Track: Quality Control

Abstract

The purpose of the current manuscript is to discuss the application experiences of Lean Six Sigma (LSS) process improvement methodology in defect reduction. The work discussed in the manuscript pertains to the results that were obtained in the quality control improvement project of a Shade Net Manufacturing plant in Botswana, to eliminate product defects. The defects in this case, were defined as the snapping of the manufactured plastic threads used in the production of the shade nets. This snapping of the threads created holes on the knitted nets which also then led to inconsistencies in the knitted pattern of the nets. At any given month, these defects amounted to an average of 60% of the total production output which compounded to a yearly monetary loss of about US$290 250 to the company. Several LSS tools were applied within the DMAIC (Define-Measure-Analyze-Improve-Control) process improvement methodology from defining the problem through control and up to recommendations that could eliminate the process defects. Tools such as SIPOC (Supplier-Input-Process-Output-Customer) diagrams, Process Maps, Cause and Effect diagrams, Process Capability Analysis, Gage Repeatability and Reproducibility (Gage R&R), Multiple Linear Regression and Design of Experiments (DOE) were applied in the project.  Ultimately, a Failure Mode Effects Criticality Analysis (FMEA) was also produced which could help the company to maintain and control the process according to the recommendations that were produced. The main findings of the study revealed through regression analysis was that four major process variables affected the tensile strength of the threads, and this led to the observed defects. Through DOE the optimal settings of these variables were identified, and the tensile strength was observed to increase by 9.1% from an average of 35.8718 MPa to 39.1269 MPa. This result also led to a significant defect reduction from 60% to only 0.025% of the total production output and a jump in the process sigma level from 1.25 to 4.98.