Mayada Omer

Resilience Analysis of Soft Infrastructure Systems

Abstract Infrastructure resilience is often associated with the ability of the hard infrastructure or physical system to cope with severe disruptions; however, the institutions and enterprises that make up the soft infrastructure systems are also prone to crises. Incorporating resilience aids systems to cope with crises and recover from disruptive events, which is not possible without an organizational foundation that is able to cope with and respond to crisis. Additionally, metrics enable stakeholders to assess the effectiveness of resilience strategies and show their added value. This paper outlines a methodology for assessing resilience of soft infrastructure using social network analysis. The methodology is applied to the National Intelligent Transportation System (ITS) where the logical architecture is viewed as a network, and the centrality measures are used to define the systems resilience metrics.

A cognitive process architecture framework for secure and resilient seaport operations

In order for a seaport to maximize its security and resilience, it must have the right information available at the right time for the right stakeholder. Due to the multiplicity of stakeholders in a seaport, which includes terminal operators, federal agencies, state agencies, and local law enforcement authorities, fragmentation often occurs resulting in information flows that do not allow for a systemic response to accidents, malicious attacks or natural disasters. By shifting more towards a cognitive seaport that adapts its behavior based on past experience and senses, understands and responds to changes in its environment, this challenge can be mitigated. The Cognitive Process Architecture Framework is proposed in this paper, allowing seaport stakeholders to monitor the implementation of responses that arise from sensing changes/events, perceiving operational scenarios, and choosing response alternatives based on tradeoffs.

A complexity driven approach for risk evaluation in use-oriented product-service systems supply chains

The dynamic and inter-connected nature of the current day business environment has transformed the supply chain of any enterprise into a highly complex system. However, the increased complexity of the supply chain has also made it more risk-prone. This paper presents a supply chain model for use-oriented product-service systems and proposes a complexity driven approach that deploys multiple domain matrices and agent based modeling for the identification and evaluation of a set of critical risk factors associated with supply chains. The findings of this research can aid systems professionals to have a better understanding of the risks associated with the complex nature of supply chains in order to develop mitigations strategies accordingly.

Sustainability Indicators: Overview, Synthesis and Future Research Directions

Indicators form an important tool to assess product sustainability. However, an overview over this body of literature and its contents, specifically in regard to indicators for measuring product sustainability, does not exist. The approach applied in this paper is exclusively literature based. In a structured and methodological literature survey, the relevant literature containing various methods for sustainability assessment as well as existing frameworks containing sustainability indicators have been collected. The results of this paper are a list of sustainability impact categories and indicators, spanning the three relevant fields of sustainability. As such, this paper represents a review of existing product-related sustainability indicators.

Structure-based System Dynamics analysis of engineering design processes

Within this work a case study is presented in which the concept of structure-based System Dynamics analysis is applied to an engineering design process. The structure-based System Dynamics analysis approach uses structural Multiple-Domain Matrix models as a basis to derive System Dynamics models which are able depict the behavior of the engineering design processes. The implications from the behavioral models can be used to analyze and optimize the structure of the underlying process. The development of an e-bike sharing system within a student project was used as basis for the case study to answer the question if the structure-based System Dynamics analysis approach can be successfully applied to model the behavior of the observed engineering design process. Based on the definition of this initial research question, the instruments to conduct the case are developed, the data is gathered and consequently analyzed. The simulation results of the engineering design process are presented, compared to the real process and finally discussed. Thereby benefits, challenges and further areas of research are identified.

A Matrix-based Framework to Support Dynamic Modeling of Sociotechnical Systems

In order to create viable sociotechnical systems, such as product-service systems, methods to design and analyze such systems are necessary. Dynamic modeling and simulation techniques such as Agent Based Modeling or System Dynamics are suitable techniques that extend the repertoire of existing model-based systems engineering for this purpose. However, due to the complexity involved in efficiently creating, managing and conducting experiments with a large number of such models, an approach is needed to support the modeling process and create transparency. The key result presented in this paper is a meta-model in the form of a MDM, which contains the domains and dependencies necessary to map the process of dynamic modeling of complex sociotechnical systems. The meta-model is the result of an academic case study, where static and dynamic models of a product-service system have been developed.

A survey on complexity management in systems engineering

In this contribution, we classify approaches towards complexity management in systems engineering. With the aid of an extensive survey of complexity, we identify similarities, differences, overlaps and gaps of complexity definitions and interactions between research areas. The overarching goal of this paper is to support a better understanding of complexity. An extensive literature review revealed seven disciplines that have direct relevance to issues of complexity. These disciplines are: Complex Systems, Product Development, Systems Engineering, Software Engineering, Management Science, Complexity Theory and Complex Networks. Additionally, the research unveiled overlaps between the various disciplines and in turn helped to expose voids or white spots between the disciplines. These white spots represent areas without any scientific contributions so far, showing need and possibilities of future research. The findings are implemented to a Venn Diagram for easy access.