Approximate estimation of man-day in ship block production: a two-stage stochastic program

• Autorzy: Genc, Yusuf , Kafali, Mustafa , Celebi, Ugur Bugra
• Języki publikacji: EN

Abstrakty

EN

It is critical to estimate the workforce requirements for the production of blocks in shipbuilding. In this study, the number of workforce (man-day) required for the production of a passenger ship’s double bottom block was estimated. Initially, the production of the block was observed, and the average working performance of the mounting, welding, and grinding workers was recorded. Block drawings were examined and the work required was calculated. The amount of work increased, depending on any revisions required due to incorrect or incomplete designs. The average working performance of an employee is uncertain due to environmental factors, including the weather and working conditions, as well as health (both physical and mental). A two-stage stochastic programming model with recourse was established to estimate man-day required and a Sample Average Approximation (SAA) technique was used to obtain a near-optimum solution. The results of the study were compared with shipyard records and an agreement of approximately 90% was achieved.

Słowa kluczowe

EN

shipbuilding; block production; planning; stochastic modeling

• Czasopismo: Polish Maritime Research
• Rocznik: 2024
• Tom: nr 1
• Strony: 146--158
• Opis fizyczny: Bibliogr. 42 poz., rys., tab.

Twórcy

autor

Genc, Yusuf

• Maritime Vocational School, Galatasaray University, Besiktas/İstanbul, Turkiye

autor

Kafali, Mustafa

• Naval Architecture and Maritime Faculty, Izmir Katip Celebi University, Cigli/Izmir, Turkiye,

autor

Celebi, Ugur Bugra

• Naval Architecture and Marine Engineering Department of Yildiz Technical University, Besiktas/İstanbul, Turkiye

Bibliografia

• 1. Y. Guo, H. Wang, X. Liang, and H. Yi, “A quantitative evaluation method for the effect of construction proces on shipbuilding quality,” Ocean Engineering, vol. 169, pp. 484-491, 2018, doi.org/101016/j.oceaneng.2018.09.046.
• 2. H. Wang, Y. Guo, X. Liang, and H. Yi, “A functionoriented quality control method for shipbuilding,” Ships and Offshore Structures, vol. 14, no. 2, pp. 220-228, 2019, doi.org/10.1080/17445302.2018.1493910.
• 3. H. Kim, J. Kang, and S. Park, “Scheduling of shipyard block assembly process using constraint satisfaction problem,”Asia Pacific Management Review, vol. 7, no. 1, pp. 119-138, 2002.
• 4. J. Li, M. Sun, D. Han, J. Wang, X. Mao, and X. Wu, “A knowledge discovery and reuse method for time estimation in ship block manufacturing planning using DEA,” Advanced Engineering Informatics, vol. 39, pp. 25-40, 2019, doi.org/10.1016/j.aei.2018.11.005.
• 5. J. Park, D. Lee, and J. Zhu, “An integrated approach for ship block manufacturing process performance evaluation: case from Korea shipbuilding company,” International Journal of Production Economics, vol. 156, pp. 214-222, 2014, doi.org/10.1016/j.ijpe.2014.06.012.
• 6. M. Kang, J. Seo, and H. Chung, “Ship block assembly sequence planning considering productivity and welding deformation,” International Journal of Naval Architecture and Ocean Engineering, vol. 10, pp. 450-457, 2018, doi.org/10.1016/j.ijnaoe.2017.09.005.
• 7. H. Kim, S. S. Lee, J. H. Park, and J. G. Lee, “A model for simulation-based shipbuilding system in a shipyard manufacturing process,” International Journal of Computer Integrated Manufacturing, vol. 18, no. 6, pp. 427-441, 2005, doi:10.1080/09511920500064789.
• 8. J. M. Lee, Y. K. Jeong, and J. H. Woo, “Development of an evaluation framework of production planning for the shipbuilding industry,” International Journal of Computer Integrated Manufacturing, vol. 31, no. 99, pp. 831-847, 2018, doi.org/10.1080/0951192X.2018.1449968.
• 9. A. Turk, S. Gurgen, M. Ozkok, and İ. Altın, “A comprehensive investigation into the performance of genetic algorithm for effective shipyard topological layout,” Proceedings of the Institution of Mechanical Engineers Part M-Journal of Engineering for the Maritime Environment, vol. 236, no. 3, pp. 726-740, 2022, doi.org/10.1177/147509022110620.
• 10. B. Lujibenkov, B. Blagojević, J. Bašić, and M. Bašić, “Procedure for reconstruction of gajeta hull form using photogrammetric measurement method,” Brodogradnja, vol. 73, no. 2, pp. 139-151, 2022, doi.org/10.21278/brod73208.
• 11. Y. J. Song, J. H. Woo, and J. G. Shin, “Research on systematization and advancement of shipbuilding production management for flexible and agile response for high value offshore platform,” International Journal of Naval Architecture and Ocean Engineering, vol. 3, no. 3, pp. 181-192, 2011, doi.org/10.2478/IJNAOE-2013-0061.
• 12. I. H. Hwang, Y. Kim, D. K. Lee, and J. G. Shin, “Automation of block assignment planning using a diagram-based scenario modelling method,” International Journal of Naval Architecture and Ocean Engineering, vol. 6, no. 1, pp. 162-174, 2014, doi.org/10.2478/IJNAOE-2013-0170.
• 13. M. Kafalı and M. Ozkok, “Evaluation of shipyard selection criteria for ship owners using a fuzzy technique,” Journal of Marine Engineering & Technology, vol. 14, no. 3, pp. 146-158, 2015, doi.org/10.1080/20464177.2015.1118787.
• 14. U. Bilen and Ş. Helvacioglu, “Data driven performance evaluation in shipbuilding,” Brodogradnja, vol. 71, no. 4, pp. 39-51, 2020, doi.org/10.21278/brod71403.
• 15. L. Lei, L. Di, W. Pengyu, and Z. Honggen, “Research on hull assembly planning based on rule reasoning” Materials Science and Engineering, vol. 751, pp. 1-7, 2020, doi:10.1088/1757-899X/751/1/012084.
• 16. M. de C. Porath, R. Simoni, R. de A. Nunes, and A. Bertoldi, “Feasibility of measurement-assisted assembly of ship hull blocks,” Marine System & Ocean Technology, vol. 14, pp. 23-33, 2019, doi.org/10.1007/s40868-018-00053-w.
• 17. M. Kafalı, N. Aydın, Y. Genc, and U. B. Celebi, “A twostage stochastic model for workforce capacity requirement in shipbuilding,” Journal of Marine Engineering &Technology, vol. 21, no. 3, pp. 146-158, 2022, doi.org/10.1 080/20464177.2019.1704977.
• 18. T. Urbanski, T. Graczyk, M. Taraska, and R. R. Iwankowicz, “Assessment of technological usefulness of panel production line in shipbuilding process,” Polish Maritime Research, vol. 25, pp. 134-144, 2018, doi:10.2478/pomr-2018-0034.
• 19. Y. K. Jeong, S. Ju, H. Shen, D. K. Lee, J. G. Shin, and C. Ryu, “An analysis of shipyard spatial arrangement planning problems and a spatial arrangement algorithm considering free space and unplaced block,” The International Journal of Advanced Manufacturing Technology, vol. 95, pp. 4307-4325, 2018, doi:10.1007/s00170-017-1525-1.
• 20. M. Afzalirad and J. Rezaeian, “Resource-constrained unrelated parallel machine scheduling problem with sequence dependent setup times, precedence constraints and machine eligibility restrictions,” Computers & Industrial Engineering, vol. 98, pp. 40-52, 2016, doi. org/10.1016/j.cie.2016.05.020.
• 21. C. Wang, P. Mao, Y. Mao, and J. G. Shin, “Research on scheduling an optimisation under uncertain conditions in panel block production line in shipbuilding,” International Journal of Naval Architecture and Ocean Engineering, vol. 8, pp. 398-408, 2016, doi.org/10.1016/j.ijnaoe.2016.03.009.
• 22. Z. Yuguang, A. Bo, and Z. Yong, “A PSO algorithm for multi-objective hull assembly line balancing using the stratified optimisation strategy,” Computers & Industrial Engineering, vol. 98, pp. 53-62, 2016, doi.org/10.1016/j.cie.2016.05.026.
• 23. R. R. Iwankowicz, “A multi-case-base assembly management method for the shipbuilding industry,” Polish Maritime Research, vol. 28, no. 2, pp. 27-35, 2021, doi:10.2478/pomr-2021-0018.
• 24. B. Kwon and G. M. Lee, “Spatial scheduling for large assembly blocks in shipbuilding,” Computers & Industrial Engineering, vol. 89, pp. 203-212, 2015, doi.org/10.1016/j.cie.2015.04.036.
• 25. M. Hadjina, N. Fafandjel and T. Matulja, “Shipbuilding production process design methodology using computer simulation,” Brodogradnja, vol. 6, no. 2, pp. 77-91, 2015.
• 26. A. Oliveire and J. M. Gordo, “Lean tools applied to a shipbuilding panel line assembling process,” Brodogradnja, vol. 69, no. 4, pp. 53-64, 2018, doi.org/10.21278/brod6944.
• 27. M. Hur, S. K. Lee, B. Kim, S. Cho, D. Lee, and D. Lee, “A study on the man-hour prediction system for shipbuilding,” Journal of Intelligent Manufacturing, vol. 26, no. 6, pp. 1267-1279, 2015, doi:10.1007/s10845-013-0858-3.
• 28. S. Hu, T. Liu, S. Wang, Y. Kao, and X. Sun, “Ahybrid heuristic algorithm for shipbuilding construction space scheduling problem,” Discrete Dynamics in Nature and Society, vol. 2015, no.7, pp. 1-6, 2015, doi:10.1155/2015/841637.
• 29. J. Zheng, Z. Jiang, and Q. Chen, “Block spatial scheduling modelling and application in shipbuilding,” International Journal of Production Research, vol. 50, no. 10, pp. 2744-2756, 2012, doi.org/10.1080/00207543.2011.588629.
• 30. Z. Liu, D. K. H. Chua, and K. H. Wee, “A simulation model for spatial scheduling for dynamic block assembly in shipbuilding,” Journal of Engineering, Project, and Production Management, vol. 1, no. 1, pp. 3-12, 2011, doi:10.32738/JEPPM.201107.0002.
• 31. S. I. Wahidi, S. Oterkus, and E. Oterkus, “Simulation of a ship’s block panel assembly process: optimising production processes and cost through welding robots,” Journal of Marine Science and Engineering, vol. 11, no. 8, pp. 1506-1522, 2023, doi.org/10.3390/jmse11081506.
• 32. B. Liu and Z. H. Jiang, “The man-hour Estimation models & its comparison of interim products assembly for shipbuilding,” International Journal of Operations Research, vol. 2, no. 1, pp. 9-14, 2005.
• 33. Y. Imai, Y. Ohta, and H. Suzuki, “A man-hour Estimation tool focused on graphical user interface,” Lecture Notes of Software Engineering, vol. 4, no. 3, pp. 175-178, 2016, doi: 10.18178/lnse.2016.4.3.245.
• 34. S. A. Seyfi, İ. Yanıkoğlu, and G. Yılmaz, “Multi-stage scenario-based stochastic programming for managing lot sizing and workforce scheduling at Vestel,” Annals of Operations Research, Published online, 2023, doi. org/10.1007/s10479-023-05741-4.
• 35. D. J. Eyres and G. J. Bruce, Ship Construction, Seventh Edition, Butterworth-Heinemann: Oxford, UK, 2012.
• 36. M. Kafalı, Y. Ünsan, and M. Özkök, “A production planning and control methodology for shipyards,” (In Turkish) Journal of ETA Maritime Science, vol. 6, no. 1, pp. 47-59, 2018, doi.org/10.5505/jems.2018.02986.
• 37. F. Dong, H. Parvin, M. P. V. Oyen, and D. J. Singer, “Innovative ship block assembly production control using a flexible curved block job shop,” Journal of Ship Production, vol. 25, no. 4, pp. 206-213, 2009, doi:10.5957/jsp.2009.25.4.206.
• 38.M. Branda, “Sample approximation technique for mixedinteger stochastic programming problems with several change constraints,” Operation Research Letters, vol. 40, pp. 207-211, 2012, doi.org/10.1016/j.orl.2012.01.002.
• 39. S. W. Wallace and W. T. Ziemba, (Eds.), Applications of stochastic programming, 1st ed., MPS SIAM- Series in Optimisation Number 5, 2005.
• 40. J. R. Birge and F. Louveaux, “Introduction to Stochastic Programming”, 2nd Edition, Springer, New York, 2011.
• 41. S. Ahmed and A. Shapiro, 2002. “The sample average approximation method for stochastic programs with integer recourse”, [Optimisation Online], 2002, http://www.optimisation-online.org.
• 42. B. Ayvaz, B. Bolat, and N. Aydin, “Stochastic reverse logistics network design for waste of electrical and electronic equipment,” Resources, Conservation and Recycling, vol. 104, pp. 391–404, 2015, doi.org/10.1016/j.resconrec.2015.07.006.

Identyfikatory

DOI

10.2478/pomr-2024-0015