COMPASS tool vision for a system of systems Collaborative Development Environment

Coleman, Joey W.; Malmos, Anders Kaels; Larsen, Peter Gorm; Peleskã, Jan; Hains, Ralph; Andrews, Zoe; Payne, Richard J.; Foster, Simon; Miyazawa, Alvaro; Bertolini, Cristiano; Didier, André

doi:10.1109/sysose.2012.6384150

Cited by 28 publications

(14 citation statements)

References 18 publications

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“…The organizational and technical complexity of SoS, with multiple independent stakeholders with their own interests, independence and cognitive biases, requires strong leadership to identify and assess technical options for SoS architecture, as well as options and strategies for coping with change/evolution. These issues of SoS leadership have been recognized in the literature (including Frank 2006;Walden 2007;Sisti &Latimer 2007;Coleman et al 2012).…”

Section: Sosmentioning

confidence: 99%

1.4.3 System of Systems Pain Points

Dahmann

2014

INCOSE International Symp

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The INCOSE SoS Working Group (SoSWG) identified the need to understand the SoS issues of importance to the systems engineering community as an initial SoSWG activity at their meeting in January 2012 in Jacksonville, Florida. The results of the survey and follow‐up interaction with SoSWG members, identified seven areas of challenge or SoS Pain Points. This paper summarizes the survey and working group feedback and describes the pain points along with the questions they pose for the systems engineering community. The work described in this paper is the product of the INCOSE Systems of Systems Working Group, and acknowledges the contributions of working group members, including Alan Harding, Scott Workinger, Kelly Griendling, Eric Honour, Claire Ingram, Michael Henshaw, Bryan Herdlick, and others who responded to the survey and participated in the formulation and discussions of these SoS pain points.

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Section: Sosmentioning

confidence: 99%

1.4.3 System of Systems Pain Points

Dahmann

2014

INCOSE International Symp

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“…The purpose of the DYMASOS (Dynamic Management of Physically Coupled Systems of Systems) project is to explore methods for the distributed management of large physically connected systems along with distributed autonomous management and global coordination [7]. COMPASS stands for Comprehensive Modelling for Advanced Systems of Systems and aims to develop collaborative research on model-based techniques for developing and maintaining SoS [8]. For example, a flexible and responsive SoS can be developed for emergency management, given the fact that individual systems were not intended for collaboration.…”

Section: Literature Review On Current and Past Sos Projectsmentioning

confidence: 99%

Executable Architectures Using Cuckoo Search Optimization Coupled with OPM and CPN-A Module: A New Meta-Architecture Model for FILA SoS

Agarwal

Wang

Dağli

2015

Complex Systems Design &Amp; Management

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Understanding System of Systems (SoS) requires novel ways to apply systems engineering processes. Acknowledged SoS have recognized objectives, a designated manager and resources for the SoS. The goal of this research is to develop a proof of concept tool suite for Acknowledged SoS systems simulation. This suite is named flexible, intelligent and learning architectures for System of Systems (FILA-SoS). FILA-SoS assists the SoS manager in architecture generation, selection, and implementation working as an aid for decision making. Binary cuckoo search constrained optimization is used to generate meta-architectures which are evaluated by a fuzzy assessor for quality assurance. The architecture is then converted into an executable structure using Object Process Methodology (OPM) and Colored Petri Nets (CPN). A hybrid methodology comprising of OPM and CPN approach is implemented for simulating the acquisition environment. Initial application for a Search and Rescue (SAR) SoS, consisting of 25 individual systems with ten capabilities gave promising results.

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“…For a more ad-hoc SoS it is less applicable being more appropriate to the design of the component systems. The COMPASS project (Coleman et al, 2012) is carrying out research into defining a SoS modelling language, COMPASS Modelling Language (CML), which has an executable element.…”

Section: Modelling Languagesmentioning

confidence: 99%

“…There has been much research into individual SoS modelling techniques, e.g., the comprehensive modelling and analysis for advanced systems of systems (COMPASS) project (Coleman et al, 2012), discrete event systems specification (DEVS) (Zeigler, 2003).…”

Section: Introductionmentioning

confidence: 99%

A model based approach to system of systems risk management

Kinder

Henshaw

Siemieniuch

2015

2015 10th System of Systems Engineering Conference (SoSE)

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The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level.A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk.Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity.The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities.Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches.It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit.In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network.Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models.The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk.Supporting models run in Monte Carlo Simulations allowed data to be generated from which A Model Based Approach to System of Systems Risk Management iii the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities.The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability.The research established that the SoS SoI is essential for effective SoS risk i...

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COMPASS tool vision for a system of systems Collaborative Development Environment

Cited by 28 publications

References 18 publications

1.4.3 System of Systems Pain Points

1.4.3 System of Systems Pain Points

Executable Architectures Using Cuckoo Search Optimization Coupled with OPM and CPN-A Module: A New Meta-Architecture Model for FILA SoS

A model based approach to system of systems risk management

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