Bharat in Betastartup field guide
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No. 748Problem statementManufacturing and materials

AI powered Hull-form optimization

Source

Source summary

Develop AI-assisted hull-form design using knowledge from existing hulls and their design relationships. The source contrasts this with manually modifying reference lines or using standard series, and asks for candidates meeting technical and operational requirements, including hull forms beyond those already built. A suggested form still requires naval-architect assessment; novelty is not proof of performance.

No. 026Existing businessManufacturing and materials

Specialty-chemical development platforms

Digitizing chemical R&D and compliance; Scimplify is the cited example.

No. 747Problem statementManufacturing and materials

Development of indigenous ship design Software

Develop secure, modular indigenous ship-design software covering concept through production for Indian defence shipbuilding. The source identifies dependence on imported proprietary tools for hulls, stability, structures and performance, along with licensing cost, export-control and support concerns. The platform should accommodate Indian design/classification rules and lifecycle support. These are proposed capabilities, not proof of an existing domestic replacement.

No. 749Problem statementManufacturing and materials

AI-Based Detection and Classification of Protective Coating Defects in Defence Platforms as per AMPP NACE SSPC ISO Standards

Develop AI inspection of protective coatings using images or video to detect, classify and grade defects against AMPP/NACE/SSPC/ISO frameworks. Named defects include rusting, blistering, cracking, peeling, pinholes and other application faults. The source addresses observer variability, weak documentation, difficult large-area inspection and work-at-height/confined-space exposure on defence platforms. Its desired objective and auditable assessment still needs validation.