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Object-Centric Conformance Checking with Synchronization of Interrelated Objects


Core Concepts
This paper presents a new formalism called object-centric Petri nets with identifiers (OPIDs) that combines the ability to capture one-to-many relations between objects with the ability to compare and synchronize objects based on their identity. The authors define alignments and the conformance checking task for this setting, and propose a conformance checking approach based on an encoding in satisfiability modulo theories (SMT).
Abstract
The paper addresses the need for object-centric process mining techniques that can accurately reflect the nature of real-world processes involving interdependent objects. It introduces a new formalism called object-centric Petri nets with identifiers (OPIDs) that combines the key modeling features of two existing approaches: The ability of object-centric Petri nets to capture one-to-many relations between objects. The ability of Petri nets with identifiers to compare and synchronize objects based on their identity. The authors define alignments and the conformance checking task for OPIDs, and propose a conformance checking approach based on an encoding in satisfiability modulo theories (SMT). This allows them to effectively overcome the shortcomings of earlier work, which was unable to track object identity and object dependencies. The paper first provides background on object-centric event logs and reviews related work on object-centric process modeling. It then formally defines OPIDs and the notion of alignments for this setting. The core of the paper is the encoding of the conformance checking problem as an SMT problem, which is shown to be correct and feasible through an implementation and experimental evaluation.
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Deeper Inquiries

What are some potential applications of the proposed object-centric conformance checking approach beyond the order-to-delivery process example

The proposed object-centric conformance checking approach using OPIDs has a wide range of potential applications beyond the order-to-delivery process example. One application could be in healthcare systems, where patient care involves multiple interconnected objects such as patient records, medications, and treatment plans. By applying object-centric conformance checking, healthcare providers can ensure that the treatment processes align with the expected protocols and guidelines, leading to improved patient outcomes and operational efficiency. Another application could be in supply chain management, where tracking the flow of goods, inventory, and orders is crucial for optimizing logistics and reducing costs. Object-centric conformance checking can help identify discrepancies in the supply chain processes, such as delays in order processing, inventory mismanagement, or incorrect shipments, leading to more streamlined operations and improved customer satisfaction. Furthermore, in manufacturing processes, where multiple objects such as raw materials, components, and finished products are involved, object-centric conformance checking can ensure that production processes adhere to quality standards, regulatory requirements, and production schedules. By detecting deviations or inefficiencies in the manufacturing processes, organizations can enhance product quality, reduce waste, and increase overall productivity.

How could the OPID formalism be extended to support exact synchronization, in addition to the subset synchronization currently supported

To extend the OPID formalism to support exact synchronization in addition to the subset synchronization currently supported, one approach could be to introduce a new type of arc inscription that explicitly captures the exact synchronization constraints between objects. This new type of arc inscription could specify that a transition can only occur if all objects related to a particular object have reached a specific state simultaneously. By incorporating this additional level of synchronization into the OPID formalism, the model would be able to accurately represent processes where exact synchronization is required, such as in critical decision-making points or regulatory compliance steps. Another approach could involve enhancing the object variable assignments in transitions to include specific rules or conditions for exact synchronization. By introducing constraints that enforce the simultaneous progression of related objects in a transition, the OPID formalism can be extended to support exact synchronization requirements. This enhancement would provide a more comprehensive modeling capability for object-centric processes that necessitate precise coordination among multiple objects.

Are there any limitations or challenges in applying the SMT-based conformance checking approach to very large or complex object-centric process models

While the SMT-based conformance checking approach offers significant advantages in terms of accuracy and automation, there are some limitations and challenges when applying it to very large or complex object-centric process models. One limitation is the computational complexity associated with solving SMT problems for large-scale models with a high number of variables, constraints, and transitions. As the size and complexity of the model increase, the time and resources required to compute optimal alignments may also escalate, potentially leading to longer processing times and resource constraints. Another challenge is the scalability of the SMT solver to handle intricate dependencies and synchronization constraints in complex object-centric process models. As the model grows in complexity, the solver may face difficulties in efficiently exploring all possible alignments and determining the optimal solution within a reasonable timeframe. Additionally, ensuring the correctness and completeness of the encoding for large models can be challenging, as errors or inaccuracies in the encoding may lead to incorrect conformance checking results. To address these limitations, researchers and practitioners can explore optimization techniques, parallel computing strategies, and model simplification methods to enhance the scalability and efficiency of SMT-based conformance checking for very large or complex object-centric process models. By leveraging advanced computational approaches and algorithmic optimizations, it is possible to overcome these challenges and effectively apply SMT-based conformance checking to a broader range of real-world scenarios.
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