The Effect Of Coal Hauling Cycle Time Recording Construction Essay

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This chapter is illustrated the issues involved in the process of implementation, Coal Hauling Cycle Time Recording (CHCTR). The research will point out the significant expected outcome benefit which occurs after implementation the system such as cost benefit analysis, cycle-time reduction, and minimized risk of human error from coal hauling transaction report. Moreover, it provides the result and analysis of the success criteria and success factor in the implementation.

4.1 Issue involved in the process

During the implementation, there are some issues involved in the process as follows:

The delay time of network communication

From Coal Hauling Cycle Layout Area, is divided the local area network for TCM in to two areas by using satellite communication. Currently, both networks join together with a bridge network by using high radio frequency then it has an impact on the delay time in application. Moreover, if one of the networks is failed then the route of transportation information from mine stock yard to port stock yard will be difficult to get access. Thus, it will have an impact on the performance report in order to analyze and predict the production plan.

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Figure 4.1: Local Area Network at MSY and PSY

The data collected is inconsistent

Due to the design of GPS tracking log, it will use the truck driver to manually press the activities such as loading, weight, haul, downtime, waiting, etc. during the coal hauling as figure 4.2. Then, if the driver cannot process completely the data will not be efficiency to evaluate the performance of contractors. Moreover, the contractors will not know the troubleshooting information which occurs to their vehicles such as engines, transmission, hydraulic, tyre, or etc.

Source: GPS tracking log manual

Figure 4.2 Process hauling

Role and responsibility of project

Figure 4.3: Project management phases compared to the System Development Life Cycle

Role and responsibility of project is unclear then it has an impact on close-out phase. According to the project initiation base on self-organized team then person who involve need support from their management team.

4.2 Expected outcome benefit

GPS tracking log and CHCTR database and application were designed by tailored equipment for iterative development which is the right for firm's mine operation. Those features were considered by many limitation and requirement from the firm. Then, the system will be hard to find in the market but if there is, the price will be higher than CHCTR. Therefore, the improving of technology will gain benefit for the firm as scenario on below.

4.2.1 Safety

From the safety reporting of truck driver for monitoring and controlling, the critical position that the firm would like to measure velocity is Km. 7+500, Km. 19+600, Km. 19+700, Km. 22+500, Km. 24+500, Km. 26+000, and Km.34+500. The result of speed will represent the effect from CHCTR which occur to driver behavior.

Figure 4.4: The critical position at coal hauling road

The incident hauling road report from year 2008-year Jun 2010 showed the expense as follows:

Year 2008: No expense from incident

Year 2009: USD 510,000

Jun year 2010: USD 131,432

From the incident hauling road report from year 2008 and year 2010, the result showed that Km.26+000 and Km.24+500 had incident so it might be the condition of road or driver.

If the firm creates the scenario to improve hauling road, it will be reduce the incident and increase productivity. From the cycle time performance and utilization of hauling truck represent average normal cycle time for one trip is approx 156 minutes6 and average daily production is approx 20,000 ton/ day. Moreover, the constant information will follow by coal price in rage of USD 60-757, working day 300/year, working hour 20 hr/day, average hauling truck capacity 60 ton/unit, total fleet of coal hauling 30 units, and coal mining operation cost in range of USD 8-188.

Scenario: Re-grade or Re-Slope length from Km.26+000 and Km.24+500 for 1.5 Km.

Figure 4.5: Cross-Section of Coal Hauling Road

Currently average up-hill speed of truck capacity 60 ton/unit is 25 Km. /hr after improved by reducing the grade of haul road. It will increase the average up-hill speed to be 45 Km./ hr. so the increasing speed will be 20 Km./hr. Therefore, the cycle time of hauling will be reduced for 4.5 min.

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Daily hauling trip: (20hr/day * 60 min.)/ (156 min.) = 7.69 trips/ day/ truck

Improved daily hauling trip: (20hr/day * 60 min.)/ (156-4.5 min.) = 7.92 trips/ day/ truck

Incremental trip: (7.92 - 7.69) = 0.23 trip/ day/ truck

Incremental hauling truck capacity: (0.23 trip/ day/truck * 30 units * 60 ton/day/unit) = 414 ton/ day

Average coal price is USD 67.5 and average coal mining operation cost is USD 13. Estimate average coal hauling cost is 30% of coal mining operation cost, USD 4/ ton. If the contractors can reduce their speed time, it might affect the coal hauling cost for 2.88% then the cost will be decreased for USD 0.12/ ton.

Estimate added revenue: (414 ton/day * USD 0.12* 300 day/year) = USD 14,904/ year*

4.2.2 Cycle-time reduction

Cycle-time reduction aims to improve and identify undesired activities and waste time. From the cycle time performance and utilization of hauling truck represent average normal cycle time for one trip is approx 156 minutes6 and average daily production is approx 20,000 ton/ day. Moreover, the constant information will follow by coal price in rage of USD 60-757, working day 300/year, working hour 20 hr/day, average hauling truck capacity 60 ton/unit, total fleet of coal hauling 30 units, and coal mining operation cost in range of USD 8-188.

Figure 4.6: The cycle time performance and utilization of hauling truck

Expected return for "Scenario I"

Figure 4.7: Scenario I

(a) Reduce time at crushing plant for 3 min. by reducing for 1 min. at loading area and 2 min. at crushing plant preparation.

(b) Reduce time at coal hauling road for 4 min. by reducing for 3 min. along coal hauling and 1 min. at Kaju station.

(c) Reduce time at port activities for 3 min. by reducing for 2 min. at port preparation and 1 min. at discharging.

Total cycle time reduction is 10 min. or 6.4%

Daily hauling trip: (20hr/day * 60 min.)/ (156 min.) = 7.69 trips/ day/ truck

Improved daily hauling trip: (20hr/day * 60 min.)/ (156-10 min.) = 8.22 trips/ day/ truck

Incremental trip: (8.22 - 7.69) = 0.53 trip/ day/ truck

Incremental hauling truck capacity: (0.53 trip/ day/truck * 30 units * 60 ton/day/unit) = 954 ton/ day

Average coal price is USD 67.5 and average coal mining operation cost is USD 13. Estimate average coal hauling cost is 30% of coal mining operation cost, USD 4/ ton. If the contractors can reduce their idle time, it might affect the coal hauling cost for 6.4% then the cost will be decreased for USD 0.26/ ton.

Estimate added revenue: (954 ton/day * USD 0.26* 300 day/year) = USD 74,412/ year

Expected return for "Scenario II"

Figure 4.8: Scenario II

(a) Reduce time at crushing plant for 3 min. by reducing for 1 min. at loading area and 2 min. at crushing plant preparation.

(b) Reduce time at coal hauling road for 4 min. by reducing for 3 min. along coal hauling and 1 min. at Kaju station.

(c) Reduce time at port activities for 3 min. by reducing for 2 min. at port preparation and 1 min. at discharging.

(d) Reduce time at truck scale for 1 min.

Total cycle time reduction is 11 min. or 7.1%

Daily hauling trip: (20hr/day * 60 min.)/ (156 min.) = 7.69 trips/ day/ truck

Improved daily hauling trip: (20hr/day * 60 min.)/ (156-11 min.) = 8.28 trips/ day/ truck

Incremental trip: (8.28 - 7.69) = 0.59 trip/ day/ truck

Incremental hauling truck capacity: (0.59trip/day/truck * 30 units * 60 ton/day/unit) =1,062 ton/ day

Average coal price is USD 67.5 and average coal mining operation cost is USD 13. Estimate average coal hauling cost is 30% of coal mining operation cost, USD 4/ ton. If the contractors can reduce their idle time, it might affect the coal hauling cost for 7.1% then the cost will be decreased for USD 0.28/ ton.

Estimate added revenue: (1,062 ton/day * USD 0.28* 300 day/year) = USD 89,208/ year

4.2.3 Minimized risk of human error

The improving contractor's performance evaluation method will decrease the human error which occurs from speed-gun measurement and key in manually. Moreover, the staffs who work in this position can do other jobs that create more value to the firm. For example the speed-gun operator will cost USD 230/month and input data administrator will cost USD 200/month. If the firm creates scenario to save the opportunities cost for 10% per month, it will reduce the expense for USD 43.

4.2.4 Cost benefit analysis

The total investment cost of CHCTR is USD 144,000

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Accident compensation cost is USD 14,904/ year*

Scenario I: Saving buffer space compensation is USD 74,412/ year

Scenario II: Saving buffer space compensation is USD 89,208/ year

Labor cost saving is USD 516/ year

Depreciation for 4 years

Discount rate9 is 11%

ROI for Scenario I in year 1: [((14,904+74,412+516)-144,000)/ (144,000)]*100 = -37.62%

The breakeven point of Scenario I in year 2

NPV = 23,010.86

IRR = 18%

ROI for Scenario II in year 1: [((14,904+89,208+516)-144,000)/ (144,000)]*100 = -27.34%

The breakeven point of Scenario II in year 2

NPV = 68,914.64

IRR = 32%

Therefore, the CHCTR will be an efficiency of operational measurement in order to increase hauling production as the cost benefit analysis.

4.3 Critical success factor

Critical success factors can be classified in to two groups which affect project performances at different phases of implementation. The first group is referred to as the strategic group that consists of factors like project mission, top management support, and project scheduling. The other group is the tactical group, which consists of factor like client consultant and personal selection and training (Schultz et al., 1987).

From the secondary data of Critical Success Factors in the Real-Time Monitoring of Construction Projects10 by K.Divakar and K.Subramanian showed that Linear Multiple Regression of these factors with the dependent factor Frequent Changes in plans, designs and working drawings, revealed that the underlying factor Role of Project Participants was said to have a more cause and effect on the dependent variable Cash flow in the project at all levels right from the client to site engineer. The summary of the regression with coefficients for the regression model is shown as follows:

Figure 4.9: Coefficients for regression model

A regression model equation which is not a functional equation but a cause and effect model was written as follows:

Cash flow in the project at all levels right from the client to site engineer = 0.890(Role of Project Participants) + 0.522(constant)

The initial factors which are included under the underlying factor Role of Project Participant are

(a) Involvement and commitment of project participants - clients, consultants, and contractors

(b) Involvement and commitment of project managers, project engineers, technical assistants, and workers

(c) Delay in finalization of utility or change in the utility

(d) Periodic discussion among project participants and timely delivery of the outcome or feedback

(e) Coordination between agencies involved in the project

(f) Controversies among project participants and hence suspension of work

(g) Preparation of Bill of Quantities and timely payment to contractors

Therefore, the role of project participant is vital in this regard. The critical factors identified in the analysis above should be monitored by the project managers. The project manager should liaison between the clients, consultants and the project engineers. At the scheduling stage the factors should be given due considerations. During the progress of the work the monitoring of the project should be done with special attention to these factors as these are the factors which causes delay if not monitored at the appropriate stages. So effective monitoring of the critical factors identified in this study will ensure successful completion of the project.

4.4 SWOT technological achieve competitiveness

Figure 4.9 SWOT

The analysis of GPS Guidance System suggests that such system may have significant impact on management of earth-moving equipment and at accuracy of mining operations. The pay back period may vary depending on the time and resources put into the system to realize, it is full potential either directly or indirectly. The ideal environment for the installation of a GPS guidance system would be in a mine with a long life (>1 year). This way the payback of the system would be ensured and the benefits and cost savings could be realized for longer.

Notes:

6: Average cycle time for one trip as appendix II

7: Source Jakarta Post March, 30 2010

8: Source of Indonesia commercial newsletter

9: Assumption of WACC in average mining industry as appendix III

10: Descriptive statistics identified 19 factors; the responses received w ere in the form of ratings on a 4 point Lickert Scale. They are: 1. No Effect, 2. Marginal Effect (where delay caused can be fully revived), 3. Significant Effect where the delay caused can be partially revived), 4. Adverse Effect (where delay caused is beyond revival). The result was showed as appendix IV

*: Road modification construction has to be trade-off between cost and return.

Appendix:

Appendix II

Source: Coal Hauling Cycle Time Recording implementation report

Appendix III

Returning to our example, let's suppose has a capital structure of 40% debt and 60% equity, with a tax rate of 30%. The borrowing rate (Rd) on the company's debt is 5%. The risk-free rate (Rf) is 5%, the beta is 1.3 and the risk premium (Rp) is 8%. The WACC comes to 10.64%. So, rounded up to the

nearest percentage, the discount rate for the average mining company is

WACC for the average mining industry

Cost of Debt

Cost of Equity

0.40 [Rd x (1-.30)]     +

0.40 [5.0 x 0.7)]         +

0.40 [3.5]                   +

                     1.40      +

                       WACC

     Rounded WACC

0.60 [RF + b(RP)]

0.60 [5.0 + 1.3(8)]

0.60 [15.4]

9.24

10.64%

11%

Appendix IV