DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIES
A mathematical model was developed for managing magnitude and risk factors of injuries in a manufacturing industry employing System Dynamics (SD) approach. Data were collected using an injury and illness investigation register. These were used to estimate and validate the parameters of the model. Th...
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2010-12-01
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Series: | Nigerian Journal of Technological Development |
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doaj-451593f0adc54e1faa91c42b4caef7a02020-11-25T03:19:24ZengFaculty of Engineering and TechnologyNigerian Journal of Technological Development2437-21102437-21102010-12-01727582DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIESH. A. Ajimotokan0 K. A. Adebiyi1 Department of Mechanical Engineering, University of Ilorin, Ilorin, Nigeria Department of Mechanical Engineering, Ladoke Akintola University of Technology, Ogbomoso, NigeriaA mathematical model was developed for managing magnitude and risk factors of injuries in a manufacturing industry employing System Dynamics (SD) approach. Data were collected using an injury and illness investigation register. These were used to estimate and validate the parameters of the model. The principle of SD was employed to identify the relevant risk management safety-related components and their interrelationships. Results obtained from the experimental data depict a random periodic upwards and downwards trend in the magnitude of injuries; whereas the predicted injuries yielded and exponential decay in the number of injuries occurrence. The means and standard deviations of the observed and predicted injuries were 27 and 9.08; and 26 and 6.61 respectively. The corresponding values for observed and predicted preventions were 18 and 9.08; and 19 and 8.48 respectively. A comparison of predicted and observed injuries depict that the model is useful for providing a decision support and predicting the main variables required for managing magnitude and risk factors of injuries in a bottling planthttp://njtd.com.ng/index.php/njtd/article/view/110 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H. A. Ajimotokan K. A. Adebiyi |
spellingShingle |
H. A. Ajimotokan K. A. Adebiyi DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIES Nigerian Journal of Technological Development |
author_facet |
H. A. Ajimotokan K. A. Adebiyi |
author_sort |
H. A. Ajimotokan |
title |
DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIES |
title_short |
DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIES |
title_full |
DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIES |
title_fullStr |
DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIES |
title_full_unstemmed |
DEVELOPMENT OF A MATHEMATICAL MODEL FOR MANAGING MAGNITUDE AND RISK FACTORS OF INJURIES |
title_sort |
development of a mathematical model for managing magnitude and risk factors of injuries |
publisher |
Faculty of Engineering and Technology |
series |
Nigerian Journal of Technological Development |
issn |
2437-2110 2437-2110 |
publishDate |
2010-12-01 |
description |
A mathematical model was developed for managing magnitude and risk factors of injuries in a manufacturing industry employing System Dynamics (SD) approach. Data were collected using an injury and illness investigation register. These were used to estimate and validate the parameters of the model. The principle of SD was employed to identify the relevant risk management safety-related components and their interrelationships. Results obtained from the experimental data depict a random periodic upwards and downwards trend in the magnitude of injuries; whereas the predicted injuries yielded and exponential decay in the number of injuries occurrence. The means and standard deviations of the observed and predicted injuries were 27 and 9.08; and 26 and 6.61 respectively. The corresponding values for observed and predicted preventions were 18 and 9.08; and 19 and 8.48 respectively. A comparison of predicted and observed injuries depict that the model is useful for providing a decision support and predicting the main variables required for managing magnitude and risk factors of injuries in a bottling plant |
url |
http://njtd.com.ng/index.php/njtd/article/view/110 |
work_keys_str_mv |
AT haajimotokan developmentofamathematicalmodelformanagingmagnitudeandriskfactorsofinjuries AT kaadebiyi developmentofamathematicalmodelformanagingmagnitudeandriskfactorsofinjuries |
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