Stochastic modeling for the quantification of risk and quality incidents in the bulk materials supply chain Saxon Ryan Dr. Gretchen A. Mosher Iowa State.

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Presentation transcript:

Stochastic modeling for the quantification of risk and quality incidents in the bulk materials supply chain Saxon Ryan Dr. Gretchen A. Mosher Iowa State University February 19th 2015

What is risk  A measure of exposure to a hazard and the effect of the hazard on a target  Target- the entity of concern  Hazard- something with the potential to cause a negative effect on the target  Exposure- a measure of how much the target has come into contact with the hazard  Effect- a measure of harm from exposure to the hazard

Start with a problem formulation  Identify the area of the system to be investigated  Grain storage  Identify the targets in grain storage  Corn  Identify the hazards for grain  Temperature  How can grain become exposed to harmful temperatures  Weather variations

Dose response  Level of effect on the target given an amount of exposure  Measuring effect on corn that is exposed to a temperature  Determine the quality and storage time of the corn  Exposure to high temperatures – Lower quality and storage time  Exposure to low temperatures – Higher quality and storage time

Exposure Data  Historical data describes the temperature the stored corn can be exposed to  Corn will be stored from November to April  Use monthly mean temperature  Assume mean storage temperature over the time period will allow an accurate calculation of storage time and quality

Exposure Data YearNovemberDecemberJanuaryFebruaryMarchApril

Stochastic temperature distribution  Likelihood of mean temperature from November to April

Exposure data  Based off of the shelled corn storage time table we can find out how long the grain will last  We are wanting to store our grain for 6 months (180 days)  Assuming the corn is stored at 16% will the corn last for 180 days

Results  At 40 degrees the corn at 16% should last about 760 days  There is no risk of quality reduction in this scenario  If the corn is stored at 20% there will be a risk  At 20% and 40 degrees the corn is expected to last 144 days

Stochastic temperature distribution Risk

Calculating risk  If the probability of exposure is.22  Effect must be determined with the exposure conditions  The effect could be a damage penalty of $.20/Bu assuming we have 5000 bushels  Severity of the effect= 5000*.2 = $1000  Risk =.22 X $1000 = $220

Conclusions  Use the shelled corn storage time table to calculate a distribution of how many days the corn can last  Provides information on how much to dry and how long to store  Find the most cost effective moisture content based on desired storage time

Risk is flexible  This methodology is flexible to allow various inputs over a vast amount of environments  Risk of quality incidents can be calculated based on the likelihood of an event  More informed decisions can be made to increase the likelihood of positive results

Questions?