PublicationsGlobal OPM Research

Development of the new artificial systems with unique characteristics is very challenging task. In this paper the application of the hybrid super intelligence concept with object-process methodology to develop unique high-performance computational systems is considered. The methodological approach how to design new intelligent components for existing high-performance computing development systems is proposed on the example of system requirements creation for ”MicroAI” and ”Artificial Electronic” systems.

An entrepreneurial university is engaged in university entrepreneurship, and entrepreneurship programs are the specific ways universities organize their activities to fulfil this purpose. Due to the lack of a conceptual framework and methodology that can address the complex and multi-scale nature of the phenomenon, the field has remained in a descriptive stage. In this dissertation, to help the field move towards prescriptive theory, a set of eight criteria are defined that the methodology needs to satisfy. It is then shown that object-process methodology (OPM), incorporating insights from systems engineering and complexity science, is capable of conceptually modelling a wide range of university entrepreneurship-related phenomena across multiple scales. The adoption of OPM implies the centrality of stakeholders and stakeholder-related phenomena as key in understanding the formation and survival of entrepreneurship programs.

To validate this insight further and demonstrate the applicability of the OPM framework, three conceptual studies and two empirical studies are designed and completed. Results of the conceptual studies utilizing systems engineering -based methods (stakeholder analysis, functional analysis, and analysis of harnessable phenomena) led to the recognition of a. 17 entrepreneurship program stakeholder types with varying expectations, b. three main functions (business operating, business developing, and business meta-developing), and three sub-functions (resource acquiring and maintaining, targeting and selecting, and value creating) an entrepreneurship program can have, and c. a scale and function-based categorization framework for phenomena a program designer can harness, including the Finnish higher education financial incentive phenomena.

First empirical study observes stakeholder-related patterns in 45 Finnish entrepreneurship programs’ value propositions, and the second longitudinal empirical study provides evidence for the importance of the program having stakeholder-matching value offerings in the survival of 117 so-called good practices of entrepreneurship support four to five years after being listed as good practice. This dissertation demonstrates the value of OPM in the study of university entrepreneurship, and the findings can help future researchers to develop prescriptive theories that are practically applicable to entrepreneurship
program designers and managers.

In this paper, we present an exhaustive description of an extensible e-Health Internet-connected embedded system, which allows the measurement of three biometric parameters: pulse rate, oxygen saturation and temperature, via several wired and wireless sensors residing to the realm of Noncommunicable Diseases (NCDs) and cognitive assessment through Choice Reaction Time (CRT) analysis. The hardware used is based on ATMEGA AVR + MySignals Hardware printed circuit board (Hardware PCB), but with multiple upgrades (including porting from ATMEGA328P to ATMEGA2560). Multiple software improvements were made (by writing high-level device drivers, text-mode and graphic-mode display driver) for increasing functionality, portability, speed, and latency. A top-level embedded application was developed and benchmarked. A custom wireless AT command firmware was developed, based on ESP8266 firmware to allow AP-mode configuration and single-command JavaScript Object Notation (JSON) data-packet pushing towards the cloud platform. All software is available in a git repository, including the measurement results. The proposed eHealth system provides with specific NCDs and cognitive views fostering the potential to exploit correlations between physiological and cognitive data and to generate predictive analysis in the field of eldercare.

In MBSE there is yet no converged terminology. The term ’system model’ is used in different contexts in literature. In this study we elaborated the definitions and usages of the term ’system model’, to find a common definition. 104 publications have been analyzed in depth for their usage and definition as well as their meta-data e.g., the publication year and publication background to find some common patterns. While the term is gaining more interest in recent years it is used in a broad range of contexts for both analytical and synthetic use cases. Based on this three categories of system models have been defined and integrated into a more precise definition.

We introduce the Concept→Model→Graph→View Cycle (CMGVC). The CMGVC facilitates coherent architecture analysis, reasoning, insight, and decision making based on conceptual models that are transformed into a generic, robust graph data structure (GDS). The GDS is then transformed into multiple views of the model, which inform stakeholders in various ways. This GDS-based approach decouples the view from the model and constitutes a powerful enhancement of model-based systems engineering (MBSE). The CMGVC applies the rigorous foundations of Category Theory, a mathematical framework of representations and transformations. We show that modeling languages are categories, drawing an analogy to programming languages. The CMGVC architecture is superior to direct transformations and language-coupled common representations. We demonstrate the CMGVC to transform a conceptual system architecture model built with the Object Process Modeling Language (OPM) into dual graphs and a stakeholder-informing matrix that stimulates system architecture insight.

A Digital Engineering Information Exchange supports an exchange of digital artifacts between system engineering entities (INCOSE). Such entities might include processes, models, and organizational elements associated with space missions design. Reducing complexity and errors, as well as improving efficiency are critical capabilities associated with a digital transformation of space missions design and delivery. In our work we propose an approach to manage a digital engineering information exchange through the DSM-based approach (Eppinger and Browning 2012). Applied to space
systems architecture, the method allows keeping track of the information exchange throughout the product development.

Such information includes the core entities and relationships of CubeSat’s subsystems. This would integrate systems engineering (MBSE) approaches and PLM methods. In our paper we apply the proposed approach to a CubeSat mission design. One of the forms of utility of the proposed approach is the ability to represent the subsystems and their interfaces including objects/processes/states in one DSM/DMM representation. In our paper we demonstrate how such evaluation can be performed. Another utility of the proposed approach is that it facilitates a digital information flow through different product lifecycle stages. A proposed approach might serve as an effective method to reduce complexity associated with different ontologies in different design tools. Ultimately, it allows engaging digital tools in a concurrent engineering environment.

The purpose of the study is to solve the systemic challenge on campus—“How might we create an informative
yet delightful campus tour experience for students, visitors and university in the lens of service design?” by
applying Object-Process Methodology (OPM) in the field of the system engineering and human-centered
design. This study contributes to design research through the seamless combination and comparison of select
methodologies from the system engineering and design thinking fields to solving the challenges faced by
university campuses. In particular, the study utilized OPM to decompose the whole campus tour system into
four main components: object, process, link and status, which helps analyze the system in the lens of insideout perspective. The results showed that using OPM inspired the individuals to revisit and to clarify the internal
organization structure and its relationships in the context of the service provider – the university. Within the
sub-systems, the study utilized a human-centered design: target group interviews, journey mapping, concept
prototyping, scenario experiment and service design refinement to identify the core cause and recommend five
key touchpoints and its design suggestions across the campus tour journey. In a way, applying a humancentered design is to view the challenge in the lens of the outside-in perspective, which underlines the user
needs in the context of service receiver – visitors, students, and investors. The example not only successfully
redesigns and improves the existing campus tour experience from both the service receiver and the service
provider, but also perfectly curate OPM with the human-centered design to scale the impact of the project.

Extant systems engineering standards are so fragmented that the conceptualization of a cohesive body of knowledge is not easy. The discrepancies between different standards lead to misunderstanding and misinterpretation, making communication between stakeholders increasingly difficult. Moreover, these standards remain document centric, whereas systems engineering is transforming from paper-based to a model-based discipline. This requires the use of advanced information exchange schema and digital artifacts to enhance interoperability. Ontologies have been advocated as a mechanism to address these problems, as they can support the model-based transition and formalize the domain knowledge. However, manually creating ontologies is a time-consuming, error-prone, and tedious process. Little has been known about how to automate the development and little work has been conducted for building systems engineering ontologies. Therefore, in this paper, we propose an ontology learning methodology to extract a systems engineering ontology from the extant standards. This methodology employs natural language processing techniques to carry out the lexical and morphological analyses on the standard documents. From the learning process, important terminologies, synonyms, concepts, and relations constructing the systems engineering body of knowledge are automatically recognized and classified. A formal and sophisticated systems engineering ontology is achieved which can be used to harmonize the extant standards, unify the languages, and improve the interoperability of the model-based systems engineering approach.

Remote-controlled or autonomous multi-rotor air
vehicles, or drones, have become common and commercially
available even to individual consumers, mostly for imaging purposes. Drones appeal to mission architects looking to extend the toolbox provided to operators performing challenging missions such as public safety operations. However, careful analysis of the operational context and concept of operations must take place before major acquisitions. The purpose of this paper is to propose a model-based operational architecture definition framework, which is based on the Department of Defense Architecture Framework (DoDAF) ontology and uses Object Process Methodology (OPM) as its underlying modeling language.
Through careful mapping of DoDAF Operational Viewpoint
(OV) ontology to OPM ontology, we were able to show that the
entire OV ontology can be covered by a small set of objects, processes, relations among them, and constructs comprising them.
We then show how to instantiate the ontology to create a model of an actual architecture of interest (AoI) while maintaining strong typing of the model elements to ensure validity, integrity, consistency, and continuous compliance with the OV. We demonstrate our approach on the case of using drones in public safety enterprises for the purpose of crowd management in massively attended events and locations. The proposed framework allows for capturing ConOps and OpsCon in a lightweight, yet robust and consistent manner, and improve communication and concept validation between operational stakeholders and enterprise architects.

A Frenemy is “a person with whom one is friendly despite a fundamental dislike or rivalry.” (OED, 2018). The Systems Modeling Language (SysML) and the Object Process Methodology (OPM) are two such frenemies. OPM and SysML are different means of achieving Model-Based Systems Engineering (MBSE), each with their own benefits, issues, supporters and detractors. The National Defense Industry Association (NDIA) defines MBSE as “an approach to engineering that uses models as an integral part of the technical baseline that includes the requirements, analysis, design, implementation, and verification of a capability, system, and/or product throughout the acquisition life cycle.” (NDIA, 2011) SysML is based on the Unified Modeling Language (UML) and includes diagrams that can be used to specify system requirements, behavior, structure and parametric relationships. SysML provides a means of defining high-level abstract systems down to detailed physical systems. OPM is a “conceptual modeling language and methodology for capturing knowledge and designing systems. Based on a minimal universal ontology of stateful objects and processes that transform them, OPM can be used to formally specify the function, structure, and behavior of artificial and natural systems in a large variety of domains.” (ISO, 2015) OPM is used in some systems engineering graduate courses. Students graduating from these institutions are struggling to integrate the differing styles, philosophies, concepts and processes of SysML and OPM. A literature search reveals some papers that contrast SysML and OPM, but none that describe how the two can work together. This paper discusses a synergy of SysML and OPM in a SysML tool rather than promoting one language over another.

As autonomous ships are currently developed, modern technologies are implemented into ship systems for enabling autonomous operations. Tight coupling in safety-critical systems created new challenges for the engineers and operators. Designing, operating and analyzing these complex systems requires a deep understanding about the system composition, requirements and expected behavior or functionality. The increasing complexity of the systems requires the implementation of modern model-based approaches. Instead of large texts, these new modelling techniques aim to present detailed system information with simplified models. This paper compares system modelling techniques known as System Modelling Language (SysML) and Object Process Methodology
(OPM). These methods are used to model a Dynamic Positioning system (DP-system). Results show that the SysML is more suitable than OPM for modelling the autonomous ship systems due to its ability to present detailed system information in a simple and coherent way.

We propose a holistic Model-Based Protocol Specification (MBPS) framework. Standards, procedures, and protocols are important anchors for interconnected systems: they facilitate the connectivity of billions of devices around the world, commodify advanced technologies and solutions, and enable efficient services involving trillions of transactions in aviation, medicine, e-commerce, transportation, infrastructure, and other domains. Domain protocols allow for conventional interactions within a domain among ecosystem entities and humans (eg, airline ticketing, financial transactions, etc). Protocol specifications must be formal, consistent, and verifiable. Nevertheless, most current standard protocols are text-based, unverifiable, and often inconsistent with themselves and with other standards. Text-based standards are difficult to manage, track, control, and adopt. MBPS includes three critical enablers: a modeling language, a modeling process, and a model-supported standardization process. This paper employs Object-Process Methodology (OPM), a model-based systems engineering framework, endorsed as ISO-19450, for modeling and simulation of the generic protocol specification process and for two examples: (a) a Kerberos authentication protocol revision based on a previous Kerberos model and on a recently discovered vulnerability and (b) a domain-specific Publish—Subscribe protocol application for selective information distribution.

On March 8, 2014, a Malaysia Airlines Boeing 777 carrying flight MH-370 from Kuala Lumpur to Beijing disappeared during its flight. In this paper, we employ a model-based approach to capture and study the chain of events leading to the disappearance of the aircraft. We show that the critical reason for the aircraft’s disappearance was a cyber-physical gap (CPG). The CPG is the difference between the real state of a physical entity and its state as perceived by cybernetic agents. Failure to acknowledge the CPG’s existence, capture it in system models, and incorporate suitable mitigation mechanisms into systems exposed to CPG, has resulted in the past and may result in the future in severe consequences. In the MH-370 case, the plane’s position and adherence to its flight course were misperceived by the air traffic control, resulting in failure to track and find the plane, to this day. Our approach to CPG analysis has been previously shown to assist both designers and users handle emergent situations resulting from CPGs, such as the Three-Mile Island nuclear reactor’s partial meltdown accident in 1979. We propose several mitigation mechanisms, whose integration with air traffic control systems could help prevent similar cases in the future.

Effective decision-supporting visualization is critical for strategic, tactic, and operational management before and during a large-scale climate or extreme weather emergency. Most emergency management applications traditionally consist of map-based event and object visualization and management, which is necessary for operations, but has small contribution to decision makers. At the same time, analytical models and simulations that usually enable prediction and situation evaluation are often analyst-oriented and detached from the operational command and control system. Nevertheless, emergencies tend to generate unpredictable effects, which may require new decision-support tools in real-time, based on alternative data sources or data streams. In this paper, we advocate the use of dashboards for emergency management, but more importantly, we propose an intelligent mechanism to support effective and efficient utilization of data and information for decision-making via flexible deployment and visualization of data streams and metric displays. We employ this framework in the H2020 beAWARE project that aims to develop and demonstrate an innovative framework for enhanced decision support and management services in extreme weather climate events.

System architecture is a key driver in defining a system’s form and function. The Object-Process Methodology (OPM) integrates system function, structure, and behavior in one model for the study of system architectures. While the methodology eliminates the challenges of managing multiple views of a system architecture, it is a descriptive approach and does not explicitly address the life cycle properties (-ilities) of a system. Thus, the quality of architecture developed depends on the experience and skill level of its architect. Integrating OPM with other, more prescriptive, architecting methodologies may address this gap. In particular, Attribute Driven Design (ADD) is an approach widely used in software-centric applications for generating architectures with desirable life cycle properties. In this paper, we integrate OPM with ADD in order to leverage the advantages of each and demonstrate its use via an illustrative system development project. The integrated approach provides explicit guidance to the architect to capture form, function and life-cycle properties early in the conceptual architecting process.

In recent years, an unprecedented level of interest has grown around the prospect of sending humans to Mars for the exploration and eventual settlement of that planet. With the signing of the 2010 NASA Authorization Act, this goal became the official policy of the United States and consequently, has become the long-term objective of NASA’s human spaceflight activities. A review of past Mars mission planning efforts, however, reveals that while numerous analyses have studied the challenges of transporting people to the red planet, relatively little analyses have been performed in characterizing the challenges of sustaining humans upon arrival. In light of this observation, this thesis develops HabNet – an integrated Habitation, Environmental Control and Life Support (ECLS), In-Situ Resource Utilization (ISRU), and Supportability analysis framework – and applies it to three different Mars mission scenarios to analyze the impacts of different system architectures on the costs of deploying and sustaining a continuous human presence on the surface of Mars. Through these case studies, a number of new insights on the mass-optimality of Mars surface system architectures are derived. The most significant of these is the finding that ECLS architecture mass-optimality is strongly dependent on the cost of ISRU – where open-loop ECLS architectures become mass-optimal when the cost of ISRU is low, and ECLS architectures with higher levels of resource recycling become mass-optimal when the cost of ISRU is high. For the Martian surface, the relative abundance of resources equates to a low cost of ISRU, which results in an open-loop ECLS system supplemented with ISRU becoming an attractive, if not dominant surface system architecture, over a range of mission scenarios and ISRU performance levels. This result, along with the others made in this thesis, demonstrates the large potential of integrated system analyses in uncovering previously unseen trends within the Mars mission architecture tradespace. By integrating multiple traditionally disparate spaceflight disciplines into a unified analysis framework, this thesis attempts to make the first steps towards codifying the human spaceflight mission architecting process, with the ultimate goal of enabling the efficient evaluation of the architectural decisions that will shape humanity’s expansion into the cosmos.

The ability to coordinate intricate operations inboth intelligence, surveillance and reconnaissance (ISR) as wellas search and rescue (SAR) operations is a complex issue. Suchoperations can be described as a System-of-Systems (SoS). Bothobject process methodology (OPM) and color petri nets (CPN)can be used to create executable architecture models for an SoS.The modeling approach proposed in this study can capture theinteractions that occur between either collaborating systems orcomponents. It can also be used to analyze the behavioral aspectsof an SoS. OPM models are easy to understand, giving
stakeholders the ability to envision architecture’s quality and scale. In contrast, the simulation capabilities of CPN can be usedfor accurate performance assessment. The proposed modellingapproach facilitates decision making by providing a better estimation and confidence of the SoS’s performance.
Development of an executable architecture for an SoS will be ofimportance to policy makers by discerning, exploring, and adjusting stakeholder’s firml
y held beliefs, finding new ways forsystems to work together, learning more cost effective SoSarrangements and aid in negotiations with component systems tobuild an SoS