Digital technologies are driving industrial engineering towards a new asset management paradigm that in-volves the integration of system design, risk analysis, prognostic predictions and cost assessment. Evidence of such evolution is the appearance of multi-simulation platforms for combined analytics, characterized by an ex-tensive sharing of information content. In this context, new approaches are required to meet the increasing complexity of modern systems. Amongst a range of activities that concern the design and construction of an industrial system, early safety assessment represents a highly interesting area of application. Early safety as-sessment helps determine the risks associated with a safety critical system and can be used to prevent expen-sive design iterations via early mitigation of such risks. For this reason, new solutions, that are able to assist design and risk engineers in early safety assessment, are getting increasingly important. This paper addresses this area by proposing a prototype solution that integrates a CAD software tool for the drawing of Piping and Instrumentation Diagrams (P&ID) with HiP-HOPS, a well-known software tool based on Compositional Safety Analysis and Model Based Safety. This prototype enables the dependability analysis and optimization of process and power plants. In this approach, risk and plant engineers can work in teams to implement a rich extended model of the P&IDs that embeds all the necessary information to automatically retrieve the fault trees associated with the process of the system. The immediate benefit is to achieve efficient dependability as-sessment at an early design stage. A case of study of a cooling water system of a chemical plant is presented and the potential of this work is demonstrated. Further benefits will arise in the future by applying innovative algorithms to the extended plant model that will be able to assist in design decisions, on the basis of the pro-cess plant characteristics.

An application for early safety assessment to bridge the gap between design and automated dependability assessment

Chiacchio F;D'Urso D;COMPAGNO, Lucio;
2016-01-01

Abstract

Digital technologies are driving industrial engineering towards a new asset management paradigm that in-volves the integration of system design, risk analysis, prognostic predictions and cost assessment. Evidence of such evolution is the appearance of multi-simulation platforms for combined analytics, characterized by an ex-tensive sharing of information content. In this context, new approaches are required to meet the increasing complexity of modern systems. Amongst a range of activities that concern the design and construction of an industrial system, early safety assessment represents a highly interesting area of application. Early safety as-sessment helps determine the risks associated with a safety critical system and can be used to prevent expen-sive design iterations via early mitigation of such risks. For this reason, new solutions, that are able to assist design and risk engineers in early safety assessment, are getting increasingly important. This paper addresses this area by proposing a prototype solution that integrates a CAD software tool for the drawing of Piping and Instrumentation Diagrams (P&ID) with HiP-HOPS, a well-known software tool based on Compositional Safety Analysis and Model Based Safety. This prototype enables the dependability analysis and optimization of process and power plants. In this approach, risk and plant engineers can work in teams to implement a rich extended model of the P&IDs that embeds all the necessary information to automatically retrieve the fault trees associated with the process of the system. The immediate benefit is to achieve efficient dependability as-sessment at an early design stage. A case of study of a cooling water system of a chemical plant is presented and the potential of this work is demonstrated. Further benefits will arise in the future by applying innovative algorithms to the extended plant model that will be able to assist in design decisions, on the basis of the pro-cess plant characteristics.
2016
978-1-315-37498-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/75282
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