Steve Evans

Comparing geometry can reveal both exact duplicates and near-matches, giving engineers a chance to reuse or consolidate parts before each version generates more drawings, purchasing records and maintenance work. They present near-duplicates—not just identical files—as the more valuable problem to investigate.

In one post, Evans describes a bracket with different hole patterns and a component with slightly different dimensions as near-duplicates worth reviewing.

• They give an illustrative calculation: 7,500 parts needing rationalisation, at two hours per part and £60 per hour, would represent £900,000 in potentially avoidable engineering effort.
• The post frames this as an estimate, not a verified saving.

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Their reasoning is that technicians need to know what is actually fitted and what has happened to it, while failure and inspection data should inform future engineering decisions. In this framing, the digital twin is the current virtual representation; the thread keeps its information connected and updated.

Evans describes linking engineering and manufacturing bills of materials to a service bill of materials, so technicians can see modified parts, serial histories and active airworthiness directives or service bulletins. They also give the example of a component failing at 2,000 flight hours rather than its rated 5,000, with that field evidence fed back to engineering.

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They make the case that accurate original geometry can help replacement parts fit, give repair teams a clearer structural reference and support analysis of ageing airframes. The argument links the quality of the digital model to practical maintenance decisions.

Evans describes turning 1,211 full-scale master loft drawings for the BAE Systems Hawk into a 3D model. The post says technicians could use the model to locate structural elements, compare scan data when assessing damage, and support replacement-part manufacture and life-extension analysis.

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It explains what a 3D digital twin of an old airframe contains and why original 1:1 loft lines matter for physical fit.

The post describes converting 1,211 1:1 master loft drawings for the BAE Systems Hawk into a high-fidelity 3D digital model.

• It lists MRO benefits: on-demand spare parts and first-time-right fit; faster structural repair and damage assessment; assisted-reality work instructions; and FEA and life-extension analysis.
• It includes an enquiry email.

For brands planning a campaign

A technical collaboration on digital thread or 3D model-based maintenance could use this as a proof point for handling original geometry rather than generic CAD conversion.

Defines the digital thread as a communications framework linking design, manufacturing, field operations and MRO.

• It connects the engineering BOM to the service BOM, describes closed-loop feedback from field failures to OEM engineering, and presents the digital twin as a virtual model kept current by the thread.
• It also covers connected technicians with smart glasses, automated inspection and logistics alerts.
• Contact details included.

For brands planning a campaign

For a digital-thread content collaboration, the post supplies useful terminology and examples: sBOM, airworthiness directives, service bulletins and closed-loop failure data.

Argues that searching 3D shape, rather than filenames, part numbers or descriptions, is the best way to reduce duplicate parts.

• It distinguishes exact duplicate files, duplicate physical geometry under different files or part numbers, and near-duplicate geometry.
• A bracket with different hole patterns serves as an example.
• The post reports that ShapeSpace grouped 1,000 CAD files into 650 unique designs and 350 duplicate or near-duplicate files.
• An ROI example calculates 7,500 duplicated parts × 2 hours × £60/hour = £900,000 of potentially avoidable engineering effort.
• Enquiry email included.

For brands planning a campaign

A campaign could focus on measurable duplicate reduction after mergers, acquisitions or PLM/PDM migrations, with shape search as the differentiator.

Calls duplication the “silent killer” of PLM efficiency, saying it happens when engineers cannot find an existing bracket or screw and design a new one.

• Lists the downstream effects: more engineering overhead, weaker procurement scale, extra inventory, tooling changes and quality control.
• Cites an industry benchmark it calls the Rule of Ten: roughly $10,000 to $25,000 to maintain a part over its lifecycle for every $1 spent on initial design.
• It says deleting 100 duplicate parts could save over $1M.
• Contact details included.

For brands planning a campaign

Useful for a PLM ROI explainer or buyer-facing post on why duplicate-part cleanup belongs in a PLM migration plan. The post presents the Rule of Ten as a common industry benchmark; ask for audited savings data before using it as proof.

Frames the shift from 2D drafting to 3D CAD as a change in methodology, while noting that 2D drawings still serve final shop-floor inspection and legal documentation.

• Covers simulation and digital twins (CFD, FEA), model-based definition, interference and clearance checking, faster prototyping, generative design that can cut bracket or engine-mount weight by 30-40%, and global supplier collaboration.
• Says regulators such as the FAA and EASA increasingly accept 3D data for certification by analysis.

For brands planning a campaign

A technical explainer series could contrast 2D and 3D workflows for aerospace manufacturers, using model-based definition and clash detection as concrete entry points.

Reports a Magic Leap 2 market withdrawal notice: under Commission Delegated Regulation (EU) 2022/30 supplementing the Radio Equipment Directive, Magic Leap 2 enterprise devices are said not to fully meet updated legal requirements.

• Sales and deliveries stop in the EU and UK effective immediately.
• Resellers and distributors are told to stop sales and return remaining inventory.
• Devices sold before 1 August 2025 remain compliant at time of sale, no recall is required, and support and warranty commitments continue.

For brands planning a campaign

For a brief involving AR or wearable maintenance tools, check regional compliance and deployment timing before planning a pilot.

A short personal reflection: 25 years earlier, Steve Evans was traveling to CSC in Farnborough to meet Procurement Director Sandra Paton. They recall sitting in a meeting room with other CSC directors, the TV on and no one talking, before ending with “RIP all those who died on that tragic day.”

For brands planning a campaign

This has limited direct campaign use.

• It may inform tone or background for a collaboration involving long-standing procurement relationships.
• Ask for evidence of current technical capability.

Asks why a government interested in British manufacturing would use Chinese steel for a major UK project.

• Calls the situation ironic because the project is a Green Power Plant.
• The post includes a link but offers no further argument.

For brands planning a campaign

Not a technical work sample. It matters only if a brief touches on UK industrial policy, procurement sourcing or public commentary.

The operational case is that re-manufactured parts can be exported straight to CNC, additive or sheet-metal processes and fit first time because they carry the original loft lines; technicians can inspect the whole structure in one digital environment instead of cross-referencing dozens of 2D sheets; scan data can be overlaid on the model to assess damage and concessions; lighter 3D assets can be served to headsets for hands-free work instructions; and finite element analysis supports life-extension programmes on airframes past their original design life. The post's core claim is that the loft geometry, not a re-drawn approximation, makes replacement parts and simulations trustworthy.

For brands planning a campaign

This is the strongest match for an MRO software brief on digital thread and 3D model-based maintenance.

• A collaboration could explore one legacy platform build in depth: which drawings were digitised, how the model was validated against the physical aircraft, and what changed for the maintenance and spares teams.
• The post shows Steve Evans can frame the buyer case as well as the engineering steps, keeping both audiences in view in a technical piece.

Examples: Source 1

It names the components: bridging engineering and manufacturing bills of materials into the service bill of materials so technicians see modified parts, serial histories and active airworthiness directives or service bulletins; feeding field failure data back to OEM engineering when a component fails earlier than rated; using the thread as the pipeline that keeps a digital twin current; streaming spatial data to smart glasses for context-aware 3D overlays and digital sign-off; pushing non-destructive testing results into asset records and work orders in systems such as IBM Maximo or SAP; and alerting logistics systems, including defence LCST frameworks, to pre-stage spares before arrival.

Defines the concept in one paragraph, then works through core components as a named list, using specific enterprise and defence system names rather than vague categories.

For brands planning a campaign

Directly useful for a digital-thread content programme.

• The framing is supplier-neutral and grounded in systems a maintenance buyer already recognises, making it easy to adapt into a joint piece.
• It is explanatory, with no case data or measured outcomes; ask the brand to supply proof points.

Examples: Source 1

One explains detection by geometry rather than filenames or part numbers: identifying the same 3D component stored under different names, which matters after mergers, acquisitions or PLM/PDM migrations, and finding parts that are geometrically very similar but not identical—the same bracket with different hole patterns, or a component differing slightly in dimensions.

• It describes searching by 3D shape so a designer can find an existing part before creating another, and grouping a library into unique designs and duplicate or near-duplicate files.
• It reports a previous manufacturing data cleanse of about 40,000 parts, including roughly 7,500 exact duplicates and another 4,000 near duplicates.
• The companion post makes the business case: fewer part lifecycles to manage, less documentation and change activity, volume buying instead of fragmented purchasing, less warehouse space and tooling change, and easier quality control.
• It cites a 'Rule of Ten' benchmark: a part costing $1 to design costs roughly $10,000 to $25,000 to maintain over its life.
• A worked example calculates that handling 7,500 duplicates at two hours each and a £60/hour loaded engineering rate amounts to about £900,000 of avoidable effort.

The savings figures are illustrative assumptions—'suppose you have'—and the 40,000-part example is described as previously reported by GemDT, not as an audited customer outcome. Treat them as a framework for a buyer's own numbers, not verified results.

For brands planning a campaign

This is a concrete, quantified topic a brand can build on, and the geometry-search method offers a more specific technical angle than generic 'reduce part count' messaging. The method is well described, but the ROI figures need the brand's own customer evidence before reuse.

Examples: Source 1 · Source 2

It covers simulation and digital twins through computational fluid dynamics and finite element analysis; model-based definition, where tolerances, materials and surface finishes sit in the model as a single source of truth rather than being re-interpreted from drawings; automatic propagation of a dimension change through assemblies and bills of materials; clash detection and virtual assembly planning in dense airframes; rapid prototyping and generative design, with a claim that AI-driven tools can cut bracket or engine-mount weight by 30–40%; and global supplier collaboration plus FAA and EASA acceptance of 3D data for certification. It ties the argument back to the Hawk.

Structured as a numbered benefits list, moving from simulation through documentation, assembly, prototyping and collaboration, with technical terms spelled out on first use.

For brands planning a campaign

Useful as an accessible explainer alongside a deeper platform-specific piece, and evidence that Steve Evans can write for a mixed technical and commercial audience. The 30–40% weight-reduction figure is asserted without a source; ask the brand for evidence before reusing it.

Examples: Source 1

The stated reason is Commission Delegated Regulation (EU) 2022/30 supplementing the Radio Equipment Directive, after which Magic Leap concluded the enterprise devices do not fully meet the updated legal requirements. The notice says devices sold before 1 August 2025 complied at the time of sale and can continue to be used, no recall is required, support and warranty commitments continue, and remaining reseller inventory may be returned to Magic Leap.

For brands planning a campaign

This documents GemDT's channel role for the AR hardware used in hands-free maintenance work, relevant to brands considering a spatial-computing or assisted-reality programme with Steve Evans. It is a product and compliance notice rather than thought leadership, so it works better as context for a partnership discussion than as content to adapt.

Examples: Source 1

It links to a supporting article. The post comments on procurement and industrial policy rather than developing an argument.

For brands planning a campaign

Shows a willingness to post political and domestic-sourcing opinions.

• For a partnership, weigh the tone and risk: posts can shift from technical commentary into policy debate.
• Decide in advance whether that range suits the brand.

Examples: Source 1

Steve Evans recalls travelling to CSC in Farnborough to meet Sandra Paton, then Procurement Director, and sitting in a meeting room with other CSC directors, the television on and nobody talking. The post closes by remembering those who died.

This is a personal post, not work-related content. It provides career background, not evidence of subject-matter expertise, so don't present it as professional content.

For brands planning a campaign

Places Steve Evans's career in a defence and IT procurement context around 2001, supporting credibility with MRO and defence buyers when explaining why they are worth working with. Keep it as background framing rather than a campaign theme.

Examples: Source 1

They do not say whether they own or work for GemDT; ask them to clarify their affiliation.

View example

This documents a GemDT reseller/distributor relationship with Magic Leap. Steve Evans's relationship to GemDT is not stated; ask them to clarify their affiliation.

Original disclosure

As a reseller/distributor, all sales must be stopped and any remaining inventory may be returned to Magic Leap.

View example

Ask GemDT to clarify whether ShapeSpace is its product or a commercial relationship.

View example

The post names the aircraft platform but not a direct commercial relationship with BAE Systems; ask GemDT to clarify whether one exists.

View example

Adavani sets out live links from PLCs, MES systems, IoT sensors and inventory databases, then lists production scheduling, bottleneck identification and predictive maintenance as uses. Evans applies the same approach to aircraft, tying engineering records to maintenance and spares decisions.

Adavani writes about the factory floor and frames digital twins as a maturity ladder, from descriptive models to higher levels, using general manufacturing examples and industry statistics. Evans stays within aerospace engineering, where the argument turns on the accuracy of original geometry in legacy drawings and on airworthiness and configuration records rather than production throughput.

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Evans makes the same case for MRO, where technicians need to know what is actually fitted and what has happened to it rather than reinterpreting disconnected records.

Ziegler writes from trade shows and vendor booths, focusing on robotics and CNC automation, with a standing partner relationship with the vendor whose equipment he describes.

• He reports on machines, controls and robot programming in person.
• Evans writes from a software and product perspective about part data, duplicate detection and legacy airframe digitisation, drawing examples from projects rather than show-floor demonstrations.

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His rule—AI interprets, engineering logic calculates, humans verify—matches Evans's approach to geometry search: find what an existing model actually contains before anyone designs again. Both also list practical automations and specify which parts should still be reviewed by an engineer.

Murtaza focuses on facade and curtain-wall design and fabrication, with examples spanning Revit families, flat-pattern conversion and factory dashboards rather than airframes. His framing is more AI-first, built around what a current model can be trusted to identify, while Evans emphasises measured geometry and configuration records.

Read original · Original 2

The two posts build a sequence a general reader can follow: what a factory digital twin is, which data feeds it (PLC, MES, IoT and inventory data), what it supports (production scheduling, bottleneck finding, layout testing, predictive maintenance and workforce planning), and a level-by-level taxonomy for automotive — asset modelling, physics-based engineering simulation and VR design reviews, with the argument that virtual models replace expensive physical development hardware.

• The post cites a McKinsey article for the claim that 86% of manufacturing executives see practical applications and 44% already implement them, giving a vendor an opening statistic for an operations-facing series.
• This is a reasonable second voice for the same campaign connecting engineering and maintenance through a digital thread if the brand wants the manufacturing-operations framing before the maintenance detail.

Neither post reaches the campaign's aerospace and maintenance needs.

• There is no airframe content, MRO configuration management, service bill of materials, loft or CAD geometry, or worked cost case comparable to the part-rationalisation estimate in Evans's work.
• A joint piece would need the vendor to provide the aerospace and maintenance detail — airworthiness directives and service bulletin tracking, spares pre-staging, repair substantiation — because the posts do not cover it.
• The writing works at the level of summarised bullet frameworks and a cited consultancy article, rather than close description of one platform project, leaving less for a reader to inspect against a real system.
• Ask for audience data and partnership terms to assess reach and commercial fit.

Examples: Source 1 · Source 2

Ziegler when the campaign needs a vendor-sponsored showcase of named production software and machine tools, with a distribution channel attached.

• Both posts are marked as sponsored Siemens partner content — one from a trade-fair booth, one from the Siemens plant in Chemnitz — and each walks a reader through a named chain: AI-assisted design in NX, planning in Teamcenter, CNC programming with NX CAM Copilot, verification in a digital twin, machining on HELLER machine tools running SINUMERIK One and predictive maintenance through Senseye, for an aerospace oil pump and turbine blade; and a machine-tool robot whose kinematics run inside the CNC control so machinists programme it in the G-code they already know.
• Both posts end with an invitation to a weekly robotics newsletter, giving a buyer an owned-audience route beyond the post itself.
• This is the closest of the three to the campaign's need for a technical-content format and shows a working sponsorship arrangement.

The posts are sponsored showcase writing about one vendor's demonstrations, not a customer account of a repair, overhaul or airframe-support programme.

• The performance figures and capability claims come from the sponsor, so a competing MRO vendor would be asking a creator to write around a rival's stack; that requires a clear firewall and its own disclosure wording.
• Neither post covers legacy aircraft, loft digitisation, part rationalisation or maintenance configuration, so a joint piece on model-based maintenance for an ageing fleet would still rest almost entirely on the brand's case.
• Ask for the rate card, deliverable list, disclosure example, approval process and audience data before assessing the partnership.

Examples: Source 1 · Source 2

The posts carry a practical automation list with an explicit four-week implementation claim (tendering pipelines, sketch-to-detail generation, drawing comparison and redlining, mobile DWG viewing and defect tagging, 3D-to-flat-pattern conversion, connected factory dashboards), and a clear statement of the AI boundary a technical buyer can test: let AI interpret messy Revit models and flag misclassified elements, keep engineering logic doing the geometry and calculation, and keep humans verifying the result. For a vendor whose product also touches construction modelling and drawing control, that is usable raw material with a stated method.

The domain is a step away from a campaign on the digital thread across engineering and service bills of materials, airframes or MRO.

• Nothing in the two posts addresses those areas, and the audience is facade, curtain-wall and BIM practitioners rather than defence and aerospace maintenance, engineering and procurement readers.
• The four-week claim for six workflows is a time-boxed assertion a vendor would have to substantiate or soften before attaching its name to it.
• The AI discussion is framed as ongoing testing against messy real project data, so results are not yet established.
• Ask for audience data and partnership terms to assess reach and commercial fit.

Examples: Source 1 · Source 2