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Optimal Preventive Maintenance Planning for Water Spray System of Drum Shearer
IFAC Workshop on Mining, Minerals and Metal Processing IFAC Workshop Workshop on Mining, Mining, Minerals and and Metal Metal Processing Processing IFAC on Minerals August 25-28, 2015. Oulu, Finland IFAC Workshop on Minerals Metal IFAC Workshop on Mining, Mining, Minerals and and Metal Processing Processing Available online at www.sciencedirect.com August 25-28, 2015. 2015. Oulu, Finland Finland August 25-28, Oulu, August August 25-28, 25-28, 2015. 2015. Oulu, Oulu, Finland Finland
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Optimal Preventive Maintenance Planning for Water Spray System Optimal Planning for Water Spray System Optimal Preventive Preventive Maintenance Maintenance of DrumPlanning Shearer for Water Spray System of of Drum Drum Shearer Shearer
S. H. Hoseinie*, B. Ghodrati**, D. Galar ***, E. Juuso**** S. D. S. H. H. Hoseinie*, Hoseinie*, B. B. Ghodrati**, Ghodrati**, D. Galar Galar ***, ***, E. E. Juuso**** Juuso**** S. H. D. S. H. Hoseinie*, Hoseinie*, B. B. Ghodrati**, Ghodrati**, D. Galar Galar ***, ***, E. E. Juuso**** Juuso**** *Division of Operation & Maintenance Engineering, Lulea University of Technology, Lulea, Sweden and *Division of Operation & Maintenance Engineering, University of Technology, Lulea, Sweden and *Division of Operation & Maintenance Engineering, Lulea University of Technology, Lulea, Sweden and Department of Mining Engineering, HamedanLulea University of Technology, Hamedan, *Division of & Engineering, Lulea University of Lulea, Sweden *Division of Operation Operation & Maintenance Maintenance Engineering, Lulea University of Technology, Technology, Lulea,Iran Sweden and and Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran (e-mail: [email protected]). Department of of Mining Mining Engineering, Engineering, Hamedan Hamedan University University of of Technology, Technology, Hamedan, Hamedan, Iran Iran Department (e-mail: [email protected]). (e-mail: [email protected]). Engineering, Lulea University of Technology, Lulea, Sweden ** Division of Operation & Maintenance (e-mail: [email protected]). (e-mail: [email protected]). Division of Operation & Maintenance Engineering, ** (e-mail:[email protected]) Division of of Operation Operation & & Maintenance Maintenance Engineering, Engineering, Lulea Lulea University University of of Technology, Technology, Lulea, Lulea, Sweden Sweden ** Division Lulea University of Technology, Lulea, Sweden ** (e-mail:[email protected]) (e-mail:[email protected]) *** Division of Operation & Maintenance Engineering, Lulea University of Technology, Lulea, Sweden (e-mail:[email protected]) (e-mail:[email protected]) *** Division Division of of Operation Operation & & Maintenance Maintenance Engineering, Lulea University University of of Technology, Technology, Lulea, Lulea, Sweden Sweden *** Engineering, Lulea (e-mail: [email protected]) *** Engineering, Lulea *** Division Division of of Operation Operation & & Maintenance Maintenance Engineering, Lulea University University of of Technology, Technology, Lulea, Lulea, Sweden Sweden (e-mail: [email protected]) (e-mail: [email protected]) **** Control Engineering Group, Faculty of Technology, University of Oulu, Finland (e-mail: [email protected]) (e-mail: [email protected]) **** Control Control Engineering Engineering Group, Group, Faculty of Technology, Technology, University University of of Oulu, Oulu, Finland Finland **** Faculty of (e-mail: [email protected]) **** Faculty of **** Control Control Engineering Engineering Group, Group, Faculty of Technology, Technology, University University of of Oulu, Oulu, Finland Finland (e-mail: [email protected]) (e-mail: [email protected]) (e-mail: (e-mail: [email protected]) [email protected])
Abstract: Water spray system is one of the most important parts of rock cutting machines, especially the Abstract: Water spray one of the most important of rock cutting machines, the Abstract: Water spray system is one of the most important parts of rock cutting machines, especially the drum shearer. Field datasystem showsis that the maintenance of thisparts system is time-consuming and especially causes major Abstract: Water spray system is one of the most parts of cutting especially the Abstract: Water spray system isthat onethe of maintenance the most important important parts of rock rock cutting machines, machines, especially the drum shearer. Field data shows of this system is time-consuming and causes major drum shearer. Field data shows that the maintenance of this system is time-consuming and causes major downtimes in the coal mines’ production process. Therefore, it is essential to find an optimum preventive drum shearer. Field data shows that the maintenance of this system is time-consuming and causes major drum shearer. Field data shows that the maintenance of this system is time-consuming and causes major downtimes the coal production process. Therefore, it is find an optimum preventive downtimes in the coal mines’ production process. Therefore, it is essential essential to find an optimum preventive maintenancein task andmines’ intervals, to reduce the downtime and minimizeto the associated costs of the downtimes in the mines’ production process. Therefore, it to find an preventive downtimes in task the coal coal mines’ production process. Therefore, and it is is essential essential tothe findassociated an optimum optimum preventive maintenance and intervals, to reduce the downtime minimize costs of the maintenance task and intervals, to reduce the downtime and minimize the associated costs of machine. In this paper, in order to suggest an optimum preventive maintenance plan, a parametric failure maintenance task task and and intervals, intervals, to to reduce reduce the the downtime downtime and and minimize minimize the the associated associated costs costs of of the the maintenance the machine. In this paper, in order to suggest an optimum preventive maintenance plan, a parametric failure machine. In this paper, in order to suggest an optimum preventive maintenance plan, a parametric failure and reliability analysis was doneto onsuggest available data from preventive an Iranian longwall coalplan, mineaaover the twofailure years. machine. In this paper, in order an optimum maintenance parametric machine. In this paper, in order to suggest an optimum preventive maintenance plan, parametric failure and reliability analysis analysis was done on on was available data from fromtoan anidentify Iranianthe longwall coalmaintenance mine over over the theinterval two years. years. and reliability done available data Iranian longwall coal mine two A reliability-based costwas modelling implemented optimum and and reliability was done available data Iranian longwall coal mine two and reliability analysis analysis was done on on was available data from fromtoan anidentify Iranianthe longwall coalmaintenance mine over over the theinterval two years. years. A reliability-based cost modelling implemented optimum and A reliability-based cost modelling was implemented to identify the optimum maintenance interval and frequencies of restoration for the water spray system. In the study, a cost rate function was introduced in A reliability-based cost modelling was implemented to identify the optimum maintenance interval and A reliability-based cost modelling was spray implemented to the identify the optimum maintenance interval and frequencies of restoration for the water system. In study, aa cost rate function was introduced in frequencies of restoration for the water spray system. In the study, cost rate function was introduced in which an as-good-as-new effectiveness for restoration actions is considered. The results of the analysis frequencies of restoration for the water spray system. In the study, a cost rate function was introduced in frequencies of restoration for the water spray system. Inactions the study, a cost rate The function wasofintroduced in which an as-good-as-new effectiveness for restoration results the which anthat as-good-as-new effectiveness for restoration actions is considered. The results of the analysis analysis showed the minimum maintenance cost per unit of time for is theconsidered. studied machine, $19.54/hour, will be which as-good-as-new effectiveness for actions is considered. The of which an anthat as-good-as-new effectivenesscost for restoration restoration actions is considered. The results results of the the analysis analysis showed the minimum maintenance per unit of time for the studied machine, $19.54/hour, will be showed the per unit for the achievedthat within a range of maintenance intervals i.e. cost T=136 to time T=142 showed that the minimum minimum maintenance cost perhours unit of of time forhours. the studied studied machine, machine, $19.54/hour, $19.54/hour, will will be be showed that the minimum maintenance cost per unit of time for the studied machine, $19.54/hour, will be achieved within aa range of intervals i.e. T=136 hours to T=142 hours. achieved within range of intervals i.e. T=136 hours to T=142 hours. achieved within a range of intervals i.e. T=136 hours to T=142 hours. achieved within a range of intervals i.e. T=136 hours to T=142 hours. © 2015, IFAC (International Federation of Automatic Control) Hosting bywater Elsevier Ltd. All rights reserved. Keywords: Cost modelling, Drum shearer, Maintenance optimization, spray system. Keywords: Cost modelling, Drum shearer, Maintenance optimization, water spray system. Keywords: Cost modelling, Drum shearer, Maintenance optimization, water spray system. Keywords: optimization, Keywords: Cost Cost modelling, modelling, Drum Drum shearer, shearer, Maintenance Maintenance optimization, water water spray spray system. system. safety and continuous operation. In longwall mining, the coal 1. INTRODUCTION safety and continuous In longwall mining, the coal safety and continuous operation. In longwall mining, the coal is usually mined by a operation. machine called a "drum shearer". It is 1. INTRODUCTION INTRODUCTION safety and continuous operation. In longwall mining, the coal 1. safety and continuous operation. In longwall mining, the coal is usually mined by a machine called a "drum shearer". It is 1. INTRODUCTION is usually mined by a machine called a "drum shearer". 1. INTRODUCTION an electrically driven hydraulic machine and is used to extract is usually usually mined mined by by aa machine machine called called aa "drum "drum shearer". shearer". It It is is Maintenance costs make up a major part of mining operation an is It is electrically driven hydraulic machine and is used to extract an electrically driven hydraulic machine and is used to extract Maintenance costs make up a major part of mining operation coal seams of 1.5 to 4 metres in thickness (Hartman, 1992). Maintenance costs make up a major part of mining operation an electrically driven hydraulic machine and is used to extract costs. Several reports have been published on the contribution an electrically driven hydraulic machine and is used to extract Maintenance costs make up a major part of mining operation Maintenance make upbeen a major part ofonmining operation The coal seams ofcoal 1.5 to 4 metres in thickness (Hartman, 1992). costs. Severalcosts reports have published the contribution contribution models are designed with different costs. Several reports been published on the coal seams 1.5 to in (Hartman, 1992). of maintenance costs have in mining. Unger and Conway (1994) The coal different seams of ofcoal 1.5 shearer to 4 4 metres metres in thickness thickness (Hartman, 1992). costs. Several reports have been published on the contribution costs. Several reports have been published on the contribution different shearer models are designed with different The different coal shearer models are designed with different of maintenance maintenance costs in mining. mining.costs Ungerofand and Conway (1994) The dimensions and power output depending on the manufacturer. of costs in Unger Conway (1994) different coal shearer models are designed with different declared that the maintenance mining equipment The different coal shearer models are designed with different of maintenance costs in mining. Unger and Conway (1994) of maintenance costs in mining.costs Ungerofand Conway (1994) dimensions dimensions andmost powerofoutput output depending on the the manufacturer. manufacturer. and power on declared that the maintenance mining equipment Nevertheless, the depending shearers consist of six main declared that the maintenance costs of mining equipment and power depending on range from 20% to over 35% the total mine dimensions dimensions andmost powerofoutput output depending on the the manufacturer. manufacturer. declared that the costs of mining equipment declared thataround the maintenance maintenance costs of of mining equipment Nevertheless, the shearers consist of six sixcutting main Nevertheless, most of the shearers consist of main range from around 20% to over 35% of the total mine subsystems: the electrical system, hydraulic system, range from around 20% to over 35% of the total mine Nevertheless, most of the shearers consist of main operating costs. In open-pit mines in both Chile and Nevertheless, most of thesystem, shearers consistsystem, of six sixcutting main range from around 20% to 35% the mine range fromcosts. around 20% to over over 35%in of ofboth the total total mine subsystems: the electrical hydraulic subsystems: the electrical system, hydraulic system, cutting operating In open-pit mines Chile and arms, cable system, water system and haulage system operating costs. In open-pit mines in both Chile and subsystems: the electrical system, hydraulic system, cutting Indonesia, the maintenance costs represent more than 60% of subsystems: the electrical system, hydraulic system, cutting operating costs. In open-pit mines in both Chile and operating costs. In open-pit mines in both Chile and arms, cable system, water system and haulage system arms, cable system, water system haulage system Indonesia, the maintenance represent more than 60% of (Hoseinie, 2011, Hoseinie et al. 2012).and A field investigation cable system, water system and haulage system the operating (Hall et costs al., 2000, Carnbell, 1997). arms, cable system, water system and haulage system Indonesia, the maintenance costs represent more 60% of Indonesia, the cost maintenance costs represent more than than 60%The of arms, (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation the operating cost (Hall et al., 2000, Carnbell, 1997). The has shown that the water system is the most critical the operating cost (Hall et al., 2000, Carnbell, 1997). The (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation corresponding value for the open-pit mines of Canada and (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation the operating operating cost cost (Hall (Hall et et al., al., 2000, 2000, Carnbell, Carnbell, 1997). 1997). The The has the shown that the water system is the most critical the is corresponding value45%, for the the open-pit mines of of Canada Canada and subsystem shearers and issystem responsible 30% critical of the corresponding value for mines has shown shownofthat that the water water system is the thefor most most critical Australia is about and open-pit for the underground minesand of has has shown that the water system is the most critical corresponding value for open-pit mines and corresponding value45%, for the the open-pit mines of of Canada Canada and subsystem of shearers and is responsible for 30% of the Australia is about and for the underground mines of machine failures (Hoseinie et al. 2011). The water system of Australia is about 45%, and for the underground mines of subsystem of and for 30% of Canada it is less than 35%and (Carnbell, 1997, Hall, 1997). Hall subsystem of shearers shearers andetis isal.responsible responsible for 30% of the the Australia about 45%, for the underground mines of Australia is about 45%, and for the underground mines of machine failures (Hoseinie 2011). The water system of machine failures (Hoseinie et al. 2011). The water system of Canada it is less than 35% (Carnbell, 1997, Hall, 1997). Hall the shearer operationally consists of three subsystems: water Canada it is less than 35% (Carnbell, 1997, Hall, 1997). Hall machine failures (Hoseinie et The water of (1997) investigations the maintenance machine failures (Hoseinie et al. al. 2011). 2011). The water system system of Canada it less 35% (Carnbell, 1997, 1997). Canadahas it is isconcluded less than than from 35% his (Carnbell, 1997, Hall, Hall, 1997). Hall Hall the the shearer operationally consists of three subsystems: water shearer operationally consists of three subsystems: water (1997) has concluded from his investigations the maintenance spray jets, valves and hoses. Water spraysubsystems: system cools the (1997) has concluded from his investigations the maintenance the shearer operationally consists of three water accounts for 30% to 65% of the overall operating cost budget the shearer operationally consists of three subsystems: water (1997) has concluded from his investigations the maintenance (1997) hasforconcluded fromofhis investigations the maintenance spray jets, valves and hoses. hoses. Water spray system system cools the the jets, valves and Water spray cools accounts 30% to 65% the operating cost budget cutting picks and controls the dust emission. The blockage of accounts for 30% to 65% of the overall overall operating cost budget spray jets, valves and Water spray cools for a typical mining company. According to Forsman and spray spray jets, valves and hoses. hoses. Water spray system system cools the the accounts for to of operating cost accounts for 30% 30% to 65% 65% of the the overall overall operating cost budget budget cutting picks and controls the dust emission. The blockage of cutting picks and controls the dust emission. The blockage of for a typical mining company. According to Forsman and the spray system causes the drum shearer machine to stop for a typical mining company. According to Forsman and cutting picks and controls the dust emission. The blockage of Kumar (1992), the cost of maintenance in the mining industry picks and controls the dust emission. The blockage of for mining company. According to Forsman and for aa typical typical mining company. According tomining Forsman and cutting the spray system causes the drum shearer machine to stop the spray system causes the drum shearer machine to stop Kumar (1992), the cost of maintenance in the industry automatically. Therefore, the reliable performance of this the spray system causes the drum shearer machine to stop varies from 40% to 50% of the equipment operating costs. the spray system causes the drum shearer machine to stop Kumar (1992), the cost of maintenance in the mining industry Kumar (1992), the cost of maintenance in the mining industry automatically. Therefore, the reliable performance of this automatically. Therefore, the performance this varies from 40% to 50% 50% of ofcoal the equipment equipment operating costs. assists the achievement of a continuous coal of cutting varies from to the automatically. Therefore, the reliable reliable performance of this Focusing on40% underground mining as operating a special costs. case, system automatically. Therefore, the reliable performance of this varies from 40% to the operating costs. varies from 40% to 50% 50% of ofcoal the equipment equipment operating costs. system assists the achievement of aa continuous coal cutting system assists the achievement of continuous coal cutting Focusing on underground mining as a special case, operation. The water spray system is a repairable item which Focusing on underground coal mining as a special case, system assists the achievement of a continuous coal cutting studies show that approximately 10% of the production time system assists the achievement of a continuous coal cutting Focusing on underground coal mining as a special case, Focusing on that underground coal 10% mining as production a special case, The water spray system is repairable which studies show approximately of the the time operation. is located on cutting drum surface which item contributes studies that approximately 10% of time operation. Thethe water spray system is aaa and repairable item which is lost show through unplanned maintenance in production the Australian operation. The water spray system is repairable item which studies show that approximately 10% of the production time studies show that approximately 10% of the production time is located on the cutting drum surface and which contributes is located on the cutting drum surface and which contributes is lost through through unplanned maintenance in 1990), the Australian Australian to 40% ofon thethe failures ofdrum the surface water system (Hoseinie et al. is lost unplanned maintenance in the is located cutting and which contributes underground coal mining industry (Clark, and that is located on the cutting drum surface and which contributes is lost through unplanned maintenance in the Australian is lost through unplanned maintenance in 1990), the Australian to 40%After of the the failures of the the water water systemsatisfactorily, (Hoseinie et et the al. to 40% of failures of system (Hoseinie al. underground coal mining industry (Clark, and that 2011). failing to perform its functions underground coal mining industry (Clark, 1990), and that to 40% of the failures of the water system (Hoseinie al. over 25% of the underground mining 40%After of the failures of the water systemsatisfactorily, (Hoseinie et et the al. underground coal mining industry (Clark, 1990), and that underground coalaccidents mining in industry (Clark,coal 1990), andoccur that to 2011). failing to perform its functions 2011). After failing to perform its functions satisfactorily, the over 25% of the accidents in underground coal mining occur spray jet can be restored to a satisfactory level of over 25% of the accidents in underground coal mining occur 2011). After failing to perform its functions satisfactorily, the during maintenance activities. 2011). After failing to perform its functions satisfactorily, the over 25% of the accidents in underground coal mining occur over 25% of the accidents in underground coal mining occur spray jet can can be be restored restored to to aa satisfactory satisfactory level level of of spray jet during maintenance activities. performance. during maintenance activities. spray jet can be restored to a satisfactory level spray jet can be restored to a satisfactory level of of during maintenance activities. during maintenance activities. performance. Longwall coal mining is a well-known mining method performance. performance. performance. Longwall coal mining is a well-known mining method aim of this study is to determine a cost effective because offers high is productivity, high mining mechanization, Longwallit coal coal mining is well-known mining method The Longwall mining aa well-known method The aim ofmaintenance this study is to determine aa cost effective The aim is cost because it offers offers high productivity, productivity, high mechanization, mechanization, preventive for management of the because it high high The aim of of this this study study interval, is to to determine determine cost effective effective The aim of this study is to determine aa cost effective because because it it offers offers high high productivity, productivity, high high mechanization, mechanization, preventive maintenance interval, for management of preventive maintenance interval, for management of the the preventive preventive maintenance maintenance interval, interval, for for management management of of the the
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failure modes of the spray jets of coal shearers in an Iranian longwall coal mine. Therefore, reliability-based cost modeling has been implemented to identify the optimum maintenance interval and frequencies of restoration for the spray jets, and thereby minimize the cost per unit of operating time. In the study, a cost rate function (CRF) has been developed in which an as-good-as-new (AGAN) effectiveness for restoration actions is considered. The CRF also considers restoration and repair times, and takes into account the costs associated with repair and restoration, and the opportunity cost of the equipment’s lost production due to maintenance downtime (i.e., scheduled and unscheduled maintenance), to arrive at the most cost-effective maintenance intervals.
167
2. CASE STUDY; WATER SPRAY SYSTEM OF DRUM SHEARER This paper documents a case study on a shearer machine in an Iranian longwall coal mine. The total power of this shearer is 600 kW and the supply voltage is 1100 V. The cutting head of the drum shearer has a diameter of 1600 mm and a maximum cutting depth of 800 mm, and it is provided with a number of picks and spraying nozzles. The spraying nozzles are mounted inside the tool holders behind the cutting picks. The spraying system is designed for operation with a maximum working pressure of 150bar. The system consists of the following elements: 33 seat units which are provided with spraying nozzles with a diameter of 0.6 mm, 18 nozzle units which are built onto the body, and 15 remaining nozzle units which are built onto the cutting drum.
2. MAINTENANCE OF REPAIRABLE SYSTEMS A repairable system is a system which, after failing to perform one or more of its functions satisfactorily, can be restored to fully satisfactory performance by any method other than the replacement of the entire system (Ascher and Feingold, 1984). The quality or effectiveness of the repair action is categorized as follows (Ascher and Feingold, 1984, Rausand and Høyland, 2004, Modarres, 2006): 1) Perfect repair, i.e. restoring the system to the original state, to a “like–new” condition, 2) Minimal repair, i.e. restoring the system to any “like-old” condition, and 3) Normal repair, i.e. restoring the system to any condition between the conditions achieved by perfect and minimal repair.
2.1. Statistical analysis of failure data The data required for this study was collected from operation and maintenance reports and direct field observations over a period of two years. Most of the desired information, such as the failure occurrence times, failure modes, types of repair actions and time to repair (TTR), was available in the mine database and only the time between failures (TBF) were calculated. The results of the trend and serial correlation tests performed on the TBF data showed that the data is free of trend and serial correlation. Thus, data is iid, and consequently the renewal process is the best method for the failure analysis and modelling of this system.
Based on the quality and effectiveness of the repair action, a repairable system may end up in one of the following five possible states after repair (Ascher and Feingold, 1984, Rausand and Høyland, 2004, Modarres, 2006): as good as new; as bad as old; better than old but worse than new; better than new and worse than old.
In order to find the best fitted distribution, different types of statistical distributions were tested on the data using the Weibull++ and Easyfit software. The Kolmogorov-Smirnov (K-S) test was used for selecting the best distribution. The results of the data analysis show that the three-parameter Weibull (Weibull-3P) distribution with the scale parameter of α=233.28, the shape parameter β=2.49 and the location parameter γ=-43.32 is the best-fitted function for the available TBF data (Fig. 1 and Table 1). The calculations show that the reliability of the spray jets reaches zero after about 430 hours of operation.
While perfect repair rejuvenates the unit to the original condition, i.e., to an AGAN condition, minimal repair brings the unit to its previous state just before repair, i.e., an as-badas-old condition, and normal repair restores the unit to any condition between the conditions achieved by perfect and minimal repair, i.e., a better-than-old but worse-than-new condition. However, states four and five may also happen. For example, if through a repair action a major modification takes place in the unit, it may end up in a condition better than new, and if a repair action causes some error or an incomplete repair is carried out, the unit may end up in a worse-than-old condition. Failures occurring in repairable systems are the result of discrete events occurring over time. These processes are often called stochastic point processes (Modarres, 2006). The stochastic point process is used to model the reliability of repairable systems, and the analysis includes the homogenous Poisson process (HPP), the renewal process (RP), and the non-homogenous Poisson process (NHPP). A renewal process is a counting process where the inter-occurrence times are independent and identically distributed (iid) with an arbitrary life distribution (Ascher and Feingold, 1984, Ebeling, 2009). Upon failure, the component is thus replaced or restored to an as good as new condition.
Fig. 1. Failure data and best fitted failure density function 2.2. Cost rate modelling Based on the field experience and machine’s catalogues the following combination of restoration and servicing tasks are 167
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currently done in case study mine:
2) The component is fully functional after scheduled and unscheduled restoration.
1) Cleaning the spray jets to remove dust and mud from the nozzles.
3) There is no safety risk related to failures. Therefore, only operational and economic consequences are considered for the cost analysis of failures and maintenance.
2) Replacing the broken nozzle heads during the restoration task.
4) The shearer operates continuously and the failure of water spray systems interrupts the planned production.
Table 1. Results data analysis and best fitted distribution Distribution Weibull (3P)
Gamma (3P) Lognormal (3P) Gamma Normal
K-S test 0.122
Best fitted distribution Weibull-3P α = 233.28 β = 2.49 γ = -43.32
The following parameters are considered in the developed cost rate model: 1) Cost of unscheduled restoration (corrective restoration) (Ccr): This is a constant and deterministic value which includes the direct cost of unplanned restoration (corrective maintenance) due to each probable failure within the restoration cycle and the respective indirect costs of shipping, man-hours, etc. In fact, it is the failure cost of the system.
0.1225 0.128 0.130 0.134
2) Cost of scheduled restoration (CRes): This is a constant and deterministic value which includes the direct cost of preventive restoration and, like the cost of repair, also consists of indirect costs for shipping, man-hours, etc.
For this purpose, the nozzle must be screwed out and cleaned and serviced according to the maintenance procedure. However, the main question still remains, namely how to define the most effective restoration interval, which is the concern of the next section.
3) Opportunity cost of the machine's lost production (CLp.res) and (CLp.rep): This cost is associated with the total machine downtime due to each type of maintenance operation (scheduled and unscheduled restoration), i.e. TR (constant values). CLp.res is the opportunity cost due to preventive restoration and CLp.rep is the opportunity cost due to repair.
Fig. 2 shows a schematic description of the maintenance events. As can be seen in the figure, the shearer machine should be stopped to perform the restoration task after “T” accumulated cutting hours. It should be noted that T only refers to the cutting time and that the time during which the machine is working but not cutting is not used in the maintenance modelling. The first restoration is performed after “T” cutting hours.
In fact, two scenarios may happen. Either the spray jet will survive until its scheduled restoration time (T), making a cycle which we call a scheduled cycle, or it will fail before its scheduled restoration time, making a cycle which we call an unscheduled cycle. Hence, the expected restoration cost per cycle is formulated as (1): Cost T ( C Re s+C Lp ) R (T )+ ( C Cr +C Lp ) [1-R (T )]
(1)
Where: T: Inspection interval Fig. 2. Purposed restoration cycle for cost modelling of water spray system
CostT: Total cost of maintenance per cycle
Since the failure behaviour of the spray jets is iid, this restoration cycle will be repeated every T hours and consequently the Nth restoration will be performed after “N.T” operating hours. The whole restoration task takes TR hours. Hence, a restoration cycle time includes T +TR.
CCr: Cost of unscheduled restoration within any Nth cycle interval
CRes: Cost of restoration within any Nth cycle interval
CLp: Cost of lost production due to restoration actions The maintenance cost per unit of operating time, considering restoration every T hrs, can be expressed as (2):
Considering the iid behaviour of system and this assumption that the repair/restoration task rejuvenates the system to the original state, i.e. a like–new condition; all the restoration cycles will be identical. Therefore, when optimizing the restoration interval, it is sufficient to consider one cycle.
Cost
T
(C
Re s
+C
Lp
) R (T )+ ( C
Cr
+C
Lp
) [1-R (T )]
(2)
Expected c ycle lengt h
The analytical model presented in this paper is based on the following assumptions:
Similarly, the expected cycle length can be estimated as follows:
1) The failures are evident.
(Length of a scheduled cycle × probability of a scheduled 168
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cycle) + (Length of an unscheduled cycle × probability of an unscheduled cycle)
performance per shift on average (Hoseinie et al. 2014). Therefore, one week of operation is equal to 48.6 hours. On the basis of Figure 2, the maintenance cost related to T=48.6 hrs is $33.29/hour. This value shows that the current maintenance schedule in the case study mine is very expensive and almost 1.7 times higher than the optimum cost ($19.54/hour). Therefore, the preventive maintenance scheduling should be changed in this mine.
Finally, the associated maintenance cost function of the spray jets can be expressed as (3): C
Total
(C
Re s
C
Lp .res
) R (T ) ( C
Cr
C
Lp .Cr
) 1 - R (T )
169
(3)
T T R (T ) tf ( t ) dt 0
3. CONCLUSIONS In this paper, the optimum maintenance scheduling for the water spray system of a drum shearer has been identified using an optimization methodology. The field data collected from an Iranian coal mine in Iran shows that the TBFs of this system are iid and the maintenance quality is as good as new. Therefore, the renewal process was selected for the reliability analysis. The data analysis showed that the TBF data follow a Weibull 3P distribution.
The optimum restoration interval (T), which minimizes the total cost of maintenance, can be achieved by the derivation of equation (3). Nevertheless, the above equation cannot be solved parametrically in an easy way. Therefore, the graphical method was used for finding the optimum T. 2.3. Optimal maintenance interval
Based on the field experiments and the design characteristics of the spray jets, restoration was selected as the maintenance policy for this system. Then a cost model was established to analyse the maintenance cost and determine the optimum restoration intervals. The optimum restoration intervals for the water spray system of the shearer machine can be selected in the period of 136 to 142. This function has a minimum value (= $19.54/hour) in the period of T=136 hrs to T=142 hrs.
The actual financial data from studied mine showed that the deterministic values for the cost parameters during 2014 are: Cres=$62.5, CCr=$38, CLp.res=$1345 and CLp.Cr=$2690. The Microsoft Excel™ software was used to enable variation of the parameters of equation (3), to identify the cost per unit of time for different values of T. Fig. 3 shows the Ctotal (the cost per unit of time) for different values of T, under the restoration strategy and based on the reliability parameter obtained from Section 2.1 and the cost parameters mentioned above.
REFERENCES Ascher, H. and Feingold, H., (1984), Repairable Systems Reliability: Modeling, Inference, Misconceptions and their Causes, Marcel Dekker, New York, USA. Carnbell, J. D., (1997), Global maintenance benchmarking, Presentation at UOA/MIAC Mining Learning Seminar #3-Mine Maintenance, University of Alberta, Edmonton, Canada. Clark, D., (1990), Tribology — Its application to equipment reliability and maintainability design in the underground coal mining industry, in Proc. Institution of Engineers Australia Tribology Conf., pp. 38–44. Ebeling, C. E., (2nd ed.), (2009). An Introduction to Reliability and Maintainability Engineering, Waveland Press Inc., Illinois, USA, p. 550. Forsman, B. O. and Kumar, U., (1992), Surface mining equipment and maintenance trends in the Scandinavian countries, J. Mines Metals Fuels 40, pp. 266–269. Hall, R., Danshmend, L. K., Lipsett, M. G. and J. Wong (2000), Reliability analysis as a tool for surface mining equipment evaluation and selection, CIM Bull. 93: pp. 78–82. Hall, R., (1997), Analysis of mobile equipment maintenance data in an underground mine, M.Sc. thesis, Department of Mechanical Engineering, Queen’s University, Kingston, Ontario, Canada. Hamilton, D. D., Hopper, J. E. and Jones, J. H. (1979), Inherently Safe Mining Systems: Executive Summary, Report No. USBM OFR 124-77, US Bureau of Mines, Washington, USA.
Fig. 3. The CTotal for different values of the restoration interval (T) It can be concluded from Fig. 3 that, the total cost of maintenance (CTotal) decreases with an increase in T until T=136. This function has a minimum value (= $19.54/hour) in the period of T=136 to T=142. After T=142, the total cost starts to increase again. Therefore, the optimum restoration intervals for the water spray system of the drum shearer machine can be selected in the period of 136 to 142. However, at present the spraying system is preventively maintained every Friday. According to the performance records of the machine, the shearer has 2.71 hours of useful 169
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Hartman, H. L., (1992), SME Handbook of mining engineering, 2nd edition, Society of Mining, Metallurgy and Exploration, USA. Hoseinie S. H., (2011), Modeling and Simulation of Drum Shearers' Reliability at Mechanized Longwall Minescase study: Tabas Coal Mine, PhD Thesis, Shahrood University of Technology, Shahrood, Iran (in Persian). Hoseinie, S. H., Ataei, M., Khalokakaie, R., and Kumar, U., (2011), Reliability modelling of water system of longwall shearer machine. Archive of Mining Science, Vol. 56, No. 2, pp. 291–302. Hoseinie, S. H., Ataei, M., Khalokakaie, R., Ghodrati, B. and Kumar, U., (2012), Reliability Analysis of Drum Shearer Machine at Mechanized Longwall Mines, Journal of Quality in Maintenance Engineering, Vol. 18 No. 1, pp. 98-119. Hoseinie, S. H., Ghodrati, B. and Kumar, U., (2014), Assessment of Reliability-Related Measures for Drum Shearer Machine, a Case Study, Sixth International Symposium High Performance Mining (AIMS 2014), 11-12 June, Aachen, Germany. Modarres, M., (2006), Risk Analysis in Engineering: Techniques, Tools, and Trends, New York: Taylor & Francis, 2006. Rausand, M. and Høyland, A., (2004), System Reliability Theory: Models, Statistical Methods and Applications, Hoboken, N.J.: John Wiley. Unger, R. L. and Conway, K. (1994), Impact of maintainability design on injury rates and maintenance costs for underground mining equipment, in Improving Safety at Small Underground Mines, compiled by R. H. Peters, Report No. Special Publication 18–94, US Bureau of Mines, Washington, pp. 140–167.
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Optimal Preventive Maintenance Planning for Water Spray System Optimal Planning for Water Spray System Optimal Preventive Preventive Maintenance Maintenance of DrumPlanning Shearer for Water Spray System of of Drum Drum Shearer Shearer
S. H. Hoseinie*, B. Ghodrati**, D. Galar ***, E. Juuso**** S. D. S. H. H. Hoseinie*, Hoseinie*, B. B. Ghodrati**, Ghodrati**, D. Galar Galar ***, ***, E. E. Juuso**** Juuso**** S. H. D. S. H. Hoseinie*, Hoseinie*, B. B. Ghodrati**, Ghodrati**, D. Galar Galar ***, ***, E. E. Juuso**** Juuso**** *Division of Operation & Maintenance Engineering, Lulea University of Technology, Lulea, Sweden and *Division of Operation & Maintenance Engineering, University of Technology, Lulea, Sweden and *Division of Operation & Maintenance Engineering, Lulea University of Technology, Lulea, Sweden and Department of Mining Engineering, HamedanLulea University of Technology, Hamedan, *Division of & Engineering, Lulea University of Lulea, Sweden *Division of Operation Operation & Maintenance Maintenance Engineering, Lulea University of Technology, Technology, Lulea,Iran Sweden and and Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran (e-mail: [email protected]). Department of of Mining Mining Engineering, Engineering, Hamedan Hamedan University University of of Technology, Technology, Hamedan, Hamedan, Iran Iran Department (e-mail: [email protected]). (e-mail: [email protected]). Engineering, Lulea University of Technology, Lulea, Sweden ** Division of Operation & Maintenance (e-mail: [email protected]). (e-mail: [email protected]). Division of Operation & Maintenance Engineering, ** (e-mail:[email protected]) Division of of Operation Operation & & Maintenance Maintenance Engineering, Engineering, Lulea Lulea University University of of Technology, Technology, Lulea, Lulea, Sweden Sweden ** Division Lulea University of Technology, Lulea, Sweden ** (e-mail:[email protected]) (e-mail:[email protected]) *** Division of Operation & Maintenance Engineering, Lulea University of Technology, Lulea, Sweden (e-mail:[email protected]) (e-mail:[email protected]) *** Division Division of of Operation Operation & & Maintenance Maintenance Engineering, Lulea University University of of Technology, Technology, Lulea, Lulea, Sweden Sweden *** Engineering, Lulea (e-mail: [email protected]) *** Engineering, Lulea *** Division Division of of Operation Operation & & Maintenance Maintenance Engineering, Lulea University University of of Technology, Technology, Lulea, Lulea, Sweden Sweden (e-mail: [email protected]) (e-mail: [email protected]) **** Control Engineering Group, Faculty of Technology, University of Oulu, Finland (e-mail: [email protected]) (e-mail: [email protected]) **** Control Control Engineering Engineering Group, Group, Faculty of Technology, Technology, University University of of Oulu, Oulu, Finland Finland **** Faculty of (e-mail: [email protected]) **** Faculty of **** Control Control Engineering Engineering Group, Group, Faculty of Technology, Technology, University University of of Oulu, Oulu, Finland Finland (e-mail: [email protected]) (e-mail: [email protected]) (e-mail: (e-mail: [email protected]) [email protected])
Abstract: Water spray system is one of the most important parts of rock cutting machines, especially the Abstract: Water spray one of the most important of rock cutting machines, the Abstract: Water spray system is one of the most important parts of rock cutting machines, especially the drum shearer. Field datasystem showsis that the maintenance of thisparts system is time-consuming and especially causes major Abstract: Water spray system is one of the most parts of cutting especially the Abstract: Water spray system isthat onethe of maintenance the most important important parts of rock rock cutting machines, machines, especially the drum shearer. Field data shows of this system is time-consuming and causes major drum shearer. Field data shows that the maintenance of this system is time-consuming and causes major downtimes in the coal mines’ production process. Therefore, it is essential to find an optimum preventive drum shearer. Field data shows that the maintenance of this system is time-consuming and causes major drum shearer. Field data shows that the maintenance of this system is time-consuming and causes major downtimes the coal production process. Therefore, it is find an optimum preventive downtimes in the coal mines’ production process. Therefore, it is essential essential to find an optimum preventive maintenancein task andmines’ intervals, to reduce the downtime and minimizeto the associated costs of the downtimes in the mines’ production process. Therefore, it to find an preventive downtimes in task the coal coal mines’ production process. Therefore, and it is is essential essential tothe findassociated an optimum optimum preventive maintenance and intervals, to reduce the downtime minimize costs of the maintenance task and intervals, to reduce the downtime and minimize the associated costs of machine. In this paper, in order to suggest an optimum preventive maintenance plan, a parametric failure maintenance task task and and intervals, intervals, to to reduce reduce the the downtime downtime and and minimize minimize the the associated associated costs costs of of the the maintenance the machine. In this paper, in order to suggest an optimum preventive maintenance plan, a parametric failure machine. In this paper, in order to suggest an optimum preventive maintenance plan, a parametric failure and reliability analysis was doneto onsuggest available data from preventive an Iranian longwall coalplan, mineaaover the twofailure years. machine. In this paper, in order an optimum maintenance parametric machine. In this paper, in order to suggest an optimum preventive maintenance plan, parametric failure and reliability analysis analysis was done on on was available data from fromtoan anidentify Iranianthe longwall coalmaintenance mine over over the theinterval two years. years. and reliability done available data Iranian longwall coal mine two A reliability-based costwas modelling implemented optimum and and reliability was done available data Iranian longwall coal mine two and reliability analysis analysis was done on on was available data from fromtoan anidentify Iranianthe longwall coalmaintenance mine over over the theinterval two years. years. A reliability-based cost modelling implemented optimum and A reliability-based cost modelling was implemented to identify the optimum maintenance interval and frequencies of restoration for the water spray system. In the study, a cost rate function was introduced in A reliability-based cost modelling was implemented to identify the optimum maintenance interval and A reliability-based cost modelling was spray implemented to the identify the optimum maintenance interval and frequencies of restoration for the water system. In study, aa cost rate function was introduced in frequencies of restoration for the water spray system. In the study, cost rate function was introduced in which an as-good-as-new effectiveness for restoration actions is considered. The results of the analysis frequencies of restoration for the water spray system. In the study, a cost rate function was introduced in frequencies of restoration for the water spray system. Inactions the study, a cost rate The function wasofintroduced in which an as-good-as-new effectiveness for restoration results the which anthat as-good-as-new effectiveness for restoration actions is considered. The results of the analysis analysis showed the minimum maintenance cost per unit of time for is theconsidered. studied machine, $19.54/hour, will be which as-good-as-new effectiveness for actions is considered. The of which an anthat as-good-as-new effectivenesscost for restoration restoration actions is considered. The results results of the the analysis analysis showed the minimum maintenance per unit of time for the studied machine, $19.54/hour, will be showed the per unit for the achievedthat within a range of maintenance intervals i.e. cost T=136 to time T=142 showed that the minimum minimum maintenance cost perhours unit of of time forhours. the studied studied machine, machine, $19.54/hour, $19.54/hour, will will be be showed that the minimum maintenance cost per unit of time for the studied machine, $19.54/hour, will be achieved within aa range of intervals i.e. T=136 hours to T=142 hours. achieved within range of intervals i.e. T=136 hours to T=142 hours. achieved within a range of intervals i.e. T=136 hours to T=142 hours. achieved within a range of intervals i.e. T=136 hours to T=142 hours. © 2015, IFAC (International Federation of Automatic Control) Hosting bywater Elsevier Ltd. All rights reserved. Keywords: Cost modelling, Drum shearer, Maintenance optimization, spray system. Keywords: Cost modelling, Drum shearer, Maintenance optimization, water spray system. Keywords: Cost modelling, Drum shearer, Maintenance optimization, water spray system. Keywords: optimization, Keywords: Cost Cost modelling, modelling, Drum Drum shearer, shearer, Maintenance Maintenance optimization, water water spray spray system. system. safety and continuous operation. In longwall mining, the coal 1. INTRODUCTION safety and continuous In longwall mining, the coal safety and continuous operation. In longwall mining, the coal is usually mined by a operation. machine called a "drum shearer". It is 1. INTRODUCTION INTRODUCTION safety and continuous operation. In longwall mining, the coal 1. safety and continuous operation. In longwall mining, the coal is usually mined by a machine called a "drum shearer". It is 1. INTRODUCTION is usually mined by a machine called a "drum shearer". 1. INTRODUCTION an electrically driven hydraulic machine and is used to extract is usually usually mined mined by by aa machine machine called called aa "drum "drum shearer". shearer". It It is is Maintenance costs make up a major part of mining operation an is It is electrically driven hydraulic machine and is used to extract an electrically driven hydraulic machine and is used to extract Maintenance costs make up a major part of mining operation coal seams of 1.5 to 4 metres in thickness (Hartman, 1992). Maintenance costs make up a major part of mining operation an electrically driven hydraulic machine and is used to extract costs. Several reports have been published on the contribution an electrically driven hydraulic machine and is used to extract Maintenance costs make up a major part of mining operation Maintenance make upbeen a major part ofonmining operation The coal seams ofcoal 1.5 to 4 metres in thickness (Hartman, 1992). costs. Severalcosts reports have published the contribution contribution models are designed with different costs. Several reports been published on the coal seams 1.5 to in (Hartman, 1992). of maintenance costs have in mining. Unger and Conway (1994) The coal different seams of ofcoal 1.5 shearer to 4 4 metres metres in thickness thickness (Hartman, 1992). costs. Several reports have been published on the contribution costs. Several reports have been published on the contribution different shearer models are designed with different The different coal shearer models are designed with different of maintenance maintenance costs in mining. mining.costs Ungerofand and Conway (1994) The dimensions and power output depending on the manufacturer. of costs in Unger Conway (1994) different coal shearer models are designed with different declared that the maintenance mining equipment The different coal shearer models are designed with different of maintenance costs in mining. Unger and Conway (1994) of maintenance costs in mining.costs Ungerofand Conway (1994) dimensions dimensions andmost powerofoutput output depending on the the manufacturer. manufacturer. and power on declared that the maintenance mining equipment Nevertheless, the depending shearers consist of six main declared that the maintenance costs of mining equipment and power depending on range from 20% to over 35% the total mine dimensions dimensions andmost powerofoutput output depending on the the manufacturer. manufacturer. declared that the costs of mining equipment declared thataround the maintenance maintenance costs of of mining equipment Nevertheless, the shearers consist of six sixcutting main Nevertheless, most of the shearers consist of main range from around 20% to over 35% of the total mine subsystems: the electrical system, hydraulic system, range from around 20% to over 35% of the total mine Nevertheless, most of the shearers consist of main operating costs. In open-pit mines in both Chile and Nevertheless, most of thesystem, shearers consistsystem, of six sixcutting main range from around 20% to 35% the mine range fromcosts. around 20% to over over 35%in of ofboth the total total mine subsystems: the electrical hydraulic subsystems: the electrical system, hydraulic system, cutting operating In open-pit mines Chile and arms, cable system, water system and haulage system operating costs. In open-pit mines in both Chile and subsystems: the electrical system, hydraulic system, cutting Indonesia, the maintenance costs represent more than 60% of subsystems: the electrical system, hydraulic system, cutting operating costs. In open-pit mines in both Chile and operating costs. In open-pit mines in both Chile and arms, cable system, water system and haulage system arms, cable system, water system haulage system Indonesia, the maintenance represent more than 60% of (Hoseinie, 2011, Hoseinie et al. 2012).and A field investigation cable system, water system and haulage system the operating (Hall et costs al., 2000, Carnbell, 1997). arms, cable system, water system and haulage system Indonesia, the maintenance costs represent more 60% of Indonesia, the cost maintenance costs represent more than than 60%The of arms, (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation the operating cost (Hall et al., 2000, Carnbell, 1997). The has shown that the water system is the most critical the operating cost (Hall et al., 2000, Carnbell, 1997). The (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation corresponding value for the open-pit mines of Canada and (Hoseinie, 2011, Hoseinie et al. 2012). A field investigation the operating operating cost cost (Hall (Hall et et al., al., 2000, 2000, Carnbell, Carnbell, 1997). 1997). The The has the shown that the water system is the most critical the is corresponding value45%, for the the open-pit mines of of Canada Canada and subsystem shearers and issystem responsible 30% critical of the corresponding value for mines has shown shownofthat that the water water system is the thefor most most critical Australia is about and open-pit for the underground minesand of has has shown that the water system is the most critical corresponding value for open-pit mines and corresponding value45%, for the the open-pit mines of of Canada Canada and subsystem of shearers and is responsible for 30% of the Australia is about and for the underground mines of machine failures (Hoseinie et al. 2011). The water system of Australia is about 45%, and for the underground mines of subsystem of and for 30% of Canada it is less than 35%and (Carnbell, 1997, Hall, 1997). Hall subsystem of shearers shearers andetis isal.responsible responsible for 30% of the the Australia about 45%, for the underground mines of Australia is about 45%, and for the underground mines of machine failures (Hoseinie 2011). The water system of machine failures (Hoseinie et al. 2011). The water system of Canada it is less than 35% (Carnbell, 1997, Hall, 1997). Hall the shearer operationally consists of three subsystems: water Canada it is less than 35% (Carnbell, 1997, Hall, 1997). Hall machine failures (Hoseinie et The water of (1997) investigations the maintenance machine failures (Hoseinie et al. al. 2011). 2011). The water system system of Canada it less 35% (Carnbell, 1997, 1997). Canadahas it is isconcluded less than than from 35% his (Carnbell, 1997, Hall, Hall, 1997). Hall Hall the the shearer operationally consists of three subsystems: water shearer operationally consists of three subsystems: water (1997) has concluded from his investigations the maintenance spray jets, valves and hoses. Water spraysubsystems: system cools the (1997) has concluded from his investigations the maintenance the shearer operationally consists of three water accounts for 30% to 65% of the overall operating cost budget the shearer operationally consists of three subsystems: water (1997) has concluded from his investigations the maintenance (1997) hasforconcluded fromofhis investigations the maintenance spray jets, valves and hoses. hoses. Water spray system system cools the the jets, valves and Water spray cools accounts 30% to 65% the operating cost budget cutting picks and controls the dust emission. The blockage of accounts for 30% to 65% of the overall overall operating cost budget spray jets, valves and Water spray cools for a typical mining company. According to Forsman and spray spray jets, valves and hoses. hoses. Water spray system system cools the the accounts for to of operating cost accounts for 30% 30% to 65% 65% of the the overall overall operating cost budget budget cutting picks and controls the dust emission. The blockage of cutting picks and controls the dust emission. The blockage of for a typical mining company. According to Forsman and the spray system causes the drum shearer machine to stop for a typical mining company. According to Forsman and cutting picks and controls the dust emission. The blockage of Kumar (1992), the cost of maintenance in the mining industry picks and controls the dust emission. The blockage of for mining company. According to Forsman and for aa typical typical mining company. According tomining Forsman and cutting the spray system causes the drum shearer machine to stop the spray system causes the drum shearer machine to stop Kumar (1992), the cost of maintenance in the industry automatically. Therefore, the reliable performance of this the spray system causes the drum shearer machine to stop varies from 40% to 50% of the equipment operating costs. the spray system causes the drum shearer machine to stop Kumar (1992), the cost of maintenance in the mining industry Kumar (1992), the cost of maintenance in the mining industry automatically. Therefore, the reliable performance of this automatically. Therefore, the performance this varies from 40% to 50% 50% of ofcoal the equipment equipment operating costs. assists the achievement of a continuous coal of cutting varies from to the automatically. Therefore, the reliable reliable performance of this Focusing on40% underground mining as operating a special costs. case, system automatically. Therefore, the reliable performance of this varies from 40% to the operating costs. varies from 40% to 50% 50% of ofcoal the equipment equipment operating costs. system assists the achievement of aa continuous coal cutting system assists the achievement of continuous coal cutting Focusing on underground mining as a special case, operation. The water spray system is a repairable item which Focusing on underground coal mining as a special case, system assists the achievement of a continuous coal cutting studies show that approximately 10% of the production time system assists the achievement of a continuous coal cutting Focusing on underground coal mining as a special case, Focusing on that underground coal 10% mining as production a special case, The water spray system is repairable which studies show approximately of the the time operation. is located on cutting drum surface which item contributes studies that approximately 10% of time operation. Thethe water spray system is aaa and repairable item which is lost show through unplanned maintenance in production the Australian operation. The water spray system is repairable item which studies show that approximately 10% of the production time studies show that approximately 10% of the production time is located on the cutting drum surface and which contributes is located on the cutting drum surface and which contributes is lost through through unplanned maintenance in 1990), the Australian Australian to 40% ofon thethe failures ofdrum the surface water system (Hoseinie et al. is lost unplanned maintenance in the is located cutting and which contributes underground coal mining industry (Clark, and that is located on the cutting drum surface and which contributes is lost through unplanned maintenance in the Australian is lost through unplanned maintenance in 1990), the Australian to 40%After of the the failures of the the water water systemsatisfactorily, (Hoseinie et et the al. to 40% of failures of system (Hoseinie al. underground coal mining industry (Clark, and that 2011). failing to perform its functions underground coal mining industry (Clark, 1990), and that to 40% of the failures of the water system (Hoseinie al. over 25% of the underground mining 40%After of the failures of the water systemsatisfactorily, (Hoseinie et et the al. underground coal mining industry (Clark, 1990), and that underground coalaccidents mining in industry (Clark,coal 1990), andoccur that to 2011). failing to perform its functions 2011). After failing to perform its functions satisfactorily, the over 25% of the accidents in underground coal mining occur spray jet can be restored to a satisfactory level of over 25% of the accidents in underground coal mining occur 2011). After failing to perform its functions satisfactorily, the during maintenance activities. 2011). After failing to perform its functions satisfactorily, the over 25% of the accidents in underground coal mining occur over 25% of the accidents in underground coal mining occur spray jet can can be be restored restored to to aa satisfactory satisfactory level level of of spray jet during maintenance activities. performance. during maintenance activities. spray jet can be restored to a satisfactory level spray jet can be restored to a satisfactory level of of during maintenance activities. during maintenance activities. performance. Longwall coal mining is a well-known mining method performance. performance. performance. Longwall coal mining is a well-known mining method aim of this study is to determine a cost effective because offers high is productivity, high mining mechanization, Longwallit coal coal mining is well-known mining method The Longwall mining aa well-known method The aim ofmaintenance this study is to determine aa cost effective The aim is cost because it offers offers high productivity, productivity, high mechanization, mechanization, preventive for management of the because it high high The aim of of this this study study interval, is to to determine determine cost effective effective The aim of this study is to determine aa cost effective because because it it offers offers high high productivity, productivity, high high mechanization, mechanization, preventive maintenance interval, for management of preventive maintenance interval, for management of the the preventive preventive maintenance maintenance interval, interval, for for management management of of the the
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failure modes of the spray jets of coal shearers in an Iranian longwall coal mine. Therefore, reliability-based cost modeling has been implemented to identify the optimum maintenance interval and frequencies of restoration for the spray jets, and thereby minimize the cost per unit of operating time. In the study, a cost rate function (CRF) has been developed in which an as-good-as-new (AGAN) effectiveness for restoration actions is considered. The CRF also considers restoration and repair times, and takes into account the costs associated with repair and restoration, and the opportunity cost of the equipment’s lost production due to maintenance downtime (i.e., scheduled and unscheduled maintenance), to arrive at the most cost-effective maintenance intervals.
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2. CASE STUDY; WATER SPRAY SYSTEM OF DRUM SHEARER This paper documents a case study on a shearer machine in an Iranian longwall coal mine. The total power of this shearer is 600 kW and the supply voltage is 1100 V. The cutting head of the drum shearer has a diameter of 1600 mm and a maximum cutting depth of 800 mm, and it is provided with a number of picks and spraying nozzles. The spraying nozzles are mounted inside the tool holders behind the cutting picks. The spraying system is designed for operation with a maximum working pressure of 150bar. The system consists of the following elements: 33 seat units which are provided with spraying nozzles with a diameter of 0.6 mm, 18 nozzle units which are built onto the body, and 15 remaining nozzle units which are built onto the cutting drum.
2. MAINTENANCE OF REPAIRABLE SYSTEMS A repairable system is a system which, after failing to perform one or more of its functions satisfactorily, can be restored to fully satisfactory performance by any method other than the replacement of the entire system (Ascher and Feingold, 1984). The quality or effectiveness of the repair action is categorized as follows (Ascher and Feingold, 1984, Rausand and Høyland, 2004, Modarres, 2006): 1) Perfect repair, i.e. restoring the system to the original state, to a “like–new” condition, 2) Minimal repair, i.e. restoring the system to any “like-old” condition, and 3) Normal repair, i.e. restoring the system to any condition between the conditions achieved by perfect and minimal repair.
2.1. Statistical analysis of failure data The data required for this study was collected from operation and maintenance reports and direct field observations over a period of two years. Most of the desired information, such as the failure occurrence times, failure modes, types of repair actions and time to repair (TTR), was available in the mine database and only the time between failures (TBF) were calculated. The results of the trend and serial correlation tests performed on the TBF data showed that the data is free of trend and serial correlation. Thus, data is iid, and consequently the renewal process is the best method for the failure analysis and modelling of this system.
Based on the quality and effectiveness of the repair action, a repairable system may end up in one of the following five possible states after repair (Ascher and Feingold, 1984, Rausand and Høyland, 2004, Modarres, 2006): as good as new; as bad as old; better than old but worse than new; better than new and worse than old.
In order to find the best fitted distribution, different types of statistical distributions were tested on the data using the Weibull++ and Easyfit software. The Kolmogorov-Smirnov (K-S) test was used for selecting the best distribution. The results of the data analysis show that the three-parameter Weibull (Weibull-3P) distribution with the scale parameter of α=233.28, the shape parameter β=2.49 and the location parameter γ=-43.32 is the best-fitted function for the available TBF data (Fig. 1 and Table 1). The calculations show that the reliability of the spray jets reaches zero after about 430 hours of operation.
While perfect repair rejuvenates the unit to the original condition, i.e., to an AGAN condition, minimal repair brings the unit to its previous state just before repair, i.e., an as-badas-old condition, and normal repair restores the unit to any condition between the conditions achieved by perfect and minimal repair, i.e., a better-than-old but worse-than-new condition. However, states four and five may also happen. For example, if through a repair action a major modification takes place in the unit, it may end up in a condition better than new, and if a repair action causes some error or an incomplete repair is carried out, the unit may end up in a worse-than-old condition. Failures occurring in repairable systems are the result of discrete events occurring over time. These processes are often called stochastic point processes (Modarres, 2006). The stochastic point process is used to model the reliability of repairable systems, and the analysis includes the homogenous Poisson process (HPP), the renewal process (RP), and the non-homogenous Poisson process (NHPP). A renewal process is a counting process where the inter-occurrence times are independent and identically distributed (iid) with an arbitrary life distribution (Ascher and Feingold, 1984, Ebeling, 2009). Upon failure, the component is thus replaced or restored to an as good as new condition.
Fig. 1. Failure data and best fitted failure density function 2.2. Cost rate modelling Based on the field experience and machine’s catalogues the following combination of restoration and servicing tasks are 167
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currently done in case study mine:
2) The component is fully functional after scheduled and unscheduled restoration.
1) Cleaning the spray jets to remove dust and mud from the nozzles.
3) There is no safety risk related to failures. Therefore, only operational and economic consequences are considered for the cost analysis of failures and maintenance.
2) Replacing the broken nozzle heads during the restoration task.
4) The shearer operates continuously and the failure of water spray systems interrupts the planned production.
Table 1. Results data analysis and best fitted distribution Distribution Weibull (3P)
Gamma (3P) Lognormal (3P) Gamma Normal
K-S test 0.122
Best fitted distribution Weibull-3P α = 233.28 β = 2.49 γ = -43.32
The following parameters are considered in the developed cost rate model: 1) Cost of unscheduled restoration (corrective restoration) (Ccr): This is a constant and deterministic value which includes the direct cost of unplanned restoration (corrective maintenance) due to each probable failure within the restoration cycle and the respective indirect costs of shipping, man-hours, etc. In fact, it is the failure cost of the system.
0.1225 0.128 0.130 0.134
2) Cost of scheduled restoration (CRes): This is a constant and deterministic value which includes the direct cost of preventive restoration and, like the cost of repair, also consists of indirect costs for shipping, man-hours, etc.
For this purpose, the nozzle must be screwed out and cleaned and serviced according to the maintenance procedure. However, the main question still remains, namely how to define the most effective restoration interval, which is the concern of the next section.
3) Opportunity cost of the machine's lost production (CLp.res) and (CLp.rep): This cost is associated with the total machine downtime due to each type of maintenance operation (scheduled and unscheduled restoration), i.e. TR (constant values). CLp.res is the opportunity cost due to preventive restoration and CLp.rep is the opportunity cost due to repair.
Fig. 2 shows a schematic description of the maintenance events. As can be seen in the figure, the shearer machine should be stopped to perform the restoration task after “T” accumulated cutting hours. It should be noted that T only refers to the cutting time and that the time during which the machine is working but not cutting is not used in the maintenance modelling. The first restoration is performed after “T” cutting hours.
In fact, two scenarios may happen. Either the spray jet will survive until its scheduled restoration time (T), making a cycle which we call a scheduled cycle, or it will fail before its scheduled restoration time, making a cycle which we call an unscheduled cycle. Hence, the expected restoration cost per cycle is formulated as (1): Cost T ( C Re s+C Lp ) R (T )+ ( C Cr +C Lp ) [1-R (T )]
(1)
Where: T: Inspection interval Fig. 2. Purposed restoration cycle for cost modelling of water spray system
CostT: Total cost of maintenance per cycle
Since the failure behaviour of the spray jets is iid, this restoration cycle will be repeated every T hours and consequently the Nth restoration will be performed after “N.T” operating hours. The whole restoration task takes TR hours. Hence, a restoration cycle time includes T +TR.
CCr: Cost of unscheduled restoration within any Nth cycle interval
CRes: Cost of restoration within any Nth cycle interval
CLp: Cost of lost production due to restoration actions The maintenance cost per unit of operating time, considering restoration every T hrs, can be expressed as (2):
Considering the iid behaviour of system and this assumption that the repair/restoration task rejuvenates the system to the original state, i.e. a like–new condition; all the restoration cycles will be identical. Therefore, when optimizing the restoration interval, it is sufficient to consider one cycle.
Cost
T
(C
Re s
+C
Lp
) R (T )+ ( C
Cr
+C
Lp
) [1-R (T )]
(2)
Expected c ycle lengt h
The analytical model presented in this paper is based on the following assumptions:
Similarly, the expected cycle length can be estimated as follows:
1) The failures are evident.
(Length of a scheduled cycle × probability of a scheduled 168
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cycle) + (Length of an unscheduled cycle × probability of an unscheduled cycle)
performance per shift on average (Hoseinie et al. 2014). Therefore, one week of operation is equal to 48.6 hours. On the basis of Figure 2, the maintenance cost related to T=48.6 hrs is $33.29/hour. This value shows that the current maintenance schedule in the case study mine is very expensive and almost 1.7 times higher than the optimum cost ($19.54/hour). Therefore, the preventive maintenance scheduling should be changed in this mine.
Finally, the associated maintenance cost function of the spray jets can be expressed as (3): C
Total
(C
Re s
C
Lp .res
) R (T ) ( C
Cr
C
Lp .Cr
) 1 - R (T )
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(3)
T T R (T ) tf ( t ) dt 0
3. CONCLUSIONS In this paper, the optimum maintenance scheduling for the water spray system of a drum shearer has been identified using an optimization methodology. The field data collected from an Iranian coal mine in Iran shows that the TBFs of this system are iid and the maintenance quality is as good as new. Therefore, the renewal process was selected for the reliability analysis. The data analysis showed that the TBF data follow a Weibull 3P distribution.
The optimum restoration interval (T), which minimizes the total cost of maintenance, can be achieved by the derivation of equation (3). Nevertheless, the above equation cannot be solved parametrically in an easy way. Therefore, the graphical method was used for finding the optimum T. 2.3. Optimal maintenance interval
Based on the field experiments and the design characteristics of the spray jets, restoration was selected as the maintenance policy for this system. Then a cost model was established to analyse the maintenance cost and determine the optimum restoration intervals. The optimum restoration intervals for the water spray system of the shearer machine can be selected in the period of 136 to 142. This function has a minimum value (= $19.54/hour) in the period of T=136 hrs to T=142 hrs.
The actual financial data from studied mine showed that the deterministic values for the cost parameters during 2014 are: Cres=$62.5, CCr=$38, CLp.res=$1345 and CLp.Cr=$2690. The Microsoft Excel™ software was used to enable variation of the parameters of equation (3), to identify the cost per unit of time for different values of T. Fig. 3 shows the Ctotal (the cost per unit of time) for different values of T, under the restoration strategy and based on the reliability parameter obtained from Section 2.1 and the cost parameters mentioned above.
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Fig. 3. The CTotal for different values of the restoration interval (T) It can be concluded from Fig. 3 that, the total cost of maintenance (CTotal) decreases with an increase in T until T=136. This function has a minimum value (= $19.54/hour) in the period of T=136 to T=142. After T=142, the total cost starts to increase again. Therefore, the optimum restoration intervals for the water spray system of the drum shearer machine can be selected in the period of 136 to 142. However, at present the spraying system is preventively maintained every Friday. According to the performance records of the machine, the shearer has 2.71 hours of useful 169
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Hartman, H. L., (1992), SME Handbook of mining engineering, 2nd edition, Society of Mining, Metallurgy and Exploration, USA. Hoseinie S. H., (2011), Modeling and Simulation of Drum Shearers' Reliability at Mechanized Longwall Minescase study: Tabas Coal Mine, PhD Thesis, Shahrood University of Technology, Shahrood, Iran (in Persian). Hoseinie, S. H., Ataei, M., Khalokakaie, R., and Kumar, U., (2011), Reliability modelling of water system of longwall shearer machine. Archive of Mining Science, Vol. 56, No. 2, pp. 291–302. Hoseinie, S. H., Ataei, M., Khalokakaie, R., Ghodrati, B. and Kumar, U., (2012), Reliability Analysis of Drum Shearer Machine at Mechanized Longwall Mines, Journal of Quality in Maintenance Engineering, Vol. 18 No. 1, pp. 98-119. Hoseinie, S. H., Ghodrati, B. and Kumar, U., (2014), Assessment of Reliability-Related Measures for Drum Shearer Machine, a Case Study, Sixth International Symposium High Performance Mining (AIMS 2014), 11-12 June, Aachen, Germany. Modarres, M., (2006), Risk Analysis in Engineering: Techniques, Tools, and Trends, New York: Taylor & Francis, 2006. Rausand, M. and Høyland, A., (2004), System Reliability Theory: Models, Statistical Methods and Applications, Hoboken, N.J.: John Wiley. Unger, R. L. and Conway, K. (1994), Impact of maintainability design on injury rates and maintenance costs for underground mining equipment, in Improving Safety at Small Underground Mines, compiled by R. H. Peters, Report No. Special Publication 18–94, US Bureau of Mines, Washington, pp. 140–167.
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