Prediction of Standard Times in Assembly Lines Using Least Squares in Multivariable Linear Models

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Abstract

Currently, the highly competitive environment of the assembly industries has been an engine for them to seek differentiating factors for improving their efficiency. One of these factors is the study of times and methods (referred to the analysis and the critical and systematic examination of how a task is presently performed, facilitating to find more effective methods), which allows alleviating internal and external aspects that affect productivity and provides the basis for management decision-making. The present work has two primary objectives; firstly, the calculation of standard times within the enterprise operative area and, additionally, the development of a mathematical model for time prediction. For the fulfillment of these purposes, a referential conceptual framework was established about the study of time and the multiple linear regression model. This framework allowed elaborating a procedure for the development of the mathematical prediction model, together with its validation. The study concludes with a discussion on the importance of having models to estimate standard times in business decision making, and the establishment of relevant conclusions.

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Ramirez, J., Guaman, R., Morles, E. C., & Siguenza-Guzman, L. (2020). Prediction of Standard Times in Assembly Lines Using Least Squares in Multivariable Linear Models. In Communications in Computer and Information Science (Vol. 1195 CCIS, pp. 455–466). Springer. https://doi.org/10.1007/978-3-030-42531-9_36

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