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The Double Diaphragm Preforming (DDPF) process uses vacuum pressure and heat to pre-shape dry carbon fabric reinforcements between flexible diaphragms in liquid composite molding (LCM). Accurate modeling of heat transfer within DDPF requires knowledge of the thermophysical properties of the constituent materials under processing conditions. This study investigates the thermal conductivity of silicone diaphragms and carbon fabrics with embedded thermoplastic binder webs, utilizing transient plane source (TPS) and modified transient plane source (MTPS) methods, respectively. Additionally, the specific heat of silicone, carbon fibers (both chopped and powdered), and binder were measured using differential scanning calorimetry (DSC). Mixed samples comprising chopped fibers with 1.8 wt% binder and powdered fibers with 3.6 wt% binder was also analyzed with DSC. This study also examined the influence of reheating cycles on the specific heat of carbon fiber—3.6 wt% binder samples—and the effect of compaction and vacuum on the thermal conductivity of carbon fabrics with an embedded binder. While silicone exhibited linear-specific heat behavior, the thermoplastic binder showed non-linearity due to phase change. The combined carbon fiber-binder samples demonstrated slight non-linear specific heat variations depending on reheating cycles. The thermal conductivity of the fabric preforms decreased with the addition of thermoplastic binder and under vacuum-compaction conditions. The established temperature-dependent specific heat relationships and thermal conductivity provide valuable data for optimizing DDPF preforming parameters and enhancing energy efficiency in composite manufacturing. [ABSTRACT FROM AUTHOR]

Composite materials are increasingly important in making high-performance products. However, contemporary composites manufacturing processes still encounter significant challenges that range from inherent material stochasticity to manufacturing process variabilities. This paper proposes a novel smart Industrial Internet of Things framework, which is also referred to as an Artificial Intelligence of Things (AIoT) framework for composites manufacturing. This framework improves production performance through real-time process monitoring and AI-based forecasting. It comprises three main components: (i) an array of temperature, heat flux, dielectric, and flow sensors for data acquisition from production machines and products being made, (ii) an IoT-based platform for instantaneous sensor data integration and visualisation, and (iii) an AI-based model for production process forecasting. Via these components, the framework performs real-time production process monitoring, visualisation, and prediction of future process states. This paper also presents a proof-of-concept implementation of the framework and a real-world composites manufacturing case study that showcases its benefits. [ABSTRACT FROM AUTHOR]

Undoubtedly, noise has become a major hazardous issue in today's industrial world, with a lot of people suffering from exposure to excessive noise in their work environments. This study was conducted to weigh and prioritize noise control methods in an Iranian tire manufacturing complex in Iran. The Delphi method and the Technique for Order Preference by Similarity and an Ideal Solution (TOPSIS) were utilized for this purpose. This cross-sectional, descriptive study was conducted in the baking hall of an Iranian tire manufacturing factory in 2016. To weigh and prioritize noise control methods, Analytic Hierarchy Process (AHP) and TOPSIS were applied. In total, 4 criteria and 8 alternatives were examined. An AHP and TOPSIS questionnaire was then designed to prioritize noise control methods in the light of the objectives, criteria, and alternatives. Then, the collected data were fed into Expert Choise. V. 11 and Excel and data analysis was carried out using TOPSIS. The results of data analysis indicated that the inconsistency rate in all the cases was smaller than 10%, hence the consistency of the responses was verified. According to the TOPSIS results and experts' opinions about the criteria, implementation and maintenance cost (with a weight of 0.481) and method effectiveness and efficiency (with a weight of 0.046) had the highest and lowest priority respectively. Based on the weights TOPSIS, the appropriate methods for controlling noise in tire manufacturing are designing and manufacturing silencer, requiring people in charge to quickly fix the leaks and change baking press washers on time. [ABSTRACT FROM AUTHOR]

Workers' exposure to excessive noise is a big universal work-related challenges. One of the major consequences of exposure to noise is permanent or transient hearing loss. The current study sought to utilize audiometric data to weigh and prioritize the factors affecting workers' hearing loss based using the Support Vector Machine (SVM) algorithm. This cross sectional-descriptive study was conducted in 2017 in a mining industry in southeast Iran. The participating workers (n = 150) were divided into three groups of 50 based on the sound pressure level to which they were exposed (two experimental groups and one control group). Audiometric tests were carried out for all members of each group. The study generally entailed the following steps: (1) selecting predicting variables to weigh and prioritize factors affecting hearing loss; (2) conducting audiometric tests and assessing permanent hearing loss in each ear and then evaluating total hearing loss; (3) categorizing different types of hearing loss; (4) weighing and prioritizing factors that affect hearing loss based on the SVM algorithm; and (5) assessing the error rate and accuracy of the models. The collected data were fed into SPSS 18, followed by conducting linear regression and paired samples t-test. It was revealed that, in the first model (SPL < 70 dBA), the frequency of 8 KHz had the greatest impact (with a weight of 33%), while noise had the smallest influence (with a weight of 5%). The accuracy of this model was 100%. In the second model (70 < SPL < 80 dBA), the frequency of 4 KHz had the most profound effect (with a weight of 21%), whereas the frequency of 250 Hz had the lowest impact (with a weight of 6%). The accuracy of this model was 100% too. In the third model (SPL > 85 dBA), the frequency of 4 KHz had the highest impact (with a weight of 22%), while the frequency of 250 Hz had the smallest influence (with a weight of 3%). The accuracy of this model was 100% too. In the fourth model, the frequency of 4 KHz had the greatest effect (with a weight of 24%), while the frequency of 500 Hz had the smallest effect (with a weight of 4%). The accuracy of this model was found to be 94%. According to the modeling conducted using the SVM algorithm, the frequency of 4 KHz has the most profound effect on predicting changes in hearing loss. Given the high accuracy of the obtained model, this algorithm is an appropriate and powerful tool to predict and model hearing loss. [ABSTRACT FROM AUTHOR]

The challenges and disadvantages of distribution channels diminish the effectiveness and efficiency of distribution channels, which affects the profits for distributors, manufacturers, and reduces customer satisfaction. Therefore, the purpose of this study is to investigate the problems of the distribution and marketing of these products. This study was conducted using a qualitative research method and a semistructured interview to analyze the main research problems. It is a case study, and its statistical population consists of the managers of the Organization of Fruit and Vegetable Fields and several managers of transportation and horticultural products distribution companies in Tehran. The sample consists of 18 managers, selected using the snowballing method. Data was collected via a semi-structured interview. The results showed the problems of distribution and marketing channels are categorized into two categories of direct and indirect. Direct factors are including transportation, warehousing, maintenance, and distribution. Indirect factors are including imports, traditional agriculture, and enforcement policies. The results also showed that unconditional mediators, lack of a formal and regulated distribution system, and worn and inefficient transportation systems are significant problems of horticultural product distribution channels. [ABSTRACT FROM AUTHOR]

Background and objectives: Maximal Aerobic Capacity (VO2-max) is an indicator for the preparedness of the cardiovascular and respiratory systems and a tool to estimate the physiological fitness of individuals for their work. This study aimed to measure the VO2-max and Physical Work Capacity (PWC) of workers at a metal industry and the factors affecting it using a single-stage step test. Materials and Methods: This cross-sectional study was conducted on 60 workers in a metal industry in Tehran. Data collection tools was a questionnaire including separate sections asking about demographic and anthropometric (height, weight and BMI) characteristics. Quantitative variables were recorded after being measured. The Tuxworth and Shahnawaz method and step test were used in order to estimate VO2-max and PWC. Data were analyzed using SPSS 22. Findings: The relative humidity of the place was 40% and local air pressure was 879 atmospheres. The average VO2-maxand average maximum PWC of the study population were 3.13±0.283L/min and 15.65±1.41 kcal/min, respectively. There was a significant relationship between VO2-max using single-stage step test and BMI (P=0.01), number of hours of exercise per week (P=0.009) and age (P=0.01). Conclusion: The step test is a rapid, easy and low-cost method to estimate physiological adaptation and PWC of individuals. Variables such asage, hours of exercise per week and BMI are effective on aerobic capacity. [ABSTRACT FROM AUTHOR]

The present study used disability adjusted life years (DALY) to estimate the burden of external cause of injuries in construction workers insured in Iran in 2012. The Global Burden of Disease method (2010) was used to estimate the years of life lost due to death (YLL) and years of life lost due to disability (YLD). DALY was calculated as the sum of YLL and YLD. There were 5352 injured construction workers in Iran (11.25 individuals per 1000). Falling was the most common incidence and included 2490 individuals (46.53%). Totally, DALY was estimated 18,557 years for all age groups and both genders including 17,821 YLD (96%) and 736 YLL (4%). The DALY related to construction work is high in Iran and it has notably affected the young. Hence more preventive methods should be applied to reduce the overall burden of specific external cause of injuries especially in young and inexperienced workers. [ABSTRACT FROM AUTHOR]

Nowadays in the world, tuberculosis is the second largest killer of adults after HIV. Due to the location of presidios that is mostly located in hazardous zones soldiers and army personnel are considered high risk, therefore we decided to determine the prevalence of tuberculosis status in this group of people. This was a cross-sectional descriptive research that studied the prevalence of pulmonary tuberculosis in soldiers and military personnel in the last 15 years in tuberculosis and lung disease research center at Tabriz University of Medical Sciences. The statistical population consisted of all the soldiers and military personnel. The detection method in this study was based on microscopic examination following Ziehl-Neelsen Stain and in Leuven Stein Johnson culturing. Descriptive statistics was used for statistical analysis and statistical values less than 0.05 were considered significant. By review information in this center since the 1988-2013 with 72 military personnel suffering from tuberculosis, it was revealed that among them 30 women, 42 men, 14 soldiers, 29 family members, and 29 military personnel are pointed. A significant correlation was found between TB rates among military personnel and their families. Although in recent years, the national statistics indicate a decline of tuberculosis, but the results of our study showed that TB is still a serious disease that must comply with the first symptoms of tuberculosis in military personnel and their families that should be diagnosed as soon as possible. [ABSTRACT FROM AUTHOR]

Introduction: Heat stress disrupts blood hormones and reduces workers' cognitive performance. To further shed light on the dysfunction of heat stress, the present study aimed to evaluate its effect on cognitive performance of petrochemical workers., Materials and Methods: This descriptive-analytical cross-sectional study was conducted in 2020 in one of the Iranian petrochemical companies. Participants were divided into 2 case groups and 1 control group. They worked 12 h and their shift entialed one week working day and one week working night. According to the ISO 7243 standard, the heat stress index of employees was measured at the beginning, in the middle and at the end of the shift separately. Continuous Performance Test (CPT) and N-back cognitive performance tests were performed at the beginning, in the middle and at the end of the shift to determine the level of cognitive performance. The data were analyzed using SPSS software version 20 and the significance level was set at 0.05., Results: Comparison of the results in the continuous performance test showed significant differences between the three groups with regard to the omission error and response time at the end of the shift. Moreover, according to the working memory test, participants reaction time during the shift significantly increased. Besides, average correct responses significantly reduced during the shift. Finally, the heat stress throughout the shift had a significant effect on the commission error and the response time of individuals., Conclusion: Heat stress affects people's cognitive performance in such a way that it can decrease their cognitive performance by increasing the commission error and response time and reducing the average correct response of site operators, generally reducing the cognitive performance of people at the end of the shift., Competing Interests: The authors declare no conflict of interest., (© 2021 Published by Elsevier Ltd.)