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Maryani, Edna
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Humanities Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering

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FORECASTING ANALYSIS OF URETHANE BLADE NEEDS ON BELT CLEANER TO MINIMIZE FORECAST ERROR (CASE STUDY AT PT. MS ENGINEERING) Hernadewita, Hernadewita; Zuniawan, Akhyar; Maryani, Edna; Karini, Nofitasari Damayanti
Journal of Industrial Engineering & Management Research Vol. 1 No. 2 (2020): Agustus 2020
Publisher : AGUSPATI Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1101.885 KB)

Abstract

MS Engineering is a company engaged in the field engineering, which is producing belt cleaners for cleaning conveyor belts in mining areas, the cement industry and the power plant. In the belt cleaner, has several parts assembled into one, including metal parts and urethane blade parts. PT MS Engineering has low forecasting accuracy, causing excess stock, especially for parts of urethane blade that have expired. The company only sees based on historical data. Therefore, to overcome these problems, it is necessary to forecast demand with the appropriate method. In this study by comparing several forecasting methods to find the highest error rate. The methods to be used include Single Moving Average, Exponential Smoothing and Weighted Moving Averages. From the discussion and analysis of the three calculation methods above, it is known that the calculation results with the 4 monthly Single Moving Average methods are better and more suitable to be applied by PT. MS Engineering in predicting the needs of Urethane Blade in January 2020, because the method has a lower error rate than the method other. The forecast error rate, MAD (Mean Absolute Deviation) of 58,906 and MSE (Mean Square Error) of 4484.57 with forecast results for January 2020 of 292.5 pcs.
Process Capability Improvement Through DMAIC Method for Aluminium Alloy Wheels Casting Maryani, Edna; Purba, Humiras Hardi; Sunadi, Sunadi
Journal of Industrial Engineering & Management Research Vol. 1 No. 4 (2020): December 2020
Publisher : AGUSPATI Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (635.693 KB) | DOI: 10.7777/jiemar.v1i4.98

Abstract

High competition in the global wheel market demands is triggering the companies who are produced to improve their process to be able to offer the best wheels quality. Process monitoring charts are employed for improving the process capability index of the process, some industries set a Cp value greater than 1.33 in assessing their process capability. The aims of this research is to reduce the number of defects in the casting process using the Define Measure Analyze Improve Control (DMAIC) method. It shows the systematic way to find out the major problem root cause at the aluminum castings by using the defect diagnostic approaches and also cause and effect diagram. Other quality tools are used such as the Fishbone diagram and Pareto diagram. These tools identified the major defects for the rejections during production were identified are leaking, porosity hole motive, and oval. In determining the proposed quality improvements using the FMEA tool. The results of data processing on the calculation of process capabilities and product performance show improvements after quality improvements in the casting process.product performance was increased from Cp = 0.81 to Cp = 1.4, sigma level = 2.9 to sigma level = 4.0. The impact for the company is the defect rate was going down and finally it created the production costs saving by IDR 417,550,000 a month. Therefore, the application of the DMAIC method can provide a significant improvement in product quality and giving an impact on production cost savings
Co-Authors Hernadewita Hernadewita Humiras Hardi Purba, Humiras Hardi Karini, Nofitasari Damayanti Sunadi, Sunadi Zuniawan, Akhyar