Modelling inoperability propagation mechanism in interdependent systems

This communication considers the issue of deriving a model to describ how the inoperating level of a particular system (a production unit, a transportation system, an energy supply plant, etc.) of interconnected or interdependent systems(neworking and interdependency are interchangeable in this communication) will impact the operating level of other systems for the purpose of analysis, simulation, prediction, risk assessment, etc. The mechanism of such impacting process may be very complex; for instance to impact the operating level of a system the inoperability of another system may need to reach a certain level (threshold), to combine (synergy) with other events or situations; there may exist some preemptivity condition (that is to destabilize a given system some particular conditions must be satisfied). The main purpose of this communication is therefore to establish a model of inoperability propagation in a networked systems when taking into account as much as possible phenomena such as thresholding, synergy, resilience, etc. Necessity of synergy appeals for a synergetic aggregation operator; to this end, we propose to consider using Choquet integral associeted with a weighted cardinal fuzzy meaure (wcfm) as the appropriate aggregation operator. Furthermore this association leads to a straightforward formula to compute the integral

A fuzzy dynamic inoperability input-output model for strategic risk management in global production networks

Strategic decision making in Global Production Networks (GPNs) is quite challenging, especially due to the unavailability of precise quantitative knowledge, variety of relevant risk factors that need to be considered and the interdependencies that can exist between multiple partners across the globe. In this paper, a risk evaluation method for GPNs based on a novel Fuzzy Dynamic Inoperability Input Output Model (Fuzzy DIIM) is proposed. A fuzzy multi-criteria approach is developed to determine interdependencies between nodes in a GPN using experts’ knowledge. An efficient and accurate method based on fuzzy interval calculus in the Fuzzy DIIM is proposed. The risk evaluation method takes into account various risk scenarios relevant to the GPN and likelihoods of their occurrences. A case of beverage production from food industry is used to showcase the application of the proposed risk evaluation method. It is demonstrated how it can be used for GPN strategic decision making. The impact of risk on inoperability of alternative GPN configurations considering different risk scenarios is analysed

Interconnecting GRRASP with additional platforms and tools: A feasibility study

As it has already been documents in several reports, the Geospatial Risk and Resilience Assessment Platform (GRRASP) under development ad the JRC is a World Wide Web oriented architecture bringing together geospatial technologies and computational tools towards the objective of supporting the analysis of critical infrastructures (CIs) A key aspect of this platform is its capability to serve as the vehicle to interlink the analysis modules and tools that over the years have been developed by the scientific community towards a one-stop-shop for critical infrastructure risk and resilience analysis. The present report illustrates how the software architecture of GRRASP has been designed and is being exploited to support the integration of GRRASP with different projects related to the analysis of CIs.JRC.E.2-Technology Innovation in Securit

Climate Vulnerability of the Supply-Chain: Literature and Methodological review

The increasing complexity of the present economic system and the strong interdependencies existing between production activities taking place in different world areas make modern societies vulnerable to crisis. The global supply-chain is a paradigmatic example of economic structures on which the impacts of unexpected events propagate rapidly through the system. Climate change, which affects societies all over the world, is one of the most important factors influencing the efficiency of the present economic networks. During the last decades a large set of studies have been oriented to investigate the direct impacts generated on specific geographical areas or productions. However, a smaller number of analyses have been oriented to quantify the cascading economic effects generated all over the world. The great complexity of the global economic system, coupled with methodological and data gaps makes it difficult to estimate the domino effects of unexpected events. A clear understanding of the possible consequences generated all over the world is, however, a fundamental step to build socio-economic resilience and to plan effective adaptation strategies. Within this context, the main objective of the present report is to provide an overview of the main studies, methodologies and databases used to investigate the climate vulnerability of the global supply chain. This information can be useful to i) support further studies, ii) to build consistent quantification methodologies, and iii) to fill the possible data gap.JRC.H.7-Climate Risk Managemen

Modeling interactions for inoperability management: from fault tree analysis (FTA) to dynamic bayesian network (DBN)

This paper considers the problem of modeling the mechanism of inoperability propagation within a network of complex systems (a production unit, a transportation system, an energy supply system, etc.). We are particularly interested in modeling one of the main attributes of complexity that is interaction; indeed, interactions between systems in a network or components in a system have the effect of propagating and perhaps even amplifying local inoperabilities. Two types of interactions are considered: influence that can be described by an acyclic hierarchical relationships graph of the interacting systems or components and interdependence for which the graphical representation of relationships allows loops. Hierarchy is mainly functional or structural and is analyzed and established in this communication using fault tree analysis (FTA) as the underlying mathematical tools whereas interdependence is apprehended through dynamic Bayesian network (DBN) by considering that effects are delayed. The ultimate DBN model (obtained in two steps: (1) a static Bayesian network (BN) isomorphic to the FTA model and then (2) DBN model by introducing delayed interdependence effects) of a complex system can serve as a decision support system for many risk related scenarios analysis and/or activities such as predictive maintenance

Quantifying economic benefits for rail infrastructure projects

Investment in rail infrastructure is necessary to maintain existing service and to cater for future growth in freight and passenger services. Many communities have realized the importance of investment in rail infrastructure projects and set up goals and visions to achieve economic development through investing in such projects. Due to limited funds available, communities have to select a single or very few projects from a variety of projects. It is very critical that right projects must be selected at the right time for a community to realize economic development. The limited methods for quantifying the economic benefits to the stakeholders often cause a problem in the selection process. Most of the conventional methods focus mainly on the economic impact of the project and ignore the metrics that convey the economic impacts in meaningful ways to the key stakeholders involved. This leads to uncertainty in the project selection and planning process and often leads to failure in achieving the goals of the project. This study aims to provide a mathematical framework that quantifies economic benefits of investment in rail infrastructure projects in meaningful ways to the key stakeholders through three different approaches, namely, Leontief-based approach, Bayesian approach and system dynamics approach. The Leontief-based approach is the easiest of all the three approaches provided that historical data is available. Bayesian approach is also very beneficial as it can be used by coupling small data with surveys and interviews. Also, system dynamics model is very useful to conduct qualitative analysis, but the quantitative analysis part can become very complex --Abstract, page iii

GRRASP version 3.1 User Manual

This report is a comprehensive manual for GRRASP including also a detailed description of the installation procedure. The user manual describes the main functionalities of GRRASP as well as how the end user can apply the models included in GRRASP. This software platform is evolving so this manual is a living document which will be updated on the basis of new functionalities.JRC.E.2-Technology Innovation in Securit