This work aims to develop a data handling strategy to enhance understanding of a particulate system and clarify the relationship between filter cake properties and the characteristics of the particles forming it. While it is commonly believed that a connection exists between cake properties and particle characteristics, the complexity of this relationship has led to the notion that measuring cake properties is the only way to understand them. This presents challenges for process engineers who need to predict outcomes from process changes. The findings provide a framework for engineers to transform results into practical experience. Establishing this connection allows for the theoretical prediction of filter performance using kinetic models previously studied. Key attributes identified for determining cake-building kinetics and gas-pressure-driven deliquoring kinetics include porosity, permeability, and capillary pressure, which were thoroughly examined concerning variations in particle size distribution. The study demonstrates that cake properties can be correlated with collective particle characteristics, influenced by cake-building mode and specific to the substance. A suggested data handling strategy facilitates the collection and analysis of information, leading to reliable estimations of particle assembly behavior under specific conditions. While no definitive solution is proposed, the emphasis is on understanding the mat
