This thesis focuses on the development of a reliable sieving system for the automated determination of particle size distribution of bulk materials. Current standard analysis sieves are prone to clogging due to particles becoming lodged in the sieve mesh during operation, thereby negatively impacting sieve functionality. This thesis investigates the realization of a self-cleaning sieving system aimed at addressing this issue. Special emphasis is placed on exploring the concept of a rotating oscillating sieve and its potential application in this context. At this point, it should be noted that the basic idea originates from Mr. Dipl.-Ing. Dr.mont. Michael Prenner. The study encompasses both theoretical considerations and practical investigations to demonstrate the feasibility and effectiveness of such a system. This involves conducting simulations to gain insights into the design and operational parameters of the self-cleaning sieving system, with a focus on achieving particle-friendly sieving function and self-cleaning capabilities during operation. By developing a dependable and efficient sieving system for determining particle size distribution in bulk materials, this thesis contributes to enhancing the reliability and accuracy of standard analysis sieve procedures.