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

Abdul Ayabar,Jaime Sanchez,Cesar Balderrama,Jorge De La Riva

doi:10.1155/2015/382673

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.

Highlights

Leibovich et al [1] argued that work overload during manual operations in industry entails issues such as excessive physical work, insufficient rest, inadequate work conditions, monotony, work stress, and poor social relations, as well as instability and perception of work insecurity in regard to attitudes to work
We propose a Standard Time (ST) Estimate Model based on energy demand to attain more equal work distribution in manual assembly lines
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

Summary

Introduction

Leibovich et al [1] argued that work overload during manual operations in industry entails issues such as excessive physical work, insufficient rest, inadequate work conditions, monotony, work stress, and poor social relations, as well as instability and perception of work insecurity in regard to attitudes to work. According to Meza and Ramırez et al [3], this is why the number of complaints associated with physical fatigue in manufacture industry workers has been increased due to the intensification of work performed throughout the working day. Krause et al.’s research [5] shows that a higher EC at work is linked to an accelerated progression of atherosclerosis, even after the cardiovascular risk factors have been controlled. This appeared among older workers and those with preexistent ischemic cardiomyopathy or carotid artery stenosis conditions

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Discussion

Conclusion