Industrial AI & Decision Systems LMD / DED proof domain Decision support only

Manish Sharma Lab

AI for Laser Metal Deposition decisions you can verify.

I build inspection-aware AI frameworks, RFQ tools, and process-monitoring notes for LMD/DED, repair, cladding, and metal additive manufacturing - grounded in public Exafuse work and bounded by engineering evidence.

Decision support only. Not final engineering approval.

Input

a rough LMD question

Output

Decision Brief v1.0

Boundary

review-ready, never approval

Active module

Decision Cockpit

  • Local session
  • No backend
  • Decision-support only
LMD Decision CockpitLMD Decision Brief v1.0No input tracking

Start with a rough LMD question. Leave with a brief.

Pick the situation, mark what is known, then expose missing information, risk flags, evidence needed, and an Exafuse review route. Inputs stay in this browser session only.

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Public-safe dummy example: worn steel shaft near bearing seat.

Review the worked output, start your own brief here, or open the full workbench.

Repair damaged/worn part: start with LMD Repairability Quick Check. Not enough information. Missing information and risk flags remain visible in the brief.

Thesis: a signal is not proof

Sense -> Model -> Decide -> Verify

A signal is not proof. Process signals can support review. They do not replace inspection, testing, expert review, or release evidence.

Flagship assets

Start with the three LMD decision assets

These are the shortest route from a vague LMD/DED question to a structured decision-support workflow.

Public proof

Public proof that anchors the LMD/DED domain

Company-owned case details and RFQs belong to Exafuse. Manish Sharma Lab uses these only as public context for frameworks, monitoring, repairability, RFQ structure, and evidence boundaries.

CS15 Public Exafuse source

Duisburg Bridge Components

750 kg+ components6 structural nodes219 h single-node buildapprox. 38 km robot path1M+ melt-pool imagesKIT validation context
Decision it helps
Helps decide how much evidence is needed before large-part LMD monitoring data becomes a defensible engineering discussion.
Source status
Source link pending until Exafuse production migration
What it proves
Public context for large-part LMD scale, monitoring, validation, and inspection planning in one documented Exafuse case.
What it does not prove
It does not prove that monitoring alone certifies quality or that this site can approve structural parts.
Related framework
LMD Quality Evidence Ladder
Decision pattern extracted
Large-scale LMD requires evidence planning, monitoring context, and an inspection boundary.

This is a pattern, not a transfer of feasibility.

CS01 Public Exafuse source

Forging Hammer Repair

local wear repair
Decision it helps
Helps decide whether local wear repair should move into expert review instead of becoming an automatic repair claim.
Source status
Source link pending until Exafuse production migration
What it proves
Public context for local wear repair, material strategy, finishing, and release-evidence planning.
What it does not prove
It does not prove every hammer or safety-critical part is repairable.
Related framework
LMD Repairability Index
Decision pattern extracted
Local repair needs material, damage depth, machining route, and inspection plan.

This is a pattern, not a transfer of feasibility.

Personal expert layer

Use this site for public frameworks and AI-readable guidance.

The useful paths are thesis, tools, proof context, agent files, and evidence-bound LMD/DED frameworks.

Commercial boundary

For services, RFQs, and company claims, use Exafuse.

This personal site avoids confidential employer/customer data and does not replace expert review, inspection, certification, or formal approval.