Table of Contents
Journal of Industrial Engineering
Volume 2015 (2015), Article ID 382673, 5 pages
http://dx.doi.org/10.1155/2015/382673
Research Article

Regression Model to Estimate Standard Time through Energy Consumption of Workers in Manual Assembly Lines under Moderate Workload

1Department of Industrial Engineering, Instituto Tecnológico de Delicias, Paseo Tecnológico Km 3.5, 33000 Delicias, CHIH, Mexico
2Division of Postgraduate Studies and Research, Instituto Tecnológico de Ciudad Juárez, Avenida Tecnológico 1340, 32500 Ciudad Juárez, CHIH, Mexico
3Department of Industrial and Manufacturing Engineering, Universidad Autónoma de Ciudad Juárez, Avenida del Charro 450 Norte, 32310 Ciudad Juárez, CHIH, Mexico

Received 19 September 2014; Accepted 31 January 2015

Academic Editor: Uğur Özcan

Copyright © 2015 Abdul Ayabar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We propose a Standard Time (ST) Estimate Model based on energy demand to attain more equal work distribution in manual assembly lines. The proposal was developed estimating the energy consumption by monitoring the heart rate (HR) of 84 people between 18 and 48 years old while performing repetitive activities under moderate workload (2.5–5.0 kilocalories/minute (Kcal/min)). Variables on one model were determined, which were based on energy consumption (EC) using the 13-variable Best-Subset function. Subsequently, a general equation for the Standard Time (ST) Estimate Model was calculated through lineal regression. Two significant variables were obtained: total kilocalories (Kcal tot.)/pieces and total Kcal/operation time (OT) for each station, which are included in a Standard Time Estimate Model. ST can be represented with a regression model measuring the total number of kilocalories consumed by workers and the OT, which can help companies to balance the cycle time in their assembly lines.