model based enterprises mbe whitepaper us

EXECUTIVE SUMMARY Business Leaders in the Aerospace and Defense (A&D) industry are facing a defining business execution challenge.1,2 With the increase of market opportunities and increasingly demanding requirements, in response to operational rate increases and as a means to make better use of existing resources, three major factors have been identified:

• Significant growth in program complexity

• Missed program development targets (in cost, schedule or capability)

• The push of sub-assembly operations (design and manufacturing) into the supply chain

AEROSPACE & DEFENSEA HOLISTIC APPROACH FOR REALIZING

MODEL BASED ENTERPRISES (MBE)

AUTHORS: Brian ChristensenGarrett Thurston

A Holistic Approach For Realizing Model Based Enterprises (MBE) 2

Business execution in the A&D market is intimately tied to program execution—either externally contracted or internally authorized efforts—in the development of products and systems (e.g., aircraft or weapons systems). The objective of a Model Based Enterprise is to elevate business execution throughout the enterprise, which by necessity includes program and project management, configuration and change management and the implementation of system engineering and detailed design, manufacturing, and support processes.

Leaders accountable for execution need to be able to manage information efficiently—including the tasks to collect, interpret, control, find, share, and maintain information.3 Successful, decision-makers (executives, program managers, architects, etc.) need to constantly track the performance of their enterprise and how its products fare in the commercial and government marketplaces. Effective product development feeds into this execution awareness and there are well-documented methods4 enabled by tools and processes to achieve such outcomes—in process models, functional decompositions, allocated requirements specifications and numerous other model artifacts.

Varying by domain, descriptive and computational models capture aspects of a system and its intended deployed mission, usage, and operating environments, which enable improved confidence in the completeness and correctness of the product specification, the validity of which is supported by a number of model-based and traditional methods including architecture, simulations, and analysis, trace, test, engineering reviews, and similarity.5 Positive business execution outcomes are the result of the use of models and improved methods and infrastructure reducing volatility and churn associated with text or documentation-only approaches.

A Model Based Enterprise (MBE) approach provides the opportunity for stepwise improvements in program execution, performance and integrity. In order to reap the benefits of an MBE across the enterprise value chains, it is critical to efficiently align a company’s extended enterprise—its people, suppliers, methods, processes, and technology.

MBE is an approach, for the people and disciplines of an extended organization, using enterprise infrastructure and applications to leverage lifecycle-managed, connected, descriptive and computational models throughout the program lifecycle to achieve organizational business objectives for process efficiency for user and organizational productivity. MBE includes PLM-grade program governance, guided, facilitated and enforced business processes and rich systems engineering enforced development processes to deliver validated, execution-enabled business models for architecture and detailed design definition, process control and performance evaluation. An MBE is used as the basis for creating the program plan and integrated master schedule. These execution models are built upon a supporting open, secure, configuration-enabled, standards-based platform. Product, environment and execution models evolve in their maturity, fidelity, and validity throughout the program. Product and environment models that serve a particular utility at one stage in the lifecycle will be transformed and translated into other models or views in subsequent stages in the program life cycle.

MBE is a holistic approach that assists stakeholders across the entire enterprise in exploring and qualifying better options. By taking into account the rich connectedness of model information, decision-makers have a powerful instrument to explore options and make actionable real-time decisions. In this paper we explore the continuing need for improving organizational execution including program improvement in the context of the historical initiatives, which leads to an

1 Lisa Brownsword, Cecilia Albert, David Carney, Patrick Place, “Results in Relating Quality Attributes to Acquisition Strategies” SEI Technical Note: CMU/SEI-2013-TN-026 February 2014.

2 Lisa Brownsword, Cecilia Albert, David Carney, Patrick Place, “A Method for Aligning Acquisition Strategies and Software Architectures” SEI Technical Note: CMU/SEI-2014-TN-019 October 2014.

3 Information is elicited from data, in “Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business” by Malcom Frank 2014 there are three types of data individuals, collectors, explorers, and sense-makers. These types of individuals convert data, to information, to knowledge and intelligence.

4 Department of Defense Systems Engineering Fundamentals, Supplementary Text Prepared by the Defense Acquisition University Press, Fort Belvoir, VA 22060-5565, January 2001.

5 SEI Presentation: Making DARPA META Goals Come True, “How do we revolutionize Verification and Validation for Complex Systems?”, Dr. Kirstie L. Bellman Computers and software Division (AISIC); The Aerospace Corporation, June 17, 2010, S5 2010, WP AFB


MBE. In addition, we identify the key building blocks of an MBE and the advantages of applying a holistic approach to program execution and the many associated development efforts.

MOTIVATING FACTORS FOR CHANGELessons learned from completed and ongoing programs uncover three important factors driving the Aerospace and Defense industry to improve program performance.

First, Aerospace and Defense programs are frequently challenged with increased development times and rising costs. In contrast, faced with similar though not identical constraints, the Automotive and Integrated Circuit industries have achieved significant program time and cost savings. Bellman suggests, “A major cause of these phenomena is the industry’s failure to update a 1960s-vintage systems engineering, integration and test process.”

1960 1990 2010 2030TODAY

METAGOAL

INTEGRATEDCIRCUITS

AUTOMOBILES

AEROSPACESYSTEMS

HISTORICAL COST GROWTH

AEROSPACE SYSTEMS (1960-PRESENT) 8-12% / YR

*

AUTOMOBILES (1960-PRESENT) 4% / YR

INTEGRATED CIRCUITS (1970-PRESENT) ~0% / YR

* NOT ADJUSTED FOR INFLATION

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COMPLEXITY OVER TIME (PART COUNT + SOURCE LINES OF CODE)

In the past, manual, document-based development methods that relied on decomposing a problem into independent disciplines, generally delivered systems of moderate complexity. A manual approach not only includes decomposing the problem into increasingly smaller and tractable problems, but at the same time fine-grained problems are disconnected because they are assigned to separate expert domains to be addressed. Once complete, the system elements would be brought together with the expectation that the desired outcome would be achieved. As systems grew more complex—many things, talking to many other things, in many different ways—the frailty of this approach became obvious as product and program failures became increasingly prevalent. Such siloed approaches not only suffered the failure of disconnected-ness but also the Tragedy of the Commons6 where organizational competition for resources led to inefficiencies and execution failures. By both decomposing the problem and disconnecting it (using best available document-centric technologies) the approach did not scale to the needs of modern complex systems. Historically, despite this vulnerability, aerospace and defense companies had some success (even on relatively complicated systems) increasing recognition of the challenge. Evidence of this frailty lurked in the shadows producing occasional spectacular failures with more frequent symptomatic evidence, in terms of costs, schedule, and functionality failures as system complexity has increased.7 The evidence suggests that program success is more likely when the challenges of contextual and system complexities are addressed.

6 Hardin, Garrett, “The Tragedy of the Commons”, Science Vol 162, 13 December 1968 pp 1243-1248.

7 Sheard, Sarah A., “Principles of Complex Systems for Systemes Engineering,” Published in Proceedings of the Seventeenth International Symposium of the International Council on Systems Engineering, San Diego, CA, June 23-28. Copyright © Third Millennium Systems LLC.

Figure 1: Contrast Automotive and Electronics Industries vs. the Aerospace Industry in tackling program complexity.


Second, program development plans are often not achieved. Program plans are frequently derailed due to budget and schedule overruns and failure to achieve key technical performance metrics. According to a 2015 U.S. Government Accountability Office report on Pentagon major weapon systems, 47 of the 78 programs within the portfolio experienced cost increases over the past year. The average delay in delivering initial capabilities (from the first full estimate of cost and schedule) increased from 1.4 months to 30.3 months.8

Dr. Bob Neches notes in an Engineered Resilient Systems review that contributing factors include:

• Rapid necking down of alternatives

• Decisions made without information

• Sequential and slow process where information is lost at every step

• Ad hoc requirements refinements.

Neches states that these factors contribute to 50 years of process reforms that have failed to control delivery time, delivered cost and program execution performance.9

Increased pressured to speed the pace of production and use existing resources more effectively resulted in companies striving to increase rate by driving sub-assembly operations into the supply chain. Aerospace business models are shifting from being OEM dominated supply chains to risk sharing supply chains. Risk sharing supply chains are decentralized across the buyers and suppliers. They jointly share increased pre-integration responsibility and models across the full development and support lifecycle. Examples of this value chain evolution include the Airbus 380 and Boeing 787 aircraft. OEM’s and their suppliers jointly share increased pre-integration responsibility and models across the full development, certification, manufacturing, and support lifecycle.10

8 United States Government Accountability Office, DEFENSE ACQUISITIONS Assessments of Selected Weapon Programs, March 2015, http://www.gao.gov/assets/670/668986.pdf

9 ERS Overview and status 20 December 2011 public release version, Dr. Robert Neches, Director, Advanced Engineering Initiatives, ODASD SE, 20 November 2011

10 Herbert A. Simon, “The Architecture of Complexity” Proceedings of the American Philosophical Society, Vol. 106, No. 6. (Dec. 12, 1962), pp. 467-482. (See Figure Reference

Figure 2: Current assessment of DOD Programs

2014 Programs ‘by the numbers’

• 78 active acquisition defense programs

• 40 programs lost buying power resulting in $2.2 billion in cost over runs*

• 30 months – average delay in delivering to schedule*

*Source: Government Accountability Office


Value chain evolution is a value predictor of this shift as evidenced by the Airbus 380 and Boeing 787 aircraft11 which shifted the Aerospace industry business model context from OEM-dominated supply chains to increasing reliance upon risk sharing with suppliers. These key suppliers are decentralized and have become an integral part of the OEMs critical supply chain,12 which profoundly affects the OEMs ability to develop and manufacture within program objectives across the buyers and suppliers. Suppliers now bear an increased burden for modeling their subsystems and pre-integration across the full development, certification, manufacturing, and support lifecycle.13

EVOLUTION

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Genesis Custom Built Product Commodity

11 Z. Tang, O. J. Pinon and D. N. Mavris, “Identification of Key Factors in Integrating Aircraft and the Associated Supply Chains during Early Design Phases”, AVIATION 2014, Atlanta, GA, 16-20 June 2014.

12 Eliyahu M. Goldratt, “Critical Chain”, North River Press, 2002

13 Z. Tang, O. J. Pinon and D. N. Mavris, “Identification of Key Factors in Integrating Aircraft and the Associated Supply Chains during Early Design Phases”, to be presented at AVIATION 2014, Atlanta, GA, 16-20 June 2014.

14 Simon Wardley, “Bits or pieces?” blog. http://blog.gardeviance.org/2013/01/evolution-begets-genesis-begets.html

Figure 3: Copyright © 2014 Boeing. All rights reserved.

Figure 4: Value Chain evolution drive and implications.14


PRECURSORS TO MODEL BASED ENTERPRISE

Innovations focused on improving program performance and integrity have yielded improvements but have not proven a remedy for all program difficulties. Some notable approaches include:

1) Model Based Design (MBD)15 Replacing a traditional drawing, MBD is defined as an annotated 3D CAD Model that contains all the information (engineering and manufacturing) needed to define a product. A traditional drawing would only be used by exception, not as a standard process.

2) Model Based Engineering (MBEng)16 Model-based Engineering (as defined by an NDIA subcommittee) is an approach to engineering in which models are an integral part of the technical baseline throughout the acquisition life cycle. MBE models are both:

• Integrated across all program disciplines (e.g., systems engineering, operations analysis, software engineering, hardware engineering, manufacturing, logistics, etc.)

• Shared or reused across acquisition programs (including government and industry stakeholders).

3) Model Based System Engineering (MBSE)17 A formalized application of modeling, Model Based Systems Engineering supports:

• System requirements

• Analysis

• Design

• Verification and validation

Model Based Systems Engineering begins in the conceptual design phase and continues through development and later lifecycle phases.

Model Based System Engineering focuses on models across the full life cycle. Encompassing multi discipline collaboration, INCOSE’s definition of MBSE brings a strong focus to formalizing the architecture definition process with the requirements and at all levels implementing validation and verification activities.

15 http://model-based-enterprise.org/model-based-definition.html

16 NDIA Final Report of the Model Based Engineering Subcommittee of the Modelling and Simulation Committee 10 February 2011.

17 https://incoseonline.org.uk/Documents/zGuides/Z9_model_based_WEB.pdf

Figure 5 : An annotated 3D CAD Model Based Design (MBD) created using CATIA.


SPECIFY ACCEPT

In addition to initiatives focused on improving program integrity, industry leaders, searching for root causes to common program execution challenges, have found that the program office program planning and control activities must be tightly linked with product development.

An IBM research paper found that “advances in systems engineering and its improved coordination with program management will produce better program results.”18 In addition, a Gantry Research paper reported a similar finding, highlighting the value of embedding program management with product life cycle management.19

A recent paper by the members of the GfSE/INCOSE working group PLM4MBSE states that one limitation of current approaches is that they manage pieces of information from mechanical, electrical and software engineering, etc. without any notion of its logical interdependencies, concluding that complex products must be considered as multidisciplinary systems made of integrated and interconnected work artifacts of various disciplines.20

THE WAY FORWARDEnterprises can transform by taking a holistic path to improve competitiveness and ability to execute. Dassault Systèmes terms the way forward as a “Model Based Enterprise” (MBE) which integrates the historical approaches of Model Based Engineering (MBe), Model Based System Engineering (MBSE), & Model Based Design (MBD), and on a platform enabling integrated Product Lifecycle Management (PLM), Program Management and Product Line Engineering (PLE).

18 Aviation Week/IBM Systems Engineering Survey, “The Impact of Systems Engineering on A&D Industry Program Results”, November 2010.

19 June 2012, Gantry White Paper: Embedding Program Management into PLM – Assessing Added Value.

20 10 theses about MBSE and PLM Challenges and Benefits of Model Based Engineering (MBe) German Chapter of INCOSE PLM4MBSE Working Group Position Paper Version 1 15 June 2015. http://gfse.de/arbeitsgruppen-mainmenu-85/plm4mbse.html

Figure 6: System Engineering “V” as defined by INCOSE.


BREADTH OF VALUE CHAIN IMPACT

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Analysis Methods • Concepts TechiniquesArchitecture Techniques • Design for X

Advanced Algorithms

Information Consistency • DataCompleteness • Transformation

Iteration • Unambiguous

Integrated Across Lifecycles and DomainsTrusted Data and Actions

Operational Agility • Execution Efficiency

• Characteristics

Features • Platforms • Portfolio

Governance and Execution Models • OBS • WBS • IMS

Environment and Product Models

• Means

Business Architecture • Process Organization

• Outcomes

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(REFERENCE)

ALM MBD

MBe

MBE

MBE is an approach, for the people and disciplines of an extended organization, using enterprise infrastructure and applications to leverage lifecycle managed, connected, descriptive and computational models throughout the program lifecycle to achieve organizational business objectives for user and organizational productivity and processes efficiency. MBE includes PLM-grade program governance capabilities, guided, facilitated, and enforced business processes and rich systems engineering enforced development processes to deliver validated execution-enabled business models. Examples of business models include: Organizational Breakdown Structure (OBS), Work Breakdown Structure (WBS) and Product Breakdown Structure (PBS). Architecture and detailed design definition, process control, and performance evaluation are the basis for creating the program plan and integrated master schedules. These execution models are built upon a supporting open, secure, configuration-enabled, standards-based platform. Product, environment, and execution models evolve in their maturity, fidelity, and validity throughout the program. Product and environment models that serve a particular utility at one stage in the lifecycle will be transformed and translated into other models or views in subsequent stages in the program life cycle.

A holistic approach to deploying a MBE requires three perspectives:

• Understanding the value of the proposed methods, processes or tools;

• Estimating the level of effort required for implementing the proposed changes,

• Evaluating the impact of the people executing the MBE process, their understanding of the value of the change, and in consequence their willingness to change.

It is important to evaluate the impact on the individuals executing the process, their understanding of the value of the change and, perhaps the most importantly, willingness to change. The holistic process focuses first on high business impact changes with low technical complexity and low cultural complexity to yield the quickest and highest value results.

Figure 7: Modeling methodologies strategic group map.


21

Success in deploying a Model Based Enterprise is centered on understanding and deploying key MBE capabilities based upon an open standards based infrastructure with appropriate process controls. This combination yields the desired outcomes of trust in data (information) and trust in action and accountability. The architecture of the system needs to make the information and assets sharable, which facilitates authoring, change and reusability in a configured context. Errors are very costly both in terms of throughput and capital. For illustration, to achieve the same throughput, additional human and facilities capital investments are necessary to overcome errors in data or errors in execution. The system through its underlying architecture should help to avoid both errors of commission as well as errors of omission.

The target of so much consideration is to reduce cost and improve efficiency. Also needed is a system that supports innovation22 in products and product development processes. Achieving cost containment is the product of both cost reduction and cost avoidance.

21 http://ezinearticles.com/?Organizational-Change-Management---Four-Truths-Leaders-Should-Know-About-Organizational-Change&id=3712808, Robert Tanner

22 Innovation is a complicated subject but considering what gets innovated is creating a new thing, or a new way of doing something or a new way of doing something with something new.

3 MAIN AREAS OF IMPACT TO CONSIDER:

Business• Can your business processes be re-evaluated?

• What KPIs best measure the outcome?

Technical

• What is your implementation plan?

• What budget?

Cultural

• What is your communication rollout?

• Will your team embrace change

Figure 8: Elements to consider to effect positive organizational change.

Figure 9: A Model Based Enterprise logical architecture.

BUSINESS PROCESSES

PROGRAMLIFECYCLE

DATAMODELS TOOLS STANDARDS/

INTEGRATIONS

ORGANIZATIONBREAKDOWN STRUCTURE

WORKBREAKDOWN STRUCTURE

INDUSTRYBUSINESS PROCESSES

INFRASTRUCTURE

PLATFORM 3DEXPERIENCE® PLATFORM SERVICES

Low Cultural ComplexityMedium Cultural ComplexityHigh Cultural Complexity

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The final building blocks for a Model Based Enterprise road to execution excellence are based on accurate decision-making. The system should be able to provide information collection, availability and accessibility, exploration, sense-making and logical validation checks. These building blocks lead to improved decision-making and help provide better options to the decision maker.

MBE BUILDING BLOCKSModels are descriptive and analytical, and capture product, environment, and execution information. Models must be captured and lifecycle managed. Multiple disciplines operate concurrently on different facets of the system, architecture or product design models—the impact of a change in one model is readily assessed in another model. Models developed by each discipline evolve in maturity throughout the life cycle and are not thrown away (or neglected) or redeveloped as the program transitions from one phase of development to the next. Such models include:

• Up-front mission analysis models

• System requirements and architecture models

• Detailed CAD and software design models

• Detailed simulation models used to assess and verify all aspects of the system as it evolves.

• Schedules, resources, validation activities, assumptions, etc.

It is critical to realize and manage not just these assets as domains, but to understand the relationships between them. In so doing (by ensuring that key connection points are maintained change can be managed along with all associated implications.

Mission shifts can be rapidly explored for their impact on downstream elements, discovering impact and the need for revalidation all the way throughout implementation verification, qualification, acceptance testing, installation, operation and maintenance.

The need for and the role of verification and validation should be emphasized as defined in INCOSE’s MBSE initiatives. When requirements models are validated early in the process – including those for manufacturing, installation, and support– significant accuracy improvements are realized in the development process, through improved realistic estimates for resources, costs, and schedules that pave the way for realistic planning activities and reduced risks.

The MBE collaborative platform foundation provides a means to share information from the model registry across the extended enterprise of customers, teammates and suppliers. The MBE platform includes modeling standards that enable information exchange. The model registry allows ready access to the different models of known pedigree or provenance. The MBE platform foundation supports a trusted environment that enforces protection of intellectual property and provides secure access to sensitive and classified data. The collaborative environment provides the infrastructure to facilitate deliberate reuse from one program to another, while enabling sharing across a family of products and system-of-systems.

The MBE ‘to-be’ state leverages MBE across the acquisition life cycle to enhance affordability, shorten delivery time, and reduce risk. This is superior to the current state where errors leading to schedule delays and cost overruns are attributable to gaps between domain silos and life cycle phase hand-offs. The future state of MBE seeks to reduce these errors though seamless integration of model data across domains and across the life cycle by aligning shared model properties and assumptions. Engineering and program knowledge is shared through a common technical and execution platform. The MBE ‘to-be’ state includes a workforce skilled in the use of integrated system engineering and program management modeling methods and tools. The MBE to-be’ builds upon an infrastructure that supports this ability and the policies that enable, facilitate, and enforce it.23

23 Adapted from NDIA Final Report of the Model Based Engineering Subcommittee of the Modelling and Simulation Committee 10 February 2011.


ENTERPRISE MBE CRITICAL SUCCESS FACTORS

MBE

MBE

MBE

MODELING PRODUCTS

SILOSENABLING COLLABORATIONON AN ONLINE, CLOUD ENABLED,SINGLE-SOURCE INNOVATION PLATFORM

APPLIED TO FULL PROGRAM LIFECYCLEDATA AND PROCESSES

ADOPTING STRUCTURED MODEL-BASEDSYSTEM ENGINEERING PROCESSES

DATA LOSS

LOOSELYCONTROLLED

PROCESSES

CREATING EXPERIENCES

A MBE approach to achieve needle-moving outcomes must holistically address people and culture, methods, processes, organization and infrastructure. The enterprise cannot meet its business objectives as long as older methods of working (including the use of siloed organizations and data) continue to be used.

Eight critical factors for successful MBE deployments are:

1. A secure platform enabling collaboration on a single-source innovation platform

2. Approach applied to Full Program Lifecycle data and execution processes

3. Adoption of structured Model-Based System and domain engineering processes

4. Models of all types (descriptive/analytical/simulation/execution, etc.) that are captured, related, and lifecycle managed

5. Use of a PLM process and infrastructure backbone of configuration/change/release management

6. Guidance of all work by program or project management capabilities

7. Full ability to model and evaluate form, fit, and function, and execution

8. Knowledge capture, management, accessibility, and process for deliberate reuse

Secure, single-source innovation platform for collaborationTo achieve program performance improvements, the key issues of trust in data or information and trust in action is critical. Without proper management of data and access to that data, the result is missing data or reliance on data that is out of date. Data errors of commission occur when an organization or individual makes a wrong decision based upon incorrect data. Data errors of omission occur when an organization or individual fails to respond (or act) as a result of missing data.

There are several ways to prevent these errors:

• The program must provide a single authoritative information source by integrating or capturing required data.

• The data should be secured and protected by strong Intellectual Property controls.

• Versions and changes over time should be tracked and available for review.

• As many disciplines as possible should be involved in the collaboration—building a system with information and a means of segregation that facilitates security of intellectual property and export data. In addition to traditional engineering and manufacturing disciplines, marketing, sales, contracts, legal, quality, support, etc. are also included in the process.

Figure 10: Transitioning from modeling products to executing a Model Based Enterprise


Apply approach to full program lifecycle data and execution processesTraditionally, improvement efforts have focused on engineering first, then manufacturing. This approach limits the potential for improvement and creates chasms between major program phases. Early, mission planning and business development activities can be conceptualized on one side of the model; support and service activities can be included on the other side. In this way, data and models can be efficiently shared, especially when reused between program phases.

Adopt structured model based system and domain engineering processesModern systems engineering tools and approaches are commonly believed to have developed from the discipline of software engineering. However, these tools, methods and approaches are applicable across all domains—including mechanical, electrical and electronics, etc. These methodologies are used with increasing frequency to address silos and barrier issues that tend to inhibit good communication and collaboration.24

Dassault Systèmes has deployed a widely applicable systems engineering approach. The System DMU (SDMU) approach uses a recursive requirement, functional, logical and physical structured development process for system modeling that is integrated with the models for validation and verification. Fully and uniquely integrated within this approach is the ability to extend the models with embedded behavioral modeling capability. The System Engineering approach is mandatory in order to manage the complexity of modern systems development.

Capture and lifecycle manage models of all typesAt the core of MBE are the models. Models of many types and formats are managed as an evolving set of data representations for key systems and execution elements definitions. Models include information models that detail both product and process. The information takes on different forms and importance depending on the domain and life cycle. This affects both up and downstream data and action, as it is also being transformed and translated throughout the life cycle. A data model that connects these evolving models and provides traceability and impact analysis is the key to realizing full promised value for model based use and reuse.

Product Lifecycle Management processes andinfrastructure The Dassault Systèmes approach to MBE leverages the company’s experience and history in Product Lifecycle Management (PLM). The core ability to create, version, revision, formally change and release process models is required to provide the controls needed to ensure data integrity and provide for certifications processes.

Guide all work by program management capabilitiesWhen product-centric (PLM) and program-centric (Program Management) solutions are embedded (which goes beyond custom integration feeds), both solutions benefit. Contract-based program manager for Dassault Systèmes is an example of seamless embedding within 3DEXPERIENCE® PLM environment. With full access to all current and historical product data and information that resides within the PLM repository, program options can be explored—providing detailed implications to the decision-maker faster, and with greater assurance. Relating program and product data creates a valuable two-way information link between and across programs and products. Moreover, by virtue of being embedded with Programs, PLM is elevated within the organization because it allows better inform high-level decision-making.

An example of needed and valuable guidance is the management of contract-based artifacts in relation to work breakdown structure (WBS).25 There are two fundamental and interrelated types of work breakdown structures—the Program WBS and the Contract WBS.

24 Aviation Week/IBM Systems Engineering Survey, “The impact of systems engineering on A&D industry program results”, November 2010.

25 Dassault Systèmes A&D Accelerator Application is part of the 3DEXPERIENCE Platform was developed in part to support the DOD 5000.2 Process including guidance gleaned from Mil HDBK 881. The WBS is a key program information model building block of execution for visibility, into, and tracking of the various execution elements.


The Program WBS provides a framework for specifying the objectives of the program. It defines the program in terms of hierarchically related product-oriented elements. Each element provides logical summary points for assessing technical accomplishments and for measuring cost and schedule performance.

The Contract WBS is the government or commercial-approved work breakdown structure for reporting purposes, and its extension to lower levels at the discretion of the enterprise, or in accordance with government or program direction and the contract work statement. It includes all the product elements for the products (hardware, software, data, or services), which are the responsibility of the contractor. The work packages associated with the system under development are the result of decomposing into subsystems, and detailed sub-system architecture items, which together constitute the Product Breakdown Structure (PBS). It is important for the MBE enterprise and its practitioners to appreciate such relationships between the architecture data model and the execution data model that are integral to the notion of MBE.

The Work Breakdown Structure serves as a coordinating medium. Through the Program WBS and the Contract WBS, work is documented as resources from the Organizational Breakdown Structure (OBS) are allocated at the task or work package level as it is related to the PBS of the system under development. All of the tasks and work packages taken together for the Integrated Master Schedule (IMS) and expended efforts are rolled up into associated Program WBS element.

Technical, schedule, and cost data are maintained and dash-boarded, and reported for the awareness of interested parties. The Work Breakdown Structures summarize data for successive levels of management and provide the appropriate information on the projected, actual, and current status of the elements for which they are responsible. The WBS keeps the program’s status constantly visible so that the program manager, in cooperation with the contractor, can identify and implement changes necessary to assure desired performance.

The work breakdown structure provides the basis for communication throughout the acquisition and development process. It is the common link that unifies the upfront planning, scheduling, cost estimating, budgeting, contracting, configuration management—based upon historical data, management and engineering judgment, and the execution performance reporting disciplines. Through consistent communications, the WBS permits the government and industry managers to evaluate progress in terms of contract performance.

The Work Breakdown Structure forms the basis for reporting structures used for contracts requiring compliance with the Earned Value Management System (EVMS)26 Dassault Systèmes’ EVMS has been developed following the Office of Performance Assessment and Root Cause Analyses (PARCA), and Guidelines contained in the Electronic Industries Alliance Standard-748 EVMS (EIA-748). Criteria and reports placed on contract such as Contractor Cost Data Reporting (CCDR), Cost Performance Reports (CPR), Contract Funds Status Reports (CFSR), and Cost/Schedule Status Reports (C/SSR).27

26 Dassault Systèmes’ EVMS has been developed following the Office of Performance Assessment and Root Cause Analyses (PARCA), and Guidelines contained in the Electronic Industries Alliance Standard-748 EVMS (EIA-748).

27 Kranz, Gordon M., Gary R. Bliss, Department of Defense Earned Value Management System Interpretation Guide, OUSD AT&L (PARCA) 18 February 2015.


CFSR

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FUTURE YEARSDEFENSE PROGRAM

PROGRAM FUNDREQUIREMENTS

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Fully model and evaluate form, fit and functionTraditional DMU approaches have been limited to analyzing form and fit. With the integration of dynamic modeling capability, Dassault Systèmes added the ability to model and analyze function as well as form and fit. Integral this approach to MBE is a modeling and simulation environment based on the open Modelica modeling language. Modelica features unique multi-engineering capabilities that allows for models that can consist of components from many engineering domains. Libraries in many different engineering domains contain components for mechanical, electrical, control, thermal, pneumatic, hydraulic, power train, thermodynamics, vehicle dynamics, air-conditioning, etc. In addition, through the FMI/FMU standard, external models may be integrated and co-simulated.

Capture and reuse knowledgeFinally, a key opportunity to achieve program execution improvement is through process and product reuse. By capturing both the enterprise models and the utilized business process, company assets can be opportunistically captured, organized, managed, and made available for reuse.

Product line engineering provides a structured, architecture-intensive means through domain analysis to elicit product line value from the legacy product-centric models as a means of enhanced program-driven product development.

Leveraging a product line capability maturity model drives the enterprise to rethink its approach to product development. Through increasing alignment with its customer-facing origins, a product line capability maturity model helps engineer products that reduce diversity in the assets that must be maintained. Products then can be provided that completely satisfies the customer need—with less effort, and with more rapid turn-around.

28 Department of Defense WORK BREAKDOWN STRUCTURES FOR DEFENSE MATERIEL ITEMS Mil-Std-881C 3 October 2011.

Figure 11: The Work Breakdown Structure is the basis of accountability 28


Insert Figure 1229,30

29 Frank van der Linden, “Family Evaluation Framework Overview & Introduction”, Eureka S! 2023 Programme, ITEA project ip02009, 5 December 2005

30 Michał Antkiewicz, Wenbin Ji, Thorsten Berger, Krzysztof Czarnecki University of Waterloo, Canada Thomas Schmorleiz, Ralf Lämmel Universität Koblenz-Landau, Germany S, tefan Sta˘nciulescu, Andrzej Wasowski IT University of Copenhagen, Denmark, “Flexible Product Line Engineering with a Virtual Platform”, ICSE ’14, May 31 – June 7, 2014, Hyderabad, India.

Figure 12: Two complementary Product Line Capability Maturity Models. 29,30


This model has been used in the electronics and automotive industries with great success. Over the last decade it has garnered attention in both aviation and defense sectors due to its potential for increasing value delivery, building on the enablement brought by the model-based enterprise.

“ The transition to a Model-Based Systems Engineering (MBSE) approach is generally viewed as essential for systems

engineering to meet increasing demands of system complexity, design cycles, productivity, and quality…to fully

leverage a model-based approach, the system model must be maintained as a fundamental part of the technical

baseline that is integrated with other engineering models and tools.”

Sandy Freidenthal and Roger Burkhart OMG Meeting 30 March 2015

SUMMARYUsing a Model Based Enterprise platform changes the standard for business and program execution. With the accompanying enablement, facilitation, and enforcement of a holistic approach to MBE, the entire enterprise makes better, actionable real-time decisions through immediate access to complete information. For example, it is possible to tracking to program and engineering milestones, engineering change orders, supplier status production status, usage and health of deployed systems and more. Enterprise collaboration, and asset accessibility and characteristics such as readiness levels help to lay the foundation for deliberate reuse. Execution models, an integral part to MBE, facilitate the ability for an enterprise to gain critical situational awareness, the state of execution and how best to meet customer commitments, collect and leverage historical knowledge and create credible winning proposals to stand out from the competition.

ABOUT DASSAULT SYSTÈMES Since its inception, Dassault Systèmes has partnered with large aerospace customers to lead large complex program enterprise product development infrastructures. Industry has increasingly adopted behaviorally-faithful 3D design for all components of complex products, such as airplanes and cars, which drove the vision for transforming 3D part design process to a systematic integrated product design. In the late 1980’s Dassault Systèmes collaborated with multiple A&D companies and delivered full digital mock-up (DMU) capabilities to the marketplace. Digital mockup capability enabled customers to reduce the number of physical prototypes and realize substantial savings in product development cycle times, and in addition helped streamline manufacturing assembly as well as maintenance, repair and overhaul efforts. Dassault Systèmes built upon the

Benefits of a Model Based Enterprise• Provides access to current and accurate information across the entire enterprise

• Eliminates silos, and promotes communication and collaboration

• Offers a single authoritative source system of record - a key architecture building block of the Model Based Enterprise.

• Provides a foundation with the granularity for effective configuration and change management that enables all other elements of MBE accountability; trust-in-action, trust-in-data.

• Allows decision-makers improved visibility to monitor program performance, contain costs and improves the quality and number of viable options and opportunities.

• Improves the future value of existing assets and deliberate reuse of latent Intellectual Property (IP) for use in product and programs yet to be developed.

• Maximizes resources (human, IP, capital) by deliberately reinforcing value-added behaviors and cultures and squeezing out non-value added activities.

Our 3DEXPERIENCE platform powers our brand applications, serving 12 industries, and provides a rich portfolio of industry solution experiences. Dassault Systèmes, the 3DEXPERIENCE® Company, provides business and people with virtual universes to imagine sustainable innovations. Its world-leading solutions transform the way products are designed, produced, and supported. Dassault Systèmes’ collaborative solutions foster social innovation, expanding possibilities for the virtual world to improve the real world. The group brings value to over 190,000 customers of all sizes in all industries in more than 140 countries. For more information, visit www.3ds.com.

Europe/Middle East/AfricaDassault Systèmes10, rue Marcel DassaultCS 4050178946 Vélizy-Villacoublay CedexFrance

AmericasDassault Systèmes175 Wyman StreetWaltham, Massachusetts02451-1223USA

Asia-PacificDassault Systèmes K.K.ThinkPark Tower2-1-1 Osaki, Shinagawa-ku,Tokyo 141-6020Japan

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DMU concept and contributed to these organizations transition to global engineering, enabling engineers to share and collaborate—through virtual means—their ongoing work across the globe. Complexity has driven the enterprise to become increasingly architecture driven; recognizing this factor as a key MBE enabler working with its customers Dassault Systèmes brought System Digital Mockup (SDMU) to market. SDMU and authoring in configured context built upon an object model that reaches into models of the system of interest, its deployment environments and execution models are key innovations that facilitated Dassault Systèmes ability to realize Model-Based Enterprise.

Decades as the Aerospace & Defense Industry design platformFor more than three decades, Dassault Systèmes has been the design platform for many of the major players in the Aerospace & Defense sector. Our solutions have enabled Aerospace companies to modernize their product development and manufacturing practice to be more effective and competitive.

The Dassault Systèmes Model Based Enterprise backgroundDassault Systèmes 3DEXPERIENCE platform is built on the concept of the legendary Harvard marketing professor Theodore Levitt, who said, “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!” The Dassault Systèmes 3DEXPERIENCE Solutions are designed to enable an MBE approach to programs activities by shifting the institutional mindset from historic norms of thinking, organizing, and operating to new executional possibilities. Our Aerospace & Defense 3DEXPERIENCE platform is composed of archetype experiences targeted to the logical parts of the business value chain (in contrast to the domains). Each experience has a number of key elements including technology enablement: for engineering the key aspects of the job to be done; a means of governance: changing the way the enterprise organizes, reasons, and decides about solving problems; situational awareness: of risk and status, decision support, as well as key stakeholder involvement. These experience archetypes incorporate industry-specific content such as, industry best practices, contract or regulatory compliance, MBE, Product Line Engineering (PLE) elements that are specifically intended to shorten the enterprise time to value.