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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.

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.

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.

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.

This paper aims to optimize the maintenance scheduling of emergency rescue wagons in railway companies using a genetic algorithm (GA). It offers an integrated model for simultaneously solving maintenance planning, preventive maintenance, prognostic information and resource planning from which optimal levels of the system performance in terms of cost and repair time could be determined.

This study initially evaluates the previous types of research in presenting the optimal model of the rescue train wagon for maintenance and repair planning and lists the identified criteria based on experts' opinions using fuzzy analytic hierarchy process (FAHP) and stepwise weight assessment ratio analysis (SWARA) techniques. Then, the final weight of the desired criteria is calculated. Later, the final decision matrix is evaluated by the experts. The final normal decision matrix is formed to select the optimal maintenance and repair planning plan based on the GA. Finally, two strategies including joint optimization strategy of preventive maintenance planning are compared with the independent preventive maintenance planning strategy.

According to the primary results, three primary parameters, including technology, human damage caused by negligence and the average failure rate, should be considered for launching the GA model. Based on the results of the second part; by comparing the preventive maintenance planning strategy independently, the joint optimization strategy reduces the total cost of production up to 8.25%. Comparison results show that the total cost of joint optimization production is less than independent preventive maintenance and repair planning. Moreover, the value of total process time in joint optimization strategy was reduced by 1.2% compared to independent preventive maintenance (PM) planning (from 137.90 to 136.20 h).

The novelty of this paper lies on the application of the GAs to develop an optimized PM scheduling to localize the maintenance planning for maximizing productivity, avoid train accidents, reduce costs and increase efficiency and capacity.