Citation

Uzor C, Oke SA. Int. J. Occup. Safety Ergonomics 2018; ePub(ePub): 1-22.

Affiliation

Department of Mechanical Engineering, University of Lagos , Lagos , Nigeria.

Copyright

(Copyright © 2018, Centralny Instytut Ochrony Pracy - Państwowy Instytut Badawczy, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/10803548.2018.1520471

PMID

30199318

Abstract

INTRODUCTION: The accurate tracking, elimination and control of hazards are fundamentals in accident avoidance at the operational machine guarding stations. This paper develops a machine guard usage compliance (MGUC) model. Nonetheless, very few studies account for operator's compliance to the usage of machine guards in workplaces.

METHODS: This paper contributes by first building up a multiple regression (MR) model, and second, to propose a novel integrated MR and Taguchi method (MR-TM) model that optimises the operator's compliance to guard usage. The comparative significance of the diverse factors was appraised and examined via analysis of variance (ANOVA).

RESULTS: A bottling process data from Nigeria illustrates the effectiveness of the proposed model. The coefficient of determination (R² = 0.997) established the efficient predictive ability of the MR model. The significant variables are the number of functional guards and damaged guards, and the number of non-compliants (p < 0.05). Simulated and field data variables exhibited good agreement (R² = 0.997). From the MR-TM model, the most significant result is the highest operator's compliance for machine guard usage with mean and signal-to-noise ratio values of 269.28 and 48.60, respectively.

CONCLUSION: The work provides safety managers with snapshot information for planning and control purposes.

Language: en

Keywords

Safety; hazards; manufacturing; process plant; risk