Model-Based Product Support

Model-based product support turns support planning from a document exercise into a predictive one. By connecting product data, support analysis and readiness models, it shows what a support decision will do to availability and life cycle cost before the budget is committed. With operation and support typically accounting for 60 to 70% of a defense system's total cost, that foresight is where affordable readiness is decided.

Model-based product support (MBPS) is the practice of planning, analyzing and managing the support of a system through connected digital models rather than disconnected documents and spreadsheets. Product data, product support analysis, and readiness and cost models draw on one authoritative data set. The result is that the effect of a support decision on availability and operating and support (O&S) cost can be predicted before the decision is made.

The term is used in two ways. As a discipline, model-based product support extends model-based systems engineering (MBSE) into integrated product support (IPS) and integrated logistic support (ILS). As a proper noun, MBPS is the US Navy program of record modernizing NAVSEA logistics IT for configuration management, provisioning, readiness modelling and technical data management. This entry covers both.

Key points

MBPS replaces document-based support planning with a connected set of models that share one source of product and support data.
Its purpose is to link support resources to readiness: what a given spend buys in operational availability, and at what life cycle cost.
It rests on open data standards, chiefly the ASD/AIA S-Series ILS specifications (S1000D, S2000M, S3000L, S4000P, S5000F, S6000T) and MIL-STD-31000 for technical data packages.
A data model alone does not produce a decision. The value of MBPS depends on the analytical models that optimize and simulate support against readiness and cost targets.

Why model-based product support matters

Operation and maintenance typically account for 60 to 70% of a defence system's total life cycle cost. The US Government Accountability Office puts O&S at about 70% for weapon systems. Many of the decisions that commit that cost are taken early, during acquisition, when the support system is still being designed.

In a document-based approach, the same data is re-entered across configuration management, logistics support analysis, provisioning and technical publications. Each handover introduces delay and drift. By the time an analysis is complete, the configuration it describes may already have changed.

Model-based product support addresses this structurally. When the support data and the system configuration stay connected, a change to either can be traced through to its effect on spares, maintenance tasks, availability and cost. The UK MoD Support Modelling and Analysis Framework (2024) sets out the same ambition: "what if" scenario and simulation testing "on a common platform using a common and endorsed support modelling data set."

The building blocks of model-based product support

Authoritative product data. Configuration, product breakdown structure, bill of materials, 3D models and the technical data package, typically defined to MIL-STD-31000.
Model-based product support analysis. Product support analysis (PSA, formerly logistics support analysis or LSA) held as structured data to ASD S3000L, including FMECA, reliability-centered maintenance, maintenance task analysis and level of repair analysis (LORA).
Readiness and cost models. Predictive models of operational availability and O&S cost, including multi-echelon, multi-indenture readiness-based sparing (RBS) and discrete-event logistics simulation.
Standardized data exchange. The S-Series ILS specifications, so data moves between the OEM, the prime and the authority without manual rework: S1000D for technical publications, S2000M for provisioning, S4000P for scheduled maintenance, S5000F for in-service feedback and S6000T for training analysis.
Decision support. Trade-off and scenario analysis that turns the connected data into a recommended support solution, with its availability and cost consequences quantified.

MBPS, MBSE and the digital thread

Model-based systems engineering describes what a system is and how it behaves. Model-based product support describes how that system will be supported in service and what that support will cost. The digital thread connects the two, carrying design data forward into support analysis and carrying in-service data back into design.

This connection matters most at the design interface, one of the 12 IPS elements. Reliability, maintainability and supportability are designed in, not added later. A support model linked to the engineering model lets supportability be assessed while design changes are still affordable.

In service, the same models become a support-focused digital twin of the fleet. Real failure rates, repair times and stock positions from S5000F-style feedback update the model, so readiness forecasts reflect the fleet as it is rather than as it was predicted to be.

The analytical core: from connected data to readiness

Connected data is a precondition, not an outcome. The questions program and support managers need answered are quantitative. What range and depth of spares meets the availability target at lowest cost? At which echelon should each item be repaired or discarded? How does the fleet perform under surge, attrition or a disrupted supply chain?

The answers sit in the gap between inherent availability (Ai) and operational availability (Ao). Ai reflects the design alone. Ao includes the logistics and administrative delays of the real support chain, and is often governed as much by spares, repair levels and turnaround times as by hardware reliability. Model-based product support makes that gap visible and measurable.

Three analytical capabilities close it:

Optimization of spares, maintenance concepts and support resources across a multi-echelon support network.
Simulation of operational scenarios, to test how the support solution performs over time and under stress.
Life cycle cost analysis, so every alternative is compared on total cost of ownership, not acquisition price.

The US Navy MBPS program

In US Navy usage, Model Based Product Support (MBPS) is a Business Capability Acquisition Category II program of record. Its stated aim is to increase weapon system uptime and reduce O&S costs by replacing ageing NAVSEA logistics IT. It is built around three components:

Navy Product Data Management (NPDM): configuration management and enterprise access to weapon system technical data packages.
Navy Common Readiness Model (NCRM): analysis, prediction and optimisation of readiness and O&S cost across the life cycle, for systems, ships, submarines and strike groups.
Navy Data Acquisition Requirements Tool (NDART): common standards, requirements and acquisition approaches for product and technical data.

The program's objectives include giving decision-makers a way to link resources to readiness and delivering accurate 3D product data for maintenance and supply actions afloat. Access to digital technical manuals at NSWC Port Hueneme has already moved from TDMIS to the MBPS system.

The Navy program is one implementation of a wider shift. The UK MoD, NATO nations and their industrial partners are moving in the same direction through the S-Series specifications and national frameworks such as the UK Defence Support Modelling and Analysis Framework.

Model-based product support with Opus Suite+

Opus Suite+ provides the analytical layer of model-based product support. It brings optimisation, simulation and life cycle cost analysis together in a single software solution, working from one model of the system, its operation and its support organization.

That single model is what makes support decisions defensible. Spares, repair levels and maintenance concepts are optimized against an availability target, tested in simulated operational scenarios, and costed across the remaining life. Data aligns with ASD S3000L, so the analysis connects to the wider product support data environment rather than sitting beside it.

Opus Suite is used across more than 100 defence industries and by the majority of NATO defence forces. On platforms including CV90, Gripen and F-35, primes and operators work from the same analytical methodology.