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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Main Authors: H. A. Ajimotokan, K. A. Adebiyi
Format: Article
Language:English
Published: Faculty of Engineering and Technology 2010-12-01
Series:Nigerian Journal of Technological Development
Online Access:http://njtd.com.ng/index.php/njtd/article/view/110
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spelling 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
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AT kaadebiyi developmentofamathematicalmodelformanagingmagnitudeandriskfactorsofinjuries
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