Analysis framework using process mining for block movement process in shipyards

Abstract

In a shipyard, block movement, unlike main operations such as assembly, outfitting and painting is rarely scheduled due to the difficulty of predicting all such movements. Nonetheless, the high operating costs of block movement compel task managers to attempt its management. To resolve this dilemma this paper proposes a new blockmovement analysis framework consisting of the following operations: understanding the entire process, log clustering to obtain manageable processes, discovering the process model and detecting exceptional processes. The proposed framework applies fuzzy mining and trace clustering among the process mining technologies in ProM, and adds additional methodologies including adjustment of the semantic expression level for process instances to obtain an interpretable process model, definition of each cluster's process model, detection of exceptional processes, and others. The effectiveness of the proposed framework was verified in a case study using real-world event logs of the Block Movement Control System (BMCS). © 2013 ISSN 1881-803X.