Designing a Digital Manufacturing Architecture for Aerospace Execution

Aerospace manufacturers are under pressure to deliver more, faster, with tighter compliance and deeper traceability. Many already have PLM, ERP, MES, and quality systems in place, yet still struggle to answer basic questions in real time: What is actually happening on this program today? Where are we off-plan, and why? Which risks are accumulating in the supply chain right now? That gap between planning numbers and operational reality is the same visibility problem described in the execution-centric view argued in the scoreboard article—but now at the level of factory systems.

This article proposes a practical, technology-agnostic digital manufacturing architecture tailored to aerospace. It focuses on clear system roles, data boundaries, and integration flows, with a specific emphasis on introducing an execution layer that sits between planning systems and the real world of production. The goal is not a greenfield redesign, but a roadmap that works in brownfield, multi-site, and multi-supplier environments.

The Current State of Digital Manufacturing in Aerospace

Typical system inventories at OEMs and larger suppliers

Most aerospace OEMs and tiered suppliers already operate a dense landscape of systems. A typical inventory includes:

• PLM and PDM for engineering data, configurations, changes, and controlled technical documentation.
• ERP for demand, MRP, capacity planning, purchasing, inventory, and financials.
• MES or shop-floor systems for work dispatching, data collection, and sometimes machine integration.
• Quality systems (QMS, eQMS, NCR/FRACAS tools) for inspections, non-conformances, concessions, corrective actions, and approvals.
• Point solutions for tooling, calibration, maintenance, document control, and test systems.

Each of these systems solves a real problem, often very well. The challenge is that they rarely form a coherent operational picture. Program leaders, industrialization engineers, and production managers end up assembling their own view through spreadsheets, status meetings, and ad hoc dashboards.

Pockets of automation alongside manual islands

A common pattern is deep automation in small pockets (for example, a highly automated machining cell or test facility) surrounded by manual coordination. Operators may log data digitally, but routing changes, rework decisions, and schedule recovery plans often move via email, shared drives, or side conversations.

This creates islands where data exists, but is not connected. A machine may be perfectly integrated to an MES, yet program management has no live visibility into whether today’s critical serial numbers are on track, blocked by quality, or waiting on supplier hardware.

Integration gaps that directly impact execution clarity

From an execution standpoint, the most damaging gaps are usually not missing systems, but missing contextual integration. Examples include:

• PLM sends BOMs and routings to ERP, but late engineering changes are not reliably propagated to the work instructions on the floor.
• MES collects operation completions, but ERP still shows the plan until someone manually reconciles exceptions.
• Quality holds and concessions live in a separate system, so planners cannot see which orders are blocked in real time.
• Supplier status is maintained in portals or emails, not as structured, machine-readable signals tied to specific assemblies and serial numbers.

The result is a fragmented view of reality. KPI dashboards may look healthy, while the true execution system is fighting fires. Closing this gap requires treating the execution layer as a first-class architectural component.

Core System Roles in Aerospace Manufacturing

PLM as design and configuration authority

In regulated aerospace, PLM is the design authority. It owns product definitions, configurations, CAD, controlled documents, and engineering change processes. PLM defines what is allowed to be built and under which configuration rules.

For a digital thread to function, PLM must clearly expose authoritative structures: engineering BOMs, manufacturing BOMs, routings, and approved work instructions. Downstream systems should not be re-creating these structures independently; they should consume them via controlled interfaces with explicit versioning, effectivity, and change control.

ERP as planning and financial backbone

ERP is the planning and financial backbone. It translates product definitions into demand, supply, capacity, and cost. It drives MRP, purchasing, lead times, and production orders. However, ERP fundamentally operates on planned states and summarized events.

In aerospace, this distinction is crucial. ERP knows what should have happened: which work orders should be in which status and when. It is not designed to track every micro-state, rework loop, or configuration-specific deviation at the level required for certification and root-cause analysis.

MES and plant systems for local control and data collection

MES and plant systems typically orchestrate work within a facility: dispatching operations, collecting inspection results, interfacing with equipment, and enforcing some aspects of process control. In many aerospace plants, legacy MES implementations are tightly coupled to specific lines or technologies, and their data models mirror local needs rather than program-wide visibility.

A well-implemented MES is vital, but it is still plant-centric. It usually lacks a program- and configuration-centric view that spans multiple sites and external suppliers. This is where an explicit execution layer becomes necessary.

Quality systems for inspections, NCs, and approvals

Quality systems are the backbone of compliance: they capture non-conformances, concessions, corrective actions, inspection plans, and audit evidence. In AS9100 and similar environments, they must remain authoritative for these records.

The architectural challenge is that quality events are often logged after the fact or in systems disconnected from live production status. That makes it hard to see, in real time, which serial numbers or assemblies are blocked, under concession, or carrying elevated risk. The execution layer has to surface quality status as part of the operational picture without compromising the QMS as the system of record.

Introducing the Execution Layer as a First-Class Component

Why existing systems struggle to represent live operational context

Most aerospace organizations discover that even with mature PLM, ERP, MES, and QMS, they still cannot reliably answer questions like:

• For this program, which serial numbers are currently in process, where are they physically, and who is working on them?
• Which operations are blocked by missing parts, tooling issues, or quality holds, and what is the downstream schedule impact?
• How many deviations from standard work have occurred this week, and how are they distributed across suppliers and sites?

The reason is architectural: each system holds a piece of the puzzle, but none is responsible for assembling current execution context across the entire value stream. That is the job of an explicit execution layer.

Execution layer responsibilities distinct from MES and ERP

A dedicated execution layer should not try to become another MES or another ERP. Its distinct responsibilities typically include:

• Live orchestration and status: maintaining a single, near-real-time model of every order, operation, and serial number across plants and key suppliers.
• Contextualizing data: joining work orders, configurations, quality events, and supplier signals into a coherent timeline per unit or lot.
• Exception management: making deviations from plan (delays, rework, holds, missing material) visible quickly and in the right context.
• Embedded traceability: capturing genealogy and process evidence as work happens, rather than reconstructing it later.

In other words, the execution layer is the operational nervous system that connects planning intent to what is actually happening, minute by minute.

Supporting multi-site and multi-supplier coordination

Aerospace programs are almost always multi-site and multi-supplier. An execution layer must therefore be designed for federated visibility from the outset. That means:

• Normalizing key identifiers (part numbers, serials, lots, orders) across organizations.
• Defining data contracts with suppliers that expose status, quality events, and certification documents in structured form.
• Handling different levels of system maturity—some suppliers may have MES, others may only have spreadsheets.

Platforms like Connect 981 operate in this space: not by replacing existing systems of record, but by serving as the execution fabric that links them into a coherent operational picture.

Key Data Flows in a Connected Aerospace Architecture

From PLM to execution: configurations, BOMs, and work instructions

The first critical flow is from PLM to the execution layer. Key elements include:

• Configuration structures (engineering and manufacturing BOMs) with clear versioning and effectivity.
• Process definitions: routings, operation sequences, key characteristics, and inspection plans.
• Controlled work instructions and reference documents that must be available at the point of work.

The execution layer does not re-author this data; it consumes it as authoritative, then maps it to specific orders, serial numbers, and sites. When engineering changes occur, the execution layer should be able to show exactly which in-process units are impacted and where rework or special instructions are required.

From execution to ERP: completions, variances, and schedule impact

The second major flow runs from the execution layer back to ERP. ERP needs summarized events: operation starts and completions, scrap, yield, and sometimes high-level reasons for variance. The execution layer should:

• Capture detailed execution events and statuses in its own model.
• Translate those events into the coarser transactions ERP expects.
• Push schedule-relevant status updates early enough that planners can adjust, rather than learning about delays after the fact.

This preserves ERP’s role as the planning backbone while ensuring its view of progress reflects what is actually happening on the floor and across suppliers.

From quality systems to execution: holds, concessions, and approvals

Quality systems remain the system of record for non-conformances, concessions, and approvals. However, the execution layer must be aware of their impact on work. Architecturally, this usually means:

• Quality events are created and managed in the QMS.
• The execution layer subscribes to these events via an integration, enriched with identifiers such as serial numbers, work orders, and affected operations.
• The execution layer enforces the operational consequences: holds, rework routing, special inspections, or additional approvals.

This separation preserves auditability while ensuring that quality decisions have an immediate and visible impact on execution.

From suppliers to OEMs: status, genealogy, and certification data

Supply chain visibility is often the weakest part of aerospace architectures. A mature execution layer should support:

• Status updates for critical parts and assemblies tied to specific orders and serials.
• Genealogy data at the level of lot, batch, and key serialized components.
• Certification artifacts (CoCs, test reports, inspection records) attached to the right units in a machine-readable way.

For suppliers with limited digital capabilities, this may start as structured data submissions via controlled templates or lightweight portals. Over time, deeper system-to-system integrations can be introduced, but the architecture should not assume all sites start at the same maturity level.

Governance, Ownership, and Change Control

Defining system-of-record responsibilities

One of the most important architectural decisions is clarifying system-of-record boundaries. A practical pattern for aerospace is:

• PLM is the system of record for product definition, configurations, and controlled engineering documents.
• ERP is the system of record for demand, orders, inventory, and financial transactions.
• QMS is the system of record for quality events, approvals, and audit trails.
• Execution layer is the system of record for current operational state: where each unit is, what has been done, and which exceptions are active.

Being explicit about these roles avoids duplication and helps resolve disputes when data disagree across systems.

Managing master data across organizational boundaries

Aerospace architectures often fail not because of interfaces, but because of inconsistent master data. Practical steps include:

• Adopting clear, shared identifiers for parts, configurations, serials, and orders.
• Defining who owns which reference data (e.g., part families, operation codes, defect codes) and how changes propagate.
• Ensuring that suppliers receive and return identifiers that can be reconciled across systems.

The execution layer can help here by acting as the place where inconsistent identifiers are mapped and reconciled, but it cannot fix master data without a governance process.

Handling upgrades and new capabilities without disrupting operations

Given the long life of aerospace programs, architectures must tolerate system upgrades and replacements. An interface-first, execution-centered design helps by:

• Decoupling core execution logic from any single MES or ERP implementation.
• Using stable APIs and data contracts at the execution layer boundary.
• Allowing local systems to evolve, as long as they continue to honor those contracts.

This approach reduces the risk that a plant-level MES replacement or ERP upgrade will destabilize program-level visibility.

Building the Architecture Incrementally

Starting with critical programs or product families

Attempting to re-architect the entire enterprise at once is rarely feasible. A more workable approach is to start with one critical program or product family where visibility gaps are already painful. For that scope, define:

• The minimum set of systems that must participate (PLM, ERP, QMS, key suppliers, key plants).
• The execution questions that must be answerable in real time (e.g., status by serial number, critical path operations, open concessions).
• The data flows required to answer those questions reliably.

Once the execution model for that program is stable, you can extend patterns and integrations to adjacent programs and suppliers.

Interface-first approaches to connecting legacy systems

Brownfield aerospace environments contain many legacy systems that cannot be easily replaced. An interface-first strategy acknowledges this reality:

• Identify where each system already emits useful data (reports, exports, log files, APIs) and how often.
• Wrap those outputs in adapters that normalize them to the execution layer’s data model.
• Prioritize bidirectional interfaces where immediate feedback is valuable (e.g., quality holds that must stop work).

This allows the execution layer to emerge without requiring big-bang system changes. Over time, some legacy components can be simplified or retired as their roles are subsumed into better-aligned platforms.

Patterns for introducing platforms like Connect 981

When introducing an execution platform such as Connect 981, the risk is often organizational rather than technical. Productive patterns include:

• Framing it as the execution fabric, not another system of record that competes with PLM or ERP.
• Aligning with compliance needs: using early pilots to prove that embedded traceability and live status reduce audit effort.
• Anchoring pilots in measurable problems: schedule adherence on a key program, reduced time-to-detect for escapes, or compressed response time to supplier disruptions.

The goal is to build confidence that the execution layer improves control without forcing disruptive rip-and-replace strategies.

Measuring Success of a Digital Manufacturing Architecture

Execution-oriented metrics: visibility, traceability, and response time

Success for this architecture should be measured in execution outcomes, not just IT milestones. Useful metrics include:

• Time required to determine the exact status of any unit or lot on a program.
• Coverage and completeness of digital traceability, including suppliers.
• Average time from issue detection (quality, material, process) to containment and plan adjustment.

These metrics directly reflect whether the execution layer is closing the gap between plan and reality.

Compliance and audit outcomes

In regulated aerospace environments, architecture should also be judged by compliance friction. Indicators include:

• Reduction in manual effort to assemble evidence for audits.
• Fewer late discoveries of missing records or incomplete traceability.
• Ability to answer auditor questions by navigating live data rather than reconstructing history.

When the execution layer is working, audit readiness becomes a byproduct of normal operations instead of a periodic crisis.

Supplier and site adoption indicators

Finally, a digital manufacturing architecture only delivers its full value when suppliers and sites adopt it. Leading indicators include:

• Percentage of critical suppliers providing structured status and genealogy data through defined interfaces.
• Sites using the execution layer as their primary view of work status, rather than private spreadsheets.
• Cross-functional teams (engineering, quality, supply chain) referencing a shared execution view in decision-making.

These behaviors show that the architecture has moved beyond an IT project and become an operational asset.

From Fragmented Systems to a Connected Execution Architecture

Aerospace performance is increasingly determined not by isolated system capabilities, but by how well those systems are connected into a coherent execution picture. PLM, ERP, MES, and QMS each have essential roles, yet none by itself can provide the operational clarity and embedded traceability that modern programs demand. That requires an explicit execution layer—an architecture that treats real-time context, exceptions, and genealogy as primary objects.

By advancing toward this architecture incrementally—program by program, supplier by supplier—organizations can move from the misleading comfort of high-level scoreboards to a grounded understanding of how their production systems actually behave. That shift, more than any single technology, is what will differentiate stable aerospace manufacturers from those constantly surprised by their own systems.