Regression Model to Estimate Standard Time through Energy Consumption of Workers in Manual Assembly Lines under Moderate Workload. (17th February 2015)

• Record Type: Journal Article
• Authors: Ayabar, Abdul; De la Riva, Jorge; Sanchez, Jaime; Balderrama, Cesar
• Other Names: Özcan Uğur Academic Editor.
• Is Part Of: Journal of industrial engineering. Volume 2015(2015)
• Publication Date: 2015-02-17
• Subjects: Industrial engineering -- Periodicals; Industrial engineering; Periodicals; 620
• DOI: 10.1155/2015/382673
• Languages: English
• ISSNs: 2314-4882

Abstract

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.