Optimization of a manufacturing process results in higher productivity and reduced wastes. Production parameters of a local steel bar manufacturing industry of Pakistan is optimized by using six Sigma-Define, measure,...Optimization of a manufacturing process results in higher productivity and reduced wastes. Production parameters of a local steel bar manufacturing industry of Pakistan is optimized by using six Sigma-Define, measure, analyze, improve, and controlmethodology. Production data is collected and analyzed. After analysis, experimental design result is used to identify significant factors affecting process performance. The significant factors are controlled to optimized level using two-level factorial design method. A regression model is developed that helps in the estimation of response under multi variable input values. Model is tested, verified, and validated by using industrial data collected at a local steel bar manufacturing industry of Peshawar(Khyber Pakhtunkhwa, Pakistan). The sigma level of the manufacturing process is improved to 4.01 from 3.58. The novelty of the research is the identification of the significant factors along with the optimum levels that affects the process yield, and the methodology to optimize the steel bar manufacturing process.展开更多
质量成本(COQ,Cost of Quality)是衡量提高质量活动的效果和效率的标准。COQ模型在质量成本研究中起着重要的作用。基于“6σ管理”中“持续改进”的思想和方法,用“kσ”作为质量水平(QL,Quality Level)的度量,笔者得到了不同质量水平...质量成本(COQ,Cost of Quality)是衡量提高质量活动的效果和效率的标准。COQ模型在质量成本研究中起着重要的作用。基于“6σ管理”中“持续改进”的思想和方法,用“kσ”作为质量水平(QL,Quality Level)的度量,笔者得到了不同质量水平下的动态总COQ模型。进而,还提供了不同质量水平下的总质量成本曲线。展开更多
文摘Optimization of a manufacturing process results in higher productivity and reduced wastes. Production parameters of a local steel bar manufacturing industry of Pakistan is optimized by using six Sigma-Define, measure, analyze, improve, and controlmethodology. Production data is collected and analyzed. After analysis, experimental design result is used to identify significant factors affecting process performance. The significant factors are controlled to optimized level using two-level factorial design method. A regression model is developed that helps in the estimation of response under multi variable input values. Model is tested, verified, and validated by using industrial data collected at a local steel bar manufacturing industry of Peshawar(Khyber Pakhtunkhwa, Pakistan). The sigma level of the manufacturing process is improved to 4.01 from 3.58. The novelty of the research is the identification of the significant factors along with the optimum levels that affects the process yield, and the methodology to optimize the steel bar manufacturing process.
文摘质量成本(COQ,Cost of Quality)是衡量提高质量活动的效果和效率的标准。COQ模型在质量成本研究中起着重要的作用。基于“6σ管理”中“持续改进”的思想和方法,用“kσ”作为质量水平(QL,Quality Level)的度量,笔者得到了不同质量水平下的动态总COQ模型。进而,还提供了不同质量水平下的总质量成本曲线。