In operations management, the learning curve has been an effective tool in estimating operator performance. However, discontinuities in work disrupt the learning process and a phenomenon called remission or forgetting...In operations management, the learning curve has been an effective tool in estimating operator performance. However, discontinuities in work disrupt the learning process and a phenomenon called remission or forgetting occurs, resulting in increased time of performing the task upon resumption of work. The study aims to identify variables that significantly affect the remission rate of sewing operations in a manufacturing setting. Four variables--length of stint 1, percent Differenceat stint t, gender, and product family, were identified. Statistical analyses, such as paired t-test, correlation, regression, and analysis of variance （ANOVA） were conducted in order to observe the relationships between the dependent variable and independent variables. For the results of the first general regression, gender was found to be an insignificant variable in predicting remission rate, while product family, length of stint 1, and percent Differenceat stint I were statistically significant. Moreover, the final general regression, which excluded the insignificant gender variable and considered the （regrouped） product families, revealed that product family, length of stint 1, and percent Differenceat stint 1 were still statistically significant. Length of stint 1 had a moderately positive correlation with remission rate, while percent Differenceat stint i had a moderately negative correlation with remission rate. Also, percent Differenceat stint 1 was the largest contributor to the remission rate model. In terms of R2, the goodness-of-fit of the model is moderate. Finally, the model yielded an absolute error of 5.08%, indicating a high accuracy in predicting remission rate.展开更多
文摘In operations management, the learning curve has been an effective tool in estimating operator performance. However, discontinuities in work disrupt the learning process and a phenomenon called remission or forgetting occurs, resulting in increased time of performing the task upon resumption of work. The study aims to identify variables that significantly affect the remission rate of sewing operations in a manufacturing setting. Four variables--length of stint 1, percent Differenceat stint t, gender, and product family, were identified. Statistical analyses, such as paired t-test, correlation, regression, and analysis of variance （ANOVA） were conducted in order to observe the relationships between the dependent variable and independent variables. For the results of the first general regression, gender was found to be an insignificant variable in predicting remission rate, while product family, length of stint 1, and percent Differenceat stint I were statistically significant. Moreover, the final general regression, which excluded the insignificant gender variable and considered the （regrouped） product families, revealed that product family, length of stint 1, and percent Differenceat stint 1 were still statistically significant. Length of stint 1 had a moderately positive correlation with remission rate, while percent Differenceat stint i had a moderately negative correlation with remission rate. Also, percent Differenceat stint 1 was the largest contributor to the remission rate model. In terms of R2, the goodness-of-fit of the model is moderate. Finally, the model yielded an absolute error of 5.08%, indicating a high accuracy in predicting remission rate.
