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This Government Contract opportunity from Department Of Defense was posted on May 12, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Predictive Modeling & Digital Twin Development

Closed
Federal

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The contract involves the development of advanced predictive models and digital twin frameworks aimed at simulating manufacturing processes and product lifecycle performance. Utilizing a combination of physics-based methods and artificial intelligence/machine learning techniques, the work will focus on creating high-fidelity simulations to enhance manufacturing efficiency and product reliability. This subcontract is associated with the Department of Defense and is classified under the NAICS code 541690, which covers scientific research and development services. Interested parties must submit their responses by May 22, 2026, with the contract notice having been posted on May 12, 2026. The scope emphasizes cutting-edge technology integration for improving manufacturing simulations, although specific geographical performance locations and detailed agency contacts have not been provided. This effort supports the DoD's strategic initiatives in modernizing manufacturing capabilities through innovative digital solutions.

General Info

Develop predictive models and digital twins using AI for DoD manufacturing process simulations.

Agency

Department Of Defense → W6QK Acc Ccdc Sttc

NAICS

541690 - Other Scientific and Technical Consulting ServicesView NAICS

Place of Performance

FL

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

PhaseClosed
Posted

subcontract

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyDepartment Of Defense → W6QK Acc Ccdc Sttc
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of Defense → W6QK Acc Ccdc Sttc
Office AddressN/A
ContactsNo contact information available

Full Description

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Develop high-fidelity predictive models and digital twin frameworks for simulating manufacturing processes and product lifecycle performance using physics-based and AI/ML methods.