International Journal of Science and Technology

International Journal of Science and Technology>> Volume 7, Number 9, September 2017

International Journal of Science and Technology


Determination of Effective Manufacturing Safety Strategy using Artificial Neural Network

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Author Adebiyi K. A., Ajayeoba A. O
On Pages 447-454
Volume No. 2
Issue No. 7
Issue Date July, 2012
Publishing Date July, 2012
Keywords safety intervention, combinations, strategy, resources, accidents


Abstract

Accidents always have a negative impact on the society, apart from causing a mishap, its occurrence in manufacturing brings great anguish to the victims while the organization suffers loss in productivity and profit. Though there are useful relevant manufacturing safety resources, the allocation may be expensive if proper tool is not used in the implementation. Therefore, suitable safety strategy is required for good safety management planning. This research work employs the artificial neural network (ANN) to allocate effectively, some given set of safety intervention programme (SIP) resources Six SIP activities were identified and are coded as: SIP-A, SIP-B, SIP-C, SIP-D, SIP-E and SIP-F for personal protective equipment (PPE), motivation of workers, accident investigation, guarding, awareness creation and training, respectively. Accident data and expenditure on safety interventions were collected from a tobacco company in Nigeria for a range of 16years. The data were then analysed using combinatorial analysis and ANN, where record of annual expenditure on the safety interventions and number of accidents occurrence were the input and output, respectively. Combination analysis yielded 62 (sixty-two) new combinations. It was observed that the combinations ADEF, ACDEF and ABDEF gave a fairly low mean square error, an evidence of applicability in time of scarce resources. However, training (SIP-F) was identified as being significantly present in the first 32 combinations. Thus, ANN serves as better tool for planning and managing manufacturing safety programme.

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