Difference between revisions of "Systems Engineering and Management"

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This part of the SEBoK focuses on the general knowledge of ''how'' systems are engineered.  It builds on [[Systems|Part 2]], which discusses ''what'' systems are.
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Part 3 provides a basis for the engineering of [[Product System (glossary)|product systems (glossary)]], the engineering of [[Service System (glossary)|service systems (glossary)]], the engineering of an [[Enterprise System (glossary)|enterprise system (glossary)]] as well as the engineering of [[System of Systems (SoS) (glossary)|systems of systems (glossary)]] as described in [[Applications of Systems Engineering|Part 4]].  Part 3 defines [[Systems Engineering (glossary)|systems engineering (glossary)]] and also provides an overview of the common [[Life Cycle Models|life cycle models]] uses in systems engineering.  The commonly-used systems engineering processes are also described, with references to common methods, tools, and techniques used within these processes.  Finally, the [[Systems Engineering Management|management]] aspects of systems engineering are discussed.
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'''''Lead Authors:''''' Jeffrey Carter and Caitlyn Singam
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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.
  
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It is important to note that Part 3 provides an overview of how systems are engineered in a generic sense.  [[Applications of Systems Engineering|Part 4]] provides specific information on how the principles discussed in Part 3 are applied differently depending on the type of system (product, service, or enterprise) being engineered.  [[Related Disciplines|Part 6]] then provides references to other/related disciplines which may be utilized in the systems engineering process, but which do not fall under the umbrella of systems engineering.
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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]''' for more detail see [[Structure of the SEBoK]]]]
  
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==Knowledge Areas in Part 3==
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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).
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Each part of the SEBoK is divided into knowledge areas:  groupings of information with a related theme.  Part 3 contains the following knowledge areas:
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*[[Life Cycle Models]]
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* DE conducts Agile system-software development based on industry open standards by employing MBSE.
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*[[Concept Definition]]
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* MBSE develops and integrates SysML design models with simulation capabilities for cross-domain collaboration across the lifecycle.
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*[[System Definition]]
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* SysML is an industry standard graphical notation with formal semantics (meaning) to define system requirements, constraints, allocations, behavior and structure characteristics
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==SE&M Knowledge Areas==
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The SE&M articles are organized into the following Knowledge Areas [KAs].
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*[[Systems Engineering STEM Overview]]
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*[[Model-Based Systems Engineering (MBSE)]]
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*[[Systems Lifecycle Approaches]]
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*[[System Lifecycle Models]]
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*[[Systems Engineering Management]]
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*[[Business and Mission Analysis]]
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*[[Stakeholder Needs Definition]]
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*[[System Architecture Definition]]
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*[[Detailed Design Definition]]
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*[[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]]
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*[[System Transition]]
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*[[System Validation]]
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*[[System Operation]]
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*[[System Maintenance]]
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*System Specialty Engineering
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*[[Logistics]]
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*[[Service Life Management]]
 
*[[Systems Engineering Standards]]
 
*[[Systems Engineering Standards]]
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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:
  
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==Systems Engineering Definition==
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*How engineering conducts system development
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There is not a community consensus on the definition of "systems engineering"; the term has many different connotations in many different domains.  One of the more commonly recognized definitions in the field is likely that of the International Council on Systems Engineering (INCOSE):
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*The purpose of each engineering artifact generated
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*How systems are integrated, and requirements verified
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*How new product designs are transitioned to production operations
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*How the resulting system is employed and sustained to satisfy customer needs
  
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<blockquote>''An interdisciplinary approach and means to enable the realization of successful systems. It focuses on defining customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem:*Operations
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==Systems Engineering & Management Overview==
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*Performance
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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.  
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*Test
 
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*Manufacturing
 
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*Cost & Schedule
 
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*Training & Support
 
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*Disposal
 
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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. Systems engineering considers both the business and the technical needs of all customers with the goal of providing a quality product that meets the user needs. (INCOSE 2010, 1)''</blockquote>
 
  
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This definition is frequently referenced throughout the SEBoK.  Systems engineering is the application of a combination of traditional engineering and holistic systems thinking, working ''with'' domain engineering, human sciences, management and commercial disciplines, to support the engineering of one or more systems of interest ([[Acronyms|SoI]]).  It may also be an interdisciplinary approach governing the total technical and managerial effort required to transform a set of customer needs, expectations, and constraints into a solution and to support that solution throughout its life.  Each of these perspectives is valuable for gaining a holistic view of systems engineering.
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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.  
  
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==Generic Systems Engineering Paradigm==
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The recent adoption of DE practices [Roper, 2020] broadens the MBSE transformation based on the following principals:
  
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In order to establish a basis for the Knowledge Areas of Part 3 and Part 4, the paradigm appearing in Figure 1 identifies the general goal of any Systems Engineering effort. That is the understanding of stakeholder value, the selection of a specific need; the transformation of that need into a system product or service that provides for the need; and the use of that product or service to provide the stakeholder value. This paradigm has been developed according to the principles of a systems approach described in the [[Applying the Systems Approach]] topic in Part 2.
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* Agile System and Software Development to prioritize capability development and respond to evolving threats, environments, and challenges.
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* 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.
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* 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.
  
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[[File:062211_BL_Paradigm.png|thumb|center|700px|Figure 1. Generic Systems Engineering Paradigm (Figure Developed for BKCASE).]]
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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.
  
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On the left hand side of the figure observe that there are three Systems of Interest identified in the form of a [[System Breakdown Structure (glossary)]]. SOI 1 is decomposed into its elements which in this case are systems as well (SOI 2 and SOI 3).  These two systems are composed of [[Element (glossary)|System Elements (glossary)]] which are not further refined.
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* 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.
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* 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
  
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On the right hand side of the figure observe that each of the Systems of Interest has a corresponding [[Life Cycle Model (glossary)]] composed of stages that are populated with processes that are used to define the work to be performed.  Note that some of the requirements defined to meet the need are distributed in the early stages of the life cycle for SOI 1 to the life cycles of SOI 2, respectively SOI 3. This decomposition of the system illustrates the fundamental concept of [[Recursion (glossary)]] as defined in the ISO/IEC 15288 standard.  That is the standard is reapplied for each of the systems of interest.
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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.  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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Note that the system elements are integrated in SOI 2, respectively SOI 3 thus realizing a product or service that is delivered to the life cycle of SOI 1 for integration in realizing the product or service that meets the stated need.
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[[File:15288_Standard_Outline_-_Model.png|thumb|center|750px|'''Figure 2.''' ISO/IEC/IEEE-15288:2015 Standard Outline (SEBoK Original)]]
  
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Some examples that relate to this system need could be an embedded system (SOI 1) composed a hardware system (SOI 2) and a software system (SOI 3), a sub-assembly composed of a chasis and a motor, a human resource system composed of a recruitment system and a capability management system.  
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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.
  
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In performing the process work in stages, most often [[Iteration (glossary)]] between stages if required.  For example, in successive refinement of the definition of the system or in providing an update (upgrade or problem solution) of a realized and even delivered product or service.
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[[File:Model-Based_System_Design_Process_Part3.png|thumb|center|600px|''Figure 3: Model-Based System Engineering Process.'' (SEBoK Original)]]
  
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The work performed in the processes and stages can be performed in a [[Concurrent (glossary)]] manner within the life cycle of any of the systems of interest and concurrent amongst the multiple life cycles.
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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).  
  
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This paradigm provides a fundamental framework for understanding generic systems engineering in Part 3 as well as for the application of systems engineering in the provisioning of the various types of systems described in Part 4.
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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.
  
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==Applying Iteration and Recursion to Systems Engineering in the Life Cycle==
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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. 
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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:
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#Develop, integrate, and employ digital system design models for cross-domain collaboration throughout the product lifecycle [i.e., engineering development, production, and sustainment].
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#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.
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#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.
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#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.
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#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.
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#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.
  
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The concept of iteration is applied also for processes.  Figure 2 below gives an example of iteration of three processes as defined in ISO-IEC 15288. The processes in this example are further discussed in the [[System Definition]] knowledge area.  
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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.
  
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[[File:Wiki_CR_Placeholder.png|thumb|center|400px|Figure 2. Example of iterations of processes related to system definition (ISO/IEC 2003,p. 21, Figure 12) Source available at http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=33898]]
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[[File:The_System_Phenomenon.png|thumb|center|750px|''Figure 4: The System Phenomenon – Hamilton’s Principle.'' (SEBoK Original)]]
  
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The complete definition of a [[System of Interest (SoI) (glossary)|System of Interest (SoI)]] is generally achieved considering decomposition layers of systems and of [[System Element (glossary)|System Elements]]. Figure 3 presents a fundamental schema of a system breakdown structure.
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==References==
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===Citations===
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OMG Systems Modeling Language [SysML®] Standard – v1.6, November 2019
  
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[[File:Wiki_CR_Placeholder.png|thumb|center|400px|Figure 3. Hierarchical decomposition of a system-of-interest (ISO/IEC 2008) Source available at http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=43564]]
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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.
  
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In each decomposition layer and for each system, the [[System Definition]] processes are applied recursively because the notion of system is recursive; the notions of System-of-Interest (SOI), system, system element are based on the same concepts – see [[Systems|Part 2]]. Figure 4 shows an example of recursion of three processes as defined in ISO/IEC 15288.
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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. Accessed May 25, 2023. Available at https://software.af.mil/wp-content/uploads/2020/10/There-Is-No-Spoon-Digital-Acquisition-7-Oct-2020-digital-version.pdf.
  
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[[File:Wiki_CR_Placeholder.png|thumb|center|400px|Figure 4. Recursion of processes on layers (ISO/IEC 2003, p.20, Figure 11) Source available at http://www.iso.org/iso/iso_catalogue/catalogue_tc/catalogue_detail.htm?csnumber=33898]]
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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.
  
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==Value of Ontology Concepts for Systems Engineering==
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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.
  
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Ontology is the set of entities presupposed by a theory (Collins English Dictionary). SE, and in particular system development, can be considered a theory because it is based on concepts related to mathematics and proven practices. A SE ontology can be defined considering the following path.
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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.
  
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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. 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 concepts. The implementation of the activities and tasks is supported by methods and modeling techniques, composed themselves of elementary tasks; they describe the “how to do”. The activities and tasks of SE are transformations of generic data using the predefined concepts. Those generic data are called Entities, Classes, or Types. Each ''entity'' is characterized by specific ''attributes'', and each attribute can get different values. 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) 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 in order to make the relationship valid. Additional information may be found in (Oliver, Kelliher, and Keegan 1997).
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===Primary References===
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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.
  
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The set of SE entities and their relationships form an ontology also often called Engineering Meta-model. Such an approach is used and defined in the standard (ISO 2007). The benefits of using an ontology are many. The ontology allows or forces:
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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.
  
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*the use of a standardized vocabulary, using the right names and avoiding using synonyms in the processes, methods, and modeling techniques;
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===Additional References===
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*reconciliation of the vocabulary used in different modeling techniques and methods;
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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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*the automatic appearance of traceability of requirements when implemented in databases, SE tools or workbenches, and also the quick identification of the impacts of modifications in the engineering data set;
 
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*checks of the consistency and completeness of engineering data, etc.
 
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==Mapping of Topics to ISO/IEC 15288, System Life Cycle Processes==
 
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Note: To facilitate readers' understanding of the standard ISO/IEC. 2008, Figure 5 below shows the relative position of the Technical Knowledge Areas (KA) of this SEBoK with respect to the processes as stated in the standard.
 
  
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[[File:SEBoKv05_KA-SystDef_Mapping_of_technical_topics_of_Know_080711.png|thumb|center|600px|center|Figure 5. Mapping of technical topics of Knowledge Areas of SEBoK with ISO/IEC 15288 Technical Processes (Figure Developed for BKCASE)]] FIGURE TO BE UPDATED
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Wasson, C. 2006. System Analysis, Design, and Development – Concepts, Principles, and Practices.’’ Hoboken, NJ: John Wiley & Sons.
  
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==References==
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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>
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===Works Cited===
 
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INCOSE. 2011. ''Systems Engineering Handbook'', version 3.2.1. San Diego, CA, USA: International Council on Systems Engineering (INCOSE).
 
  
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ISO/IEC. 2003. ''Systems Engineering — A Guide for The Application of ISO/IEC 15288 System Life Cycle Processes.'' Geneva, Switzerland: International Organization for Standardization (ISO)/International Electronical Commission (IEC), ISO/IEC 19760:2003 (E).
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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. Available at http://www.omgsysml.org/MBSE_Methodology_Survey_RevB.pdf.  
  
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ISO/IEC 2008. ''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 15288:2008.
 
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ISO. 2007. ''Systems Engineering and Design.'' Geneva, Switzerland: International Organization for Standardization (ISO). ISO 10303-AP233.
 
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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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===Primary References===
 
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No primary references have been identified for version 0.75.  Please provide any recommendations on additional references in your review.
 
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===Additional References===
 
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No additional references have been identified for version 0.75.  Please provide any recommendations on additional references in your review.
 
 
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<center>[[Dynamically Changing Systems|<- Previous Article]] | [[SEBoK Table of Contents|Parent Article]] | [[Life Cycle Models|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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[[Category: Part 3]][[Category:Part]]
 
  
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<center>'''SEBoK v. 2.9, released 20 November 2023'''</center>
  
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{{5comments}}
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[[Category: Part 3]]
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[[Category:Part]]

Latest revision as of 23:42, 18 November 2023

Lead Authors: Jeffrey Carter and Caitlyn Singam

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. Accessed May 25, 2023. Available at 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. Accessed April 13, 2015. Available at http://www.omgsysml.org/MBSE_Methodology_Survey_RevB.pdf.

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