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PERFORMANCE MEASUREMENT OF SURFACE MINING EQUIPMENT BY USING OVERALL EQUIPMENT EFFECTIVENESS.

Byline: M. Waqas, S. M. Tariq, M. Shahzad, Z. Ali and S. Saqib

ABSTRACT:

Over the last few decades, surface mining industry has focused on utilization of large sized, high capacity automated equipment for getting greater production to meet the international market demands. In order to achieve high rate of production with low unit price, it is necessary to use equipment as affectively as possible. Overall Equipment Effectiveness (OEE) is a tool that is increasingly being used to measure the effective utilization of equipment in terms of their availability, performance and quality. This study was carried out for the measurement of Overall Equipment Effectiveness (OEE) of the mining equipment being utilized in DeraGazi Khan (DG) cement quarries. The OEE value of two shovels and six dumpers was calculated and were compared with the bench mark values. The values of OEE were found to be 75% and 50% for two shovels and for dumpers, it was found to vary from 49% to 56%.

Keywords: Overall equipment effectiveness, Quarry equipment, Shovel performance, Dumper performance.

INTRODUCTION

Due to globalization, the world has become an open market for all companies which have led the companies to develop new trends in the production system by using large sized and high capacity automatic equipment to meet the international market requirements. These trends are also being seen in the mining industry especially the surface mining. Over the last few decades, the development of large sized cutting, loading, hauling and dumping equipment has made it possible to deal with greater tonnages on surface mines, thus facilitating in achieving greater production rates. This large scale equipment requires huge capital investment. Therefore, it is necessary to use them as effectively as possible in order to achieve high productivity with overall reduced production cost. Overall Equipment Effectiveness (OEE) is a tool for measuring effective utilization of the equipment and is gaining popularity for the last two decades. It was proposed by Nakajima (1988).

Since that time, many studies have been done by various researchers in this area (Prickett, 1998; Jonsson and Lesshammar, 1999; Dal et al., 2000; Jeong and Phillips, 2001; Ljungberg, 2001; Hansen, 2002; Bamberet al., 2003; Elevli and Elevli, 2010; Pillai et al., 2011; Samad et al., 2012; Norden and Ismail, 2012).

Although OEE has become a renowned tool in manufacturing industry, however very less application of OEE is found in mining industry. A part of OEE technique has been applied to get higher production by equipment management in Australian coalmines (Emery, 1998). Norden and Ismail (2012) defined OEE and its parameters forbord and pillar coal mining operation.

They calculated the value of OEE by considering losses in various mining operations such as cutting and hauling etc. and gave suggestions for the improvement of OEE value. Ercelebi et al. (1999) measured the performance of mining equipment by using OEE technique. They found mining environment very harsh for mining equipment which caused hindrances in getting maximum output from them.

The benchmark value of OEE for manufacturing equipment has been set to be 85 %, comprising of a product having more than 90% availability, 95 % efficiency and 99 % quality (Nordan and Ismail, 2012). In case of mining equipment, benchmark has been set only for shovel that is 77%, consisting of more than90 % availability, 90 % performance and 95 % quality (Elevli and Elevli, 2010). No benchmark value of OEE was found for dumpers or other mining equipment's. This study has been carried out for the determination of OEE of various equipment being utilized in the quarry operations of Dera Ghazi Khan Cement industry. The focus of this study was to determine various losses during operation of loading and dumping and to give suggestions for improvement of OEE value for these equipments.

MATERIALS AND METHODS

The technique of OEE was used to measure the effectiveness of various loading and hauling equipments that were in use in Dera Ghazi Khan Cement industry located in Chakwal, Punjab. A total of two shovels and six dumpers were evaluated for their effectiveness. There were two sites from where the material was loaded and hauled to the main crusher. Shovel 1 was used to load the dumpers 1 and 6 at site 1 which was close to the main crusher, while shovel 2 was utilized to load dumper 2 at site 2 which was relatively away from the crushing unit. Dumpers 3, 4 and 5 were loaded by front end loader at site 3. Loading time-based approach was used to measure time losses. These losses were categorized into three major classes: downtime losses (availability), speed losses (performance) and defect losses (qaulity).

The loss in availability of equipment involved the losses in production either in case of any event of equipment failure due to technical or any other reasons or in case of minor stoppages of equipment during operation. The loss in availability of the equipment was determined by the relation given below:

(1) The loss in equipment performance included the loss in speed of the equipment during operation due to substandard material, road conditions, operator's inefficiency, job conditions, slope conditions etc. which was calculated as given below:

(2) The defect of quality accounted the losses in the product. It happened due to inefficiency of the equipment to perform at its best capacity. In case of loading equipment such as shovel and front end loader etc. and hauling equipment like truck and dumper etc., it was the fill factor which meant how sufficiently it was filled according to its capacityas described by Elevli and Elevli (2010) and Akande et al. (2013) who defined quality loss for surface mining equipment as follows:

(3) Equations 1, 2 and 3 were used to determine losses in terms of availability, performance and quality of these equipment. Equation 4 was used to determine the Overall Equipment Effectiveness (OEE) of these equipments.

After determining these losses, the value of OEE was calculated by using the relation given below:

(4) After calculating the value of OEE, it was compared with the standard value and suggestions given for increasing equipment effectiveness by reducing various time losses.

RESULTS AND DISCUSSIONS

The various time losses (average) measured for shovel 1 and 2 are presented in Table-1. The values of three parameters of OEE were calculated and OEE was determined for both shovels.

The OEE values of shovel 1 and 2 were calculated to be 75% and 50 % respectively. The OEE value of shovel1 was found to be very close to the benchmark value i.e. 77 % (Elevli and Elevli, 2010). The main reason found for this higher value was the location of the site at which the shovel was working, the relatively better management of hauling equipment (dumpers) with respect to the operation of shovel was done to the site of shovel being very close to the main crusher. Due to this reason, the travel time for the dumpers was very low, and hence shovel did not wait much for any dumper. Moreover, two dumpers were loaded by the shovel which also caused a reduction in dumper waiting time. It was found that the setup and adjustment time was high for the shoveli. e. 42 minutes, which was found to be the main reason for its lower OEE value. The value of OEE for the shovel could further be improved by minimizing the setup and adjustment time.

This could be done by enhancing the operator's ability to operate the shovel in the most effective way. The loading and digging practices fall directly under the control of operator. Our findings are supported by the work carried out by (Paterson, 2001) who further reported that the operator should be capable, to change the shovel position towards next excavation point during the absence of dumper which would result in no waiting for the dumper and would increase the shovel capacity and productivity per shift.

The value of OEE for shovel 2 was found to be far less than the benchmark value. The reasons behind the low value of OEE for the shovel were found to be the excavation method, location of shovel working site (site 2) and poor management of dumpers with respect to the operation of the shovel. At this site, the material was being excavated by drilling and blasting operations that resulted in relatively large sized material. Poor drilling and blasting operations cause substandard digging operation resulting in reduced filling factor. The filling factor for the shovel under consideration was observed to be 90%. Further, inefficiency in drill and blast operation increased the number of passes required to fill the dumper, thus increasing loading time which resulted in higher cycle time of transporting operation being in line with the finding of (Paterson, 2001).

Moreover, only one dumper was utilized for transporting the material from the site to the main crusher, therefore, the shovel had to wait for a longer time for the dumper, resulting in to about 36% time losses. As, the site was located far away from the main crusher which resulted in the increased cycle time of the dumper. It was also observed that it increased the dumper waiting time, thus affecting the performance of the shovel. The dumper waiting time appeared to be the core cause which hindered the loader's availability. These finding are supported by the work done by (Akande et al., 2013). It required at least two dumpers in order to increase the effective utilization of the shovel. It was further observed that diesel was usually filled during the working, which resulted in more idle time, thus reducing the value of OEE for shovel under study. It is therefore suggested that shovels should be fuelled between the shift break in order to improve the working efficiency.

However, no speed losses were found for both shovels as they were operating at their optimum speeds.

Various time losses for the six dumpers were measured and their OEE values were calculated (Table- 2). The major losses for dumpers were found to be due to high setup and adjustment time which varied between 33 to 37 minutes, which reduced their availability resulting in lower equipment productivity. According to Moore (1998), 1% increase in availability of equipment may generate 1.7-3.5% profit. Therefore, it is important to keep the equipment available for working. This can be done by enhancing the operator's capability to operate the equipment in the best possible way, thus reducing the time losses in equipment availability. Paterson (2001) was also of the view that the use of double back-up loading resulted in minimum dumper spotting time. It was further noted that more shovel waiting time for dumpers was found to vary between 29 to 91 minutes. This situation was observed at site 1 which was close to main crusher and where single shovel was loading two dumpers.

The higher speed losses found in loading time of dumpers varied from 142 to 146 minutes. The speed losses were considered to be dependent upon many factors including haul road characteristics, truck characteristics and operator's ability being in line with the findings of (Doktan, 2001). The major speed losses could be reasoned by poor road conditions, higher rolling resistance and track profile (curve and gradient). The road was not smooth due to the irregularities created by scattered pieces of stones, thus creating higher rolling resistance and causing a reduction in dumper speed.

Table 1.Showing time losses and Overall Equipment Effectiveness estimation of shovels

###Shovel 1###Shovel 2

Type of###Item

###Time (minutes) OEE Factors###Time (minutes) OEE Factors

###losses

###Total time###360###600

###Unscheduled maintenance time###0###0

###Setup and adjustment time###42###31

Availability###0.79###0.56

###Idle time###5###15

###Dumper waiting time###29###216

###Job conditions###0###0

Speed###Speed loss###0###1.00###0###1.00

###Propel time###0###0

Quality###Quality loss (filling factor)###95%###0.95###90%###0.90

Overall Equipment Effectiveness (OEE), %###75###50

Table 2.showing various time losses measured for six dumpers being working in DG cement industry and their corresponding OEE values

###Dumper 1###Dumper 2###Dumper 3###Dumper 4###Dumper 5###Dumper 6

Type of losses###Item###Time###OEE###Time OEE###Time###OEE###Time###OEE###Time###OEE Time###OEE

###(mm.) Factor (mm.) Factor (mm.) Factor (mm.) Factor (mill.) Factor (mm.) Factor

Avai-

labil-

ity###Total time###600###600###600###600###600###600

###Unscheduled

###0###0###0###0###0###0

###maintenance

###Setup and###36###0.85###35###0.82###0.86###0.85###0.87###0.79

###adjustment

###Idle time###12###12###12###0###11###0

###Shovel waiting time 40###60###35###59###29###91

Spe-

ed###Job conditions###3###2###1###2###1

###speed loss###0###0.72###0###0.70###0###0.72###0###0.71###0###0.72###0###0.69

###loading time los###142###146###145###143###143###144

###Quality loss###90%###0.90###90%###0.90###90% 0.90###90% 0.90###90%###0.90###90% 0.90

Overall Equipment

Effectiveness (OEE).###%###55###52###56###54###56###49

The lower fill factor which was found to be 90 % for all the dumpers. Doktan (2001) who considered fill factor as an operational variable affected by loading strategy, operator experience and willingness to fill the bucket and the angle of repose of the material. In the current scenario, it was the operator's experience and loading strategy that caused reduction in fill factor. Paterson (2001) was of the view that truck/dumper should be filled to its maximum capacity as the truck/shovel operation was thought to consume about 30% costs of the total system cost. However it should be remembered that both overloaded and under loaded trucks are detrimental to the operation as the overloading accelerates fatigue and induces premature failure, while under loaded tends to be uneconomical. Therefore, the best practice would be to load the dumper/truck to its 100% capacity.

In General, Overall Equipment Effectiveness values of all dumpers operated at DG Khan Cement factory were found to be very low and vary between 49- 56%. The reasons for the poor OEE values may include; diesel filling during working time, minor stoppages in journey, minor repair work during shift time and poor cycle time management.

Conclusions: The concept of OEE was employed to measure the effective utilization of loading shovels and hauling dumpers being used in Cement quarries. OEE value for shovel 1 was very close to benchmark value but still there was a need to improve the operation of shovel

1. The value of shovel 2 was found very low due to poor management of dumpers with respect to operation of shovel

2. The OEE values of dumpers varied between 49 56%. Although, there was no benchmark value available in the literature but still the OEE values were found too low for dumpers. It was found that dumpers took more time for their setup and adjustment. Time loss due to diesel filling during working hours was another factor. It was further observed that inappropriate management of dumpers at various sites caused in increased shovel waiting time and loading time losses, thus resulted into ineffective utilization. In order to improve the Overall Equipment Effectiveness of dumpers, it is recommended that drive by situation should be used at every site. The dumpers should be managed according to the travel distance between loading points and dumping site. In case of long travel distances, two or more dumper may be used to reduce the shovel idle time.

It is also recommended that the diesel filling of the dump trucks during shift break time can also improve the Overall Equipment Effectiv eness.

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Waqas, M. (2013). Measuring Performance of Mining Equipments Used in Cement Industry by Using Overall Equipment Effectiveness (OEE). MSc. Thesis, Department of Mining Engineering, University of Engineering and Technology, Lahore, Pakistan.
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Publication:Pakistan Journal of Science
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Date:Jun 30, 2015
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