{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T10:14:00Z","timestamp":1773310440734,"version":"3.50.1"},"reference-count":38,"publisher":"Emerald","issue":"9","license":[{"start":{"date-parts":[[2014,10,7]],"date-time":"2014-10-07T00:00:00Z","timestamp":1412640000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,10,7]]},"abstract":"\n Purpose<\/jats:title>\n \u2013 The purpose of this paper is to develop a risk assessment method for production processes of large-size steel ship hulls. <\/jats:p>\n <\/jats:sec>\n \n Design\/methodology\/approach<\/jats:title>\n \u2013 This study uses a quantitative-probabilistic approach with involvement of clustering technique in order to analyse the database of accidents and predict the process risk. The case-based reasoning is used in here. A set of technological hazard classes as a basis for analysing the similarities between the production processes is proposed. The method has been explained using a case study on large-size shipyard. <\/jats:p>\n <\/jats:sec>\n \n Findings<\/jats:title>\n \u2013 Statistical and clustering approach ensures effective risk managing in shipbuilding process designing. Results show that by selection of adequate number of clusters in the database, the quality of predictions can be controlled. <\/jats:p>\n <\/jats:sec>\n \n Research limitations\/implications<\/jats:title>\n \u2013 The suggested k<\/jats:italic>-means method using the Euclidean distance measure is initial approach. Testing the other distance measures and consideration of fuzzy clustering method is desirable in the future. The analysis in the case study is simplified. The use of the method according to prediction of risk related to loss of health or life among people exposed to the hazards is presented. <\/jats:p>\n <\/jats:sec>\n \n Practical implications<\/jats:title>\n \u2013 The risk index allows to compare the processes in terms of security, as well as provide significant information at the technology design stage of production task. <\/jats:p>\n <\/jats:sec>\n \n Originality\/value<\/jats:title>\n \u2013 There are no studies on quantitative methods developed specifically for managing risks in shipbuilding processes. Proposed list of technological hazard classes allows to utilize database of past processes accidents in risk prediction. The clustering method of analysing the database is agile thanks to the number of clusters parameter. The case study basing on actual data from the real shipyard constitutes additional value of the paper.<\/jats:p>\n <\/jats:sec>","DOI":"10.1108\/imds-06-2014-0193","type":"journal-article","created":{"date-parts":[[2014,10,20]],"date-time":"2014-10-20T06:40:28Z","timestamp":1413787228000},"page":"1499-1518","source":"Crossref","is-referenced-by-count":24,"title":["Clustering risk assessment method for shipbuilding industry"],"prefix":"10.1108","volume":"114","author":[{"given":"Remigiusz","family":"Romuald Iwa\u0144kowicz","sequence":"first","affiliation":[]},{"given":"Wlodzimierz","family":"Rosochacki","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020122800410245900_b1","doi-asserted-by":"crossref","unstructured":"Basuki, M.\n , \n Manfaat, D.\n , \n Nugroho, S.\n and \n Dinariyana, A.\n (2014), \u201cProbabilistic risk assessment on the shipyard industry using the Bayesian method\u201d, International Journal of Technology, Vol. 5 No. 1, pp. 88-97.","DOI":"10.14716\/ijtech.v5i1.157"},{"key":"key2020122800410245900_b2","unstructured":"BS 8800\n (2004), Guide to Occupational Health and Safety Management Systems, British Standards Institution, London."},{"key":"key2020122800410245900_b3","doi-asserted-by":"crossref","unstructured":"Cho, K.K.\n , \n Oh, J.S.\n , \n Ryu, K.R.\n and \n Choi, H.R.\n (1998), \u201cAn integrated process planning and scheduling system for block assembly in shipbuilding\u201d, Annals of CIRP, Vol. 47 No. 1, pp. 419-422.","DOI":"10.1016\/S0007-8506(07)62865-0"},{"key":"key2020122800410245900_b4","doi-asserted-by":"crossref","unstructured":"Choudhary, A.K.\n , \n Harding, J.A.\n and \n Tiwari, M.K.\n (2009), \u201cData mining in manufacturing: a review based on the kind of knowledge\u201d, Journal of Intelligent Manufacturing, Vol. 20 No. 5, pp. 501-521.","DOI":"10.1007\/s10845-008-0145-x"},{"key":"key2020122800410245900_b5","doi-asserted-by":"crossref","unstructured":"Copas, J.\n (1999), \u201cStatistical modelling for risk assessment\u201d, Risk Management, Vol. 1 No. 1, pp. 35-49.","DOI":"10.1057\/palgrave.rm.8240013"},{"key":"key2020122800410245900_b6","doi-asserted-by":"crossref","unstructured":"Cuny, X.\n and \n Lejeune, M.\n (2003), \u201cStatistical modeling and risk assessment\u201d, Safety Science, Vol. 41 No. 1, pp. 29-51.","DOI":"10.1016\/S0925-7535(01)00056-X"},{"key":"key2020122800410245900_b7","doi-asserted-by":"crossref","unstructured":"Dey, P.K.\n (2010), \u201cManaging project risk using combined analytic hierarchy process and risk map\u201d, Applied Soft Computing, Vol. 10 No. 4, pp. 990-1000.","DOI":"10.1016\/j.asoc.2010.03.010"},{"key":"key2020122800410245900_b8","doi-asserted-by":"crossref","unstructured":"Dey, P.K.\n (2012), \u201cProject risk management using multiple criteria decision-making technique and decision tree analysis: a case study of Indian oil refinery\u201d, Production Planning & Control, Vol. 23 No. 12, pp. 1-19.","DOI":"10.1080\/09537287.2011.586379"},{"key":"key2020122800410245900_b9","doi-asserted-by":"crossref","unstructured":"Dey, P.K.\n , \n Charoenngam, C.\n , \n Oguniana, S.O.\n and \n Kajornkiat, D.\n (2009), \u201cMulti-party risk management helps manage cement plant construction in Thailand\u201d, International Journal of Services Technology and Management, Vol. 11 No. 4, pp. 411-434.","DOI":"10.1504\/IJSTM.2009.024577"},{"key":"key2020122800410245900_b10","doi-asserted-by":"crossref","unstructured":"Dey, P.K.\n , \n Kinch, J.\n and \n Ogunlana, S.O.\n (2007), \u201cManaging risk in software development projects: a case study\u201d, Industrial Management & Data Systems, Vol. 107 No. 2, pp. 284-303.","DOI":"10.1108\/02635570710723859"},{"key":"key2020122800410245900_b11","doi-asserted-by":"crossref","unstructured":"Dey, P.K.\n , \n Ogunlana, S.O.\n and \n Naksuksakul, S.\n (2004), \u201cRisk-based maintenance model for offshore oil and gas pipelines: a case study\u201d, Journal of Quality in Maintainance Engineering, Vol. 10 No. 3, pp. 169-183.","DOI":"10.1108\/13552510410553226"},{"key":"key2020122800410245900_b12","unstructured":"Galwey, L.\n (2004), \u201cQuantitative risk analysis for project management. 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