Difference between revisions of "Systems Engineering and Management"

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'''''Lead Authors:''''' ''Bud Lawson, Alan Faisandier,'' '''''Contributing Authors:''''' ''Rick Adcock, Dick Fairley, Garry Roedler, Ray Madachy, Deva Henry, Sanford Friedenthal''
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'''''Lead Authors:''''' Jeffrey Carter and Caitlyn Singham
 
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Part 3 of the Guide to the SE Body of Knowledge (SEBoK) focuses on the general knowledge of ''how'' systems are engineered.
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Part 3: Systems Engineering and Management (SE&M) materials provide system lifecycle best practices for creating and executing interdisciplinary processes to ensure that customer needs are satisfied with a technical performance, schedule, and cost compliant solution.  The figure below depicts the context of SE&M processes and practices guidance within the SEBoK.  The SE&M materials are currently being updated to provide system design practitioners with Model-Based Systems Engineering [MBSE] implementation guidance employing the Systems Modeling Language (SysML®).
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[[File:SEBoK_Context_Diagram_Inner_P3_Ifezue_Obiako.png|centre|thumb|600x600px|'''Figure 1 SEBoK Part 3 in context (SEBoK Original).''' For more detail see [[Structure of the SEBoK]]]]
 
  
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This part builds upon Part 2: [[Foundations of Systems Engineering]], which discusses the need for a {{Term|Systems Approach (glossary)}} applied to one or more {{Term|Engineered System (glossary)}} contexts as a part of managed interventions into {{Term|Complexity (glossary)|complex}} real world problems.  Part 3 provides an overview of the common uses of [[Life Cycle Models|life cycle models]] to organize the technical and non-technical aspects of SE and discusses [[Systems Engineering Management]] activities. Part 3 also discusses the most commonly used SE technical processes and provides additional references to the common methods, tools, and techniques used in these processes.
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[[File:SEBoK_Context_Diagram_Inner_P3_Ifezue_Obiako.png|centre|thumb|600x600px|'''Figure 1: SEBoK Part 3 SE&M Context [SEBoK Original]'''or more detail see [[Structure of the SEBoK]]]]
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The commonly recognized definition of {{Term|Systems Engineering (glossary)|systems engineering}} (SE) used across the SEBoK (INCOSE 2015) defines SE as an interdisciplinary approach which applies across the complete life cycle of an identified {{Term|System-of-Interest (glossary)|System-of-Interest}}.  The definition states that systems engineering “'''integrates all the disciplines and specialty groups into a team effort forming a structured development process that proceeds from concept to production to operation'''”. Thus, SE is an engineering discipline concerned with all aspects of an engineered systems life, including how we organize to do the engineering, what is produced by that engineering and how the resulting systems are used and sustained to meet stakeholder needs.
 
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Part 3 provides only an overview of how systems are engineered in a generic sense. [[Applications of Systems Engineering|Part 4]] provides more specific information as to how the principles discussed in Part 3 are applied differently in consideration of  {{Term|Product System (glossary)|product systems}},  {{Term|Service System (glossary)|service systems}}, {{Term|Enterprise System (glossary)|enterprise systems}}, and {{Term|System of Systems (SoS) (glossary)|systems of systems}} (SoS) contexts. [[Enabling Systems Engineering|Part 5]] explains how people and organizations may approach utilizing these principles as part of a holistic systems approach. [[Related Disciplines|Part 6]] contains references to other engineering and management disciplines, which work with the SE processes within a systems life cycle, but do not fall under the umbrella of SE.
 
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Systems engineering, like many other engineering disciplines, is transitioning to a model-based approach, {{Term|Model-Based Systems Engineering (MBSE) (glossary)|model-based systems engineering (MBSE)}}.  The aim is to enhance productivity and quality, and to cope with the design of increasingly complex systems.  Although models have always been used by systems engineering to create information about engineered systems, that information has been translated and managed through document based artifacts. In a model-based approach, the information about the system is captured in a shared system model, made up of a set of integrated models appropriate to the life cycle stages.  This model is managed and controlled throughout the system life cycle as noted in Part 2 under [[Representing Systems with Models|Representing Systems with Models]]. This provides the ability to maintain more consistent, precise, and traceable information about the system. The system model provides an authoritative source of information that can be communicated across the development team and other stakeholders, used to generate views of the system relevant to particular stakeholders, and used to generate documentation about  the system similar to more traditional systems engineering documentation. The model can also be analyzed to assess the integrity of the system specification and design. A model also captures knowledge in a way that can be more readily reused than traditional document-based approaches. In a model-based systems engineering approach, the processes referred to in this and other Parts of the SEBoK remain fundamentally the same, but the artifacts produced are model-based. Some examples of MBSE methods are highlighted in [[A Survey of Model-Based Systems Engineering (MBSE) Methodologies]] (Estefan 2008). It is anticipated that as the transition to model-based practices occurs, the SEBoK will be updated to reflect the body of current and emerging practice.
 
  
 
==Knowledge Areas in Part 3==
 
==Knowledge Areas in Part 3==
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Each part of the SEBoK is divided into knowledge areas (KAs), which are groupings of information with a related theme. Part 3 contains the following knowledge areas:
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Each part of the SEBoK is divided into knowledge areas (KAs), which are groupings of information with a related theme. Part 3 contains the following themes:
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*[[Introduction to Life Cycle Processes]]
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*[[Systems Engineering STEM Overview]]
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*[[Life Cycle Models]]
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*[[Model-Based Systems Engineering (MBSE)]]
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*[[Concept Definition]]
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*[[Systems Lifecycle Approaches]]
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*[[System Definition]]
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*[[System Lifecycle Models]]
 +
*[[Systems Engineering Management]]
 +
*[[Business and Mission Analysis]]
 +
*[[Stakeholder Needs Definition]]
 +
*[[System Architecture Definition]]
 +
*[[Detailed Design Definition]]
 +
*[[System Analysis]]
 
*[[System Realization]]
 
*[[System Realization]]
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*[[System Deployment and Use]]
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*[[System Implementation]]
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*[[Systems Engineering Management]]
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*[[System Integration]]
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*[[Product and Service Life Management]]
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*[[System Verification]]
 +
*[[System Transition]]
 +
*[[System Validation]]
 +
*[[System Operation]]
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*[[System Maintenance]]
 +
*[[Logistics]]
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*[[Service Life Management]]
 
*[[Systems Engineering Standards]]
 
*[[Systems Engineering Standards]]
 
See the article [[Matrix of Implementation Examples]] for a mapping of case studies and vignettes included in Part 7 to topics covered in Part 3.
 
See the article [[Matrix of Implementation Examples]] for a mapping of case studies and vignettes included in Part 7 to topics covered in Part 3.
  
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==Value of Ontology Concepts for Systems Engineering==
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The SE&M articles depicted within an outline of the Part 3 materials with the status of model-based guidance updates can be found in the [[SEBoK Table of Contents]]. The SE&M processes and practices provide tailorable guidance for an engineering organization to satisfy strategic business goals and individual project objectives including:
  
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Ontology is the set of entities presupposed by a theory (Collins English Dictionary 2011). Systems engineering, and system development in particular, is based on concepts related to mathematics and proven practices. A SE ontology can be defined considering the following path/rationale.
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*How engineering conducts system development
 +
*The purpose of each engineering artifact generated
 +
*How systems are integrated, and requirements verified
 +
*How new product designs are transitioned to production
 +
*How the resulting system is employed and sustained to satisfy customer needs
  
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SE provides engineers with an approach based on a set of concepts (i.e., stakeholder, requirement, function, scenario, system element, etc.) and generic processes (Madni and Sievers, 2018). Each process is composed of a set of activities and tasks gathered logically around a theme or a purpose. A process describes “what to do” using the applied concepts. The implementation of the activities and tasks is supported by methods and modeling techniques, which are composed themselves of elementary tasks; they describe the “how to do” of SE. The activities and tasks of SE are transformations of generic data using predefined concepts. Those generic data are called entities, classes, or types. Each ''entity'' is characterized by specific ''attributes'', and each attribute may have a different value. All along their execution, the activities and tasks of processes, methods, and modeling techniques exchange instances of generic entities according to logical ''relationships''. These relationships allow the engineer to link the entities between themselves {{Term|Traceability (glossary)|(traceability)}} and to follow a logical sequence of the activities and the global progression (engineering management). Cardinality is associated with every relationship, expressing the minimum and maximum number of entities that are required in order to make the relationship valid.  
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==Systems Engineering & Management Overview==
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{| class="wikitable mw-collapsible"
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Systems engineering (SE) conducts behavioral and structural design analyses applying interdisciplinary processes and practices to integrate System, Electrical, Mechanical, Software, and Specialty Engineering (EE, ME, SW, and SP) disciplines. The design objective is to develop a holistic technical solution that satisfies specific customer application criteria.  SE has traditionally applied intuitive domain-specific practices emphasizing processes and procedures with good writing skills to manually organize information in a disparate collection of documents. The traditional SE deliverables are textual system requirement specifications, analysis reports, system design descriptions and interface specifications.  
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|''‘Cardinality in systems is associated with every relationship, expressing the number of  entities that are required to make the relationship stand. As such a relationship  can be viewed in one of three ways:'' One-2-One,  One-2-Many or Many-to-Many ''and described in terms of quantity, pattern and arrangement.’''
 
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|}
 
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Additional information on this subject may be found in ''Engineering Complex Systems with Models and Objects'' (Oliver, Kelliher, and Keegan 1997).
 
  
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The set of SE entities and their relationships form an ontology, which is also referred to as an "engineering meta-model". Such an approach is used and defined in the ISO 10303:AP233 standard (ISO 2007). There are many benefits to using an ontology including:
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Figure 2 depicts the “Digital Trinity” of innovative design practices to transform traditional system development including the adoption of Agile System / Software Development, a Modular Open Systems Approach [MOSA], and Digital Engineering.  
  
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*the use of a standardized vocabulary, with carefully chosen names, which helps to avoid the use of synonyms in the processes, methods, and modeling techniques
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<center>'''Note: Figure 2: Digital Trinity of Current Design Practices will be added when copyright permission is received.'''</center>
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*the reconciliation of the vocabulary used in different modeling techniques and methods
 
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*the automatic appearance of the traceability requirements when implemented in databases, SE tools or workbenches, and the quick identification of the impacts of modifications in the engineering data set
 
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*the continual observation of the consistency and completeness of engineering data; etc.
 
  
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Throughout Part 3, there are discussions of the ontological elements specifically relevant to a given topic.
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The governing principle of Digital Engineering is development of system design models with high-fidelity simulation capabilities to realistically emulate systems in virtual computing environments. The design model includes functional, logical, and physical system design representations with high-fidelity simulation capabilities that are integrated with EE, ME, SW, and SP design disciplines for system functional and performance assessments. The integrated simulations provide a digital twin with digital threads of critical system characteristics to evaluate design alternatives in virtual computing environments to discover and resolve design defects before the expense of producing physical prototypes.
  
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==Mapping of Topics to ISO/IEC 15288, System Life Cycle Processes==
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* Digital threads are analytical frameworks providing end-to-end system simulation representations to evaluate logical operations and key performance parameters in virtual environments by exchanging information between different modeling tools across the lifecycle.
 +
* Digital twins are authoritative representations of physical systems including the digital thread end-to-end connections with all the data, models, and infrastructure needed to create and optimize a system’s lifecycle digitally. Digital twins enable project team collaboration, system simulation functional performance assessments, design change impact evaluations, and product-line management reuse libraries
  
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Figure 2, below, shows the relative position of the KA's of the SEBoK with respect to the processes outlined in the ISO/IEC/IEEE 15288 (ISO 2015) standard.  
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The digital engineering transformation includes the adoption of Model-Based Systems Engineering [MBSE] as an alternative approach to traditional document-based systems engineering methods. INCOSE defines MBSE as the formalized application of graphical modeling with specific semantic definitions throughout the system lifecycle. MBSE includes the creation, development, and utilization of digital design models with domain product-specific [e.g., aerospace, automobile, software, consumer, …] analyses to define system requirements and behavior/structure characteristics.
  
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As shown, all of the major processes described in ISO/IEC/IEE 15288:2015 are discussed within the SEBoK.
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The design model provides a Single Source of Truth [SSoT] for the system technical baseline enabling project team and stakeholder collaboration. The design model contains diagrams and meta-data depicted with a graphical modeling language [e.g., Systems Modeling Language [SysML<sup>®</sup>]. The modeling language has precise semantic definitions for depicting systems design characteristics. There are several commercially available tools compliant with the Object Management Group’s [OMG’s] industry SysML<sup>®</sup> standard.
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[[File:Mapping_of_tech_topics_SEBoK_with_ISO_IEC_15288techPro_060612.jpg|thumb|center|600px|'''Figure 2. Mapping of Technical Topics of Knowledge Areas of SEBoK with ISO/IEC/IEEE 15288 Technical Processes.''' (SEBoK Original)]]
 
  
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The ISO/IEC/IEEE 15288:2015 marked with an * are new or have been renamed and modified in scope for this revision of the standard.
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MBSE enhances the ability to capture, analyze, share, and manage authoritative information associated with the complete specification of a product compared to traditional document-based approaches. MBSE provides the capability to consolidate information in an accessible, centralized source, enabling partial or complete automation of many systems engineering processes, and facilitating interactive representation of system components and behaviors.
  
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These changes and associated changes to the SEBoK now mean that the two are significantly more closely aligned than before.  It should also be noted that the latest update of the INCOSE SE Handbook (INCOSE 2015) is now fully aligned with the 2015 revision of the standard.
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The legacy SE&M materials are all impacted by the adoption of MBSE practices, and the SEBoK is updating its materials accordingly to reflect best practices and principles in an integrated model-based engineering environment. The updated materials to specify system behavior and structure characteristics with traceability to the associated requirements are organized in accordance with the ISO/IEC/IEEE-15288:2015 ''Systems Lifecycle Processes'' Standard shown in the figure below.
  
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Any future evolution of Life Cycle Process knowledge in the SEBoK will be complementary to these standard descriptions of the generic SE process set.
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[[File:15288_Standard_Outline_-_Model.png|thumb|center|750px|'''Figure 3.''' ISO/IEC/IEEE-15288:2015 Standard Outline (SEBoK Original)]]
  
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==References==  
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Figure 4 depicts a generic example of the model-based system design process.  The approach is consistent with INCOSE’s Systems Engineering Handbook guidance with the addition of a system design model repository to manage the project technical baseline. The MBSE design process is independent of any specific design methodology (e.g., structured analysis, object orientated, etc.) employed. Each design model element has a single definition with multiple instantiations on various diagrams depicting system structure and behavior characteristics including traceability to the associated requirements. The model-based design process may be tailored for projects dependent on the domain-area, development, and lifecycle approaches.
 +
 
 +
[[File:Model-Based_System_Design_Process_Part3.png|thumb|center|600px|''Figure 4: Model-Based System Design Process.'' (SEBoK Original)]]
 +
 
 +
Product domain-area system design knowledge and expertise are still mandatory with implementation of an MBSE approach, which employs integrated modeling tools instead of legacy drawing tools (e.g., Powerpoint, Visio), textual-based specifications (e.g., DOORS), and engineering analysis reports and design descriptions (Word).
 +
 
 +
The SE&M model-based system design guidance enables a multi-disciplinary team to manage a project’s technical baseline within a single, consistent, and unambiguous system design model.  The integrated MBSE design model contains system functional and logical representations with the physical detailed design implementation to specify, analyze, design, and verify that requirements are satisfied.  The guidance defines conventions for developing design models to specify system behavior and structure characteristics with traceability to the project’s requirements.  The design models provide a digital authoritative source of truth information repository for a project’s technical baseline.  Model simulation with test cases facilitate initial design verification in digital computing environments to discover and resolve design defects before incurring the expense of producing physical prototypes. 
 +
 
 +
MBSE practices transform SE from the current document-based approach to employing computer aided design tools comparable to the evolution of the EE, ME, SW, and SP disciplines years ago.  The value-added benefit is employment of integrated modeling tools instead of traditional static drawing tools [e.g., PowerPoint, Visio] for product development, integration, and verification across the system lifecycle. 
 +
The SE&M model-based system design guidance provides MBSE best practices for implementing a digital engineering strategy to develop system design models for specifying and simulating behavior / structure characteristics with traceability to the associated requirements based on the following principles:
 +
#Develop, integrate, and employ digital system design models for cross-domain collaboration throughout the product lifecycle [i.e., engineering development, production, and sustainment].
 +
#Manage product-lines based on industry open standards with libraries of customized variants adapted for customers with new, modified, and existing [reuse] system design capabilities.
 +
#Maintain a digital authoritative source of truth information repository for each product variant’s approved technical baseline throughout the product lifecycle to facilitate collaboration and inform decision making.
 +
#Conduct model simulations with verification test cases to evaluate system behavior and structure in digital computing environments to discover design defects before the expense of producing physical prototypes.
 +
#Define digital threads of technical key performance parameters and synchronize information across SE, EE, ME, SW, and SP design modeling tools to ensure system requirements, interactions, and dependencies are commonly understood.  Design changes are automatically reflected in all model usages across engineering discipline tools and assessed for compliance, with any issue(s) flagged for corrective action.
 +
#Utilize “Agile” development processes to provide consistent methods for developing system design models and identifying digital threads for data synchronization across engineering disciplines within the integrated model-based engineering environment.
 +
 
 +
The SE&M model-based system design approach has a theoretical scientific foundation based on the system phenomenon defined by Hamilton’s Principle: a system is composed of hierarchical elements which interact by exchanging data, energy, force, or mass to modify the state of cooperating elements resulting in emergent, discrete, or continuous behaviors at progressive levels of aggregation or decomposition as shown in Figure 4. 
 +
 
 +
[[File:The_System_Phenomenon.png|thumb|center|750px|''Figure 4: The System Phenomenon – Hamilton’s Principle.'' (SEBoK Original)]]
 +
 
 +
==References==
 +
===Citations===
 
Collins English Dictionary, s.v. "Ontology." 2011.
 
Collins English Dictionary, s.v. "Ontology." 2011.
  
Line 64: Line 89:
  
 
INCOSE. 2015. ''Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities'', version 4.0. Hoboken, NJ, USA: John Wiley and Sons, Inc, ISBN: 978-1-118-99940-0.
 
INCOSE. 2015. ''Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities'', version 4.0. Hoboken, NJ, USA: John Wiley and Sons, Inc, ISBN: 978-1-118-99940-0.
 +
 +
ISO. 2007. ''Systems Engineering and Design.'' Geneva, Switzerland: International Organization for Standardization (ISO). ISO 10303-AP233.
  
 
ISO/IEC/IEEE. 2015. ''Systems and Software Engineering -- System Life Cycle Processes''. Geneva, Switzerland: International Organisation for Standardisation / International Electrotechnical Commissions / Institute for Electrical and Electronics Engineers. ISO/IEC/IEEE 15288:2015.
 
ISO/IEC/IEEE. 2015. ''Systems and Software Engineering -- System Life Cycle Processes''. Geneva, Switzerland: International Organisation for Standardisation / International Electrotechnical Commissions / Institute for Electrical and Electronics Engineers. ISO/IEC/IEEE 15288:2015.
  
−
ISO. 2007. ''Systems Engineering and Design.'' Geneva, Switzerland: International Organization for Standardization (ISO). ISO 10303-AP233.
+
Oliver, D., T. Kelliher, and J. Keegan. 1997. ''Engineering Complex Systems with Models and Objects''. New York, NY, USA: McGraw-Hill.
 +
OMG Systems Modeling Language [SysML®] Standard – v1.6, November 2019
 +
 
 +
Roper, W. 2020. ‘’There is No Spoon: The New Digital Acquisition Reality.’’ Arlington, VA: US Space Force, US Air Force, Assistant Secretary of the Air Force. 07 October 2020. https://software.af.mil/wp-content/uploads/2020/10/There-Is-No-Spoon-Digital-Acquisition-7-Oct-2020-digital-version.pdf
 +
 
 +
Schindel, B. 2016. “Got Phenomena? Science-Based Disciplines for Emerging Systems Challenges,” International Council on Systems Engineering (INCOSE), 2016 INCOSE International Symposium Proceedings, Edinburgh, Scotland.
 +
 
 +
Schindel, B. 2018. “The System Phenomenon, Hamilton’s Principle, and Noether’s Theorem as a Basis for System Science,” International Council on Systems Engineering (INCOSE), 2018 INCOSE International Workshop Proceedings, Torrance, California.
 +
 
 +
U.S. DOD. 2018. ‘’Digital Engineering Strategy.’’ Arlington, VA: Office of the Deputy Assistant Secretary of Defense for Systems Engineering. June 2018.
  
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Oliver, D., T. Kelliher, and J. Keegan. 1997. ''Engineering Complex Systems with Models and Objects''. New York, NY, USA: McGraw-Hill.
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Wasson, C. 2006. System Analysis, Design, and Development – Concepts, Principles, and Practices.’’ Hoboken, NJ: John Wiley & Sons.
  
 
===Primary References===
 
===Primary References===
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<center>[[Applying the Systems Approach|< Previous Article]] | [[SEBoK Table of Contents|Parent Article]] | [[Introduction to Life Cycle Processes|Next Article >]]</center>
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<center>[[Applying the Systems Approach|< Previous Article]] | [[SEBoK Table of Contents|Parent Article]] | [[Systems Engineering STEM Overview|Next Article >]]</center>
  
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<center>'''SEBoK v. 2.5, released 15 October 2021'''</center>
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<center>'''SEBoK v. 2.6, released 20 May 2022'''</center>
  
 
[[Category: Part 3]]
 
[[Category: Part 3]]
 
[[Category:Part]]
 
[[Category:Part]]

Revision as of 19:28, 20 May 2022

Lead Authors: Jeffrey Carter and Caitlyn Singham

Part 3: Systems Engineering and Management (SE&M) materials provide system lifecycle best practices for creating and executing interdisciplinary processes to ensure that customer needs are satisfied with a technical performance, schedule, and cost compliant solution. The figure below depicts the context of SE&M processes and practices guidance within the SEBoK. The SE&M materials are currently being updated to provide system design practitioners with Model-Based Systems Engineering [MBSE] implementation guidance employing the Systems Modeling Language (SysML®).

Figure 1: SEBoK Part 3 SE&M Context [SEBoK Original]or more detail see Structure of the SEBoK

Knowledge Areas in Part 3

Each part of the SEBoK is divided into knowledge areas (KAs), which are groupings of information with a related theme. Part 3 contains the following themes:

See the article Matrix of Implementation Examples for a mapping of case studies and vignettes included in Part 7 to topics covered in Part 3.

The SE&M articles depicted within an outline of the Part 3 materials with the status of model-based guidance updates can be found in the SEBoK Table of Contents. The SE&M processes and practices provide tailorable guidance for an engineering organization to satisfy strategic business goals and individual project objectives including:

  • How engineering conducts system development
  • The purpose of each engineering artifact generated
  • How systems are integrated, and requirements verified
  • How new product designs are transitioned to production
  • How the resulting system is employed and sustained to satisfy customer needs

Systems Engineering & Management Overview

Systems engineering (SE) conducts behavioral and structural design analyses applying interdisciplinary processes and practices to integrate System, Electrical, Mechanical, Software, and Specialty Engineering (EE, ME, SW, and SP) disciplines. The design objective is to develop a holistic technical solution that satisfies specific customer application criteria.  SE has traditionally applied intuitive domain-specific practices emphasizing processes and procedures with good writing skills to manually organize information in a disparate collection of documents. The traditional SE deliverables are textual system requirement specifications, analysis reports, system design descriptions and interface specifications.

Figure 2 depicts the “Digital Trinity” of innovative design practices to transform traditional system development including the adoption of Agile System / Software Development, a Modular Open Systems Approach [MOSA], and Digital Engineering.

Note: Figure 2: Digital Trinity of Current Design Practices will be added when copyright permission is received.

The governing principle of Digital Engineering is development of system design models with high-fidelity simulation capabilities to realistically emulate systems in virtual computing environments. The design model includes functional, logical, and physical system design representations with high-fidelity simulation capabilities that are integrated with EE, ME, SW, and SP design disciplines for system functional and performance assessments. The integrated simulations provide a digital twin with digital threads of critical system characteristics to evaluate design alternatives in virtual computing environments to discover and resolve design defects before the expense of producing physical prototypes.

  • Digital threads are analytical frameworks providing end-to-end system simulation representations to evaluate logical operations and key performance parameters in virtual environments by exchanging information between different modeling tools across the lifecycle.
  • Digital twins are authoritative representations of physical systems including the digital thread end-to-end connections with all the data, models, and infrastructure needed to create and optimize a system’s lifecycle digitally. Digital twins enable project team collaboration, system simulation functional performance assessments, design change impact evaluations, and product-line management reuse libraries

The digital engineering transformation includes the adoption of Model-Based Systems Engineering [MBSE] as an alternative approach to traditional document-based systems engineering methods. INCOSE defines MBSE as the formalized application of graphical modeling with specific semantic definitions throughout the system lifecycle. MBSE includes the creation, development, and utilization of digital design models with domain product-specific [e.g., aerospace, automobile, software, consumer, …] analyses to define system requirements and behavior/structure characteristics.

The design model provides a Single Source of Truth [SSoT] for the system technical baseline enabling project team and stakeholder collaboration. The design model contains diagrams and meta-data depicted with a graphical modeling language [e.g., Systems Modeling Language [SysML®]. The modeling language has precise semantic definitions for depicting systems design characteristics. There are several commercially available tools compliant with the Object Management Group’s [OMG’s] industry SysML® standard.

MBSE enhances the ability to capture, analyze, share, and manage authoritative information associated with the complete specification of a product compared to traditional document-based approaches. MBSE provides the capability to consolidate information in an accessible, centralized source, enabling partial or complete automation of many systems engineering processes, and facilitating interactive representation of system components and behaviors.

The legacy SE&M materials are all impacted by the adoption of MBSE practices, and the SEBoK is updating its materials accordingly to reflect best practices and principles in an integrated model-based engineering environment. The updated materials to specify system behavior and structure characteristics with traceability to the associated requirements are organized in accordance with the ISO/IEC/IEEE-15288:2015 Systems Lifecycle Processes Standard shown in the figure below.

Figure 3. ISO/IEC/IEEE-15288:2015 Standard Outline (SEBoK Original)

Figure 4 depicts a generic example of the model-based system design process. The approach is consistent with INCOSE’s Systems Engineering Handbook guidance with the addition of a system design model repository to manage the project technical baseline. The MBSE design process is independent of any specific design methodology (e.g., structured analysis, object orientated, etc.) employed. Each design model element has a single definition with multiple instantiations on various diagrams depicting system structure and behavior characteristics including traceability to the associated requirements. The model-based design process may be tailored for projects dependent on the domain-area, development, and lifecycle approaches.

Figure 4: Model-Based System Design Process. (SEBoK Original)

Product domain-area system design knowledge and expertise are still mandatory with implementation of an MBSE approach, which employs integrated modeling tools instead of legacy drawing tools (e.g., Powerpoint, Visio), textual-based specifications (e.g., DOORS), and engineering analysis reports and design descriptions (Word).

The SE&M model-based system design guidance enables a multi-disciplinary team to manage a project’s technical baseline within a single, consistent, and unambiguous system design model. The integrated MBSE design model contains system functional and logical representations with the physical detailed design implementation to specify, analyze, design, and verify that requirements are satisfied. The guidance defines conventions for developing design models to specify system behavior and structure characteristics with traceability to the project’s requirements. The design models provide a digital authoritative source of truth information repository for a project’s technical baseline. Model simulation with test cases facilitate initial design verification in digital computing environments to discover and resolve design defects before incurring the expense of producing physical prototypes.

MBSE practices transform SE from the current document-based approach to employing computer aided design tools comparable to the evolution of the EE, ME, SW, and SP disciplines years ago. The value-added benefit is employment of integrated modeling tools instead of traditional static drawing tools [e.g., PowerPoint, Visio] for product development, integration, and verification across the system lifecycle. The SE&M model-based system design guidance provides MBSE best practices for implementing a digital engineering strategy to develop system design models for specifying and simulating behavior / structure characteristics with traceability to the associated requirements based on the following principles:

  1. Develop, integrate, and employ digital system design models for cross-domain collaboration throughout the product lifecycle [i.e., engineering development, production, and sustainment].
  2. Manage product-lines based on industry open standards with libraries of customized variants adapted for customers with new, modified, and existing [reuse] system design capabilities.
  3. Maintain a digital authoritative source of truth information repository for each product variant’s approved technical baseline throughout the product lifecycle to facilitate collaboration and inform decision making.
  4. Conduct model simulations with verification test cases to evaluate system behavior and structure in digital computing environments to discover design defects before the expense of producing physical prototypes.
  5. Define digital threads of technical key performance parameters and synchronize information across SE, EE, ME, SW, and SP design modeling tools to ensure system requirements, interactions, and dependencies are commonly understood. Design changes are automatically reflected in all model usages across engineering discipline tools and assessed for compliance, with any issue(s) flagged for corrective action.
  6. Utilize “Agile” development processes to provide consistent methods for developing system design models and identifying digital threads for data synchronization across engineering disciplines within the integrated model-based engineering environment.

The SE&M model-based system design approach has a theoretical scientific foundation based on the system phenomenon defined by Hamilton’s Principle: a system is composed of hierarchical elements which interact by exchanging data, energy, force, or mass to modify the state of cooperating elements resulting in emergent, discrete, or continuous behaviors at progressive levels of aggregation or decomposition as shown in Figure 4.

Figure 4: The System Phenomenon – Hamilton’s Principle. (SEBoK Original)

References

Citations

Collins English Dictionary, s.v. "Ontology." 2011.

Estefan, J. 2008. A Survey of Model-Based Systems Engineering (MBSE) Methodologies, rev, B. Seattle, WA: International Council on Systems Engineering. INCOSE-TD-2007-003-02. Available at: http://www.omgsysml.org/MBSE_Methodology_Survey_RevB.pdf. Accessed April 13, 2015.

INCOSE. 2015. Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities, version 4.0. Hoboken, NJ, USA: John Wiley and Sons, Inc, ISBN: 978-1-118-99940-0.

ISO. 2007. Systems Engineering and Design. Geneva, Switzerland: International Organization for Standardization (ISO). ISO 10303-AP233.

ISO/IEC/IEEE. 2015. Systems and Software Engineering -- System Life Cycle Processes. Geneva, Switzerland: International Organisation for Standardisation / International Electrotechnical Commissions / Institute for Electrical and Electronics Engineers. ISO/IEC/IEEE 15288:2015.

Oliver, D., T. Kelliher, and J. Keegan. 1997. Engineering Complex Systems with Models and Objects. New York, NY, USA: McGraw-Hill. OMG Systems Modeling Language [SysML®] Standard – v1.6, November 2019

Roper, W. 2020. ‘’There is No Spoon: The New Digital Acquisition Reality.’’ Arlington, VA: US Space Force, US Air Force, Assistant Secretary of the Air Force. 07 October 2020. https://software.af.mil/wp-content/uploads/2020/10/There-Is-No-Spoon-Digital-Acquisition-7-Oct-2020-digital-version.pdf

Schindel, B. 2016. “Got Phenomena? Science-Based Disciplines for Emerging Systems Challenges,” International Council on Systems Engineering (INCOSE), 2016 INCOSE International Symposium Proceedings, Edinburgh, Scotland.

Schindel, B. 2018. “The System Phenomenon, Hamilton’s Principle, and Noether’s Theorem as a Basis for System Science,” International Council on Systems Engineering (INCOSE), 2018 INCOSE International Workshop Proceedings, Torrance, California.

U.S. DOD. 2018. ‘’Digital Engineering Strategy.’’ Arlington, VA: Office of the Deputy Assistant Secretary of Defense for Systems Engineering. June 2018.

Wasson, C. 2006. System Analysis, Design, and Development – Concepts, Principles, and Practices.’’ Hoboken, NJ: John Wiley & Sons.

Primary References

INCOSE. 2015. Systems Engineering Handbook - A Guide for System Life Cycle Processes and Activities, version 4.0. Hoboken, NJ, USA: John Wiley and Sons, Inc, ISBN: 978-1-118-99940-0.

ISO/IEC/IEEE. 2015. Systems and Software Engineering -- System Life Cycle Processes. Geneva, Switzerland: International Organisation for Standardisation / International Electrotechnical Commissions. ISO/IEC/IEEE 15288:2015.

Additional References

Bell Telephone Laboratories. 1982. Engineering and Operations in the Bell System. Murray Hill, NJ, USA: Bell Telephone Laboratories.

Fortescue, P.W., J. Stark, and G. Swinerd. 2003. Spacecraft Systems Engineering. New York, NY, USA: J. Wiley.

Madni, A. M. and Sievers, M. 2018. Model‐based systems engineering: Motivation, current status, and research opportunities, Systems Engineering. 2018; 21: 172– 190. https://doi.org/10.1002/sys.21438

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