What’s Next for Connected Product Development and Manufacturing
At Nora IPLM Lab, we are developing new ways to manage engineering changes, bring AI into practical PLM workflows, reuse product structures more efficiently, align engineering and manufacturing, connect product knowledge, and control configurations.
Modern product work needs a faster-moving PLM partner
Product teams manage increasingly complex BOMs, variants, requirements, suppliers, documents, changes, and manufacturing processes. Traditional PLM systems can govern these records, but the relationships between them are often difficult to understand when a decision must be made quickly.
Nora IPLM Lab is where we turn those challenges into active product development. We are building on a governed product lifecycle management foundation, testing several improvements at once, and bringing the strongest ideas closer to real product work.
Multiple PLM capabilities moving forward in parallel
This is a working development portfolio, not a single technology campaign. Nora IPLM Lab turns high-value engineering, manufacturing, and product-data problems into focused product work, with each evaluated for practical value, governance, usability, and readiness to grow into the platform.
Change Cockpit for Engineering Change Impact Analysis
Engineering change reviews become difficult when affected BOMs, documents, requirements, manufacturing processes, and service records are spread across separate views. Reviewers may approve an ECO or ECR without a complete picture of downstream risk.
Nora’s product team is actively developing the Change Cockpit as an engineering change management workspace that brings impact, ownership, decisions, approvals, and implementation readiness into one governed review.
Accelerate ECO and ECR reviews with connected product context
See affected BOMs, documents, requirements, processes, and service data before release
Capture traceable decisions, ownership, approvals, and risk signals
Reduce downstream manufacturing, quality, and service surprises
Coordinate engineering, manufacturing, quality, and service teams
Selective Structure Clone for Controlled BOM Reuse
Creating a new product or variant from an existing structure can save time, but uncontrolled copying creates duplicate product data, unclear ownership, and disconnected lifecycle records.
The team is actively designing Selective Structure Clone to support controlled product structure reuse. Teams would be able to choose whether each object is cloned, kept as an existing reference, or excluded; carry over approved configuration context; and review the resulting structure before creation.
Set up new products, programs, and variants faster
Choose clone, keep-as-is, or exclude behavior by object or subtree
Reuse approved objects without duplicating product data
Preview the target structure, configuration scope, and effectivity carryover
Apply consistent product-data governance to reuse workflows
MBOM Cockpit for Manufacturing Context and Release Readiness
Turning an engineering definition into a build-ready manufacturing structure requires more than copying an EBOM. Teams need to manage plant context, item allocations, lifecycle states, effectivity, resource dependencies, and readiness checks together.
At Nora IPLM Lab, we are developing the MBOM Cockpit as a governed workspace for creating and validating manufacturing contexts, reviewing EBOM-to-MBOM deltas, and coordinating release readiness.
Compare engineering baselines with manufacturing contexts and resolved MBOMs
Track added, modified, replaced, and deleted items across revisions
Coordinate MBOMs, process plans, resources, work instructions, and ERP or MES packages
Surface blocking checks and warnings before approval
Preserve lifecycle, effectivity, and change traceability
Manufacturing Process Management and Digital Twin Planning
Once an MBOM defines what will be built, teams still need to define how it will be built. Operations, sequences, work centers, resources, instructions, cycle times, and production constraints must remain connected to product and change context.
At Nora IPLM Lab, we are developing Manufacturing Process Management to plan the bill of process, allocate resources, simulate production scenarios, and evaluate the effect of engineering or manufacturing changes before release.
Create and manage operations, sequences, work centers, tools, and resources
Link process plans and work instructions directly to the MBOM
Evaluate production scenarios through digital-twin simulation
Review cycle time, throughput, WIP, energy use, and production constraints
Understand how product changes affect manufacturing execution
Knowledge Thread for Connected Product Context
Critical product context extends beyond a BOM tree. Items connect to suppliers, drawings, issues, baselines, attachments, changes, processes, configurations, and service records, yet these pathways can be difficult to follow across separate views.
Nora is building Knowledge Thread as an interactive, relationship-aware workspace for exploring upstream and downstream product context. It is designed to strengthen discovery, impact analysis, and AI-assisted PLM with visible, governed source relationships.
Explore upstream and downstream relationships from the active product object
View items, suppliers, drawings, issues, baselines, and attachments together
Highlight or filter relationships by object type, lifecycle state, and attributes
Reveal change pathways, dependencies, risks, and reuse opportunities
Give Nora Prima AI traceable product context for stronger explanations
Configuration Cockpit for 150% and 100% BOM Control
Configurable product families introduce complex option rules, effectivity conditions, market requirements, and order-specific structures. Duplicating a product definition for every variation increases maintenance effort and weakens traceability.
The team is actively developing the Configuration Cockpit as a focused product configuration management workspace for comparing variants, validating rules, reviewing effectivity, and resolving an accurate 100% BOM from governed 150% BOM logic.
Compare product variants, features, options, and rule outcomes
Validate configuration logic and effectivity before release
Resolve accurate 100% BOMs from controlled 150% BOM structures
Reduce duplicate product definitions across markets, models, and orders
Connect configuration decisions with lifecycle traceability
Nora Prima AI Phase 2 for Context-Aware PLM Work
The next phase of AI in PLM needs to do more than answer general questions. It should understand the product, structure, change, document, or workflow a user is working on and provide useful support without losing governance or traceability.
At Nora IPLM Lab, we are developing Nora Prima AI Phase 2 around focused, context-aware assistance that can analyze product data, surface opportunities, prepare structured outputs, and help users move through controlled PLM workflows.
Work with the active BOM, change, document, project, or product context
Identify part reuse, duplication, and standardization opportunities
Summarize change impact, risks, dependencies, and open decisions
Prepare structured drafts and recommendations for user review
Keep human approval, source context, and lifecycle traceability visible
From real product problems to practical capabilities
Nora IPLM Lab is where we research, prototype, and evaluate new capabilities for product development and manufacturing. Every concept begins with a specific workflow problem and is tested for usability, connected data, governance, technical feasibility, and practical value before it can become part of the platform.
What we start with
- A specific engineering or manufacturing task that needs improvement
- The people, systems, and product data involved
- Where decisions, handoffs, or approvals slow the work down
- The governance and traceability the workflow must preserve
- A clear outcome worth improving
What we evaluate
- Whether the capability is understandable and useful in day-to-day work
- How well it connects product, manufacturing, and process context
- Whether ownership, approvals, and lifecycle history remain visible
- Technical feasibility, performance, and scalability
- Evidence that it can reduce effort, risk, or delay
Have a complex PLM workflow worth exploring?
Share the product-data, change, manufacturing, or configuration problem with the Nora IPLM team.
Active product development grounded in real PLM work
Nora IPLM Lab developments are evaluated against practical engineering, manufacturing, product-data, and lifecycle-governance outcomes.
Connected by default
Every capability should strengthen the digital thread across BOMs, changes, requirements, documents, suppliers, and processes instead of creating another isolated workflow.
Visible before automated
Teams should receive explainable context, impact, ownership, and risk visibility before AI or workflow automation acts on complex lifecycle decisions.
Flexible with governance
Experiences should support different product structures and processes while preserving ownership, traceability, approvals, and lifecycle control.
From product problem to validated PLM capability
Every Nora IPLM Lab concept is evaluated against real engineering, manufacturing, and product-data workflows before it becomes a product capability. Concepts may evolve, combine, or change before release.
Discover
Define the workflow problem, affected teams, connected product data, and outcome worth improving.
Prototype
Test interaction patterns, lifecycle relationships, governance needs, and technical feasibility.
Validate
Evaluate the concept against representative BOM, change, configuration, and manufacturing workflows.
Productize
Refine usability, performance, governance, documentation, packaging, and release readiness.