Digital Twins and the Rise of Design Thinking

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Metrics to meaning

For years, sustainability in manufacturing has revolved around metrics — energy use, water intensity, emissions per unit of output. They remain necessary, but they do not explain how a product lives or dies. What matters now is the structure of industrial systems: how design choices echo through use, repair, and reuse.

This is where digital twins are starting to make a different kind of impact. Once tools for predictive maintenance or factory throughput, they are evolving into engines for circular design thinking — dynamic models that map not just production but disassembly, remanufacture and material return.

The newest frameworks, such as the Bi-Flow Product-Process-Resource Asset Network (Bi-PAN) developed by researchers studying battery disassembly, show how twins can guide circular practice from the outset. 

From simulation to lifecycle integration

A traditional digital twin mirrors a process: a virtual clone of a machine or plant updated by sensor data. Bi-PAN adds another dimension. It connects forward and reverse flows of product, process and resource information, linking how something is made with how it will be un-made.

When applied to electric-vehicle batteries, the model simulates how pack architecture, fasteners, adhesives and cooling layouts influence the ease, safety and yield of disassembly. The same parameters that optimise assembly for speed may hinder recovery later. By modelling both directions, engineers can visualise and quantify trade-offs before a design is frozen.

That is a cultural shift. The twin ceases to be a record of what happened; it becomes a forum for negotiation between design, operations and sustainability.

What circular twins reveal

The approach yields insights that go beyond sustainability rhetoric.

• Recovery economics: modelling reveals where a small material change could cut disassembly time or contamination, raising recovery yield.

• Design modularity: the twin can show how redesigning battery modules into sub-assemblies affects automation of reuse.

• Workforce and safety: process mapping highlights where manual disassembly carries risk and where automation is justified.

These are practical levers — not moral arguments but business ones. They align profitability with responsibility, a combination manufacturing has long claimed but rarely proven.

Why the timing matters

Circular-economy policy is no longer theoretical. The EU’s Battery Regulation (2023) mandates material recovery targets and digital product passports by the end of the decade. 

OEMs and tier suppliers face an unavoidable question: redesign now or retrofit later at higher cost?

Digital twins offer the bridge. They make compliance proactive, not reactive. Instead of discovering recyclability problems when products hit the end of life, teams can see them years earlier in simulation.

Joining the dots between design and recovery

Adopting a circular twin is less about technology than leadership. It demands that functions that rarely speak — design, manufacturing, service, recycling — share data and objectives.

Leaders must decide who “owns” the twin. In most firms it starts in engineering, but true value emerges when procurement, quality and sustainability have access too. For example:

• Procurement can test how a supplier’s material affects downstream disassembly.

• Operations can anticipate future recovery volumes and plan reverse logistics.

• Sustainability teams can use twin data for regulatory reporting instead of post-hoc estimates.

In effect, the digital twin becomes a living governance model — a shared source of truth on circular performance.

Practical starting points 

1. Map a single product line. Begin with high-value components such as batteries, motors or printed-circuit assemblies.

2. Capture empirical data. Use teardown studies to feed accurate process times, tool requirements and recovery yields.

3. Build feedback loops. Connect design software and PLM systems so lessons from disassembly feed back into the next design generation.

4. Quantify benefit. Track reduced waste handling, material recovery income and compliance savings.

Pilots following this method typically reveal both quick wins (fewer adhesives, better fastener choices) and long-term insights (module standardisation across models).

Ownership to stewardship

Circular twins change the psychology of manufacturing. They re-cast teams from owners of assets to stewards of material flows. That shift can be uncomfortable. Engineers trained to design for performance must also design for undoing. Managers accustomed to linear throughput must value reversibility.

Forward thinking companies use training programmes that pair design engineers with recycling experts for short rotations. The result is empathy — and more pragmatic design decisions. The technology alone cannot deliver that; leadership tone does.

Barriers and realism

Not every manufacturer is ready. Barriers include:

• Data fragmentation — PLM, MES and sustainability databases rarely align.

• Supplier opacity — tier networks may resist sharing proprietary material data.

• Skills gap — few engineers understand both product architecture and recovery systems.

• ROI perception — benefits accrue over lifecycle, not quarterly reports.

Each obstacle is manageable but requires governance. Successful firms treat the twin as core infrastructure, budgeting for its maintenance like a production asset rather than a project.

Case parallels

Outside batteries, similar principles are emerging. White-goods manufacturers use twins to optimise plastics separation. Aerospace firms model part traceability for certified reuse. Even consumer-electronics companies are mapping adhesive use to automate screen disassembly.

These examples share one rule: data continuity across the product lifecycle. Once achieved, design, production and recovery cease to be distinct silos — they become one circular system.

Final thought: Modelling the future we intend to build

Digital twins were born to improve efficiency; they may end up redesigning responsibility. By embedding disassembly, reuse and recycling logic into design itself, manufacturers can anticipate environmental outcomes rather than apologising for them later.

For leadership teams, the message is pragmatic. Circularity is not a slogan — it is a design constraint that can be simulated, measured and optimised. The firms that master it first will meet regulation smoothly, recover more value and command greater trust.

When your design and recovery data speak the same language, sustainability stops being a separate conversation. It becomes how you build.