Integrating Process Mining with Probabilistic Model Checking via Continuous Time Markov Chains

Process mining represents a methodological approach that facilitates the in-depth analysis of business operations with the aim of revealing significant insights pertaining to their efficacy, efficiency, and regulatory compliance. In a seamless business setting, it's essential to evaluate, refine, and confirm these process models. Traditional methods for checking these models excel in validating their accuracy but cannot handle the inherent probabilistic and real-time behavior of these models. To address this, our research paper presents a new methodology that enhances probabilistic model checking (PMC) for process models. This is made possible by leveraging continuous time Markov chains (CTMCs) as the basic model. This amalgamation creates an inclusive analytical structure that improves the reliability and accuracy of process mining results, thereby enabling corporations to derive deeper insights from their processes and make decisions based on data.