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Über dieses Buch

This book gathers all papers presented at the third edition of the international conference “Complex Systems Design & Management Asia” (CSD&M Asia 2018), which was held at the National University of Singapore (NUS) on December 6-7, 2018.

Mastering complex systems requires an integrated understanding of industrial practices as well as sophisticated theoretical techniques and tools. This vision was the inspiration for creating an annual forum in the Asia-Pacific region dedicated to bringing together academic researchers & industrial actors working on architecture, modeling & engineering of complex technical & organizational systems.

These proceedings cover the latest trends in the emerging field of complex systems, both from an academic and a professional perspective. Special emphasis is placed on “Smart Transportation.”

The CSD&M Asia 2018 conference is organized under the guidance of CESAM Community which is managed by the non-profit organization CESAMES. The goal of CESAM Community is to structure the sharing of good practices in enterprise and systems architecture, and to certify the level of knowledge and proficiency in this field by means of CESAM certification.



A Net-Based Formal Framework for Causal Loop Diagrams

Causal Loop Diagrams (CLDs) are a modeling tool employed in Business Dynamics. Such a diagram consists of many tightly coupled loops to capture dynamic behavior of systems. Intuitive operational semantics, describing how changes are propagated among the loops, provide a basis for model animation or manual inspection. They are, however, not precise enough to enable automated property checking. This paper proposes and defines a net-based formal framework, showing true concurrency, so that automated analysis is made possible.
Guillermina Cledou, Shin Nakajima

Modeling Operations of a Custom Hiring Center Using Agent Based Modeling and Discrete Event Simulation

Custom Hiring Centers (CHCs) for agricultural equipment and services are being promoted by the Government of India and various state governments. CHCs are important part of the complex agricultural system. They are beneficial to the community as small and marginal farmers, instead of having to purchase costly machines, can rent the machines as needed. Key factors that affect profitability are the type and number of equipment hosted by the CHC. Each piece of equipment entails a sunk cost as well as maintenance cost. However, since most agricultural operations are time sensitive, the demand is concentrated in time, and having too few pieces of equipment would entail inability to serve the demand and lost revenue. This paper presents a model to simulate the operations of a CHC, under varying scenarios, in order to estimate its profitability. The model uses a combination of Agent Based Modeling (ABM) and Discrete Event Simulation (DES) approaches. Farmers and equipment are modelled as the agents in the system while the CHC operations are modelled using DES approach. The use of the model is also demonstrated with the help of an example. The results showed that even for one combination of equipment, the profitability varies a lot. This significant variation in profitability arises from variation in the percentages of areas under different types of crop, as well as the inherent variation in crop growth rates, readiness of individual fields for particular operations within the seasonal window, as well as propensity of individual farmers to wait for CHC equipment if not immediately available. Results also demonstrate that simulation is useful to model CHC operations in a complex agricultural system and take informed decision about number and types of equipment to buy.
Yatin Anil Jayawant, Nikhil Joshi

Modelling the Efficacy of Assurance Strategies for Better Integration, Interoperability and Information Assurance in Family-of-System-of-Systems Portfolios

Military systems, and more broadly society’s, are increasingly complex and interconnected enabling hitherto only dreamed of capabilities and yet also humanity’s forays into wholesale malicious cyber-warfare. Loosely coupled families-of-systems of systems cooperate and evolve sporadically when using linear lifecycles and project-by-project development, defying capability control and assurance at that mesa-level. The U.S. Defense has evolved systematic ways for their families-of-systems to be progressively more integrated, interoperable and information assured and this is dramatically differentiating its capability assurance from its allies. This paper reports new Markovian testability modelling comparing the abstract efficacy of assurance experimentation and testing strategies employed by Australia Defence against the new U.S. strategies that are now able to quantitatively illustrate the widening gap between these allies. The modelling technique has potential to tailor Australian plans to keep pace with its ally and in modelling civilian families-of-system-of-systems in transportation, energy healthcare and the like.
Keith Joiner, Mahmoud Efatmaneshnik, Malcolm Tutty

Multi-class Fleet Sizing and Mobility on Demand Service

This paper addresses multi-class fleet sizing and vehicle assignment problem where we aim to provide Autonomous Mobility-on-Demand (AMoD) service using a fleet of heterogeneous vehicles. We present a chain of transportation with three classes of autonomous vehicles including cars, buggies and scooters. Each class of vehicle can access a subset of the network, such that, there are some links exclusive for that particular class. Our fleet management system then assigns available vehicles to trips based on the travel time for passenger pick-up and drop-off, their queue time and accessibility of the road network by the vehicle. Each assignment may consist of a set of vehicles allocated for one trip that is composed of multiple-legs served by different vehicles. For example, first mile pick-up by a scooter, middle mile on a car and last-mile trip on a buggy. We apply a genetic algorithm for heterogeneous fleet sizing and propose a hierarchical structure for travel time optimal assignment of the multi-class autonomous vehicles to passengers. We validated our approach with a range of heterogeneous fleet sizes constrained on the given budget. Our approach is more time efficient than taking a ride on a single-class autonomous vehicle for middle mile plus walking during the first and the last miles. Hence, we provide the convenience of autonomously covering the entire journey using multi-class vehicles with no additional travel or transit delays compared to single-class.
Malika Meghjani, Scott Drew Pendleton, Katarzyna Anna Marczuk, You Hong Eng, Xiaotong Shen, Marcelo H. Ang, Daniela Rus

SMACOF Hierarchical Clustering to Manage Complex Design Problems with the Design Structure Matrix

Defense system engineering is complex in nature that requires systematic approaches. The design structure matrix (DSM) is a powerful tool for supporting architecture analysis and management of systems. This paper facilitates quantitative analysis by revealing the hidden problem structure. A combined approach using Scaling by MAjorizing a Complicated Function (SMACOF) and hierarchical clustering is proposed to manipulate the design DSM. This algorithm calculates the relevance among the system elements and shows how large problems can be organized into smaller, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units. The algorithm also uses Cost and the Jaccard index to guide comparison of results. A simple example is used to illustrate the solution procedure. Also, two real industrial application examples—an aircraft design problem and a satellite multidisciplinary team organization problem—are chosen to demonstrate how the proposed DSM approach manages complexity in the design process.
Li Qiao, Mahmoud Efatmaneshnik, Michael Ryan

Modelling Safe and Secure Cooperative Intelligent Transport Systems

Automated Vehicles (AVs) are expected to help in significantly reducing traffic injuries and fatalities in the near future. However, to achieve this goal, they must be safe and secure. The recent news of the first fatal crash of AV including pedestrian confirm the urgent need of addressing AV safety and security issues to prevent such accidents from happening in the future. In order to outperform human drivers, AVs need to communicate with the other traffic participants, which makes them more vulnerable to cyberattacks. Cooperative Intelligent Transport Systems (C-ITS), which include vehicle-to-vehicle and vehicle-to-infrastructure communications, are expected to be launched in Europe next year. Thus, assuring their safety and security is crucial. This paper presents an approach, CESAM&SSM, for modelling safe and secure C-ITS using the CESAM method and the Six-Step Model. A combination of these two methods enables comprehensive analysis of C-ITS from operational, functional, constructional, safety, and security perspectives. The propose approach is compliant with three international standards: ISO 26262 – vehicle safety standard, SAE J3061 – vehicle cybersecurity standard, and ISO 21217 – intelligent transport system architecture standard.
Giedre Sabaliauskaite, Jin Cui, Lin Shen Liew, Fengjun Zhou

Detection of Teamwork Behavior as Meaningful Exploration of Tradespace During Project Design

The increasing complexity of Systems requires Teams of Teams (TofT) from different functional domains to work together. This research aims to better detect and understand the teamwork behaviors and interactions amongst the TofT. Using the Project Design approach, 19 groups participated in a model based simulation experiment to reduce the cost and duration of an implementation project for an autonomous vehicle. The performance of the groups was ranked based on generation of non-dominated (cost and schedule) plan alternatives as they explored and simulated the project model. Indicators for coherence in the decision-making process of the groups were explored by the means of visualizing the meaningful exploration of the tradespace via tree diagrams and a “chunking” process. However, sensors to detect meaningful exploration as proposed were not consistently indicative, leading to recommendations for future work on measurement of team exploration and learning during project design.
Puay Siang Tan, Bryan R. Moser

Leveraging Data Analytics in Systems Engineering – Towards a Quantum Leap in Railway Reliability

Today’s world sees data analytics more prevalent than ever before, mining and interpreting data through various trends. In Singapore, the Land Transport Authority’s (LTA) new role as asset owner for its railway operating assets has also given impetus towards establishing a sustainable digital ecosystem. Timely decisions are enabled based on accurate understanding of the asset condition from the network of data and analytic processes, to maintain safety and reliability of the Rapid Transit Systems (RTS) throughout its service life. In addition to expounding on the data analytics process, this paper also explores the potential benefits from the data discovery and the challenges in doing so. The crux is to provide a more robust, reliable and resilient public transport system through data analytics, as we strive towards a quantum leap in railway reliability for our commuters.
Thaddeus Tsang, Joyce Hong, Mun Yih Wong, Kum Fatt Ho


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