![Fig. 2. An integrated model for business continuity assessment [219].](/figures/fig-2-an-integrated-model-for-business-continuity-assessment-21c06mll.webp)
![Fig. 1. A conceptual model for the business continuity process [219].](/figures/fig-1-a-conceptual-model-for-the-business-continuity-process-2dappknu.webp)
Q2. What is the purpose of the integration of computational resources into physical processes?
To the benefit of safe operation, the integration of computational resources into physical processes is aimed at adding new capabilities to stand-alone physical systems, to enable functionalities of real-time monitoring, dynamic control and decision support during normal operation as well as in case of accidents.
Q3. What is the common framework used to describe the uncertainties in the assessment?
The common framework used to describe the uncertainties in the assessment stands on probability theory, and particularly on the subjectivistic (Bayesian) theory of probability, as the adequate framework within which expert opinions can be combined with statistical data to provide quantitative measures of risk [91,92].
Q4. What are the challenges of the current methods of describing and modeling quantitatively risk?
The changes and innovations that the World is experiencing, with digitalization and the complexity of cyber-phyiscal systems (CPSs), climate change and extreme natural events, terrorist and malevolent threats, challenge the existing methods to describe and model quantitatively risk.
Q5. What is the way to ensure the resilience of CPS to failures?
Resilience of CPS to failures can be granted by self-adaptiveness of control decisions on actuators, resorting to intelligent control systems that properly manipulate sensors measurements [116].
Q6. What are the main causes of failures of embedded hardware components?
During operation, failures of embedded hardware components (e.g., sensors and actuators) can be induced by aging, degradation, and process and operational conditions, which modify the way components work and interact with each other, generating multiple failure modes [195].
Q7. What is the role of the reliability of components and systems in the world?
TIn this fast-pace changing environment, the attributes related to the reliability of components and systems continue to play a fundamental role for industry and those of safety and security are of increasing concern, as a right to freedom.
Q8. What are the common emergency measures used in the business process?
Emergency measures, e.g., the intervention of a fire brigade, are needed when the mitigation measures fail to stop the propagation of the accident [199].
Q9. What is the definition of quality review of a risk assessment?
Quality review of a risk assessment is essential, as opposition to a particular decision often takes the form of raising questions to the validity of the risk assessment [11].
Q10. What are the main criticisms of the quantitative analysis?
The quantitative analysis is often criticized in view of the difficulty of assigning probabilities (e.g., to human errors or software failures), the difficulty of verifying the assumptions behind the models at the basis of the assessment, the inherent uncertainty involved in the phenomena of interest.
Q11. What is the challenge in managing the variety of risk information that can be utilized to the scope?
The challenge is in the management of the variety of risk information that can be utilized to the scope, including that coming from outside the local environment, e.g. across the industry.
Q12. How long has the probabilistic analysis been used in the analysis of risk?
For more than 35 years, the probabilistic analysis has provided the basis for the quantification of risk (see reviews by Rechard [161,162]), with its first application to large technological systems (specifically nuclear power plants) dating back to the early 1970s [138].
Q13. What is the main strategy for the simulation of large sets of system life histories?
Two main strategies are currently followed to address the two research questions and related challenges above presented:• Simulation of large sets of system life histories using the increased computational power made available through parallel computing, cloud computing etc. • Simulation by adaptive sampling, which amounts to intelligently guiding the simulation towards the system states of interest (i.e., those belonging to the CRs).
Q14. Why is the computational cost of a system CR so high?
Although computational power is continuously increasing, in many practical instances computational cost still remains an issue for simulation-based risk assessment, because in such cases the high computational cost for the simulation of even a single system life history prevents the analyst from running and exploring the large number of input configurations for mining knowledge to characterize the system CRs.
Q15. What are the main challenges of the traditional design validation and verification process?
this expanded capability and flexibility, and the dynamic nature of the model-based design environment, also pose challenges to the execution of traditional design validation and verification (V&V) processes.