Duisburg bridge components · 2024
Duisburg bridge components, 2024: led process monitoring and control work that enabled unattended builds and coordinated the overall project timeline. Testing was outside his role.
Read the project and my rolePublic work
A public map of my current work that can be referenced safely: professional context, LMD/DED work, public frameworks, tools, research maps, and profile availability.
Public category
Industrial AI & Decision Systems
Core thesis
AI for industrial decisions that need evidence, not just predictions.
Current proving ground
LMD/DED at Exafuse
Boundary
Public technical material only
Professional experience
Manish Sharma is Head of AI & R&D at Exafuse. He leads additive-manufacturing projects across process development, sensing, software, quality checks and delivery.
Duisburg bridge components, 2024: led process monitoring and control work that enabled unattended builds and coordinated the overall project timeline. Testing was outside his role.
Read the project and my roleBuilt an integrated LMD control system spanning modelling, simulation, path planning, camera and sensor monitoring, software, data processing and live control. This work forms part of his doctoral thesis.
Inside the LMD control systemCompany-side project leadership and proposal development, connecting manufacturing requirements with university research.
Read the Exafuse project articlePersonally invited guest lectures, additive-manufacturing advice and contributions to WAAM machine development for rocket-nozzle manufacturing.
Additive-manufacturing advice to Tata Steel and Bharat Heavy Electricals Limited (BHEL), Haridwar, and technical talks at Outokumpu and Data Science Ruhrgebiet.
Built Exafuse's website, presenting industrial services, technical case studies and tools for preparing engineering enquiries.
Visit ExafuseEstablished work
This is the deepest current public proof for my broader Industrial AI & Decision Systems work: AI for Laser Metal Deposition and Directed Energy Deposition at Exafuse.
Established work
Public work around monitoring signals, anomaly review, and inspection-aware evidence boundaries.
Established work
Vision and signal interpretation for LMD/DED process understanding.
Established work
Public profile context around robotic DED/LMD systems and toolpath workflows.
Established work
Repairability screening, RFQ structure, cladding, machining allowance, and inspection planning.
Established work
Schemas, prompts, decision rules, and missing-information checks for LMD requests.
Documented examples
Each story keeps the industrial problem, public source and scope together. The Duisburg page also includes my personal account of monitoring, control and timeline responsibility. Company project results remain attributed to Exafuse.
Exafuse public case
Large structural metal components for a pedestrian bridge in Duisburg.
For large LMD, manufacturability, toolpaths, monitoring, finishing, and verification must be planned as one decision system.
Useful decision pattern
Large-scale LMD requires evidence planning, monitoring context, and an inspection boundary.
It is not a blanket approval for another bridge or safety-critical component.
Exafuse public case
A high-value extrusion screw in a production environment with no immediate replacement available.
Repair evidence starts by defining what must be removed, rebuilt, finished, and inspected—not by covering a visible defect.
Useful decision pattern
Repair/RFQ quality depends on complete facts, downtime context, and service context.
It does not establish certified performance, exact tolerance, or service-life extension.
Exafuse public case
Anonymous valve-seat and wear-ring geometries with wear-critical functional surfaces.
A visible inspection result is useful evidence only when it is attached to geometry, material, heat, finishing, and acceptance context.
Useful decision pattern
Surface function needs material, heat, finishing, inspection, and acceptance context.
It does not guarantee crack-free performance for another material, substrate, or ring geometry.
Exafuse public case
A public 130 mm drill demonstrator in the Exafuse build-and-coat context.
Geometry, surface function, material compatibility, finishing, and verification should be prepared as one route.
Useful decision pattern
Build-and-coat routes need geometry, surface function, material, finishing, and validation.
It does not certify performance for another drilling application.
Public framework
Working tool
Public evidence
Public artifact
Public profile links
Public Exafuse context
Identity path