Comparison between Planned and Actual Data of Block Assembly Process using Process Mining in Shipyards

Dongha Lee, Jae Hun Park, Hyerim Bae

Abstract


This paper proposes a method to compare planned processes with actual processes of bock assembly operations in shipbuilding industry. Process models can be discovered using the process mining techniques both for planned and actual log data. The comparison between planned and actual process is focused in this paper. The analysis procedure consists of five steps : 1) data pre-processing, 2) definition of analysis level, 3) clustering of assembly bocks, 4) discovery of process model per cluster, and 5) comparison between planned and actual processes per cluster. In step 5, it is proposed to compare those processes by the several perspectives such as process model, task, process instance and fitness. For each perspective, we also defined comparison factors. Especially, in the fitness perspective, cross fitness is proposed and analyzed by the quantity of fitness between the discovered process model by own data and the other data(for example, the fitness of planned model to actual data, and the fitness of actual model to planned data). The effectiveness of the proposed methods was verified in a case study using planned data of block assembly planning system (BAPS) and actual data generated from block assembly monitoring system (BAMS) of a top ranked shipbuilding company in Korea.


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References


van der Aalst, W. M. P. and Basten, T., “Inheritance of workflows : An approach to tackling problems related to change,” Theoretical Computer Science, Vol. 270, No. 1, pp. 125-203, 2002.

van der Aalst, W. M. P., “Business alignment : using process mining as a tool for Delta analysis and conformance testing,” Requirements Engineering, Vol. 10, pp. 198-211, 2005.

Cho, K. K., Oh J. S., Ryu K. R. and Choi H. R., “An integrated process planning and scheduling system for block assembly in shipbuilding,” Annals of the CIRP, Vol. 47, No. 1, pp. 419-422, 1998.

Cho, K. K., Sun J. G. and Oh J. S., “An automated welding operation planning system for block assembly in shipbuilding,” International Journal of Production Econo-mics, Vol. 60-61, pp. 203-209, 1999.

Goedertier, S., de Weerdt, J., Martens, D., Vanthienen, J. and Baesens, B., “Process discovery in event logs : An application in the telecom industry,” Applied Soft Computing, Vol. 11, pp. 1697-1710, 2011.

Hur, W. C., Bae, H., Kim S. and Jeong, K. S., “A method for business process analysis by using decision tree,” The Journal of Society for e‐Business Studies, Vol. 13, No. 3, pp. 51-66, 2008.

Vullers, Jansen‐M. H., van der Aalst, W. M. P., and Rosemann, M., “Mining configurable enterprise information systems,” Data and Knowledge Engineering, Vol. 56, No. 3, pp. 195-244, 2006.

Jung, J. Y., “PROCL : A process log clustering system,” The Journal of Society for e‐Business Studies, Vol. 13, No. 2, pp. 181-194, 2008.

Lee, D. and Bae H.., “Analysis framework using process mining for block movement process in shipyards,”ICIC Express Le- tters, Vol. 7, No. 6, pp. 1913-1917, 2013.

Lee, S., Kim B., Huh M., Cho S., Park S. and Lee D., “Mining transportation logs for understanding the after assembly block manufacturing process in the shipbuilding industry, Expert Systems with Applications,” Vol. 40, No. 1, pp. 83-95, 2013.

de Medeiros, A. K. A, Weijters, A. J. M. M. and van der Aalst, W. M. P., “Genetic Process Mining : An Experimental Evaluation, Data Mining and Knowledge Discovery,” Vol. 14, No. 2, pp. 245-304, 2007.

Rozinat, A. and van der Aalst, W. M. P., “Decision Mining in ProM, Proc,” 4th Int. Conf. on Business Process Management, pp. 420-425, 2006.

Song, M., Günther C. W. and van der Aalst, W. M. P., “Trace clustering in process mining,” BPM 2008 Workshops, Lecture Notes in Business Information Processing, Vol. 17, pp. 109-120, 2009.

de Weerdt, J., Schupp, A., Vanderloock, A. and Baesens, B., “Process Mining for the multi‐faceted analysis of business processes–A case study in a financial ser- vices organization,” Computer in Industry, Vol. 64, pp. 57-67, 2013.

Weijters, A. J. M. M., van der Aalst, W. M. P. and de Medeiros A. K. A., “Process Mining with Heuristics Miner Algorithm,” BETA Working Paper Series, WP 166, Eindhoven University of Technology, Eind- hoven, 2006.


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