Companies can lose a substantial portion of their revenues due to deterioration in value of their products as a result of processing impediments, which might occur in the entire supply chain. Sometimes, the reasons for a decline in product quality are not fully understood, and thus there are no appropriate measures taken to prevent it. Yet, it is vital to comprehend what is actually happening during production and material handling so that proper, well-informed decisions can be made. This project deals with one of the unexplored problems -- quality loss due to product cross-contamination, which is a common occurrence in material handling, multi-product plants. It is a process of mixing product going through multi-purpose equipment and piping with leftover residue that is currently there, which takes place when there is no intermediate cleaning in between two consecutive products, though the precise character of it is usually not known. Omitting cleaning runs to save production time and money is a common practice in the industry. This research introduces a novel simulation method to quantify and predict the extent of cross-\-con\-ta\-mi\-na\-tion as well as to assess its effects. Many models for material handling in multi-product plant have been made in the past but very few relate to the issue of cross-contamination, which is of extreme importance in quality assurance and informed decision-making. As no similar models have been developed previously, or other research done based on a real industrial setting, it is a truly innovative study, intended to establish foundation for further research, and to raise awareness of the issue by starting to fill a gap of knowledge about what can happen during material processing. Initially, a thorough literature research is done, dealing with issues of trade-offs in manufacturing, cross-contamination in production, as well as how to combine scheduling methodologies with a powder mixing model in a discrete event simulation (DES). Then modelling boundaries and assumptions are established together with a conceptual model. Based on that, a general DES building blocks -- class models for a bagging machine, conveyor, mixer, silo as well as product batches and orders are created. Specific analysis is performed in Sloten, a young animal feed plant in Deventer, the Netherlands, in order to find a more precise character of cross-contamination over time, as well as to test the model application in a realistic setting. Contamination measurements using tracer--collector method over material flow with multiple intermediate sampling points help, together with relevant theoretical models, build mathematical representation of chaotic changes occurring within material flow. Obtained curves fitted with a sum of two exponentially decreasing curves correspond well to the measurements but do not explain everything that happens during the process. Nevertheless they are used to model the cross-contamination phenomenon. Two unique cross-contamination models suitable for implementation in DES are developed, basing on principles of segmentation, quantity conservation, product similarity and proportionality, and are fundamentally models of mixing between material flow and residue in the crossed container. More general one, called partial mass exchange model, allows to customize fraction of material mixed, characteristic to a given piece of equipment, while the other, mixing model, assumes homogeneous resulting composition. Finally, a case-specific simulation model, joining material handling system with cross-contamination calculations as well as customizable layout configuration and settable scheduling methodologies, is established. Experimental setup with four-stage production process consisting of ingredient feeder, a single mixer, limited intermediate storage buffers and multiple system exits, mostly bagging machines, connected by conveying equipment, is discussed. All of the machines involved are multi-purpose, flexible but with some limitations, together with the interconnections and logic among them, basing on a genuine example. Analysis shows considerable impact of system layout and scheduling rules on product contamination. In order to limit cross-contamination appropriate product sequencing, minimising the differences between consecutive products in all stages of the process in needed, while that might impede throughput because of resulting constraints. There is thus a trade-off relation among various aspects of production efficiency, as well as amidst that efficiency and flexibility, when number of storage buffers and their capacity is changed. In the end, research first benefits from measuring the extent of cross-contamination, then succeeding in giving an original example of how to build a cross-contamination model, and how to combine it with a stochastic DES, capable of suiting different designs and scheduling methodologies. Performed experiments show, that cross-contamination effects can be reasonably well simulated with a DES model. It also describes possible effects of certain interventions on various performance indicators, and demonstrates possible risks of increasing flexibility in the system. Additional, more thorough trials are needed in the future to improve the model and generalise it further. Yet, the very important first step to understand the issue has been taken, which will aid in application to other types of systems as well as help in mitigating product contamination.