8 research outputs found
Modelling occupational health and safety risks among unskilled workers in construction industry
No full textTo enhance workers’ protection in construction tasks, Occupational Health and Safety Risks (OHSR) needs to be properly recognized, assessed and controlled. This study modeled Health and Safety Risk (HSR) among unskilled workers in construction works. Data was collected from 150 subjects in 12 construction sites located in Southwest Nigeria. Variables considered to play key roles in HSR causation were measured with questionnaire. All variables that correlated significantly (p≤ 0.05) to HSR on the tasks were noted by Spearman’s rho correlation (Src) using SPSS software. The model prediction was by adjusted R2 and was validated by comparison with Human Professionals’ Predictions (HPP). Model Cook’s distance and its closeness to being normally distributed were evaluated. 37 attributes variables were initially collated with 13 predictor variables remained in the optimum model. Wrong work-methods, lack of work-control and harsh outdoor environment ranked among the strongest positive β coefficients (0.217, 0.127 and 0.126 respectively). The maximum coefficient of the adjusted R2 determination was 0.708. The histogram of the residuals suggested closeness to being normally distributed and 0.930 as the maximum Cook’s distance. Comparison between the OHSR model and the HPP had Src strength of 0.965 (p<.01). The OHSR showed statistically significantly higher level of hazards’ rating (3.7533 ± 0.233) compared to HPP (3.2667 ± 0.18097), t(28) = -1.648, p = 0.197. OHSR model was developed and the performance was rated good, satisfied the study’s objectives. The author recommended development of measures at reducing β coefficients of all the predictor variables to minimize workplaces OHS
Development of a Permeable Meter for Mould Industries Using Locally Sourced Materials
No full textOne of the major factors for production of quality casting is the control of properties of moulds and cores to make them uniform and consistent quality. Permeable meter is used for the determination of the venting ability of sand moulds and cores. This testing equipment is being imported to the country as at today. The cost is high, and they are not readily available to foundry operators.Hence there is need to design and develop a permeable meter using locally sourced materials and make it available at an affordable price, thereby improving foundry technology in Nigeria. Two different method could be used to measure permeability of sand; determination of air flow rate and measurement of pressure difference between the orifice and the top of sand specimen. The first method was adopted in the development of the Permeable meter. On testing, the values of permeability measured using the equipment was comparable to the results obtained from thestandardized imported one. The cost of production was 30% of the cost of imported one, not even now that exchange rate to international currency has skyrocketed. The work has incorporated design and fabrication principles that resulted in a relatively cheap product that can be constructed locally by an average Fabricator and Technicia
Assessment of Strength Characteristics of Propylene Glycol Self-curing Concrete
No full textConcrete with special features of self-curing had assisted in ameliorating the problem of improper curing in construction industries. This study evaluated the use of Propylene Glycol (PG) in the compressive and flexural strength of self-curing concrete. Concrete grades M15, M20, and M30 were batched by weight, and propylene glycol was added to the mix, within the dosage of 0.5, 1.0, 1.5, and 2%, respectively. Concrete cubes and prisms of sizes 150 × 150 × 150 mm and 100 × 100 × 400 mm were cast from the mixtures and allowed to cure internally in the open air for 28 days to produce Propylene Glycol Self-Cured Concrete (PGSCC). Two control samples were cast without PG addition, cured by ponding and open air for 28 days to produce Open-air Cured Concrete (OCC) and Ponding Cured Concrete (PCC). Compressive and flexural strength tests were conducted on the PGSCC and control samples. PGSCC had compressive strengths of 18.67, 22.40, and 31.29 N/mm2 and flexural strengths of 3.24, 3.55, and 4.20 N/mm2 compared to the control’s compressive strengths of 16.41, 20.59, and 27.70 N/mm2 and flexural strengths 3.03, 3.43 and 3.95 N/mm2 for concrete grade M15, 20 and 30, respectively. Propylene glycol addition within the dosage of 0.5 to 1.5% in concrete improves the compressive and flexural strength of concrete. The use of propylene glycol was found to be effective and a good agent for self-curing concrete technology
A Shoveling-related Pain Intensity Prediction Expert System for Workers’ Manual Movement of Material
No full textIn
this study, a fuzzy-based expert system called the Pain Intensity Prediction
Expert System (PIPES) was developed to predict pain severity risk (PSR) in
shoveling-related tasks. The primary objective was to develop a non-changing rating risk assessment ergonomics
tool that both efficient
and comparable with those obtained from human ergonomics experts in the field
of application. PIPES used fuzzy set
theory (FST) to make decisions about the level of pain associated with a
selected worker base on the measured task variables, namely scooping rate, scooping time, shovel load, and
throw distance as input and PSR as the result. Values obtained from variable measurements from a sand shoveling task
were run with PIPES, and the results were compared with the workers’
self-reported pain (WSRP) intensity using a numeric rating scale (NRS) tool. The result of validation showed that there was a
strong positive relationship between WSRP NRS and PIPES NRS, with a correlation
coefficient of 0.70. The independent sample t-test for mean difference showed that WSRP had a statistically significantly lower level of NRS (4.35 ± 2.1)
compared to PIPES (4.75 ± 2.2), t (38) = - 0.591, p = 0.558. With a
significance level of 0.001 at 95% confidence, the groups’ means were not
significantly different. The study developed an expert system, PIPES, which can be used as a computerized
representation of ergonomics experts, who are scarce. PIPES can be applied to construction industries, sand mine locations,
and any workplace where materials are manually moved using a shovel
Assessment of Strength Characteristics of Propylene Glycol Self-Curing Concrete
No full textConcrete with special features of self-curing had assisted in ameliorating the problem of improper curing in construction industries. This study evaluated the use of Propylene Glycol (PG) in the compressive and flexural strength of self-curing concrete. Concrete grades M15, M20, and M30 were batched by weight, and propylene glycol was added to the mix, within the dosage of 0.5, 1.0, 1.5, and 2%, respectively. Concrete cubes and prisms of sizes 150 × 150 × 150 mm and 100 × 100 × 400 mm were cast from the mixtures and allowed to cure internally in the open air for 28 days to produce Propylene Glycol Self-Cured Concrete (PGSCC). Two control samples were cast without PG addition, cured by ponding and open air for 28 days to produce Open-air Cured Concrete (OCC) and Ponding Cured Concrete (PCC). Compressive and flexural strength tests were conducted on the PGSCC and control samples. PGSCC had compressive strengths of 18.67, 22.40, and 31.29 N/mm2 and flexural strengths of 3.24, 3.55, and 4.20 N/mm2 compared to the control’s compressive strengths of 16.41, 20.59, and 27.70 N/mm2 and flexural strengths 3.03, 3.43 and 3.95 N/mm2 for concrete grade M15, 20 and 30, respectively. Propylene glycol addition within the dosage of 0.5 to 1.5% in concrete improves the compressive and flexural strength of concrete. The use of propylene glycol was found to be effective and a good agent for self-curing concrete technology
Women's behavioral patterns in domestic tasks in Western Nigeria : hazards forecasting with neural network classifier
No full textBehavioral pattern is the characteristic ways a person acts and has been recognized as a cause of many home accidents (h-accd). This study reviewed the types and prevalence of injuries among women in domestic works and proposes a model using Artificial Neural Network (ANN) function to forecast the safety level of women in domestic duty. The study was conducted in some parts of Western Nigeria among 340 subjects (171 married and 169 unmarried) using questionnaire. SPSS was used for data analysis. The ANN function was developed in MATLAB 2015a using the subjects’ behavioral patterns and the model was used to predict safety in domestic duties (d-duties) among some women. ‘Cuts/laceration’ (40%) and ‘skin contact with hot substance’ (35.6%) were commonly reported. Carelessness (26.5%) and distraction (22.1%) were the main leading factors across the groups. Marital status and h-accd (Chi-square =4.323 and p= .038); ‘hours spent on domestic works’ and ‘the h-accd’ were both significant among other tested groups variables. With the developed ANN function, the results of the MSE was 0.33626 indicating that the function predicted the exact value. The result of the predicted h-accd (safety= -0.5445, hazards= 1.0228) in d-duties of the tested variables with the ANN function, showed a very low level of safety. The article concludes that the developed model is reliable and a recommended ergonomic tool useful in all homes, most especially where women perform most domestic works.http://vc.bridgew.edu/jiwshj2021Electrical, Electronic and Computer Engineerin
