Noise Reduction of Ceiling Fans in Mass Production Applying DMAIC-Six Sigma ApproachSource: Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems:;2021:;volume( 004 ):;issue: 003::page 031006-1DOI: 10.1115/1.4050264Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Success and business reputation depend upon the quality of products where product quality relies on the capability of a process, yield value, sigma score, etc. The poor quality of ceiling fans was determined from the Pareto analysis of the define, measure, analyze, improve and control (DMAIC) model, which was humming noise during running, and further actions were undertaken regarding the reduction of the humming noise. Noise data were collected from random samples to determine the current sigma score, which was 3.14. Also, the weak value (1.05) of the Process Potential Index implied that the process condition was below the standard (< 1.33) and needed to be improved badly. Then, root cause analysis and relationship diagram were used to identify the possible causes. With the design of experiments and correlation analysis, it was clear that the air gap between the stator and rotor was the main culprit behind the humming noise. The suitable range of air gap was determined from boxplot analysis, which was 0.2 mm–0.225 mm and the corresponding amount of sound level in dB (37.5–40.3 dB) for a 0.225-mm air gap with the watt consumption (83 w) from the hypothesis test for the corresponding air gap. Finally, the updated sigma score and process capability analysis were performed with control charts to show the comparison after applying the DMAIC-Six Sigma methodology. The final sigma score was 5.1, which indicates a significant improvement of the process with the capability of saving 23,438 USD/year caused by the poor quality of ceiling fans.
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| contributor author | Hasan, Md. Zahid | |
| contributor author | Ahammed, Rubel | |
| date accessioned | 2022-02-05T21:51:03Z | |
| date available | 2022-02-05T21:51:03Z | |
| date copyright | 3/24/2021 12:00:00 AM | |
| date issued | 2021 | |
| identifier issn | 2572-3901 | |
| identifier other | nde_4_3_031006.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4276457 | |
| description abstract | Success and business reputation depend upon the quality of products where product quality relies on the capability of a process, yield value, sigma score, etc. The poor quality of ceiling fans was determined from the Pareto analysis of the define, measure, analyze, improve and control (DMAIC) model, which was humming noise during running, and further actions were undertaken regarding the reduction of the humming noise. Noise data were collected from random samples to determine the current sigma score, which was 3.14. Also, the weak value (1.05) of the Process Potential Index implied that the process condition was below the standard (< 1.33) and needed to be improved badly. Then, root cause analysis and relationship diagram were used to identify the possible causes. With the design of experiments and correlation analysis, it was clear that the air gap between the stator and rotor was the main culprit behind the humming noise. The suitable range of air gap was determined from boxplot analysis, which was 0.2 mm–0.225 mm and the corresponding amount of sound level in dB (37.5–40.3 dB) for a 0.225-mm air gap with the watt consumption (83 w) from the hypothesis test for the corresponding air gap. Finally, the updated sigma score and process capability analysis were performed with control charts to show the comparison after applying the DMAIC-Six Sigma methodology. The final sigma score was 5.1, which indicates a significant improvement of the process with the capability of saving 23,438 USD/year caused by the poor quality of ceiling fans. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Noise Reduction of Ceiling Fans in Mass Production Applying DMAIC-Six Sigma Approach | |
| type | Journal Paper | |
| journal volume | 4 | |
| journal issue | 3 | |
| journal title | Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems | |
| identifier doi | 10.1115/1.4050264 | |
| journal fristpage | 031006-1 | |
| journal lastpage | 031006-16 | |
| page | 16 | |
| tree | Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems:;2021:;volume( 004 ):;issue: 003 | |
| contenttype | Fulltext |