MINING OPERATION PRODUCTIVITY IMPROVEMENT BY USING LEAN SIX SIGMA FRAME WORK (CASE: ASM MINE)

• Main Author: Juaeni, Ahmad
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/53353
• Institution: Institut Teknologi Bandung

After the downward trend in coal prices from 2013 to 2016, coal prices then went up in mid-2016 and continued to rise up to 2018. Large potential market was not been followed by production performance. The production of ASM coal in first semester of 2018 is still 11 percent below the target. The actual coal production during the period was 2.47 million tons. The company has not been able to fulfill all market demand which reduced company’s revenue. Based on performance appraisal, there are 3 (three) main factors causing the decline in company revenue, namely coal quantity, coal quality and delivery time to customers. Internal analysis and discussion shows that coal quantity is the main factors, followed by the time of delivery and then the quality of coal in the third position. The main business processes started from overburden stripping, coal getting and coal crushing. This final project is made to improve the coal production process, especially in the aspect of coal quantity for customer demand. Low coal quantity is caused by low achievement of overburden stripping. Given that overburden stripping is the first process of the mining sequential process, this final project wil focus on stripping activity to increase overburden removal so that coal production can be optimized. This project is also focuses on technical issues that could be controlled. External factors that cannot be controlled such as rain is not in this case. Six Sigma was originally applied in the manufacturing process, but was later adopted into various types of industries, including mining. The ASM applied six sigma methods to improve coal production performance in its business processes. The Define-Measure-Analyze-Improve-Control (DMAIC) stage is used to get consistent improvements. The Define phase comes from the customer's voice and calculates the potential loss that ends up with the project charter. The measurement phase consists of calculating the baseline conditions and identifying the main problems by field cycle time oberservation. In the Analysis phase, group meetings are held to determine root cause analysis by fishbone and Failure Mode Effect Analysis (FMEA). This stage indicating that overburden stripping activity become a bottle neck and looks for solutions to improve stripping performance. Process improvement is carried out by the ASM team especially at overburden stripping through improving stripping method and field condition which eventually reducing cycle times and increasing the productivity of excavators. The loading time of excavator drops from 2 minutes 48 seconds to 2 minites 35 seconds, while truck exchange time decrease from 43 seconds to 33 seconds. As a result, the excavators productivity increases from 750 BCM/hour to 813 BCM/hour. The six sigma level for overburden stripping activity increases form 1.1 to 2.4. Improvement of the stripping process which causes better overburden removal and more coal to be extracted. This improvement increases the company's revenue that comes from increasing productivity of excavators.