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DC Field | Value | Language |
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dc.contributor.author | Ewemoje, T. A. | - |
dc.contributor.author | Ewemooje, O. S. | - |
dc.date.accessioned | 2018-10-09T14:11:12Z | - |
dc.date.available | 2018-10-09T14:11:12Z | - |
dc.date.issued | 2012 | - |
dc.identifier.other | Journal of Nigerian Institute of Industrial Engineers 3. pp. 91-97 | - |
dc.identifier.other | ui_art_ewemoje_hatchery_2012 | - |
dc.identifier.uri | http://ir.library.ui.edu.ng/handle/123456789/1635 | - |
dc.description.abstract | Optimization of hatchery production processes was carried out using the Monte Carlo method. In the economics of engineering, decisions with the objective of the investor identifying an optimum solution. An investor chooses his or her optimal solution from the set of scenarios that offer maximum expected return for varying levels of risk. Outcomes associated with these random numbers are then analysed to determine the likely results and the associated risks. Taking a major day old hatchery as a case study, data were obtained from the daily production spreadsheet for a period of six years (2003-2008). Excel spreadsheet was used in simulating 6,631 iterations for each day old chick production quantity. Hatching 45000 fertile eggs always yields the largest expected profit when compared with the profit margin of hatching 5000, 15000, 25000 or 35000 fertile eggs. Therefore it appears as if hatching 45000 fertile eggs is the optimum production decision. Producing below the optimum production quantity, the mean profit obtained is very much lowered compared to the mean profit of the optimum 45000 production quantity. Also, production risks are higher below the optimum 45000 production quantity. This situation implies underutilization of the hatchery production system. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Optimum production, | en_US |
dc.subject | Profit, | en_US |
dc.subject | Risk analysis, | en_US |
dc.subject | Iterative solution, | en_US |
dc.subject | Monte Carlo | en_US |
dc.title | Hatchery production optimisation using Monte Carlo approach | en_US |
dc.type | Article | en_US |
Appears in Collections: | scholarly works |
Files in This Item:
File | Description | Size | Format | |
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(8)ui_art_ewemoje_hatchery_2012.pdf | 1.09 MB | Adobe PDF | ![]() View/Open |
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