I have been away from writing on the blog, even my personal opinions on current research topics (OK, that's what almost all of this writing is) due to travel, deadlines, and other obligations. I do want to take an opportunity to announce that a new paper from the SEED research group co-authored by Dr. Francis and Behailu Bekera has just been accepted for publication in the journal Reliability Engineering and System Safety. I am very excited about this, because I enjoy reading articles from this journal, and have found this research community engaging and interesting in person, as well as on paper. I'll write a more "reflective" entry about this sometime later, but if you'd like to take a look at the paper, please find it here. We will be presenting an earlier version of this work as a thought piece at ESREL 2013. More on the conference paper closer to the date of the conference in October.
Tag: systems thinking
Revisiting Stan Kaplan’s “The Words of Risk Analysis”
Recently in a SEED group paper discussion, we re-visited the words of Stan Kaplan in his 1997 "The Words of Risk Analysis." This is a transcript of a plenary lecture delivered to an Annual Meeting of the Society for Risk Analysis. SEED Ph.D. student Vikram Rao presents some highlights from this article that I'm sure you'll enjoy as well.
I enjoyed the Kaplan article. I liked how it was written in an informal style which helped the article flow well and was easy to understand. It was a good introduction to risk analysis. It asked the three questions needed for a risk assessment – What can happen?, How likely is it?, and What are the consequences? These constitute the risk triplet. The diagrams were helpful, especially the dose response curve and the evidenced based approach. And the diagrams that explained the decision making process with QRA were especially useful to get an overview of the whole process.
We need to recognize that risk assessments are going to be a bigger part of our decision making process considering the complexity of systems today. Systems such as aircraft, cars, and microprocessors have so many parts that the complexity is even bigger than before. Mitigating risks is a key to having successful complex systems. We need to be able to identify risks and have strategies for overcoming them. We can do this by eliciting expert opinions, doing simulations, and increasing our knowledge base.
We also see the rise in risks that have consequences on a national and global scale, such as global warming and climate change. By recognizing that effective risk mitigating strategies have vast importance today we can prepare ourselves well for the challenges of the future.
A Resilience Perspective on System Safety
Today, I'm presenting a guest post from Behailu Bekera, a first-year EMSE PhD student working in the SEED Group. He is studying the relationship between risk-based and resilience-based approaches to systems analysis.
Resilience is defined as the capability of a system with specific characteristics before, during and after a disruption to absorb the disruption, recover to an acceptable level of performance, and sustain that level for an acceptable period of time. Resilience is an emerging approach towards safety. Conventional risk assessment methods are typically used to determine the negative consequences of potential undesired events, understand the nature of and to reduce the level of risk involved. In contrast, the resilience approach emphasizes on anticipation of potential disruptions, giving appropriate attention to perceived danger and establishing response behaviors aimed at either building the capacity to withstand the disruption or recover as quickly as possible after an impact. Anticipation refers to the ability of a system to know what to expect and prepare itself accordingly in order to effectively withstand disruptions. The ability to detect the signals of an imminent disruption is captured by the attentive property of resilience. Once the impact takes place, the system must know how to efficiently respond with the aim of quick rebound.
Safety, as we know it traditionally, is usually considered as something a system or an organization possesses as evidenced by the measurements of failure probability, risk and so on. Concerning the new approach, Hollnagel and Woods argue that safety is something an organization or a system does. Seen from a resilience point of view, safety is a characteristic of how a system performs in the face of disruptions, how it can absorb or dampen the impacts or how it can quickly reinstate itself after suffering perturbation.
Resilience may allow for a more proactive approach for handling risk. It puts the system on a path of continuous performance evaluation to ensure safety at all times. Resilient systems will be flexible enough to accommodate different safety issues in multiple dimensions that may arise and also robust enough to maintain acceptable performance.
Participatory Dynamics of Urban Systems
During the holiday break, I have had the opportunity to do some undirected reading in a variety of areas. One of the topics I’ve browsed is urban data. My favorite source for this type of work, IBM Smarter Planet, indirectly led me to a transcript of a talk by an IBM Distinguished Engineer, Colin Harrison. He was discussing the advent of Urban Information Networks during the Paris 2030 Colloque.
Harrison specifically focused on the type of data used to link urban services and their users to each other using three classes: the invisible rendered visible, information for resource management, and open data 2.0. Urban information networks are tearing down the boundaries between citizens and their participation in the pragmatic management of their own urban resources by increasing process transparency at the same time exclusivity of information access is reduced.
One of the possibilities emblematic of the types of problems I hope to address in this space is an anecdote Harrison gives concerning CalTrans:
An example of how information enables the inhabitants to most effectively use the immediately available capacity of the total, multi-modal transportation system comes from our work with CalTrans in the San Francisco bay area. Here inhabitants with smart mobile telephones can subscribe to a service that enables CalTrans to observe their journeys based on the GPS reading from the telephone. From these observations CalTrans can determine the individual user’s common journeys. When the system sees the user beginning a familiar journey, for example commuting from home to the workplace, it looks at the multi-modal choices available to the traveller and the operational status of each of those systems along the required paths, and then makes a recommendation to the traveller for the optimal way to make this journey at this time. The traveller thus makes the journey with the minimum delays and disruptions and the transportation systems’ loads can be balanced.
The opportunities in understanding the impacts of the interplay between user behaviors and system properties is truly awesome. Let us work together to continue seeking understanding of how these emerging problems can be more greatly understood.