Humming noise reduction of ceiling fan in the mass production applying DMAIC-six sigma approach

Abstract

Purpose Success and business reputation depend upon the quality of products where product quality depends upon the capability of a process, yield value and sigma score, etc. Poor quality of ceiling fan and mass rejection from quality check resulted in an alarming amount of cost for rework. As a result, the fulfillment of the production target was getting difficult day by day. The main purpose of this research is to identify the crucial causes for humming noise of ceiling fans and control it to a tolerable level so that maximum quality can be achieved. Design/methodology/approach The poor quality of ceiling fans was determined from the Pareto analysis of the define, measure, analyze, improve and control model which was humming noise during running and further actions were undertaken regarding the reduction of the humming noise. Project charter was formed before initiating the measure phase to study the suppliers, inputs, processes, outputs and customers diagram with process parameters and existing noise data were collected from random samples to determine the rolled throughput yield (94.95% existing) and existing sigma score which value of 3.14 and also the poor value (1.05) of process potential index implied that the process condition was below standard (<1.33) and need to be improved badly. Then root causes analysis and relationship diagram was prepared to identify the possible causes and 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. Findings The minimum value of air gap was determined from boxplot analysis which was 0.2 mm–0.225 mm and the corresponding mean, the minimum and maximum value of sound level in dB (37.5–40.3 dB) for 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 US$23,438/year caused by the poor quality of ceiling fans. Practical implications Only quantitative values of the causes behind the humming noise were possible to identify. Other trivial many causes elimination might improve the sigma score closer to 6.00. The final sigma score that was achieved from this research was sustainable. Originality/value A structural approach with proper data analysis and application of various tools to detect the actual cause behind the humming noise of ceiling fans with numerical value has not been found in any literature. This research study can be a valuable asset for ceiling fan mass producers.