Developing a ranking methodology for chemical industrial clusters: a multi-criteria decision making approach

Casciano, Martina (2019) Developing a ranking methodology for chemical industrial clusters: a multi-criteria decision making approach. [Laurea magistrale], Università di Bologna, Corso di Studio in Ingegneria chimica e di processo [LM-DM270], Documento full-text non disponibile
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The clustering process in the chemical industries is becoming more important due to economic, social and political issues. Clustering means agglomeration of companies in the same geographical area in order to increase the productivity and reduce costs. The birth of agreements between companies allows to arouse their interest in other disciplines different from the socio-economic aspect, as safety and security, to name but few. The first step of the methodology is represented by the safety and security risk assessment, followed by the analysis of the relationships within firms in terms of strategic and operation alliances. In the present study, safety risk should be interpreted as an average dangerousness and, at the same time, security risk as average vulnerability of installations in the cluster’s area. Risk, for this evaluation, will not be a function of frequency and magnitude and it will represent an inclination to damage, the potential of chemical cluster to incur in accident(s)/incident(s). The strong influence of the results obtained before can be analysed with the analytic network process that, with pairwise comparisons, is able to assess which parameters have a major influence among the others. In this tool, comparisons within more than one chemical cluster can be taken into account. The final outcome of this methodology is a ranking of chemical clusters, a classification depending on a large number of criteria covering many aspects of safety and security, but as well considering the existing management and relationship within companies. A simple case study has been built in order to investigate, inside the model of the ANP, benefits, costs and risks associated with the selected chemical clusters.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Casciano, Martina
Relatore della tesi
Correlatore della tesi
Corso di studio
Ingegneria di processo
Ordinamento Cds
Parole chiave
Data di discussione della Tesi
14 Marzo 2019

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