. The tests were completed in a 2.5 litre flotation cell. Timed concentrates were collected after 0.5, 1.5, 2.0, 2.0, 2.0, 2.0 and 2.0 minutes for a total flotation time of 12 minutes. The seven concentrate and tailing samples generated for each test were prepped and submitted for assay. What data do I need? The weights for each of the concentrates and the tailing samples as well as the assays are required to complete a mass balance for each of the tests. Additional information such as the ph, reagent additions and any observations made during the test are also helpful. How do I analyse the data collected? The weights and assays are to be put into a spreadsheet that allows you to calculate the cumulative grades and recoveries for each of the tests. These data can then be used to construct lead grade/recovery curves (Figure 22). From the mass balanced data it is also possible to determine the kinetics (ie flotation rate constant and maximum recovery) using Equation 11, and the selectivity for galena against the gangue minerals. R = R e kt max ( 1 ) (11) To assist with interpretation the kinetic data and the selectivity data can be tabulated. For example, Table 14 shows the lead concentrate grade, as well as the zinc and iron sulfide recoveries, at 80 per cent lead recovery. Selectivity curves can also be drawn. What does it mean? Laboratory lead rougher flotation tests conducted on strategic process streams suggested that the introduction of regrinding significantly improved the position of the lead grade/recovery curve. Figure 22 shows that as the degree of regrinding increased the position of the lead grade/recovery curve improved. For example, at 80 per cent lead recovery the lead grade was increased from 30.8 per cent for the test conducted without regrinding, to 42.2 per cent after 20 minutes regrinding. The improvement in lead grade was due to better selectivity for galena against sphalerite and iron sulfides (Table 14). In the laboratory, regrinding improved lead metallurgy, and with the improved selectivity for galena against sphalerite it is expected that zinc metallurgy would also improve. Plant trial (Chapter 10) As the existing lead regrind mill was inadequate for this duty, a larger mill would be required if improvements in metallurgical performance were to be realised. In light of the very first comment made at the beginning of this chapter about utilising the Pb grade, % Pb recovery, % No regrinding 5 minutes regrinding 10 minutes regrinding 15 minutes regrinding 20 minutes regrinding FIG 22 - Lead grade/recovery curves for lead rougher flotation tests conducted on lead first cleaner tailing, demonstrating the effect of regrinding. TABLE 14 Lead grade and diluent recoveries, at 80 per cent lead recovery, for lead rougher flotation tests conducted on lead first cleaner tailing demonstrating the impact of regrinding. Test description Pb grade (%) Diluent recovery (%) Zn IS No regrinding minutes regrinding minutes regrinding minutes regrinding minutes regrinding Spectrum Series 16 Flotation Plant Optimisation

25 resources around you, and especially people, this problem was discussed with the operations team and a solution was quickly found. As capital was not readily available an experienced flotation operator suggested swapping the lead and zinc regrinding mills, as the zinc regrinding mill was larger and more able to cope with the higher tonnages experienced in the lead circuit. Redirecting the lead scavenger concentrate and lead first cleaner tailing process streams to the zinc regrind mill was accomplished through a simple change in the pipe work. The existing pipe work to the old lead regrind mill was left intact so that a plant trial could be conducted. A randomised block on/off trial was designed, following the guidelines prescribed by Tim Napier-Munn in Chapter 10: Designing and Analysing Plant Trials, that would use the shift mass balanced data to statistically analyse the metallurgical performance of the Eureka Concentrator with and without effective lead regrinding. When the new lead regrind mill was turned on the impact on lead and zinc metallurgy was immediate and dramatic. Because of the magnitude of the improvements the on/off trial was abandoned. However changes of this magnitude are not always apparent, and strong statistical data analysis is often required as proof that there is a statistically confident change in the plant which was due to your implemented solution. In some cases, trials can run for a number of months but persistence pays off when you achieve the result you were aiming for. The lead recovery to final concentrate from June 1998 through to February 2000 is presented in Figure 23. It is apparent that the lead recovery has increased on average from 65 per cent up to 81.5 per cent. The most significant improvement to lead recovery was achieved through the application of an effective regrinding stage. Despite not undertaking the randomised block trial as first thought, it was possible to complete a statistical analysis using plant data from before and after the change. Using the Student t-test to analyse the data showed that installing effective lead regrinding produced the following results: the lead recovery was improved by 16.5 ± 2.5 per cent, with greater than 99 per cent confidence; the lead concentrate grade improved by 4.0 ± 0.8 per cent, with greater than 99 per cent confidence; and the zinc grade in the lead concentrate was reduced by 1.8 ± 0.6 per cent, with greater than 99 per cent confidence. These changes to the lead circuit resulted in a decrease in the amount of sphalerite reporting to the lead concentrate, and shifted this material into the zinc circuit. Hence, zinc metallurgy was also improved, with: the zinc recovery increased by 1.5 ± 0.4 per cent, with greater than 99 per cent confidence; and the zinc concentrate grade increased by 2.1 ± 0.5 per cent, with greater than 99 per cent confidence. Other statistical methods (for example, comparison of regression lines) produced similar values. THE CYCLE BEGINS AGAIN Despite the application of effective regrinding in the lead circuit, and the massive improvements in metallurgical performance, there is still room for improvement. There is not time to rest on your laurels, as the Senior Project Metallurgist it is your job to identify problems and develop cost-effective solutions to implement in the plant. You ve only solved part of the problem, and opportunities for further improvement are available. So, sorry but the Senior Project Metallurgist s work is never finished! The key areas where efforts can be made to improve metallurgy are: the optimisation of both the lead and zinc regrinding circuits, to improve liberation and subsequently concentrate grades and recoveries; the optimisation of chemistry for flotation to improve selectivity of valuable minerals against gangue minerals, and consequently increased concentrate grades; and to continue minimising variations in the process. More surveys To move forward it is necessary to continue monitoring the process through: analysis of shift mass balances, analysis of monthly composite samples (by size and liberation class), New Pb Feed distributor Average % Rec MF4 used as lead regrind mill Complete Pb froth level control + new 6" Pb regrind cyclones + Dedicated float operators Level on Pb conditioning tank dropped Initial Pb froth level control 5 7-Jan Jan Feb Mar-98 1-Apr Apr May-98 3-Jun Jun Jul-98 5-Aug Aug Sep-98 7-Oct Oct Nov-98 9-Dec Dec Jan Feb-99 3-Mar Mar Apr-99 5-May May Jun-99 7-Jul Jul Aug-99 8-Sep Sep Oct Nov-99 1-Dec Dec Jan-00 2-Feb-00 W/E Average Average CL UCL LCL FIG 23 - Lead recovery versus time data from June 1998 to February Some milestones are highlighted. Flotation Plant Optimisation Spectrum Series 16 25

26 routine metallurgical and pulp chemical surveys, flotation cell characterisation (Chapter 5), and the introduction of a future ores testing program (Geometallurgy, Chapter 12). After all, to measure is to know! Chemistry With the improvements in the lead circuit through better regrinding perhaps it is time to study the chemistry of the system. Pulp chemistry The pulp chemistry indicated that the lead rougher circuit operated in oxidising conditions, with Eh values between 150 and 200 mv (SHE). Figure 15 shows the Eh-pH curve for the circuit. The curve is essentially parallel to the water-oxygen line for the lead rougher circuit, and suggested that any changes in Eh or ph were due to the maintenance of water equilibria. These conditions points to a system operating in oxidising conditions. Solution chemistry The EDTA extractable lead increased from approximately five per cent in the copper rougher tailing up to 17 per cent in the lead scavenger tailing. The EDTA extractable zinc and iron values were an order of magnitude lower than those reported for lead. These data suggest that the galena in the lead circuit feed is moderately oxidised, while the galena remaining in the lead scavenger tailing is heavily oxidised. The main point to come from this analysis is that there would appear to be a significant quantity of galena oxidation products present within the pulp, which under the right circumstances could lead to the inadvertent activation of sphalerite. Surface chemistry To confirm your theory developed from the pulp chemistry observations it is wise to complete surface analysis on selected samples. Alan Buckely, in Chapter 8: Surface Chemical Characterisation for Identifying and Solving Problems Within Base Metal Sulfide Flotation Plants, provides details of the types of surface analysis and how they may be used in your quest for more information. What do I have to do? With the decision made to complete surface analysis to validate your hypothesis you need to provide the institution conducting the surface analysis with a scope of work. It is imperative that you provide the surface scientist with a focused question that defines what you hope to get out of the surface analysis. In your case, at the Eureka Mine, you are very interested in knowing the surface chemistry of liberated sphalerite that reports to the lead rougher concentrate, and how this compares with free sphalerite in the lead rougher tailing. This essentially means that the surface scientist will examine liberated sphalerite in lead rougher concentrate and tailing process streams to identify differences that may explain why some of the liberated sphalerite is being recovered into the rougher concentrate. The surface scientist will suggest the surface analysis technique that they feel is best for your application. ToF-SIMS is frequently used because of its high surface sensitivity and its ability to analyse individual particles. What data do I need? When collecting the samples for surface analysis it is important to use the right sample preparation protocols. The surface scientist will provide you with these. Generally, once the samples have been collected they need to be purged with nitrogen gas to remove oxygen from the pulp to prevent further oxidation. The sample is then sealed in the sample vial, and snap frozen in liquid nitrogen. The sample pairs are then shipped to the surface analysis facility frozen in a cryogenic container. Ideally, when you collect the samples for surface analysis you should complete a block survey of that part of the circuit of interest. At Eureka, a block survey of the lead rougher circuit would be the order of the day. Conducting a survey gives you a reference point in terms of metallurgical performance that can be used for comparison purposes. It is also wise to complete a pulp chemical and EDTA extractable metal ion analysis on the sample process streams that the surface analysis samples were collected from. This information should be transmitted to the surface scientist as it gives them some idea of the chemistry of the system and helps explain the observations they will make. How do I analyse the data collected? The surface scientist will provide you with an analysis of the findings. You are not expected to know everything! However, it is wise to read the surface analysis report and ask questions. If you do not understand the analysis of the surface chemical data ask the surface scientist to explain. This will allow you to question the surface scientist to determine how they reached the conclusions and help you to understand these techniques, and the valuable information they can add to an investigation. It is very important to link the surface chemical observations to the pulp chemistry and metallurgical performance of the plant. After all the data generated will be used to confirm your theory as to why something is happening (at Eureka identification of the activating species on liberated sphalerite), and from this you will propose solutions for testing in the laboratory to solve the problem. What does it mean? Surface analysis was completed on samples of lead rougher concentrate and tailing samples using ToF-SIMS to determine the dominant species on the surfaces of the liberated sphalerite particles. The surface analysis investigation indicated that the liberated sphalerite particles contained within the lead rougher concentrate had statistically more collector, copper, silver and lead species on their surfaces than those reporting to the tailing (Figures 24 and 25). The conclusions reached from the chemical analysis were that: The flotation pulp in the lead rougher circuit operated in oxidising conditions. The level of EDTA extractable lead within the lead circuit was high, indicating the presence of a large quantity of galena oxidation species capable of activating sphalerite. The surface analysis confirmed the suspicion that the liberated sphalerite was activated by lead ions. Copper and silver were also observed on the surfaces of the sphalerite particles, but in lower concentrations. These data would suggest that some of the sphalerite is being recovered into the lead concentrate because it is activated by lead ions. You should propose that laboratory test work be completed examining the effect of various reagents to depress activated sphalerite. Should these tests prove positive, and the solution is economically sound, then it should be tested in the plant using statistically rigorous trial methodology. 26 Spectrum Series 16 Flotation Plant Optimisation

27 (+) SIMS sphalerite Normalised Intensity Pb cleaner con Pb cleaner tail Mg Ag Si Ca Fe Cu Zn FeOH Pb PbOH (+) Fragment (-) SIMS sphalerite Normalised Intensity Pb cleaner con Pb cleaner tail C CH O OH S SO3 SO4 IEX (-) Fragment FIG 24 - Positive and negative mass spectra for sphalerite particles in the lead cleaner concentrate and tailing process streams confidence intervals calculated for 95 per cent. (A) (B) FIG 25 - ToF-SIMS images of sphalerite particles within the lead rougher concentrate: (A) the zinc ion image; and (B) the lead ion image. COMMUNICATION The technical aspects of concentrator performance are very important in achieving optimum metallurgy. However, the best technical expertise is of little consequence if people and maintenance issues are not adequately addressed. Process variations are probably the hardest to monitor and control, and can result in operations personnel treating symptoms rather than causes (ie fire fighting ). In most instances process variations, such as ore hardness, mineralogical changes with ore type, and head grade variation, are very difficult to measure online, but can be partially overcome with an effective ore characterisation program (geometallurgy) and good communication between the mine and the mill. Behavioural variations are often easily identified, but are difficult to correct because of the human factor. One way of improving the behavioural variations within a concentrator is to document and standardise each task. That is, if each operator performs the same task the same way, by following as standard work procedure, then behavioural variations can be minimised. Unfortunately, this is easier said than done. Another key element in altering behaviour to maximise metallurgical performance is the development of a proactive, interventionist metallurgical team, such that there are definite metallurgical targets and procedures prescribed to achieve these goals. A change in the perception of the metallurgist is required such that he should be viewed as a member of the team with specialist knowledge that is on-call when problems arise. CONCLUSIONS At the Eureka Concentrator the use of classical metallurgical techniques (recovery- and liberation-by size analysis) has provided a high degree of certainty in determining the source of the metallurgical problem. Initially galena/sphalerite liberation was identified as a significant impediment to achieving better Flotation Plant Optimisation Spectrum Series 16 27