SAFETY STRATEGY ALLOCATION SIMULATOR FOR ACCIDENT REDUCTION AND COST SAVINGS IN SAFETY MANAGEMENT SYSTEM
الموضوعات :
1 - Department of Mechanical Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria q
الکلمات المفتاحية: Cost, Safety Management, Simulator, Computer programme, Safety Strategies,
ملخص المقالة :
Accidents happen and they upset the normal functioning of any organization causing real damage to persons, equipment, and loss of revenue. To mitigate these problems, safety performance metrics, and system dynamics have been implemented widely to solve the challenges of delays, feedback, and nonlinearity. A mathematical description of the relationships among the identified variables coupled with computer modeling was used to develop the Computer Programme Simulator (CPS) using MATLAB to code the dynamic relationship of the manufacturing safety system to determine accident prevention strategies.The safety dynamic equations were subsequently computed and this was followed by the processes of model application and experimentation. The results of the study showed that parameters such as “the constants”, “initial state variables”, “graphs to plot”, “export graph” and “export table” allows the user plug the desired variables into the CPS and provide data on the number of accidents to be reduced after the selection of the appropriate strategy. The first successful simulation of the CPS also produced a P = 60% and T = 10% reduction in the number of factory accidents. This study concluded that the CPS interactive interface which was developed serves as a useful tool for predicting, preventing, and even reducing factory accidents and makes safety management systems easy. The outputs of all the simulations also revealed that the reduction of accidents and the cost of accidents in all the values of the proportion of available budget and desired accident reduction target computed are practicable.
[1] Iyer P.S., Haight J.M., Castillo E.D., Tink B.W. and Hawkins P.W. (2005). A research model forecasting incident rates from optimized safety programme intervention strategies. Journal of Safety Research, 36, 341 – 351.
[2] Jacobson, S.H., J.M. Bowvan, and J.E. Kebza. 2007. ―Modeling and Analyzing the Performance of Aviation Security Systems Using Baggage Value Performance Measures‖. Transportation Science, 41; (2): 182 -194.
[3] Karanikas N, 2016. Critical review of safety performance metrics. Int. J. Business Performance Management, 17, (3), 43 – 55.
[4] Fernandez-Muniz B., Montes-Peon J.M., and Vazquez-Ordas C.J. (2012). Safety climate in OHSAS 18001-certified organizations: Antecedents and consequences of safety behavior. Accident Analysis and Prevention. 45, 745– 758.
[5] Williams B and Harris B (2005). System Dynamics Methodology. A document prepared as part of a workshop organized by Glenda Eoyang, Bob Williams, Bill Harris for staff of the WK Kellogg Foundation.
[6] Tidwell V.C., Passell H.D., Conrad S.H., and Thomas R.P. (2004). System dynamics modeling for community - based water planning: Application to the Middle Rio Grande. Aquatic Sciences. 66, 357–372.
[7] Adebiyi K. A. and Ajayeoba A.O. (2015) “Integrated Modeling of Manufacturing Safety Interventions Planning and Management” International Conference on Aeronautical and Manufacturing Engineering (ICAAME). March 14-15, 2015 Dubai, UAE. 61 – 65.
[8] Jabbari, M.M., and Tohidi, H. (2012). “Decision role in management to increase effectiveness of an organization”. Procedia-social and behavioral sciences, 32: 825-828. https://doi.org/10.1016/j.sbspro.2011.12.149.
[9] Duzgun, H. S. B and Einsten, H. H. (2004). Assessment and Management of Roof Fall Risks in Underground Coal Mines. Safety Science. 42 (1), 23 –41.
[10] Adebiyi K. A. (2006). The Development of Manufacturing Safety Programme Simulator. Unpublished Ph.D. Thesis. Industrial Engineering Department, Faculty of Engineering, University of Ibadan, Ibadan.
[11] Adebiyi K. A., Ajayeoba A. O. and Akintan A. L. (2018). Economic Implication of Safety – Policy on Manufacturing Safety Programme Performance. International Journal of Engineering Research in Africa. 36, 137 – 146. International Journal of Engineering Research in Africa. 38, 79 – 86.