A relational oriented approach to system of systems assessment of alternatives for data link interoperability

Relational Oriented Systems Engineering (ROSE) is applied to a large scale system of systems tactical data link interoperability problem. A model driven framework structure developed using the ROSE methodology is employed to prescribe a repeatable approach for determining viable candidate solutions that completes and makes rigorous a previous capability based exploratory analysis performed by the Office of the Chief Engineer of the U.S. Navy. This novel and efficient approach to a long standing problem concentrates on the relationships between models to provide a framework and factorization of a system of systems architecture for portfolio selection and evaluation. The approach is demonstrated in a simplified but end-to-end case study derived from the original data link interoperability analysis. The abstract approach employed can be applied to a much wider class of problems than data link interoperability

A Product Line Systems Engineering Process for Variability Identification and Reduction

Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a Product Line Systems Engineering process is proposed. Specifically, the process extends research in the System Orthogonal Variability Model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of the process in the reduction of variation points, it is further applied to case studies in different engineering domains at different levels of complexity. Subject to system model availability, reduction of 14% to 40% in the number of variation points are demonstrated in the case studies.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal on 3rd June 201

A Formal Transformation Method for Automated Fault Tree Generation from a UML Activity Model

Fault analysis and resolution of faults should be part of any end-to-end system development process. This paper is concerned with developing a formal transformation method that maps control flows modeled in UML Activities to semantically equivalent Fault Trees. The transformation method developed features the use of propositional calculus and probability theory. Fault Propagation Chains are introduced to facilitate the transformation method. An overarching metamodel comprised of transformations between models is developed and is applied to an understood Traffic Management System of Systems problem to demonstrate the approach. In this way, the relational structure of the system behavior model is reflected in the structure of the Fault Tree. The paper concludes with a discussion of limitations of the transformation method and proposes approaches to extend it to object flows, State Machines and functional allocations.Comment: 1st submission made to IEEE Transactions on Reliability on 27-Nov-2017; 2nd submission (revision) made on 27-Apr-2018. This version is the 2nd submission. 20 pages, 11 figure

Relational oriented systems engineering framework for flight training

The integration of systems of systems (SoS) associated with a flight training mission directly reflects the problem of developing a system engineering process for the design of live, virtual and constructive (LVC) experiments. Due to the complexity and disparity of the technology in a flight training SoS (FTSoS), modeling and analysis of architecture is becoming increasingly important. Relational Oriented Systems Engineering (ROSE) methodology is used to develop a framework for simulation and analysis of a navigational SoS for a typical aircraft. The framework can be used for both the prescription of navigation systems entering and exiting the SoS and for the analysis of pilot behavior as navigation quality of service (QoS) changes. ROSE offers a novel approach to developing a model-based systems engineering (MBSE) process for simulation and analysis of a complex SoS problem

Harmonization of IEEE 1012 and IEC 60880 standards regarding verification and validation of nuclear power plant safety systems software using model-based methodology

© 2017 Elsevier Ltd This paper compares two standards, namely IEC 60880 and IEEE 1012, and defines a harmonized core amongst them with regard to their verification and validation processes for the nuclear power plant instrumentation and control safety system software. The problem of harmonizing standards requires a transparent representation of standards in order to make comparison possible. A model-based methodology using SysML is used to establish this transparency. Transformation rules are a crucial part of the methodology. These enable the natural language used in a standard to be translated into structural and behavioural models in SysML. Due to the high level of ambiguity of natural language, certainty definition rules for objects and operations are established as well. The result is a rigorously developed harmonized core that is traceable to the parent standards. The core developed using our methodology supports the argument that there is no one-to-one mapping between major IEEE and IEC standards. Nevertheless, some intersections between them do exist, which support the opinion of other experts. The extent of the harmonization depends on the conformance or traceability. The methodology also offers promise to address the challenge of establishing a harmonized core and the formal transferability between future standards

Structure Preserving Transformations for Practical Model-based Systems Engineering

In this third decade of systems engineering in the twenty-first century, it is important to develop and demonstrate practical methods to exploit machine-readable models in the engineering of systems. Substantial investment has been made in languages and modelling tools for developing models. A key problem is that system architects and engineers work in a multidisciplinary environment in which models are not the product of any one individual. This paper provides preliminary results of a formal approach to specify models and structure preserving transformations between them that support model synchronization. This is an important area of research and practice in software engineering. However, it is limited to synchronization at the code level of systems. This paper leverages previous research of the authors to define a core fractal for interpretation of concepts into model specifications and transformation between models. This fractal is used to extend the concept of synchronization of models to the system level and is demonstrated through a practical engineering example for an advanced driver assistance system.Comment: Accepted by the 8th IEEE International Symposium on Systems Engineering (ISSE 2022), Special Session on Theoretical Foundations of System Engineering (THEFOSE

A brief history of models and model based systems engineering and the case for relational orientation

Models are at the heart of science and engineering. Model-based approaches to software development and systems engineering use technologies to include graphical modeling languages, such as the Systems Modeling Language, that support system design and analysis through machine readable models. This paper traces key historical contributions of software and systems engineers over the past five decades to show a coherent concept of models and how they can be used for software and systems engineering. Recent model-based systems engineering methodologies supported by commercially available modeling tools are also summarized. Relational orientation is seen to be the underlying viewpoint that expresses and binds these approaches. Relational orientation for systems engineering (ROSE) is then specified using a general systems methodology. Systems are seen to access each other's models in ROSE much like classes in object orientation access each other's objects. Object-oriented frames for software engineering are extended to relational frames to specify an innovative framework for system design and analysis. This generalizes the axiomatic design approach of N. P. Suh. A repeatable procedure supporting greater concurrency between design and verification is also demonstrated for searching the solution space in linear axiomatic design

A formal transformation method for automated fault tree generation from a UML activity model

IEEE Fault analysis and resolution of faults should be part of any end-to-end system development process. This paper is concerned with developing a formal transformation method that maps control flows modeled in unified modeling language activities to semantically equivalent fault trees. The transformation method developed features the use of propositional calculus and probability theory. Fault propagation chains are introduced to facilitate the method. An overarching metamodel comprised of transformations between models is developed and is applied to an understood traffic management system of systems problem to demonstrate the approach. In this way, the relational structure of the system behavior model is reflected in the structure of the fault tree. The paper concludes with a discussion of limitations of the transformation method and proposes approaches to extend it to object flows, state machines, and functional allocations

Dynamic production system identification for smart manufacturing systems

This paper presents a methodology, called production system identification, to produce a model of a manufacturing system from logs of the system's operation. The model produced is intended to aid in making production scheduling decisions. Production system identification is similar to machine-learning methods of process mining in that they both use logs of operations. However, process mining falls short of addressing important requirements; process mining does not (1) account for infrequent exceptional events that may provide insight into system capabilities and reliability, (2) offer means to validate the model relative to an understanding of causes, and (3) updated the model as the situation on the production floor changes. The paper describes a genetic programming (GP) methodology that uses Petri nets, probabilistic neural nets, and a causal model of production system dynamics to address these shortcomings. A coloured Petri net formalism appropriate to GP is developed and used to interpret the log. Interpreted logs provide a relation between Petri net states and exceptional system states that can be learned by means of novel formulation of probabilistic neural nets (PNNs). A generalized stochastic Petri net and the PNNs are used to validate the GP-generated solutions. The methodology is evaluated with an example based on an automotive assembly system

Networked engineering notebooks for smart manufacturing

A goal of the industrial internet is to make information about manufacturing processes and resources available wherever decision making may be required. Agile use of information is a cornerstone of data analytics, but analytical methods more generally, including model-based investigations of manufacturability and operations, do not so easily benefit from this data. Rather than relating anonymous patterns of data to outcomes, these latter analytical methods are distinguished as relying on conceptual or physics-based models of the real world. Such models require careful consideration of the fitness of the data to the purpose of the analysis. Verification of these analyses, then, is a significant bottleneck. A related problem, that of ascertaining reproducible results in scientific claims, is being addressed through executable notebook technology. This paper proposes to use notebook technologies to address that bottleneck. It describes how this notebook technology, linked to internet-addressable ontologies and analytical metamodels, can be used to make model-based analytical methods more verifiable, and thus more effective for manufacturers