Difference between revisions of "Systems Engineering and Management"

From SEBoK
Jump to navigation Jump to search
(added navigation image)
Tag: visualeditor
m (Text replacement - "<center>'''SEBoK v. 2.6, released 20 May 2022'''</center>" to "<center>'''SEBoK v. 2.7, released 31 October 2022'''</center>")
(38 intermediate revisions by 5 users not shown)
Line 1: Line 1:
−
Part 3 of the Guide to the SE Body of Knowledge (SEBoK) focuses on the general knowledge of ''how'' systems are engineered.
+
----
−
[[File:SEBoK Navigation Management.PNG|centre|thumb|743x743px|'''Figure 1 SEBoK Part 3 in context (SEBoK Original).''' For more detail see [[Structure of the SEBoK]]]]
+
'''''Lead Authors:''''' Jeffrey Carter and Caitlyn Singham
 +
----
 +
Systems Engineering and Management (SE&M) articles provide system lifecycle best practices for defining 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.
  
−
This part builds upon Part 2: [[Foundations of Systems Engineering]], which discusses the need for a [[Systems Approach (glossary)]] applied to one or more [[Engineered System (glossary)]] contexts as a part of managed interventions into [[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 none technical aspects of SE and discusses [[Systems Engineering Management]] activities. Part 3 also discusses the most commonly-used SE technical processes; provides additional references to the common methods, tools, and techniques used in these processes
+
[[File:SEBoK_Context_Diagram_Inner_P3_Ifezue_Obiako.png|centre|thumb|600x600px|'''Figure 1: SEBoK Part 3 SE&M Context [SEBoK Original]''' for more detail see [[Structure of the SEBoK]]]]
  
−
The commonly recognized definition of [[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 [[System-of-Interest (glossary)|System-of-Interest]].  The definition states that systems engineering “'''integrates all the disciplines and speciality 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.
+
The SE&M materials are currently being updated to provide system design practitioners with Digital Engineering [DE] and Model-Based Systems Engineering [MBSE] implementation guidance employing the Systems Modeling Language (SysML).
  
−
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  [[Product System (glossary)|product systems]], [[Service System (glossary)|service systems]], [[Enterprise System (glossary)|enterprise systems]], and [[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.
+
* DE conducts Agile system-software development based on industry open standards by employing MBSE.
 +
* MBSE develops and integrates SysML design models with simulation capabilities for cross-domain collaboration across the lifecycle.
 +
* SysML is an industry standard graphical notation with formal semantics (meaning) to define system requirements, constraints, allocations, behavior and structure characteristics
  
−
Systems engineering is transitioning to a model-based approach, [[Model-Based Systems Engineering (MBSE) (glossary)|model-based systems engineering (MBSE)]], like many other engineering disciplines.  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, can be used to generate views of the system relevant to particular stakeholders, and be 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.
+
==SE&M Knowledge Areas==
−
 
+
The SE&M articles are organized into the following Knowledge Areas [KAs].
−
==Knowledge Areas in Part 3==
+
*[[Systems Engineering STEM Overview]]
−
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:
+
*[[Model-Based Systems Engineering (MBSE)]]
−
*[[Introduction to Life Cycle Processes]]
+
*[[Systems Lifecycle Approaches]]
−
*[[Life Cycle Models]]
+
*[[System Lifecycle Models]]
−
*[[Concept Definition]]
+
*[[Systems Engineering Management]]
−
*[[System Definition]]
+
*[[Business and Mission Analysis]]
 +
*[[Stakeholder Needs Definition]]
 +
*[[System Architecture Definition]]
 +
*[[Detailed Design Definition]]
 +
*[[System Analysis]]
 
*[[System Realization]]
 
*[[System Realization]]
−
*[[System Deployment and Use]]
+
*[[System Implementation]]
−
*[[Systems Engineering Management]]
+
*[[System Integration]]
−
*[[Product and Service Life Management]]
+
*[[System Verification]]
 +
*[[System Transition]]
 +
*[[System Validation]]
 +
*[[System Operation]]
 +
*[[System Maintenance]]
 +
*System Specialty Engineering
 +
*[[Logistics]]
 +
*[[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.
+
The SE&M articles provide exemplar processes and practices which are tailorable for an engineering organization to satisfy strategic business goals and individual project objectives including:
  
−
==Value of Ontology Concepts for Systems Engineering==
+
*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 operations
 +
*How the resulting system is employed and sustained to satisfy customer needs
  
−
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.
+
==Systems Engineering & Management Overview==
 +
The role of Systems Engineering [SE] is to define system requirements, constraints, allocations, behavior and structure characteristics to satisfy customer needs.  The system is defined in terms of hierarchical structural elements and their behavior interactions.  The interactions include the exchange of data, energy, force, or mass which modifies the state of the cooperating elements resulting in emergent, discrete, or continuous behaviors.  The behaviors are at sequential levels of aggregation [bottoms-up] or decomposition [top-down] to satisfy requirements, constraints, and allocations. SE collaborates within an integrated product team with electrical, mechanical, software, and specialty engineering to define the subsystem and component detailed design implementations to develop a holistic technical solution.  
  
−
SE provides engineers with an approach based on a set of concepts (i.e., stakeholder, requirement, function, scenario, system element, etc.) and generic processes. 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 [[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. Additional information on this subject may be found in ''Engineering Complex Systems with Models and Objects'' (Oliver, Kelliher, and Keegan 1997).
+
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 including textual system requirement specifications, analysis reports, system design descriptions, and interface specifications. Traditional SE is often referred to as a document-centric approach. System design practitioners have cultivated model-based techniques since the late 1990s to facilitate communications, manage design complexity, improve product quality, enhance knowledge capture and reuse. MBSE is defined as the formalized application of graphical modeling with precise semantic definitions for operational analysis, requirements definition, system design development and verification activities beginning in the conceptual phase and continuing throughout later lifecycle phases [INCOSE, 2015].  MBSE conducts system development employing an engineering ecosystem consisting of commercially available tools to create a system design model with SysML compliant semantics that represents the system requirements, constraints, allocations, behavior and structure characteristics.  The system design model provides an Authoritative Source of Truth [ASoT] for the project technical baseline with integrated end-to-end simulation capabilities to evaluate system key performance parameters in digital computing environments. MBSE includes the creation, development, and utilization of digital design models with domain product-specific analyses including aerospace, automobile, consumer, defense, and software.  
  
−
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 standard (ISO 2007). There are many benefits to using an ontology. The ontology allows or forces:
+
The recent adoption of DE practices [Roper, 2020] broadens the MBSE transformation based on the following principals:  
  
−
*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
+
* Agile System and Software Development to prioritize capability development and respond to evolving threats, environments, and challenges.
−
*the reconciliation of the vocabulary used in different modeling techniques and methods
+
* Modular Open System Approach [MOSA] to develop product-lines based on industry standards that can adapt to evolving customer needs with new, modified, and existing [reuse] capabilities.
−
*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
+
* Digital Engineering [DE] to develop, integrate, and employ MBSE design models with simulation capabilities to realistically emulate systems in digital computing environments for cross-domain collaboration across the system design development, verification, production, and sustainment lifecycle.
−
*the continual observation of the consistency and completeness of engineering data; etc.
 
  
−
Throughout Part 3, there are discussions of the ontological elements specifically relevant to a given topic.
+
The system design model includes functional, logical, and physical system design representations with capabilities that are integrated with electrical, mechanical, software, and specialty design disciplines for system functional and performance assessments. Design model scripts can export functional (SSS, B1, B2, B5) specifications, interface (IRS, ICD, IDD) specifications, design & requirements traceability reports, and design descriptions (SADD, SSDD, SWDD).  The integrated simulations provide a digital twin with digital threads of system key performance parameters to evaluate design alternatives in digital computing environments to discover and resolve design defects before the expense of producing physical prototypes.
  
−
==Mapping of Topics to ISO/IEC 15288, System Life Cycle Processes==
+
* Digital threads are analytical frameworks providing end-to-end system simulations to evaluate logical operations and key performance parameters in digital computing environments by exchanging information between different engineering modeling tools across the lifecycle.  Evaluation of the digital thread simulations ensure that requirements, interactions, and dependencies are commonly understood across engineering disciplines.  Design changes are automatically reflected in all design model usages to assess compliance, with any issue(s) flagged for corrective action.
 +
* 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 define 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
  
−
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.  
+
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.
  
−
As shown, all of the major processes described in ISO/IEC/IEE 15288:2015 are discussed within the SEBoK.
+
[[File:15288_Standard_Outline_-_Model.png|thumb|center|750px|'''Figure 2.''' ISO/IEC/IEEE-15288:2015 Standard Outline (SEBoK Original)]]
−
[[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)]]
 
  
−
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.
+
Figure 3 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.
  
−
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.
+
[[File:Model-Based_System_Design_Process_Part3.png|thumb|center|600px|''Figure 3: Model-Based System Engineering Process.'' (SEBoK Original)]]
  
−
Any future evolution of Life Cycle Process knowledge in the SEBoK will be complementary to these standard descriptions of the generic SE process set.
+
Product domain-area system design knowledge and expertise are still mandatory with the 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).  
  
−
==References==
+
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.
−
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. Accessed April 13, 2015 at http://www.omgsysml.org/MBSE_Methodology_Survey_RevB.pdf
+
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.
  
−
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
+
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. 
  
−
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.
+
[[File:The_System_Phenomenon.png|thumb|center|750px|''Figure 4: The System Phenomenon – Hamilton’s Principle.'' (SEBoK Original)]]
  
−
ISO. 2007. ''Systems Engineering and Design.'' Geneva, Switzerland: International Organization for Standardization (ISO). ISO 10303-AP233.
+
==References==
 +
===Citations===
 +
OMG Systems Modeling Language [SysML®] Standard – v1.6, November 2019
  
−
Oliver, D., T. Kelliher, and J. Keegan. 1997. ''Engineering Complex Systems with Models and Objects''. New York, NY, USA: McGraw-Hill.
+
INCOSE. 2015. ''[[INCOSE Systems Engineering Handbook|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.
 +
 
 +
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
 +
 
 +
ISO/IEC/IEEE 15288:2015. ''Systems and Software Engineering -- System Life Cycle Processes''. Geneva, Switzerland: International Organization for Standardization / International Electrotechnical Commissions / Institute for Electrical and Electronics Engineers. ISO/IEC/IEEE 15288:2015.
 +
 
 +
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.
  
 
===Primary References===
 
===Primary References===
−
INCOSE. 2015. ''[[INCOSE Systems Engineering Handbook|Systems Engineering Handbook]] - ''A Guide for System Life Cycle Processes and Activities<nowiki>''</nowiki>, version 4.0. Hoboken, NJ, USA: John Wiley and Sons, Inc, ISBN: 978-1-118-99940-0
+
INCOSE. 2015. ''[[INCOSE Systems Engineering Handbook|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. [[ISO/IEC/IEEE 15288| Systems and Software Engineering -- System Life Cycle Processes]]. Geneva, Switzerland: International Organisation for Standardisation / International Electrotechnical Commissions. ISO/IEC/IEEE 15288:2015.
+
ISO/IEC/IEEE. 2015. [[ISO/IEC/IEEE 15288| Systems and Software Engineering -- System Life Cycle Processes]]. Geneva, Switzerland: International Organization for Standardization / International Electrotechnical Commissions. ISO/IEC/IEEE 15288:2015.
  
 
===Additional References===
 
===Additional References===
−
Bell Telephone Laboratories. 1982. ''Engineering and Operations in the Bell System''. Murray Hill, NJ: Bell Telephone Laboratories.
+
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.
 +
 
 +
Madni, A. M. and Sievers, M. 2018. ''Model‐based systems engineering: Motivation, current status, and research opportunities'', Systems Engineering. 2018; 21: 172– 190. <nowiki>https://doi.org/10.1002/sys.21438</nowiki>
  
−
Fortescue, P.W., J. Stark, and G. Swinerd. 2003. ''Spacecraft Systems Engineering''. New York, NY, USA: J. Wiley.
+
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.
  
 
----
 
----
−
<center>[[Applying the Systems Approach|< Previous Article]] | [[SEBoK Table of Contents|Parent Article]] | [[Introduction to Life Cycle Processes|Next Article >]]</center>
+
<center>[[Applying the Systems Approach|< Previous Article]] | [[SEBoK Table of Contents|Parent Article]] | [[Systems Engineering STEM Overview|Next Article >]]</center>
  
−
{{DISQUS}}
+
<center>'''SEBoK v. 2.7, released 31 October 2022'''</center>
  
−
[[Category: Part 3]][[Category:Part]]
+
[[Category: Part 3]]
 +
[[Category:Part]]

Revision as of 08:34, 10 October 2022

Lead Authors: Jeffrey Carter and Caitlyn Singham

Systems Engineering and Management (SE&M) articles provide system lifecycle best practices for defining 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.

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

The SE&M materials are currently being updated to provide system design practitioners with Digital Engineering [DE] and Model-Based Systems Engineering [MBSE] implementation guidance employing the Systems Modeling Language (SysML).

  • DE conducts Agile system-software development based on industry open standards by employing MBSE.
  • MBSE develops and integrates SysML design models with simulation capabilities for cross-domain collaboration across the lifecycle.
  • SysML is an industry standard graphical notation with formal semantics (meaning) to define system requirements, constraints, allocations, behavior and structure characteristics

SE&M Knowledge Areas

The SE&M articles are organized into the following Knowledge Areas [KAs].

The SE&M articles provide exemplar processes and practices which are tailorable 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 operations
  • How the resulting system is employed and sustained to satisfy customer needs

Systems Engineering & Management Overview

The role of Systems Engineering [SE] is to define system requirements, constraints, allocations, behavior and structure characteristics to satisfy customer needs. The system is defined in terms of hierarchical structural elements and their behavior interactions. The interactions include the exchange of data, energy, force, or mass which modifies the state of the cooperating elements resulting in emergent, discrete, or continuous behaviors. The behaviors are at sequential levels of aggregation [bottoms-up] or decomposition [top-down] to satisfy requirements, constraints, and allocations. SE collaborates within an integrated product team with electrical, mechanical, software, and specialty engineering to define the subsystem and component detailed design implementations to develop a holistic technical solution.

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 including textual system requirement specifications, analysis reports, system design descriptions, and interface specifications. Traditional SE is often referred to as a document-centric approach. System design practitioners have cultivated model-based techniques since the late 1990s to facilitate communications, manage design complexity, improve product quality, enhance knowledge capture and reuse. MBSE is defined as the formalized application of graphical modeling with precise semantic definitions for operational analysis, requirements definition, system design development and verification activities beginning in the conceptual phase and continuing throughout later lifecycle phases [INCOSE, 2015]. MBSE conducts system development employing an engineering ecosystem consisting of commercially available tools to create a system design model with SysML compliant semantics that represents the system requirements, constraints, allocations, behavior and structure characteristics. The system design model provides an Authoritative Source of Truth [ASoT] for the project technical baseline with integrated end-to-end simulation capabilities to evaluate system key performance parameters in digital computing environments. MBSE includes the creation, development, and utilization of digital design models with domain product-specific analyses including aerospace, automobile, consumer, defense, and software.

The recent adoption of DE practices [Roper, 2020] broadens the MBSE transformation based on the following principals:

  • Agile System and Software Development to prioritize capability development and respond to evolving threats, environments, and challenges.
  • Modular Open System Approach [MOSA] to develop product-lines based on industry standards that can adapt to evolving customer needs with new, modified, and existing [reuse] capabilities.
  • Digital Engineering [DE] to develop, integrate, and employ MBSE design models with simulation capabilities to realistically emulate systems in digital computing environments for cross-domain collaboration across the system design development, verification, production, and sustainment lifecycle.

The system design model includes functional, logical, and physical system design representations with capabilities that are integrated with electrical, mechanical, software, and specialty design disciplines for system functional and performance assessments. Design model scripts can export functional (SSS, B1, B2, B5) specifications, interface (IRS, ICD, IDD) specifications, design & requirements traceability reports, and design descriptions (SADD, SSDD, SWDD). The integrated simulations provide a digital twin with digital threads of system key performance parameters to evaluate design alternatives in digital 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 simulations to evaluate logical operations and key performance parameters in digital computing environments by exchanging information between different engineering modeling tools across the lifecycle. Evaluation of the digital thread simulations ensure that requirements, interactions, and dependencies are commonly understood across engineering disciplines. Design changes are automatically reflected in all design model usages to assess compliance, with any issue(s) flagged for corrective action.
  • 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 define 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

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

Figure 3 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 3: Model-Based System Engineering Process. (SEBoK Original)

Product domain-area system design knowledge and expertise are still mandatory with the 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

OMG Systems Modeling Language [SysML®] Standard – v1.6, November 2019

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.

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

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

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.

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 Organization for Standardization / International Electrotechnical Commissions. ISO/IEC/IEEE 15288:2015.

Additional References

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.

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

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.

< Previous Article | Parent Article | Next Article >
SEBoK v. 2.7, released 31 October 2022
Retrieved from "https://sandbox.sebokwiki.org/index.php?title=Systems_Engineering_and_Management&oldid=66707"