Determination of Variables That Affect the Remission Rate of Sewing Operations in a Textile Company  

作　　者：Josefa Angelie Dilla Revilla Leianne Yusi Casupang Iris Ann Galarosa Martinez Ma. Laami Dilla Revilla 

机构地区：[1]University of the Philippines Los Bafios, Laguna, Philippines [2]University of the Philippines Diliman, Quezon City, Philippines [3]Philippine Institute for Development Studies, Makati City, Philippines

出　　处：《Chinese Business Review》2015年第9期411-422,共12页中国经济评论（英文版）

摘　　要：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.

关 键 词：remission rate learning remission model learning curve effects of work break continuous performance manufacturing 

分 类 号：U469.11[机械工程—车辆工程] X53[交通运输工程—载运工具运用工程]