Food product contamination leading to a food borne illness is real and has potentially devastating impact on supply chain operations and cost. However, it is not well understood from the quantitative perspective. This research seeks to fill this gap by providing a generic model of a multi-stage food supply chain consisting of a supplier/grower, processing center and retailer(s) and analyzing the impact of food product contamination in this model. The supplier corresponds to the farm/grower of the raw material such as fruits and vegetables, the processing center processes the raw material into a final food product and the retailer corresponds to the supermarkets and grocery stores selling the food product to a customer. A situation where a contamination occurs at the supplier or processing center potentially resulting in a food borne illness to the customer is considered. The contamination is discovered through periodic sampling tests conducted by the grower, processing center or through the outbreak of a food borne illness. The supply chain is modeled utilizing a G/G/1 queuing system at the processing center and an order- up to policy at the retailer(s).
This research develops and compares multi-stage supply chain models with varying number of retailers. The negative dependence of contamination on the origin and mode of detection of the contamination is quantified. The differences in individual food product attributes which can impact the cost of contamination are analyzed. The impact of supply chain structure and properties and detection policies on the severity of potential contamination cases is studied. The most cost effective sampling strategies which companies can adopt in the event of product contamination are derived. The payoff from the implementation of a quality control process which can eradicate contamination is evaluated. A numerical study of the impact of a real-world contamination event on a tomato and lettuce supply chain is also conducted.
Finally, a traceability system capable of tracking and tracing back products in the event of a food product recall is incorporated in the supply chain model. The value of traceability for different supply chain scenarios is assessed through the implementation of an ARENA based simulation model.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2012-05-10724 |
| Date | 2012 May 1900 |
| Creators | Chebolu-Subramanian, Vijaya |
| Contributors | Gaukler, Gary M. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | thesis, text |
| Format | application/pdf |
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