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Digital Product Support

ALCL 023
Alternate Definition

The DoD PSM Guidebook provides a working definition of Digital Product Support: "Digital product support uses digital engineering methods and digital data and system models to implement the Product Support Strategy, enable data-driven decision making, and deliver effective and efficient product support outcomes throughout the system lifecycle."

Two key concepts within the definition are:

  1. Digital Engineering: “an integrated digital approach that uses authoritative sources of systems’ data and models as a continuum across disciplines to support lifecycle activities from concept through disposal.” 
  2. Product Support: “the package of support functions required to field and maintain the readiness and operational capability of covered systems, subsystems, and components, including all functions related to covered system readiness.” 
Alternate Definition Source
  1. DoD PSM Guidebook, paragraph 1.2
  2. DAU Glossary, Digital Engineering
  3. 10 USC 4324, Life-cycle management and product support (10 USC 4324(d)(1))
General Information

Overview

Digital product support is an approach which leverages authoritative system data and models to implement the PSS. This applies to: (1) systems which are “born digital” (e.g., designed using modern digital engineering tools); (2) digitally-engineered modifications to legacy systems; and (3) sustainment of systems employing digital principles. In execution of a digital product support approach, digital engineering and product support activities and teams are tightly integrated and mutually reinforcing in delivering affordable readiness to the warfighter across the life cycle. The twelve Integrated Product Support (IPS) Elements which comprise the PSS, can each benefit, in many cases substantially, from utilization of digital system models, including 3-dimensional computer-aided design (3D CAD) models, Systems Modeling Language (SysML) models, and discrete event simulations. This article describes a digital product support approach to each of the IPS elements. 

For information on contracting for Digital Product Support, see this article.

  1. Product Support Management - Use of digital models is inherent in the Product Support Manager’s (PSM) 10 USC 4324 statutory responsibility to “ensure the life cycle sustainment plan is informed by appropriate predictive analysis and modeling tools that can improve material availability and reliability, increase operational availability rates, and reduce operation and sustainment costs.” Early in the system life cycle, models can be used to capture and manage warfighter product support requirements, for example in a systems modeling language like SysML. Modeling and simulation (M&S) can be used to refine requirements allocation and system design to achieve product support metrics (such as availability, maintainability, reliability, and operating and support costs). As the system definition matures, models, including virtual prototypes, also inform trade studies (e.g., cost-capability trades and Sustainment Key Performance Parameter (KPP)/Key System Attribute (KSA)/Additional Performance Attribute (APA) trades). Models inform cost estimating (CE) and reduction initiatives, test and evaluation (T&E), validation and verification (V&V) of the support package, business case analyses (BCA) (including sensitivity analyses), logistics assessments, and Sustainment Reviews (SR).  The PSM captures the program's Digital Product Support approach in the Life Cycle Sustainment Plan (LCSP), paragraph 4.6.3 and throughout.

    The product support management team must advocate for the necessary data (including models) with the appropriate license rights to be procured as part of system (or modification) design and development contracts to facilitate digital product support. Configuration management (CM), critical to effective and efficient life cycle management, is embodied in a model-based Authoritative Source of Truth (ASoT), i.e., the system's configuration controlled digital baseline (see DoDI 5000.88, para 3.4a(3)(m)), managed within a Product Lifecycle Management (PLM) or equivalent system. Permissions (role)-based access ensures all stakeholders can quickly find and operate from the single authoritative data set. The PSS, which includes the product support business model (PSBM) and product support arrangements (PSA), must consider the needs and capabilities of model “consumers” throughout the enterprise, to include product support integrators (PSI) and providers (PSP) (e.g., supply and/or maintenance providers). Finally, the PSM team must establish and maintain robust, ongoing collaboration with the systems engineering (and later sustaining engineering) teams to manage and utilize the system’s ASoT for life cycle product support. 
     
  2. Design Interface - This element is described in the IPS Element Guidebook as “participating in the systems engineering process to impact the system design for maximum availability and effectiveness at lowest cost.” During development, the program systems engineering team will be the primary custodians of system models (e.g., via oversight of models under the contractor’s configuration control) until Physical Configuration Audit (PCA) at which point, if tasked under the Statement of Work (SOW), Contract Data Requirements List (CDRL) and appropriate license rights, models are delivered to the Government. Within this element, the PSM team collaborates with the systems engineering (and specialty engineering) team(s) to analyze, evaluate, and influence system and support design. This includes participation in supportability analyses (e.g., Fault Tree Analysis (FTA); Model-Based Failure Mode, Effects, and Criticality Analysis (FMECA); Reliability-Centered Maintenance Analysis (RCMA), Maintenance Task Analysis (MTA) and Level of Repair Analyses (LORA)) as members of the Reliability and Maintainability (R&M) Working Group or Design Integrated Product Team (IPT).  

    The product support management team, user and depot representatives (e.g., field and depot maintenance subject matter experts) will evaluate virtual prototypes (e.g., as described in Department of the Army Pamphlet (DA PAM) 700-127, para. 6-7), digital mockups, and the model-based Human Engineering Design Approach Document-Maintainer (HEDAD-M, DI-HFAC-80747), to influence product support package development to achieve contractual and Reliability, Availability, Maintainability and Cost (RAM-C) Rationale Report objectives embodied in the Capability Development Document (CDD), verify maintainability and deployability requirements, specify Materiel Fielding Plan requirements, etc. The PSM team will also participate in model-based technical and design reviews (e.g., Preliminary and Critical Design Review (PDR and CDR)) and other reviews identified in DoDI 5000.88, Engineering of Defense Systems (para 3.5a(2)) that may feature fly-through “movies” of the system by structure or sub-system with color coding of electrical, fuel, hydraulic, oil, and air conduits, and progressive nose-to-tail (stem-to-stern) “peelback” to reveal key features such as interfaces, structural loading points, danger areas, etc. These reviews will increasingly rely on models and other digital artifacts (see the Air Force (AF) Digital Building Code for Digital Acquisition versus static and/or 2D products. The team will also monitor technical performance measure prediction and achievement, and conduct trade studies for various system and support designs necessary to achieve warfighter requirements such as Mean Time Between Failure (MTBF), Mean Time to Repair (MTTR), Turnaround Time (TAT), etc. 
     
  3. Sustaining Engineering - This element is where a digital product support approach leverages maximum benefit after initial system fielding to ensure uninterrupted and affordable system availability for the Warfighter. Consider the value of a fully defined system model and digital thread paired with in-service usage and maintenance data for maintaining an accurate digital twin for each tail, hull, or vehicle number. The ability to perform data analytics to assess system trends, identify where product improvement is needed, virtually assess the impact of modifications (including service life extensions) and configuration changes, and develop responses to requests for engineering assistance (including troubleshooting and battle damage and non-standard repairs) is a significant technological leap over a system defined only by 2D drawings.  For product improvement, changing component model parameters and simulating the long-term system-level impacts could inform the Materiel Improvement Project Review Board’s prioritization of candidate projects by identifying the greatest return (e.g., availability) on investment (cost of the modification). Alternatively, for user-directed capability-improving modifications, the systems engineering and PSM team can update supportability analyses and deliver model-informed results to assess any second- and third-order effects to RAM-C metrics.  

    In terms of engineering assistance, models support replication of field conditions to diagnose persistent or new failure modes. Models can facilitate remote, real-time engineering assistance to maintainers using virtual reality or even augmented reality capabilities through the use of tablets or other smart devices (including "wearable" technology such as smart glasses). Model-based design also yields tremendous benefit for corrosion control and prevention, enabling a digital twin approach to map and manage damage such as corrosion and cracking on a tail-, hull-, or vehicle-number basis for trending and prioritization of repairs, selecting the best of the fleet for operational unit deployment taskings, and, later in the life cycle, for prioritized retirement/disposal. Finally, models enable effective and efficient resolution of Diminishing Manufacturing Sources and Material Shortages (DMSMS), obsolescence management, and technical refresh by providing an ASoT to qualify new manufacturers and assess system-level impacts of form, fit, and function replacements that may have different underlying technical performance characteristics.  Other sustaining engineering activities will be described below in their applicable IPS element section. 
     
  4. Supply Support - In this element, models inform processes such as provisioning and cataloging, spares modeling, alternative sourcing and DMSMS/obsolescence management, and advanced/additive manufacturing of repair parts and components.  Use of ASoT models (and where necessary, derivative products such as 3D PDFs) across the end-to-end supply chain is important for keeping the entire sustainment enterprise aligned and up to date versus part procurement based on outdated and stovepiped versions of logistics product data, which leads to unnecessary delays and rework.  Beginning with the engineering and manufacturing Bills of Material (BOM) and related product data, provisioning is the first opportunity to leverage models for supply.  The Defense Logistics Agency (DLA) Logistics Information Services (DLIS) has demonstrated the ability to consume 3D PDFs (PDFs with embedded, rotatable models) as Engineering Data for Provisioning (EDPF) to properly document and catalog new or modified parts and assign National Stock Numbers.  Subject matter experts (SMEs) may rely on models to assist them with validating contractor-proposed Source, Maintenance and Recoverability (SMR) codes for proper provisioning for the field and depot level.  

    Next, the digital approach’s ASoT (including models and related logistics product data such as proposed spare parts lists) inform sparing analysis such as Readiness Based Sparing.  While the models themselves are not heavily engaged at this stage, the indentured product tree structure managed in a PLM system as the ASoT, is critical. Once sparing levels are established, models may assist SMEs in estimating spares package footprints by providing dimensional and weight data.  Models also assist engineers in determining and documenting the optimal placement of markings on parts for item unique identification (IUID), serialized management, radio frequency identification (RFID), or other total asset visibility requirements.  In terms of Supply Chain Risk Management (SCRM), future models could assist with counterfeit prevention and detection, for example by comparing scanned physical part characteristics versus the toleranced master model, etc. The Supply Chain Risk & Resiliency Playbook (see A9.11) cites the use of Digital Thread/Digital Twin concepts and discrete event simulation to conduct What-if drills and redesign supply networks based on possible risk scenarios. 
     
  5. Maintenance Planning & Management - In this element, models aid in developing the product support package for the maintainer (field and depot level).  As discussed under Design Interface, a model-based HEDAD-M is an insightful tool for assessing maintainability (e.g., access to components for servicing and repair procedures) early in system design and making improvements before “metal is bent” (production starts). Reliability requirements captured and managed in a modeling language aid in designing the optimum maintenance strategy (e.g., mix of preventive, corrective, and on-condition maintenance) for the system. Models inform design of diagnostic, predictive, and prognostic strategies, Reliability-Centered Maintenance (RCM), and Condition Based Maintenance (CBM+). CBM+ is effectively the "central nervous system" for the Digital Twin.  Models inform validation of MTA and LORA, particularly for new and unusual subsystems and components where a virtual 3D representation aids subject matter experts in recommending specific maintenance levels and strategies. It’s important to assess early in the life cycle, prior to fielding, any organic depot considerations for use of models. This may include model-based instructions (covered below in Technical Data), model-based manufacturing (to include advanced and additive manufacturing), and delegated engineering authority personnel tools and training needed to access and manipulate models for daily and non-standard work.  
     
  6. Packaging, Handling, Storage, and Transportation (PHS&T) - In addition to spares footprint determination and part marking mentioned above in the Supply Support section, models may support other PHS&T activities. For example, rotatable models assist packaging designers in quickly determining areas of the component (e.g., sharp or protruding components) requiring enhanced physical protection or transportability restrictions (see DA PAM 700-127 paragraphs 6-13).  Models may also assist in determining with great precision whether existing design reusable containers will fit a new part. In addition, “stackable” models (in the virtual and physical sense) may inform material handling requirements and cube/weight limitations. Finally, for deployable systems, imagine load-planning for strategic or tactical sea- or airlift with design models that represent a precise outer mold line of the system that integrate seamlessly with load planning software to maximize available space in scarce air- and sea-lift resources.    
     
  7. Technical Data - This element is the ultimate embodiment of a digital product support approach, because it includes the models themselves in their native and derivative forms.  The Technical Data Package (TDP), which defines the system or product, consists of models, drawings, lists, databases, software documentation, interface control documents, and the indentured product tree structure. Derivative products of the living ASoT TDP include operational information (such as operator and maintenance manuals) and associated product information such as test results.  The PSM team must work closely with systems engineers (to include configuration management and data management), contracting, and PMs to create a data and license rights and Intellectual Property (IP) Strategy which will ensure the contractor delivers a complete, properly marked TDP for use throughout the system life cycle. This requires early collaboration with organic product support providers such as depots and supply chain management organizations (i.e., primary or secondary inventory control authorities (PICA/SICA)).  The program office team must also establish or secure access to a PLM or equivalent system to house and manage the TDP upon delivery to maintain and update digital product design data throughout the lifecycle (see the Department of the AF Pamphlet (DAFPAM) 63-128, Table 11.2).  

    This element also includes technical manuals (such as S1000D-compliant Interactive Electronic Technical Manuals (IETM)), which typically contain derivative representations of system models such as model-based instructions, illustrated parts breakdowns (catalog), etc. To keep these manuals in sync with the ASoT, the PSM team should consider implementing an architecture and processes which facilitate machine-to-machine update of manuals (in near real-time or at the desired frequency) when changes to the ASoT are made and certified/verified. These updates include “effectivity” management, which is aided by the digital twin concept that manages data to the tail-, hull-, or vehicle number.  For example, if different fleet configurations exist, the PLM, configuration management, and operator and maintenance manuals must all be in sync to ensure safe and effective operation and sustainment of the system. 
     
  8. Support Equipment - This element, which includes ground support equipment (GSE), material handling equipment, automated test stations/equipment, tools, etc., benefits from a digital product support approach in a manner similar to the system being procured. While some legacy equipment (particularly those fielded in earlier decades) may not have a digital TDP, newly designed equipment will likely be built on a model-based design. These designs may be evaluated and serve as a basis for maintenance and supply planning just like the primary system. For example, for newly designed support equipment, inclusion of model(s) in the Support Equipment Recommendation Data (SERD) (e.g., an embedded 3D in a PDF) will assist SMEs in evaluating equipment design, functionality, and safety.  

    In addition, the interface between support equipment and the primary system can be analyzed virtually prior to prototype production and manufacturing to identify problems or issues such as electrical, hydraulic, fuel, oil, and air connections, equipment reach (i.e., height), safety considerations, etc.  While not strictly “support equipment,” model-based designs also assist review of proposed locally manufactured tools. Models could then form the basis for production (including additive or other advanced manufacturing technique) at the unit level. In sustainment, this may greatly decrease replacement tool lead time, as a new tool can be “printed” on demand.  More robust models of support equipment may also support analyses for system modifications, product improvement, etc., by virtually evaluating various performance characteristics. 
     
  9. Training & Training Support - This element, like Technical Data, can directly benefit from a model based approach such that system models are reused for operator and/or maintenance training.  Model-rich virtual reality (VR), augmented reality (AR), or mixed reality training creates an immersive experience to deliver high-fidelity training and mission rehearsal. Early in the life cycle, models may be used to support familiarization and contractor (e.g., Type 1) training, including classroom instruction with or without the use of physical prototypes. Model-based simulations enhance comprehension of complex and dynamic processes. Training devices (e.g., simulators, weapon system trainers, operational flight trainers, part-task trainers, maintenance trainers, etc.) are designed using the system’s model-based ASoT and ideally delivered prior to system fielding to train the initial cadre of operators, maintainers and instructors. Then, as the system is modified or upgraded during production, deployment, and fielding, model updates flow seamlessly “downstream” to the training system PSI/PSP(s), which update the training device hardware and software to reflect the fielded configuration(s). 
     
  10. Manpower & Personnel - While the use of 3D models to analyze human-machine interaction is described above in the Design Interface section, other types of models are useful in determining manpower requirements for systems, particular maintenance manpower. For example, analytical models, such as the Air Force's Logistics Composite Analysis Toolkit (LCOM ATK), built on reliability and maintainability factors can be used to determine the optimum mix of manpower, experience, and specialty (e.g., specialty code, Military Occupational Specialty (MOS), or rating).  When maintained throughout the system life cycle, these models can be updated to account for reliability or maintainability improvements, system modifications, etc. 
     
  11. Facilities & Infrastructure - For this element, models inform physical requirements for the facilities requirement plan and site activation.  This may include physical dimensions, load and thrust-bearing requirements, utilities interfaces, security, and safety factors.  As discussed above in Supply Support, models can inform space requirements for spares storage as well. Finally, system models may interface with or support installation-managed model-based digital condition-based monitoring of key facilities. 
     
  12. Information Technology (IT) Systems Continuous Support - This element includes a program's PLM system, which often forms part of a broader Digital Engineering Ecosystem (DEE), and provides key capabilities for storing and managing the model-based ASoT in an indentured product-tree format.  Depending on the needs of the PM, engineering community, PSM/PSI/PSP, and customer, other IT tools are often required. These include engineering and multi-physics analytical tools such as Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), CAD authoring, system architecture modeling, and others. Logistics tools such as technical manual authoring, logistics product databases, etc., also will interface directly, machine-to-machine with the PLM system to eliminate air-gap and human-induced errors when moving data between systems.  This element also requires an appropriate Intellectual Property (IP) strategy, cybersecurity strategy, and program protection plan that governs the procurement and management of models across the life cycle. Model formats may be a particular concern for PSPs based on available “viewer” software as mentioned above in Supply Support for provisioning and cataloging, and for part reprocurement, additive or other advanced manufacturing, etc. Also within this element are the Systems Integration Lab (SIL) and Software Development Lab (SDL), if procured, and supporting capabilities for the Software Support Agency for continuous delivery and continuous integration of software. SIL and SDL use of the ASoT is critical. 

Summary:  A digital product support approach holds great potential to deliver more effective, efficient, and affordable support to the Warfighter. The basic tenet of a model-based ASoT in itself has tremendous potential for time and cost savings as the approved system configuration resides in a single system with permissions-based (role-based) access. Finally, use of authoritative system data and models to inform and support all downstream product support processes enable vertical and horizontal alignment to an extent that far exceeds analog, paper-based, and stovepiped processes. Finally, below are a few examples of Service initiatives related to digital product support.

DoD Digital Strategy Documents

DoD Digital Engineering Strategy, 2018

DoD Data, Analytics, and Artificial Intelligence Adoption Strategy, 2023

Service and Defense Agency Initiatives Enabling Digital Product Support

  1. Department of the Navy. Model Based Product Support (MBPS) is a Naval Sea Systems Command (NAVSEA)-managed, Chief of Naval Operations (OPNAV)-resourced program that seeks to modernize the Navy's current legacy logistics data systems that provide configuration management, provisioning, readiness modeling and technical data management support for ships and weapons systems.  Its objectives include increasing weapon system uptime and reduce support costs by providing a decision support capability to relate resources to readiness; a maintenance and supply resource optimization model to dynamically meet mission readiness requirements; management and delivery of accurate, integrated, and modern 3D product data necessary to execute maintenance and supply actions on ships and submarines; and common standards, requirements, and acquisition approaches for product and technical data.  MBPS supports the 2020 US Navy and Marine Corps Digital Systems Engineering Transformation Strategy
     
  2. Department of the Air Force. The Department of the Air Force (DAF) Digital Product Support Vision (c. Feb 2023) confirms the department's commitment to "adopting digital tools and processes to accelerate development and delivery of new capabilities providing a more lethal, agile, and ready force." The vision document includes a recommended definition of Digital Product Support, a description of Digital Product Support across the life cycle, an Enterprise Overview, and a list of resources for life cycle logisticians, including workforce development opportunities. 

    (a) The Air Force Materiel Command (AFMC)'s original Digital Campaign objective was to move the activities of the government and industry enterprise to modern digital capabilities and processes, including a collaborative, integrated digital environment that includes all functional disciplines to deliver capabilities to the Air Force with speed and efficiency. In early 2023, AFMC refocused the effort from a campaign to ongoing Digital Transformation including the concept of "Digital Materiel Management" (DMM). In June 2023, AFMC published a new white paper, "Digital Materiel Management: An Accelerated Future," which calls for the command to "shatter existing paradigms and adopt DMM capabilities to radically accelerate our fielding, sustainment, and modernization." The white paper includes a description of Lifecycle DMM, its six key initiatives, and the multi-disciplinary cross-functional nature of the approach. For additional details, see this interview with AFMC Commander, General Duke Richardson. 

    (b) The U.S. Space Force (USSF) Vision for a Digital Service is an interconnected, innovative, digitally dominant force.  This includes a Digital Engineering Ecosystem that establishes the interconnected foundation and analytic underpinning for fluid, flexible, and frictionless force design, capability planning, development, test, delivery, operations, and sustainment across mission areas at the speed of need.  
  3. Department of the Army. The Army Digital Transformation Strategy (ADTS) is the overarching framework that will set the vision, establish lines of effort (LOE), and implement strategic digital transformation initiatives prioritized and resourced as required to achieve the end state of a more ready, lethal, and modern force. In May 2024, the Army published Directive 2024-03, Army Digital Engineering, designed to enable the Army to rapidly adopt and institutionalize modern Digital Engineering (DE) practices pursuant to DoDI 5000.02 and DoDI 5000.97. The directive includes four tenets, including: focus areas, interoperability and implementation, pathfinder programs, and talent and expertise development.

     

  4. Defense Logistics Agency. DLA has published an Additive Manufacturing Implementation Plan that describes DLA's lines of effort aimed at integrating Additive Manufacturing (AM) into the supply chain. Of note, the plan states "to consider AM as a viable option, the supply chain needs a consistent digital thread." One of the plan's focus areas is a common DoD data framework called JAMMEX that is a secure web-based system that makes 3D AM models available across DoD.

Notes:

1. DAU learning assets designed specifically for the Life Cycle Logistician now include:

2. The May 2022 DoD PSM Guidebook contains several references to Digital Product Support, including:

  • Employing Digital Product Support for programs "born digital" and for digitally engineered modifications to legacy systems (para 1.2)
  • PSM collaboration with Systems Engineering to develop and implement the program's Digital Engineering Implementation Plan (para 1.2 and 3.14)
  • Use of a Digital Engineering Ecosystem, Integrated Digital Environment (IDE), or Product Lifecycle Management (PLM) capability (para 4.2.3 and I.3) 
     

3. The DoD Life Cycle Sustainment Plan (LCSP) Outline V3.0 also contains several references to Digital Product Support, including para 4.6.3 which includes summarizing the aspects of the program's digital engineering strategy and implementation plan, consistent with the program's Systems Engineering Plan, that relate to executing the Product Support Strategy
 

4. Relevant Defense Acquisition Magazine articles include:

5. MIL-HDBK-539, Digital Engineering and Modeling Practices (Dec 2022) is a relatively new resource to "help identify how digital engineering (DE) and modeling activities can be considered for all disciplines and functional areas within the acquisition lifecycle." The handbook includes information on the DoD and Service campaigns and initiatives; a robust set of definitions (including Model Based Product Support and Model Based Sustainment); a comparison of traditional vs. digital for product development, definition, and sustainment; diagrams depicting the evolution of product data and data management across the life cycle; information on Product Lifecycle Management and a "DE Logistics Structure"; and contracting language for digital.  While the handbook features many US Navy examples and terms, it is broadly applicable across DoD. (Note: this handbook is currently being revised and is expected to be re-published in FY25).

6. DoD Instruction 5000.97, Digital Engineering (Dec 2023) is a new instruction that complements DoD Instruction 5000.88, Engineering of Defense Systems, and prescribes policy for implementing digital engineering including authoritative definitions and a Digital Engineering Ecosystem framework.