An empirical regression model toward optimized ergonomic conditions for monitoring room operators using RSM. Issue 7 (6th December 2020) - Fallahiarezoudar, Ehsan; Ahmadipourroudposht, Mohaddeseh; Ngadiman, Nor Hasrul Akhmal
Abstract : Purpose: This study aims to provide an ergonomic design of the monitoring room that has resulted in safe, functional and comfortable environment for the operators, which may lead to improve the efficiency. Currently, uses of closed‐circuit televisions to monitor the critical environments are widely applicable. The information is continuously transferred and analyzed through a center called monitoring room. Design/methodology/approach: Here, through creating a systematic analysis, a series of experiments was performed initially to evaluate and then optimize the parameters such as illumination, visual angle, operator-screen distance, number of scenes display in a single screen, workstation height, screen dimension and monitoring time that may affect the visual skill of the operators. Taguchi orthogonal array was used to analyze the significance of parameters on operator's response time to a threat. The five parameters were distinguished as significant. Later response surface methodology was utilized to optimize the parameters. Findings: Quadratic empirical model developed for the response time exposes the optimum response time was achievable at illumination of 500 lux, visual angle of 13°, operator-screen distance of 60 cm, three scenes, workstation height of 120 cm, screen dimension of 34" and monitoring time of 15 min. This shortened the response time by 28 per cent. The adequacy of the fitted model was successfully verified using the confirmation test with α = 95 per cent. Originality/value: The novelty of this work lies in the application of a systematic statistical analysis, which enables considering the interaction among the noise parameters and controllable one simultaneously. Furthermore, the obtained regression model can widely be used for adjusting the parameters accordingly based on various anthropometric data.