Ball Mills What Are These Machines and How Do They Work? Short flash video at bottom of page showing batch ball mill grinding in lab. May have to click on browser "Allow Active X blocked content" to play A Ball Mill grinds material by rotating a cylinder with steel grinding balls, causing the balls to fall back into the cylinder and onto the material to be ground. The rotation is usually between 4 to 20 revolutions per minute, depending upon the diameter of the mill. The larger the diameter, the slower the rotation. If the peripheral speed of the mill is too great, it begins to act like a centrifuge and the balls do not fall back, but stay on the perimeter of the mill. The point where the mill becomes a centrifuge is called the "Critical Speed", and ball mills usually operate at 65% to 75% of the critical speed. Ball Mills are generally used to grind material 1/4 inch and finer, down to the particle size of 20 to 75 microns. To achieve a reasonable efficiency with ball mills, they must be operated in a closed system, with oversize material continuously being recirculated back into the mill to be reduced. Various classifiers, such as screens, spiral classifiers, cyclones and air classifiers are used for classifying the discharge from ball mills. This formula calculates the critical speed of any ball mill. Most ball mills operate most efficiently between 65% and 75% of their critical speed. Photo of a 10 Ft diameter by 32 Ft long ball mill in a Cement Plant. Photo of a series of ball mills in a Copper Plant, grinding the ore for flotation. Image of cut away ball mill, showing material flow through typical ball mill. Flash viedo of Jar Drive and Batch Ball Mill grinding ore for testing Return To Crushing Info Page Contact Us Copyright 1994-2012 Mine-Engineer.Com All Rights Reserved
In Grinding, selecting (calculate)the correct or optimum ball sizethat allows for the best and optimum/ideal or target grind size to be achieved by your ball mill is an important thing for a Mineral Processing Engineer AKA Metallurgist to do. Often, the ball used in ball mills is oversize just in case. Well, this safety factor can cost you much in recovery and/or mill liner wear and tear.
There are basically two groups of Grinding Mill Liners. Ones with a HIGH PROFILE and those with a LOW PROFILE. The high profile liner is designed to give the media the higher lift. This type will be used in mills that are designed for primary grinding and as a result require the impact of the higher cascade. Ball mills working as the secondary portion of a grinding circuit will utilize the lower profile liners. The reason is as lift decreases, friction increases. To function effectively they need this type of grinding action to obtain the maximum contact of their high surface area. There are two other factors that the liner design must accommodate other than the degree of lift. The TYPE of grinding media and the SIZE of the media. To do this, there have been developed different liner profiles, RIPPLE LINERS, WAVE LINERS, SINGLE STEP LINERS, DOUBLE STEP LINERS, SHIPLAP LINERS and LIFTER BARS. These are also known as a KICKER BAR LINERS. The important measurements being the WIDTH of the valleys, the HEIGHT of the lifting portion of the liner and the overall THICKNESS of the liner.
(A liner takes up space and will reduce the tonnage accordingly.) When a mill is being designed, the type of liner that will be used is very important. The wrong liner design will increase power and steel consumption, as well as reduce the grind and throughput of the mill.
Liners not only come in different designs, they are available constructed from different materials. Liners may he built from MANGANESE STEEL for rod mills and ball mills that use bigger than two inch balls. Or they may be what is known as CHILLED CAST IRON LINERS. This type of liner have their own content formulas and are cast in their own manner as well. An example of such a liner is the NIHARD LINERS. In the last few years RUBBER LINERS for secondary grinds have also been used with some success.
For an operator the biggest effect that the liners will have on his job will be the result of wear.As the liners wear out the lifting portion of the liner will be reduced until the liner has a lower profile.
This means that the cascade of the media will become flatter as the as the leading edge of the lifter wears away. The amount of unground material will slowly increase until the mill can no longer grind the bigger ore. When this happens the liners will have to be changed.
If you ever have to start up a mill that has had a complete liner change I would suggest starting at a reduced tonnage and slowly bring the tonnage up to its maximum. This is because the new liners may have too much lift and literally throw the media across the mill spoiling the cascade action. Once the LEADING- EDGE of the liner has worn off a bit you will be able to increase the tonnage again. You will notice that the grind will continue to improve due to the liners slowly wearing away providing a longer retention time for the ore to be processed in. This of course has a limit, once the liners wear past a critical size the efficiency of the mill will slowly deteriorate until the liners are completely worn out requiring replacement.
This system combined rubber plates with cast manganese lifter bars which assures that the major portion of the surface of the mill will be protected with an abrasion -resistant resilient surface under compression and that the remaining portion of the lining will be capable of sustaining the lifting load, will maintain a uniform lift and will resist abrasion .
Todays rubber mill liners have built up from these origins and rubber liner manufacturers have worked closely with the mill operators to develop better compounds and better designs to provide the best liner system for each application.
Abrasion Resistance: Todays rubber compounds are specifically designed to resist wear by abrasion. The success has been well documented in regrind mill applications where rubber has outlasted cast metal liners and given better cost effectiveness.
Impact Resistance: This feature is more important in the larger grinding mills. Rubber liners absorb the impact of the larger grinding media and thus protecting the mill structure and prolonging its life.
Weight: Rubber weighs about 15% of an equivalent volume of steel. This means that a rubber liner system reduces the load on the mill structure and also reduces the basic power draw. Another benefit is that liner components are lighter, easier and safer to handle. A major factor in todays milling operation where fewer people are available for liner changeouts.
Tight Seal: Because rubber liners can be produced to relatively close tolerances and rubber is deformable, a rubber liner system is designed as a tight liner. This protects the structure of the mill from any abrasive or corrosive wear. Another very important side benefit for gold operations is that the amount of free gold trapped between or underneath the liners is significantly reduced.
Flexibility: This feature of rubber is particularly significant in the use of rubber for grate discharge mills. The natural flexibility of rubber reduces the potential of blinding the grates. This will be discussed in greater detail later in this paper.
The design of rubber mill liners is very specific to the grinding application and will not be covered in this paper. Instead, three design concepts based on rubber as a lining material will be discussed. These are combination liners, rubber grates and rubber covered pulp lifters.
Long ago, it was recognized that there were grinding applications where rubber alone was not effective. The patent for the combination liner was issued for a design that extended the use of rubber into those applications. Although rubber technology has improved, there are still applications today where rubber alone is not effective and the combination liner is successfully used. These applications include semi autogenous mills and primary single stage ball mills.
The revised and updated design of a combination liner is a rubber plate with a separate metal lifter bar. Most of the volume of the liner is rubber so that the features and benefits of a rubber liner are retained. This plate can be either a plain contoured slab liner plate as shown or it may have a molded intermediate rubber lifter if required due to the chordal spacing, the size of the grinding media and feed.
The rubber plate is held in place by the metal lifter bars. A metal spacer sits between the rubber slabs and lifters to keep the liner from shifting. This spacer is usually made of low cost mild steel and is a one time item as it does not experience any wear and does not need replacing. This results in significant cost reduction of the liner system.
The metal lifter bar design is generally a function of the grinding application and mill size. The cross section however must retain two critical dimensions. The first is that the lips or edges of the lifter that extend over the rubber plates must be kept at a minimum of 25 mm to provide adequate clamping of the liner plates by the lifter.
The second critical dimension is the depth of the base. This should also be a minimum of 25 mm to prevent any lateral displacement. The base of the metal lifter must also be a flat smooth surface in order to properly seat on top of the metal spacer. The lifter bar is bolted through the shell with oval head taper grade 5 forged bolts.
This design has several important benefits. First, the amount of scrap loss in metal lifter bars at change out is kept to a minimum through the use of the mild steel spacer. The spacer also provides a solid base for the lifter so that the liner bolts can be properly torqued down. The second benefit of this design is that there is no metal in the rubber plates, as the lifter is supported by the permanent metal spacer. This simplifies the manufacturing of the rubber liners, and makes the plates lighter and easier to handle on installation.
The metallurgy of the lifter bars must be carefully matched to the grinding application. In mills with high impact such as large SAG mills, a high impact resistant Cr-Mo steel is required. In applications of low impact, the more abrasion resistant, castings such as Nihard are utilized to achieve maximum life through high abrasion resistance.
Selecting a successful maintenance strategy requires a good knowledge of maintenance management principles and practices as well as knowledge of specific facility performance. There is no one correct formula for maintenance strategy selection and, more often than not, the selection process involves a mix of different maintenance strategies to suit the specific facility performance and conditions.
There are a number of maintenance strategies available today that have been tried and tested throughout the years. These strategies range from optimization of existing maintenance routines to eliminating the root causes of failures altogether, to minimize maintenance requirements. Ultimately, the focus should be on improving equipment reliability while reducing cost of ownership.
An effective maintenance strategy is concerned with maximizing equipment uptime and facility performance while balancing the associated resources expended and ultimately the cost. We need to ensure that we are getting sufficient return on our investment.
Are we satisfied with the maintenance cost expended versus equipment performance and uptime? There is a balance to be had in terms of maintenance cost and facility performance. We can develop a suitable maintenance strategy to help tailor this balancing act in order to ensure the return on investment is acceptable (Figure5.11).
A maintenance strategy should be tailored specifically to meet the individual needs of a facility. The strategy is effectively dynamic and must be updated periodically as circumstances change. The strategy must include a detailed assessment of the current situation at the facility and consider the following questions:
Once we have clarity on the current situation and constraints, we need to define the objectives of the maintenance plan. The objectives must align with the business objectives of the company. They must be developed by all of the key facility stakeholders and be clear, concise and realistic. There may be a number of components to the strategy objectives for example: improve equipment uptime, reduce maintenance costs, reduce equipment operating costs, extend equipment life, reduce spare parts inventory, improve MTTR, etc
An example of a maintenance strategy workflow is illustrated in Figure5.12. This workflow is developed to optimize and improve an existing facility maintenance program. Depending on the specific circumstances at the facility, our strategy may also take us into the direction of a step change approach to maintenance management and opt for a reliability-centered maintenance (RCM) program, which may replace our existing maintenance program. This strategy is labor and time intensive and can be expensive; we will discuss RCM in section 5.7.1.
It is a common theme in the industry that maintenance budget and resources are very thin on the ground relative to the amount of work that needs to be done. Therefore, prioritization of maintenance resources is absolutely essential in order to be successful. Once we have defined our maintenance strategy objectives, we need to define facility equipment criticality. We have discussed the concept of criticality in Chapter4. Criticality is a risk-based approach that can help us to prioritize our resources effectively. It can also help to appraise the requirement and effectiveness of maintenance tasks already populated in the MMS or CMMS.
Another common theme in the industry is that many computer maintenance management systems are populated with a large proportion of preventive maintenance tasks that may be considered as superfluous and even not necessary. These tasks may consume a large proportion of the maintenance resources and time without an acceptable return on the investment made (maintenance cost). The maintenance strategy should also ensure the current data in the CMMS is value adding and therefore carry out a cleansing exercise. A data cleansing exercise critically reviews and appraises the current CMMS tasks and aims to eliminate the tasks that may not be adding value and therefore are superfluous. By focusing on equipment criticality, these activities can be reviewed and appraised in a logical and systematic way.
Once the equipment criticality assessment is completed and the strategy objectives have been reviewed and updated, maintenance resources can then be aligned to the strategy. The maintenance strategy objectives will dictate the resources and associated maintenance costs. The next step in the strategy development process is to update the equipment maintenance and operating plan as presented in section 5.5. The EMOP is the primary record and source of maintenance and operation information of each equipment item and includes the up-to-date maintenance and operating strategies. It provides the baseline information including equipment maintenance and operating parameters. We are then in a position to implement the maintenance strategy on the facility.
It is important to understand the impact (and the success) of the new maintenance strategy. This is achieved by setting key performance indicators (KPIs) to assess the facility maintenance performance. This is done by first developing a benchmark data set. How is the facility currently performing? What is the cost of maintenance? What is the MTBF? What is the MTTR? What is the maintenance rework ratio? Once the current facility maintenance performance is benchmarked, we can then measure maintenance performance against this benchmark. Maintenance performance is reviewed periodically and, depending on the results, may be reviewed and updated more frequently. We will look at facility integrity KPIs and dashboards in Chapter9.
If the maintenance performance is in line with business objectives, then the facility operation will continue; however, if there is any deviation in performance or change in the facility process or criticality ranking, then the maintenance strategy should be revisited.
In 1978 Stanley Nowlan and Howard F. Heap published a report aimed at determining new and more cost-effective ways of maintaining complex systems in the aviation industry. It was called Reliability-Centered Maintenance (RCM) [5.2].
Today, reliability-centered maintenance (RCM) is used across many industries and is recognized as one of the leading practices for oil and gas and petrochemical facility maintenance. RCM acknowledges that all equipment in a facility does not have an equal importance and that there are significant advantages in prioritizing maintenance efforts on certain facility equipment. RCM effectively provides a structured approach to the development of a maintenance program. It focuses on equipment needs and ultimately results in a well-grounded basis for facility maintenance with a high proportion of proactive maintenance. RCM addresses the basic causes of equipment and system failures. It aims to ensure that controls are in place to predict, prevent or mitigate these functional failures and hence the associated business impact [5.3]. RCM is defined by a technical standard from the Society of Automotive and Aerospace Engineers (SAE), namely SAE JA1011 (1999) [5.4].
Reliability-centered maintenance (RCM) analysis provides a structured framework for analyzing the functions and potential failures of facility equipment, such as pumps, compressors, a facility processing unit, etc. The emphasis of the analysis is to preserve system function, instead of focusing on preserving the actual equipment. The output of an RCM program is a series of scheduled maintenance plans. The RCM standard, SAE JA1011, describes the minimum criteria that a process must comply with to qualify as an RCM Process [5.4].
First the RCM team should be carefully assembled. The team should comprise a cross-section of facility operations, maintenance and FI&R teams with a strong technical understanding of the equipment to be analyzed. The team should also be conversant with the RCM analysis methodology.
RCM analysis requires a large investment of time and resources. Given this, it is often necessary for the facility maintenance group conducting the analysis to focus on a selection of equipment or systems. The equipment or systems to be analyzed should be identified and boundaries drawn around the battery limits of systems. This is to ensure clear demarcation of the RCM scope so that efforts and time are directed appropriately. It is often the case that a criticality assessment is used to determine the equipment or systems selection.
Reliability-centered maintenance focuses on preserving equipment functionality. The next step in the process is to determine the function or functions that the equipment or systems are intended to perform. Equipment functions should also be prescriptive in the definition of a function and include performance limits, for example.
Once the functions are clearly defined by the RCM team, their corresponding potential functional failures are defined. Functional failures may also include poor performance of a function or overperformance of a function as well.
The next step in the process is to identify and evaluate the effects of the equipment failure. This step enables the RCM team to prioritize and choose an appropriate maintenance strategy that can tackle the failure. It is common to employ a logic diagram to structure this part of the process in order to consistently evaluate and categorize the effects of failure.
It is important to leverage the skills and experience of the RCM team in order to ensure the cause of the failure is clear and accurate. The cause of the failure should be described in sufficient detail at this stage. This is so that we are able to ensure the maintenance task selection step in the process is confidently and reliably completed. It may be appropriate to refer to the RCM standard, SAE JA1012, which presents useful guidance as to how to identify causes of failure [5.4].
At this stage in the process, we have identified the functions that equipment is intended to perform and the ways that these functions could fail. We have evaluated the effects of functional failures and identified their causes; the next step in the RCM process is to select appropriate maintenance tasks for the equipment to prevent such failures. There are a number of ways to carry out this exercise; however, the RCM teams skill set and knowledge is the key factor.
The final step in the RCM process is to package the maintenance tasks into a practical and robust maintenance program. This process involves reviewing the selected maintenance tasks and grouping them in a logical way so that they can be uploaded into the facility CMMS. The ultimate goal in packaging the RCM tasks is to arrive at a practical and efficient maintenance program.
Reliability-centered maintenance (RCM) has been in use for a number of years. It provides a structured and systematic framework which can result in an effective maintenance management program for facility equipment.
It is no surprise that RCM is a resource intensive and time-consuming process that can be expensive to develop and implement. There are a number of iterations of RCM that attempt to reduce the effort needed to develop and implement an RCM program, with varying degrees of success. It is important to maintain the key principles of RCM and not to overstretch the battery limits that were agreed on by the facility maintenance team at the start of the process. This may lead to disillusionment and frustration and eventually may result in a failed implementation effort.
The approach to the development and implementation of an RCM maintenance program must be executed with dedication and tenacity. It is also important for the facility management team and the wider facility functional groups to buy in and support the RCM implementation effort.
Failure mode and effects analysis (FMEA) is a useful and practical tool for analysis of equipment failures. FMEA, which dates back to the 1940s, was one of the first techniques used as a methodical approach to failure analysis.
It was initially developed by the US military to address problems with the premature failure of military equipment and systems. It is detailed in MIL-P-1629, which is a US Armed Forces Military Procedure [5.5]. FMEA has evolved over the years and is now extensively used across a number of industries including space agencies, food service, software, healthcare, petrochemical and oil and gas. FMEA may also be referred to in standard SAE J1739 (Potential Failure Mode and Effects Analysis in Design) [5.6] and standard IEC 60812 (International Standard on Fault Mode and Effects Analysis) [5.7]
FMEA can also form part of a reliability program such as an RCM study. It involves reviewing equipment systems, subsystems and components to identify failure modes, their causes and their effects. The effects analysis involves examining the consequences of the failures on the particular equipment systems, subsystems or components. For each subsystem or component the failure modes and their resulting effects are recorded in an FMEA worksheet. There are many variations of FMEA worksheets to record the output of the analysis.
FMEA studies are particularly useful when applied to specific equipment or systems. This is because the tool is designed originally for standalone military equipment. We may also wish to target the FMEA study on specific equipment or systems may have been highlighted as the result of a criticality analysis.
Planned maintenance optimization (PMO) is a well-established, tried and tested maintenance strategy, dating back to the 1990s. Around this time there was a lot of concern from the industry that RCM did not suit the requirements for facilities that had existing maintenance programs with limited resources and timescales to perform an RCM study. This is because primarily RCM is a tool that is designed for use in the design stage of the facility life cycle. PMO, on the other hand, is specifically designed to target existing maintenance programs.
The PMO process is illustrated in the workflow in Figure5.14. PMO identifies planned maintenance database activities from an existing facility CMMS, categorizing them into planned maintenance craft groups. The workflow then reviews each corresponding facility equipment history to determine if the planned maintenance task is necessary. These tasks are critically evaluated and ultimately optimized based on the added value. Finally the maintenance program is updated along with the CMMS.
A PMO study may be conducted manually in a task force team or by employing commercially available software. There are numerous PMO software titles available in the market, some of which can be interfaced with a CMMS. Typically the decision to implement a PMO strategy is made in an ad hoc fashion by the maintenance management team. It is usually driven by budget and resource constraints.
Equipment failures are a result of defects; therefore by eliminating defects we can improve equipment reliability. Defect elimination is a maintenance strategy that takes us back to design. It aims to prevent defects being introduced at the early stages of the equipment life cycle, thereby removing the defects during the operational stage of the equipment life cycle.
By eliminating the defects that have potential to cause future equipment failures, maintenance requirements will also be reduced, resulting in improved equipment uptime. Defect elimination can actually reduce the maintenance requirements on equipment or systems and hence lower maintenance cost.
Defect elimination aims to identify failure modes and eliminate them at the outset. Each part of the equipment is taken in its component parts and corresponding defects are identified. Mitigation plans are then prepared for each and every defect identified in order to eliminate the failure mode. Control measures and quality assurance standards are developed in order to detect and eliminate defects before they are designed into the equipment and systems. One of the methods that could be employed in defect elimination is the FMEA tool as presented in section 5.7.2, which is based on failure mode and effects analysis.
In some instances maintenance managers may decide to purposefully overdesign a particular equipment or system on the facility. The idea behind this is that these particular equipment items or systems are therefore able to withstand deterioration processes more and function for longer periods of time between failures.
This decision may be made when dealing with highly critical processes on the facility, such as processing toxic or hazardous materials or chemicals, or where there is a requirement to increase the reliability of a certain part of a process that may warrant additional robustness of equipment design.
This is a strategic maintenance decision intended to prolong facility equipment and systems life and therefore maintain longer periods of production. It involves increasing the design specification of equipment or systems with more robust parts, higher specification materials of construction, better surface protection coatings, etc.
Maintenance management is a continuous improvement process. The intention is to add value by improving equipment reliability while reducing cost of ownership. Clearly there is a balance to be had with cost of ownership versus additional value added, particularly with this strategy. There may be a higher cost of ownership; however, this is offset against the improvements to the production output.
Such work is typically done as an overhaul, where the whole of the equipment is removed from operation during a shutdown and taken to the workshop to be stripped down to its component parts and rebuilt as new.
Use of shutdown overhaul maintenance strategy is aimed at ensuring uninterrupted production for a specific period of time. By renewing or overhauling equipment regularly we remove the wear-out related stoppages. Once equipment is overhauled to manufacturers standards we can expect as-new performance. However, we are also exposed to infant mortality risks due to poor quality control, mistakes during assembly, incorrect material selection and introduced damage.
Maintenance can be considered as the replacement or repair of components and assemblies (before or after failure), so that the unit concerned can perform its designated function over its expected life.
Formulating the best life plan (see Figure4.10) for each unit. This is a comprehensive program of maintenance procedures repair/replace/inspect at various frequencies spanning the expected life of the unit.
Formulating a maintenance schedule for the plant (see Figure4.11). This should be assembled from the programs of work contained in the unit life plan(s) but should be dynamic, e.g. readily adjustable in the light of changes in the production schedule.
Establishing the organization to enable the scheduled, and other, maintenance work to be resourced (see Figure4.12, which also shows that maintenance strategy and capital replacement policy are interrelated, i.e. maintenance cost influences unit replacement decisions and vice versa).
R4.1With industrial plant the physical assets have a fixed location and are connected together via a batch or process arrangement to perform the overall plant function. The function is to provide a manufactured product to a market. The objective is to maximize long-term profitability. The best way of modeling such operations is by process flow diagrams down to the unit level of plant supplemented as necessary by systems diagrams for the services.With an open cast coal mining operation the physical assets are spread over a wide geographic area and can be divided into mining assets, conveying/transport assets and coal preparation assets. The mining/transportation assets are mobile. The function of the operation is to provide mined coal to a market. The operation can be modeled using a combination of modified process flow diagrams (see Figure 1 in Case study 5 of Chapter 12) and status diagrams for the mobile plant (see Figure 2 in Case study 5 of Chapter 12).With a public transport bus fleet the physical assets are mobile and operate over a wide geographic area. The function is to provide a public transport service. The best way of modeling fleets is via a status diagram (see Figure 1 in Case study 6 of Chapter 12).The physical assets of a transmission/distribution system are spread over wide geographic area. The function is to provide electricity to consumers. With privatized utilities the objective is to maximize long-term profitability. With publically owned utilities the objective is to provide a defined level of service at best cost (these objectives are very different and have considerable influence on maintenance strategy).The operation is best modeled at the highest level as a complete generation/transmission/distribution system (see Figure 1 of the Power Utilities case studies introduction). Each part of the system, e.g. distribution can then be modeled in more detail but in the context of the complete system (see Figure 1 in Case study 9 of Chapter 12).R4.2Definition of a unit: A collection assemblies, sub-assemblies and component parts interconnected mechanically and/or electrically to enable the whole to perform a specific production sub-function of the plant.A unit in an open cast coal mine would be a haulage truck.A unit in a bus fleet would be a bus.A unit in a distribution utility would be a transformer.R4.3Many of the sub-assemblies and component parts of a unit have been designed with a useful life longer than the longest production run of the unit, but shorter than the expected life of the unit. Such parts have to be replaced/repaired during the life of the unit to ensure the unit remains reliable during production. By selection of the best possible sub-assemblies and component parts a unit could be designed to be maintenance free over its designed life, say 25 years. This is not done mainly because it would be too expensive but also because in some cases such long-life parts would not be technologically possible.R4.4The replacement of large high-cost units of plant is influenced by many factors to include the availability of capital, taxation policy, production needs, maintenance costs and the availability record of the existing unit. The maintenance managers advice should be sought but in general he does not take the replacement decision.
With industrial plant the physical assets have a fixed location and are connected together via a batch or process arrangement to perform the overall plant function. The function is to provide a manufactured product to a market. The objective is to maximize long-term profitability. The best way of modeling such operations is by process flow diagrams down to the unit level of plant supplemented as necessary by systems diagrams for the services.
With an open cast coal mining operation the physical assets are spread over a wide geographic area and can be divided into mining assets, conveying/transport assets and coal preparation assets. The mining/transportation assets are mobile. The function of the operation is to provide mined coal to a market. The operation can be modeled using a combination of modified process flow diagrams (see Figure 1 in Case study 5 of Chapter 12) and status diagrams for the mobile plant (see Figure 2 in Case study 5 of Chapter 12).
With a public transport bus fleet the physical assets are mobile and operate over a wide geographic area. The function is to provide a public transport service. The best way of modeling fleets is via a status diagram (see Figure 1 in Case study 6 of Chapter 12).
The physical assets of a transmission/distribution system are spread over wide geographic area. The function is to provide electricity to consumers. With privatized utilities the objective is to maximize long-term profitability. With publically owned utilities the objective is to provide a defined level of service at best cost (these objectives are very different and have considerable influence on maintenance strategy).The operation is best modeled at the highest level as a complete generation/transmission/distribution system (see Figure 1 of the Power Utilities case studies introduction). Each part of the system, e.g. distribution can then be modeled in more detail but in the context of the complete system (see Figure 1 in Case study 9 of Chapter 12).
Definition of a unit: A collection assemblies, sub-assemblies and component parts interconnected mechanically and/or electrically to enable the whole to perform a specific production sub-function of the plant.A unit in an open cast coal mine would be a haulage truck.A unit in a bus fleet would be a bus.A unit in a distribution utility would be a transformer.
Many of the sub-assemblies and component parts of a unit have been designed with a useful life longer than the longest production run of the unit, but shorter than the expected life of the unit. Such parts have to be replaced/repaired during the life of the unit to ensure the unit remains reliable during production. By selection of the best possible sub-assemblies and component parts a unit could be designed to be maintenance free over its designed life, say 25 years. This is not done mainly because it would be too expensive but also because in some cases such long-life parts would not be technologically possible.
The replacement of large high-cost units of plant is influenced by many factors to include the availability of capital, taxation policy, production needs, maintenance costs and the availability record of the existing unit. The maintenance managers advice should be sought but in general he does not take the replacement decision.
Capital replacement decisions have to take into account a multitude of considerations: production, maintenance and acquisition costs (and their variation), likely income from sale, plant reliability, fiscal considerations (tax incentives, import duty, etc.), cost of borrowing, obsolescence, alternative investment, etc. The greater the number of such considerations that a replacement calculation includes, the much greater is the complexity of the algebra. In general capital replacement models only take account of a few of the more important variables in any particular case and are, to that extent. always an approximation. The following simplified example is offered as an illustration. It is of deterministic nature in which averaged costs and trends are fairly predictable, as might be the case with a substantial unit of capital equipment.
A fixed-time replacement model for a unit of plant when new, the units-operating cost is 0 (year).Thus, rises linearly with time at a rate I (/year/year) so that after n years the operating cost would be 0 + ni (/year) and averaged over that time the mean-annual-operating cost would be 0 + (ni/2) (/year).
There will also be the cost of raising the above money which could have been done by borrowing (A S)+ for n years (repaying this in annual installments over the period) and borrowing S* for n years (repaid at the time of sale). Assuming simple interest at rate r, and remembering that the amount borrowed decreases steadily, the mean cost of the first amount borrowed would be (A S)r/2 (/year); the mean cost of the second amount* borrowed would be Sr (/year).The total mean borrowing cost would therefore be the sum of these two, which is (A + S)r/2 (/year).
Failure-based maintenance is usually considered acceptable for components with low risk of failure. Risk of failure consists of two components: failure consequences and failure probability. Use-based maintenance is acceptable for components whose failure mode and timing are predictable. Condition-based maintenance is acceptable when the extent of deterioration is measurable.
The required level of serviceability of the structure can also dictate the extent of repairs. For example, small cracks in concrete structures are tolerable in most cases and yet for water-retaining structures and those exposed to chlorides and aerosols they are not tolerable.
A recommended maintenance strategy should be based on scientific data from related studies of ideal irrigation and the requirements and convenience of daily nursing practice. Best-practice recommendations, including preirrigation preparation, irrigation solution [22, 42] and frequency , orientation  and volume  need to be developed and implemented. Before irrigation, nursing staff should check whether blood component or medication precipitate remains in the connecting route through the whole intravenous line. Preirrigation preparation should be done in order to remove residue and minimize microscopic deposits in the whole extension. Based on the literature review [4244, 48], normal saline is recommended as irrigation solution because it is easily available and does not increase the risk of lumen occlusion . The irrigation should be done every 3months . The ideal needle orientation is best achieved by inserting the noncoring needle as close as possible to perpendicular into the silicone diaphragm while keeping the needle opening opposite to the opening of the injection chamber. The orientation of the noncoring needle should not be adjusted to accommodate the wound dressing. The minimum recommended irrigation volume should be the 20-fold of the total intraluminal volume of the implanted ports that revealed by ex vivo simulation . The internal volume of implanted port and intraluminal volume per unit length of implanted catheter should be provided by manufacturers and implanted catheters should be preserved by surgeons. The resulting recommended irrigation volume is therefore 10mL for SVC port and 20mL for IVC port in most clinical scenarios .
Figure 11.3 shows the process flow of the milling plant of a gold mine. The mine is decoupled from the milling plant by the inter-stage ore storage. The milling process is the mines rate-determining process. For the foreseeable future (the next 5 years) management want to operate the milling process continuously. This will result in no plant-level windows of maintenance opportunity. Downstream from the cyclone towers the offline maintenance can be scheduled at unit level by exploiting redundancies (e.g. at any one time only three of the available five thickeners are required).
Scheduled offline maintenance, or failure of the crusher circuit, can stop the whole plant, although the plant can then be kept going for 3 days via the alternative crushing process, but at four times the cost of normal crushing. Scheduled offline maintenance or failure of one of the Ball Mills (or its ancillary equipment) causes a 50% loss of milling production.
The crushing circuit has a mean running time to failure of 6 months. Failure predictability is poor because of the large number of failure modes many of which are induced by randomly occurring production events. The Ball Mills also have a mean running time to failure of about 6 months but with good failure predictability. The main items needing replacement are the rubber lifters and liners.
The location of the mine is such that contract labor is extremely expensive. The resident labor force is manned up to the peak offline maintenance workload and hence is not very productive for most of the time. The quality of the labor is good, with an excellent knowledge of the plant, and in particular of the corrective maintenance methods. Because of the high cost of production downtime the maintenance objective appears to be to maximize milling plant availability.
The crusher circuit is operated-to-failure (or near-failure as indicated by the operators informal monitoring). Since failure is expected there is a considerable level of pre-planning (e.g. preparation of spares, job methods, decision guidelines). When the plant is offline because of failure, opportunity maintenance (including inspection) is carried out on the other units of the crusher circuit. Plant operation is sustained via the alternative crushing process.
The Ball Mills are on a schedule of 4-monthly overhaul. The main job is the repair or replacement of the lifters and liners, but other work is carried out on the mill to ensure its reliable operation over the following 4 months. In addition, preventive maintenance is carried out on other units in the stream (e.g. the conveyors). This causes a workload peak and contract labor has then to be employed. Some of the work is time-based, some deferred corrective maintenance, but most is repair-on-inspection.
While the existing fixed-time approach (4-monthly shutdowns) for the Ball Mills may not be the best policy it is regarded as an effective one. Explain why this is so? How do you think this approach could be improved?
Solutions to problems of this kind cannot be the exact ones. The proposals below must be regarded not as optimal solutions but as guidelines to good solutions. Various number of points raised are open to debate.
The factors that could be neglected are standards of safety and plant condition (longevity). Corporate management must be made aware of the link between maintenance effort (and resources) and safety.The budget must take into account the longer-term major maintenance work that influences equipment longevity.
The adoption of a condition-based approach could extend running time of units without reducing equipment reliability. This, however, assumes that a monitorable meaningful parameter can be found. If this is the case, condition-based policies would improve unit availabilities and also reduce maintenance costs. The downside of this could be that the workload might fluctuate erratically (perhaps with very large peaks). It would not be easy to co-ordinate maintenance work with production requirements or to use the common centralized maintenance resources efficiently. If the workload varied erratically across such a large plant, the organization would need to be designed to match, i.e. resources would have to be plant- flexible or greater use would have to be made of contract labor.Based on the limited information given it would seem likely that if condition-based maintenance were introduced as the strategic driver it would be a more cost-effective strategy. Because of the nature of the process equipment (failure mechanisms such as wear, corrosion, etc.) it should be easy to find condition-monitoring techniques that would be effective in predicting the onset of failure. The lumpiness of the maintenance workload that might result from such a policy should be able to be overcome by improved production-maintenance planning coupled with condition-based lead times and resource flexibility.
Based on the limited information given it would seem likely that if condition-based maintenance were introduced as the strategic driver it would be a more cost-effective strategy. Because of the nature of the process equipment (failure mechanisms such as wear, corrosion, etc.) it should be easy to find condition-monitoring techniques that would be effective in predicting the onset of failure. The lumpiness of the maintenance workload that might result from such a policy should be able to be overcome by improved production-maintenance planning coupled with condition-based lead times and resource flexibility.
If the fixed-time policy were largely retained, condition-based procedures might still be adopted, for two reasons, viz.:To help predict the corrective work needed during shutdowns, this improves planning.To avoid unexpected failures.
A base-load power station shutdown might well take 12 weeks and employ as many as a thousand artisans. The date must, therefore, be fixed some considerable time ahead, to facilitate the necessary extensive planning and resourcing. The maintenance workload might have a peak/trough ratio (shutdown/normal) of up to 10:1, which would necessitate the employment of contract labor. The fundamental difference between the power station and refinery strategies is caused by the difference in the way the plant is designed and operated. This in turn governs the shape of the workload. For the refinery, the major work can be smoothed over the year and carried out by an internal labor force; for the power station, extensive use of contract labor for resourcing the shutdown peak will be necessary.
Option (iii) is already in use and is proving too expensive. If option (i) is considered (as it must be) the causes of failure need to be identified and options considered for their elimination. This, however, is a long-term approach and the most cost-effective attack is likely to be the adoption of a condition-based policy. The information given is that the main causes of failure are wear, corrosion or fouling. Therefore, for most items, monitoring techniques for predicting failure can probably be found and effort would need to be directed at the historically unreliable items. This might allow maintenance of the crusher circuit to move from operate-to- failure to a policy based on condition-based shutdown (albeit with short notice) plus opportunity maintenance. Even with such short notice the monitored information (and history) should facilitate improved preparation and planning.
The main reason for Ball Mill shutdown maintenance is the replacement of the 0 lifters and liners. Their deterioration is time related and is statistically predictable so fixed-time replacement is an effective policy for controlling their reliability. It is not unlikely, however, that some form of condition monitoring might facilitate running the Ball Mills for longer periods before the lifters and liners need replacing. In many cases this would take the running time past 6 months and in some cases it might be as little as 4 months. However, if the inspection techniques gave an adequate planning lead time, the advantage is that the shutdown could still be scheduled.
Generally, the maintenance strategy is classified into two categories, based on the repair timing: corrective maintenance and preventative maintenance (DoD, 2008), as shown in Fig. 23.7. In corrective maintenance, the repair or retrofitting activities are only performed after the facility fails to meet the requirement of operation. Preventative maintenance tends to prevent the incipient failure of a facility through previous interventions at periodic or predicated times. For a tunnel, the maintenance plan is usually made during construction stage; however, during operation stage its adjustment should be periodically conducted, based on the degradation condition. In addition, the maintenance strategy should strike a balance between preventative and corrective maintenance, according to the facility function and operation conditions (FHWA, 2015). For a pipeline tunnel under desirable conditions, corrective maintenance may be effective. In contrast, for a transportation tunnel, preventative maintenance should be performed within a safer limit designed in advance.
In practice, tunnels deteriorate in various ways, depending on the material used, the support system, the operation condition, and etc. One tunnel may degrade slightly over a long period, whereas the another one under serious operation conditions may deteriorate to the serviceability limit over several years. Additionally, the influence of deteriorations on a concrete tunnel varies depending on its type, location, and size. Accordingly, the deterioration tendency over years of a similar tunnel should be referenced to make and modify a maintenance plan. If the tunnel is vulnerable to severe deterioration, the preventative maintenance should be considered, otherwise, the corrective maintenance may be more desirable. Nevertheless, the maintenance strategy should also take into consideration the LCC.
Typically, an operator proceeds to itemize basic goals. The highest priority is to maximize production. Optimizing production per unit of energy is part of that aim. Maximum availability and reliability (i.e., no unplanned downtime) are also critical. Operators struggle with financial budgets and the pressure of reducing costs in the attempt to minimize maintenance, service, and repair activity.
Too little maintenance results in unexpected failures and consequential major losses of production and/or customers (Figure 7-1). This impractical approach is termed reactive strategy and should be avoided on all important machinery. Optimum maintenance strategy balances reasonable costs with maxmium possible availability and reliability. The two main maintenance strategies employed by companies today are labelled predictive strategy and preventive strategy. These are part of a balanced approach as shown in Figure 7-2.
Predictive maintenance strategies operate without a regular plan for service work or exchange of parts. A maintenance plan is only set up if there is proof of deterioration. Consequently, a company with a predictive strategy favors minimizing cost over maximizing use. The annual cost of this strategy may typically only average 1%2% of the prime equipment price.
In contrast with the predictive strategy, a preventive strategy aims toward maximum safety against unexpected failures. The basic concept is to predict the average lifespan of a part and then replace it before the end of that lifespan. Annual cost is therefore higher (8%10% of the prime equipment price) because it is necessary to purchase and warehouse more spare parts.
Aside from the effects of a given maintenance strategy on troubleshooting time and effort required, the application service of the unit also has an effect. With increasingly tough environmental legislation that in turn demands maximum energy usage and/or recovery, power recovery processes are increasing in number. The deregulation of the power industry that results in the increase of small power producers (such as process plants) also serves to increase this number.
A profit-centered maintenance strategy requires effective and reliable maintenance planning, estimating, and scheduling (RMPES) and many other best practices. RMPES is considered by me and many others as one of the most important maintenance best practices because it is a very important enabler of profit, gained value customer service, craft labor productivity, and physical asset productivity. Effective and reliable maintenance planning, estimating, and scheduling enables:
The last of the three maintenance strategies to look at is condition-based maintenance. CM involves regular inspections of the equipment and removal of those components that the monitoring technique indicates are about to fail. CM is often advocated to be the cheapest maintenance strategy. The cost of CM is assumed to be $25/tube/year ($100 every four years). A comparison of RM and CM costs is presented in Fig.10.7. As can be seen, whether RM or CM is the cheaper depends wholly on the effectiveness of CM at preventing forced outages. If CM is 100% successful, then this is by far the cheaper method. However, if CM does not stop 10% or even 1% of potential tube failures, then RM tends to be cheaper.
Consider the following periodic maintenance strategy for a FTC system described by Xn in Fig. 1: The initial state of the system is assumed to be fault-free, 0=0=0; for every period TM, if the system is up, it goes to the maintenance state which brings the system to the initial state; and if the system is under repair at TM, we continue the repair, after which the system restarts from the initial state.
This maintenance policy and operation cycle can be considered as a special case of the system described in (Bloch-Mercier, 2000), and we therefore have the following result available for maintenance scheduling.
Lemma 1. (Bloch-Mercier, 2000) The mean duration time of maintenance and repair are denoted as SM and SR respectively. The reliability function of the system without maintenance and repair is denoted as R(t). The stationary availability A2(TM) of the overall system with maintenance period TM is then given as follows:
It implies that the stationary availability is monotonously increasing when TM is large enough, and the best strategy is not to take maintenance. So the relation between f(TM) and SMSR determines the existence of optimal maintenance period, as summarized in the following theorem.
The Bond work index is not solely a material constant but is influenced by the grinding conditions. For example, the finer the grind size desired, the higher is the kWh/t required to grind to that size. Magdalinovic  measured the Bond work index of three ore types using different test screen sizes. He produced a correlation between the mass of test screen undersize per revolution, G, and the square root of the test screen size, D:
The constant K2 is also dependent on ore type and ranged from 1.4 to 1.5. A regression of Magdalinovics data including the feed 80% passing size gives an average value of 1.485 for K2. If we extend this relationship to any sample of screened material then this gives an approximate estimate of the 80% passing size as 67.3% of the top size. This compares with a value of 66.7% of the 99% passing size obtained from data in Table3.3.
Using Magdalinovics method, from the results of a Bond work index test at a single test screen size, the constants K1 and K2 can be calculated and from these values, the work index at any test screen size can be estimated.
An alternative approach to determine the effect of closing screen size on the Bond ball mill work index (BWi), in the absence of extensive test work, is to use computer simulation. The batch grinding process has been modelled using the sizemass balance approach (Austin , Chapter11) and if we can do this, then we can effectively simulate the Bond ball mill work index test. Yan and Eaton  measured the selection function and breakage distribution parameters for the Austin grinding model and demonstrated the BWi simulation with soft and medium/hard ore samples. The measured BWi was 14.0 and 6.6kWh/t for the medium/hard and soft ore, respectively, at a closing screen size of 106 m compared with the simulated values of 13.2 and 5.6kWh/t.
The ability to simulate the Bond work index test also allows examination of truncated ball mill feed size distributions on the work index. For grinding circuits where the feed to a ballmill is sent directly to the classifier and the cyclone underflow feeds the ball mill (see Figure3.10), a question arises as to whether this practice will alter the ball mill work index (BWi) of the material being ground and hence have an impact on the energy used in the mill for grinding. Some might conclude that a higher percentage of coarse material in the mill feed will increase the amount of material that needs to be ground to produce the end product and hence it will affect the BWi. Others, in the absence of contrary evidence, assume that there is no change in the work index. Figure3.11 shows the typical circuit represented by the standard Bond work index correlation and Figure3.10 represents the scalped or truncated feed case.
The procedure for the work index test bases the BWi value on the calculation of new fines generated in the test. This means that the fraction of fines in the feed should not influence the test result significantly, if at all. For example, for a sample with 20% of 300 m material in the feed, if this is not scalped out of the fresh feed, then the mill charge, at 250% circulating load will contain 0.2/3.5 or 5.7% of 300 m in the mill charge compared with 0% for a scalped fresh feed, at a closing screen of 300 m. This should not have a great influence on the production of new fines unless the test was carried out in a wet environment and the fines contained a high percentage of clays to affect the viscosity of the grind environment. Thus for a Bond test (dry test), the difference between the scalped and unscalped BWi result is expected to be minor. In a plant operation where the environment is wet and clays are present, a different result may be observed.
Tests carried out to confirm this have clouded the water a little. Three rock types were tested with scalped and unscalped feeds with two samples showing higher BWi values for the scalped ore and the other sample showing a lower value .
In the work index test simulation, it is easy to change the closing screen size to examine the effect on the BWi. The results of such a simulation are shown in Figure3.12 where the simulated test was performed at different closing screen sizes and different scalping sizes. This shows that for scalping sizes at or below the closing screen size of the test, the BWi values are not affected. The scalping size of zero refers to the un-scalped mill feed. For scalped screen sizes above the closing screen size, the BWi values start to increase. The increase in BWi is more pronounced at the larger closing screen sizes. At a closing screen size of 300 m and a scalped size of 600 m, the increase in BWi is 4%.
Another outcome of the simulation is the effect of the closing screen size on the work index. As the closing size decreases, the ore must be ground finer, using more energy and producing a higher work index. Further simulations at even larger closing screen sizes show the BWi to increase. This dip in BWi with closing screen size has been observed experimentally, as shown in Figure3.13, with the minimum in BWi occurring at different closing screen sizes for different rock types [41,42].
Bond impact crushability work index (CWi) (Bond, 1963) results reported for iron ores vary from hard iron ore (17.7kWh/t) to medium hardness iron ore (11.3kWh/t) and friable iron ore (6.3kWh/t) (Table 2.11; Clout et al., 2007). The CWi for hard iron ores typically overlaps with those reported for BIF (taconite) iron ores while the range in values in Table 2.11 covers that for different types of iron ores and materials reported earlier by Bond (1963), with some relevant data in Table 2.12.
The most widely used parameter to measure ore hardness is the Bond work index Wi. Calculations involving Bonds work index are generally divided into steps with a different Wi determination for each size class. The low energy crushing work index laboratory test is conducted on ore specimens larger than 50mm, determining the crushing work index (WiC, CWi or IWi (impact work index)). The rod mill work index laboratory test is conducted by grinding an ore sample prepared to 80% passing 12.7mm ( inch, the original test being developed in imperial units) to a product size of approximately 1mm (in the original and still the standard, 14 mesh; see Chapter 4 for definition of mesh), thus determining the rod mill work index (WiR or RWi). The ball mill work index laboratory test is conducted by grinding an ore sample prepared to 100% passing 3.36mm (6 mesh) to product size in the range of 45-150m (325-100 mesh), thus determining the ball mill work index (WiB or BWi). The work index calculations across a narrow size range are conducted using the appropriate laboratory work index determination for the material size of interest, or by chaining individual work index calculations using multiple laboratory work index determinations across a wide range of particle size.
To give a sense of the magnitude, Table 5.1 lists Bond work indices for a selection of materials. For preliminary design purposes such reference data are of some guide but measured values are required at the more advanced design stage.
A major use of the Bond model is to select the size of tumbling mill for a given duty. (An example calculation is given in Chapter 7.) A variety of correction factors (EF) have been developed to adapt the Bond formula to situations not included in the original calibration set and to account for relative efficiency differences in certain comminution machines (Rowland, 1988). Most relevant are the EF4 factor for coarse feed and the EF5 factor for fine grinding that attempt to compensate for sizes ranges beyond the bulk of the original calibration data set (Bond, 1985).
The standard Bond tumbling mill tests are time-consuming, requiring locked-cycle testing. Smith and Lee (1968) used batch-type tests to arrive at the work index; however, the grindability of highly heterogeneous ores cannot be well reproduced by batch testing.
Berry and Bruce (1966) developed a comparative method of determining the hardness of an ore. The method requires the use of a reference ore of known work index. The reference ore is ground for a certain time (T) in a laboratory tumbling mill and an identical weight of the test ore is then ground for the same time. Since the power input to the mill is constant (P), the energy input (E=PT) is the same for both reference and test ore. If r is the reference ore and t the ore under test, then we can write from Bonds Eq. (5.4):
Work indices have been obtained from grindability tests on different sizes of several types of equipment, using identical feed materials (Lowrison, 1974). The values of work indices obtained are indications of the efficiencies of the machines. Thus, the equipment having the highest indices, and hence the largest energy consumers, are found to be jaw and gyratory crushers and tumbling mills; intermediate consumers are impact crushers and vibration mills, and roll crushers are the smallest consumers. The smallest consumers of energy are those machines that apply a steady, continuous, compressive stress on the material.
A class of comminution equipment that does not conform to the assumption that the particle size distributions of a feed and product stream are self-similar includes autogenous mills (AG), semi-autogenous (SAG) mills and high pressure grinding rolls (HPGR). Modeling these machines with energy-based methods requires either recalibrating equations (in the case of the Bond series) or developing entirely new tests that are not confused by the non-standard particle size distributions.
Variability samples must be tested for the relevant metallurgical parameters. Ball mill design requires a Bond work index, BWi, for ball mills at the correct passing size; SAG mill design requires an appropriate SAG test, for example, SPI (Chapter 5). Flotation design needs a valid measure of kinetics for each sample, including the maximum attainable recovery and rate constants for each mineral (Chapter 12). Take care to avoid unnecessary testing for inappropriate parameters, saving the available funds for more variability samples rather than more tests on few samples. Remember that it must be possible to use the measured values for the samples to estimate the metallurgical parameters for the mine blocks in order to describe the ore body, and these estimates will be used in process models to forecast results for the plant. Always include some basic mineralogical examination of each sample.
The expression for computing the power consumption (P) derived theoretically by Rose and English  involved the knowledge of Bonds work index (Wi). To evaluate the work index they considered the maximum size in the feed and also the maximum size of particles in the discharge from the crusher. To determine the size through which 80% of the feed passed, they considered a large database relating the maximum particle size and the undersize. From the relation it was concluded that F80 was approximately equal to 0.7 times the largest size of particle. Taking the largest size of the particle that should be charged to a jaw crusher as 0.9 times the gape, F80 was written as
Also, to establish the P80 from the largest product size, Rose and English considered that the largest particle size discharged from the bottom of the crusher would occur at the maximum open set position and hence
For operating a jaw crusher it is necessary to know the maximum power required consistently with the reduction ratio and the gape and closed side settings. The maximum power drawn in a system will occur at the critical speed. Thus for maximum power, Q in Equation (4.51) is replaced with QM from Equation (4.19) to give
The largest size of ore pieces mined measured 560mm (average) and the smallest sizes averaged 160mm. The density of the ore was 2.8t/m3. The ore had to be crushed in a C-63 type jaw crusher 630 440. At a reduction ratio of 4, 18% of the ore was below the maximum size required. Determine:1.the maximum operating capacity of the crusher,2.the optimum speed at which it should be operated.
Finally, a look should be taken at coal elasticity, hardness and strength. However, a particular matter of importance which arises from those consideration is the ease of coal grinding, an important step in whatever coal preparation efforts for further processing. The more fundamental material properties are covered reasonably by Berkowitz (1994), so the discussion here will be limited to coal grindability. For that purpose, use is made of two different indices, both determined experimentally with the material to be ground. One is the Hardgrove grindability index and the other the Bond work index.
The Hardgrove index is determined using the ASTM method D 40971. It involves grinding 50g of the material, e.g. coal, of specified size (1630 mesh cut) in a specified ball-and-race mill for 60 revolutions. The amount of 200 mesh material is measured (w grams) and the index is defined as I = 13+ 6.93w. Thus, the higher the index, the easier is the grinding task. This method loosely assumes that the specific energy consumed is proportional to the new surface generated, following the concept of Rittingers law of comminution.
Berkowitz (1994 p.96) gives a generalized variation of the Hardgrove index with coal rank. According to the variation, anthracites are hard to grind, bituminous coals the easiest, and the subbituminous more difficult, with lignites down to the same low index level as anthracites. It is suggested that the decrease in the index below daf coal of 85% is caused by plastic deformation and aggregation of the softer coal particles, hence reducing the 200 mesh fraction generated by the grinding test.
The Bond work index (Bond, 1960) is based on Bonds law, which states that the energy consumed is proportional to the 1.5 power of particle size rather than the square of Rittingers law. Accordingly, the energy consumed in reducing the particle size from xF to xp (both measured as 80% undersize) is given by
We should note that the higher the value of the work index, the more difficult it is to grind the material. A compilation of data is available, for example, in Perrys Chemical Engineers Handbook (Perry et al., 1984). For coal, one average value is given, with Ei = 11.37 for = 1.63. Bonds law is useful because of the extensive comparative database.
Interestingly, Hukki (1961) offers a Solomonic settlement between the different grinding theories (rather than laws). A great deal of additional material related to grinding, or size reduction, comminution, is available in handbooks, e.g. by Prasher (1987) and research publications in journals such as Powder Technology. A very brief overview of grinding equipment is given in Section 1.5.3.
Rock fragmentation is a consequence of unstable extension of multiple cracks. Theoretically, rock fragmentation is also a facture mechanics problem. Two major differences between rock fracture and rock fragmentation are that (1) rock fragmentation deals with many cracks, but rock fracture deals with only one or a few, and (2) rock fragmentation concerns the size distribution of the fragments produced, but rock fracture does not. There are two important factors in rock fragmentation: (1) total energy consumed and (2) size distribution of fragments. In a study on crushing and grinding, fracture toughness has been taken as a key index similar to the Bond Work Index. Due to many cracks dealt with, rock fragmentation is a very complicated and difficult fracture problem. To achieve a good fragmentation, we need to know how the energy is distributed, which factors influence energy distribution, what is the size distribution, and so on. In practice such as mining and quarrying, it is of importance to predict and examine size distribution so as to make fragmentation optimized by modifying the blast plan or changing the fragmentation system. About size distribution, there are a number of distribution functions such as Weibulls distribution function , Cunninghams Kuz-Ram model , and the Swebrec function . In engineering practice, how to develop a feasible and simple method to judge rock fragmentation in the field is still a challenging but significant job and will be in the future.
Although the fracture toughness of a rock is very important in rock fracture, the strengths of the rock are also useful in rock engineering. In the following we will see that the strengths and fracture toughness of a rock have a certain relation with each other, partly because of a similar mechanism in the micro-scale failure.
Bong's Work Index is used in Bong's law of comminution energy. It states that the total work useful in breakage is inversely proportional to the length of the formed crack tips and directly proportional to the square root of the formed surface:
where W is the specific energy expenditure in kilowatt-hours per ton and dp and df are the particle size in microns at which 80% of the corresponding product and feed passes through the sieve; CB is a constant depending on the characteristics of materials; and Sp and Sf are the specific surface areas of product and initial feed, respectively. Wi is called Bond's Work Index in kilowatt-hours per ton. It is given by the empirical equation:
where P1 is the sieve opening in microns for the grindability test, Gb.p. (g/rev) is the ball mill grindability, dp is the product particle size in microns (80% of product finer than size P1 passes) and df is the initial feed size in microns (80% of feed passes). A standard ball mill is 305mm in internal diameter and 305mm in internal length charged with 285 balls, as tabulated in Table 2.1. The lowest limit of the total mass of balls is 19.5Kg. The mill is rotated at 70 rev/min. The process is continued until the net mass of undersize produced by revolution becomes a constant Gb.p in the above equation.
To investigate the influence of the coal type on the stampability factor K, stamping tests with eight different coals (C1C8 in Table11.1) were carried out, using the Hardgrove grindability index (HGI) as a measure for the material dependency. The grindability is broadly defined as the response of a material to grinding effort. It can be interpreted as the resistance of the material against particularization. It is not an absolutely measurable physical property of the material. Generally, grindability can be determined either based on product constant fineness method (Bond work index Wi) or on constant useful grinding work method (HGI). The correlation between HGI and Wi can be described by the formula (11.5):
HGI is influenced by the petrographic composition of coal. HGI was developed to find a relationship between petrographic properties and strength of coal particles thus aiming to interpret the coking behavior of coals (Hardgrove 1932). HGI correlates to VM content, and the relationship is empirically specified for most of the hard coals and given with VM from 10% to 38% (db) by Eqs. (11.6) and (11.7):
For the execution of each test, further coal property parameters, particle size distribution and moisture content, as well as the height of fall of the stamp and the number of stamping steps were kept constant, so that the only parameter varied was the coal rank characterized by HGI.
The obtained data of each test was analyzed as described above to calculate the stampability factor K. A higher value for the HGI is equivalent to a lower resistance to stamping, i.e., a better stampability. The determined values of the stampability factor K are plotted against HGI in Fig.11.12.
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Amidst the general fall in metal prices over the last few years, the gold price has remained comparatively stable in the US$1,000-1,250/oz range. Gold bulls were disappointed that the price did not break through the $2,000/oz ceiling; nevertheless the current stable price run has helped to maintain a strong interest in gold projects.
The second is the sustained, and dare I say sustainable, use of cyanide for gold leaching in the last 100 years or more in a world of increasing environmental concerns and general aversion to the use of toxic chemical like cyanide. Alternatives to cyanide are not the subject of this article, but it is suffice to say that recent applications of alternatives to cyanide, e.g. thiosulfate at Goldstrike Nevada, have been driven by technical rather than environmental imperatives. In the case of Goldstrike, this was a double-refractory ore combining sulphide-occluded gold with preg-robbing carbonaceous material that rendered the ore unsuitable for conventional cyanide leaching and carbon adsorption.
In most cases, gold processing with cyanide leaching, usually with carbon adsorption, is still the core technology and the critical thing is understanding the mineralogy in order to optimise flowsheet selection and cost drivers, and get the best out of the process.
Traditionally, the process selection choice was between a conventional, well-tried, three-stage crushing circuit followed by ball milling, or single-stage crushing followed by a semi-autogenous (SAG) mill and ball mill. The latter is preferred for wet sticky ores to minimise transfer point chute blockages, and can offer savings in both capital costs and long-term operating and maintenance costs. However, the SAG route is more power-intensive and, for very hard ores, comes with some process risk in predicting performance.
Now that initial wear issues have largely been overcome, they offer significant advantages over a SAG mill route where power costs are high and the ore is very hard. They can be attractive too in a heap leach where the micro-cracking induced by the high pressure has been demonstrated in many cases to improve heap leach recovery.
The hashing stage (corresponding to metal extraction and recovery stages) is a little more complex for gold ores, as the optimal process flowsheet selection choice is heavily dependent on a good understanding of two fundamental geometallurgical parameters, the gold mineralogical associations, and the gold particle size and liberation characteristics. These are summarised in Table 2, where the processing options that correspond to the various combinations of mineral associations and liberation are shown along with some examples.
This is common in tropical environments (e.g. West Africa) and typically oxidises gold-bearing sulphides down to 50-100m, transforming commonly refractory gold in sulphides to free-milling gold, behaving in a similar fashion to gold associated with quartz.
Refractory ores are typically treated by flotation and the resulting flotation concentrate may be sold directly to a smelter (common for example in China) or subjected to downstream processing by pressure oxidation or bio-leach.
An ore containing 1% sulphur will produce a mass pull of approximately 5% by weight to a bulk flotation concentrate where recovery is the key driver. If this ore also contains 1g/t Au (for GSR =1), and 90% recovery to concentrate is achieved, then 0.90g will be recovered and with a concentration ratio of 20 (5% to concentrate) this corresponds to 18g/t Au in concentrate.
Both smelter treatment charges and oxidation or bio-leach costs are at least $200/t of concentrate and payables/recovery in the 90% range, so a minimum GSR for effective downstream processing is around 0.5. Clearly this is a function of gold price, but in the current gold price and cost environment, a good rule of thumb is that a minimum GSR of 0.5 is required for downstream processing of a gold-bearing concentrate.
A lower GSR can be tolerated if the flotation concentrate is amenable to direct cyanide leaching without the costly oxidation stage to release the gold from the sulphides. And on-site dor production avoids the off-site costs of transport and smelter charges, but usually with lower recovery (flotation recovery then oxidation-leach recovery) so a trade-off analysis is required.
Smelters typically pay >95% (Au) and 90% (Ag) in copper and lead concentrates, but will only pay 60-70% (maximum, depending on degree of Pb/Zn smelter integration) for gold and silver in zinc concentrates.
It can be seen that the key cost elements are: power, cyanide and grinding steel plus, for refractory ores, the costs associated with pressure oxidation or bio-leaching. It should also be noted that, where cyanide destruction is required (increasingly the norm), then cyanide detox unit costs are usually of a similar order of magnitude to the cyanide unit cost.
In summary, and of particular relevance to project screening, an early appreciation of gold mineralogical associations and liberation can provide considerable insight into metallurgical process flowsheet selection and processing costs.
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