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Article InfoBackground: Noise pollution is one of the common physical harmful factors in many work environments. The current study aimed to assess the personal and environmental noise level and project the sound map of an Iranian tire manufacturing complex using Surfer V.14 and Noise At Work tools. Materials and Methods: This descriptive study was conducted in the curing hall [including curing, sandblast, and trimming units] of a tire manufacturing complex in 2018. Following ISO 9612:2009, Casella Cel-320 was used to measure the personal noise level, while CEL-450 sound level meter (Casella-Cel, the UK) was employed to assess the environmental sound pressure level [ISO 1996[ISO -1:2016.The sound and isosonic maps were projected using Surfer V.14 and Noise At Work. Results: The results indicated that the highest received dose (163.30%) and personal equivalent sound level [87.13 dBA] were recorded for workers in the curing unit. The results of measuring the environmental sound pressure level also revealed that out of 101 measurement stations in the curing unit, 76 stations (75.25%) were hazardous areas (over 85 dBA). Conclusions: Over 75% of the curing hall had a sound pressure level greater than 85 dBA. The curing unit was found to be the most dangerous area in terms of noise pollution. It is, therefore, necessary to implement noise control measures (e.g., the use of screens, barriers, enclosures), apply hearing conservation programs, and conduct auditory tests on workers in this unit.

BACKGROUND: Noise is a common harmful physical factor in the work environment. OBJECTIVE: This study sought to prioritize noise control methods using the analytical hierarchy process (AHP) in a tire factory. METHODS: The study, which adopted a cross-sectional, descriptive, analytical design, was conducted in the baking hall of an Iranian tire manufacturing factory in 2018. 4 criteria (namely implementation and maintenance cost, method applicability, method effectiveness and efficiency, and intervention in the process) and 8 alternatives (including reducing individuals’ noise exposure time, designing and installing sound isolation chamber for operators, using of earmuffs and earplug simultaneously, changing processes or operational procedures in machinery with excessive noise generation, forming noise control engineering teams, requiring people in charge to quickly fix the leaks and change baking press washers on time, using acoustic panels in the ceiling and walls, and designing and manufacturing silencer and nuzzle for the steam and compressed air outlet of baking press machinery) were selected. Then, to prioritize noise control methods based on objectives, criteria, and alternatives, an AHP questionnaire was developed and completed by domain experts and noise control specialists. Data analysis was performed using Expert Choice V. 11 and Excel. RESULTS: The results showed that the inconsistency rate in all cases was less than 10%, hence the consistency of responses was approved. Based on experts’ opinion about the selected criteria, “implementation and maintenance cost” had the highest weight (0.481), while “method effectiveness and efficiency” recorded the lowest one (0.046). With regard to the alternatives, “change in the process” registered the greatest weight (0.193), whereas “individuals’ noise exposure time” had the lowest weight (0.046). CONCLUSIONS: Based on the final weights, the most appropriate noise control methods in this industry are changing processes in machinery with excessive noise generation, forming noise control engineering team, and manufacturing silencer and nuzzle for the steam and compressed air outlet of baking press machinery. Furthermore, AHP is a suitable approach for prioritizing decisions related to noise control.