Operational techniques for implementing traceability in bulk product supply chains.

摘要

Implementation of traceability techniques in bulk food product supply chains is a complex task. A systems approach was used to develop a framework for implementation of traceability in bulk grain supply chain in the United States. A relational database model was developed to facilitate internal traceability at a grain elevator, which is one of the first nodes in a food supply chain. This data management technique could mitigate the bulk grain handling problems by recording all grain lot transformations/activities, including movement, aggregation, segregation, and destruction as well as supplier and customer information. The system can be queried to retrieve information related to incoming, internal and outgoing lots and to retrieve information that connects the individual incoming grain lots to an outgoing shipment. Next, a mathematical multi-objective mixed integer programming (MIP) model was proposed with two objective functions; to calculate the minimum levels of lot aggregation and minimum total cost of blending grain in order to meet the customer contract specifications. Constraints on the system include contract specifications, availability of grain at the shipping elevator location as well as other locations and the blending requirements. The solutions include the quantities of grain from different storage bins to be used for blending for a shipment while using the minimum number of storage bins and the total cost. The numerical results are presented for a corn shipment scenario to demonstrate the application of this model to bulk grain blending. Pareto optimal front is computed for the problem for simultaneous optimization of lot aggregation and cost of blending. This model provides an effective method for minimizing the traceability effort by minimizing the food safety risk caused by lot aggregation. Finally, a new methodology for modeling the traceability information using the UML statecharts following an event management approach in bulk food production is introduced. A generic model is presented and evaluated based on its practical application in bulk food production by providing illustrations from two supply chains; pelagic fish and grain. The statecharts are developed for frozen mackerel production and corn wet milling processes. All states and events for these processes as well as the information that needs to be captured for each transition are indentified that includes the product, process and quality information. The data capture points were identified based on the various states and events that occur during food production and are connected to product, process as well as quality information.