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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

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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NAICS: 541690
New
RFQ6082 Noise Compliance & Air Quality Testing Services
Solicitation # RFQ6082
Management & Training Corporation (MTC) is soliciting bids for industrial hygienist services to conduct noise compliance and air quality testing at the San Diego Job Corps Center in Imperial Beach, California. The scope of work involves full-day monitoring and reporting from 7:00 am to 4:00 pm, specifically targeting Building 13 hard-trades shops and Building 225A welding shop. The selected contractor must perform a noise compliance audit based on OSHA 29 CFR 1910.95 and ANSI standards, as well as air quality assessments for particulate matter, welding fumes, VOCs, combustion gases, and ventilation performance in accordance with OSHA, ACGIH, and EPA standards. Deliverables include comprehensive Noise Compliance and Air Quality Compliance reports submitted in PDF format via email. This is a fee-for-service subcontracting opportunity under NAICS code 541690, open to various small business set-asides including SDB, WOSB, HUBZone, VOSB, and SDVOSB. Bidders must submit a lump sum fee via a bid sheet, along with a completed supplier packet containing a W-9, self-certification form, and proof of insurance by September 16, 2026, at 3:00 PM PST. The contract requires adherence to Service Contract Labor Standards and prevailing wage determinations for San Diego County. Award selection will be based on the best value as determined by MTC. Contractors must also comply with federal regulations regarding the protection of sensitive information and the Buy American Act.
San Diego Job Corps Center

POSTED

about 10 hours ago

DEADLINE

in 5 days

AI Contract Overview

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The contract seeks the development of high-fidelity predictive models and digital twin frameworks to simulate manufacturing processes and product lifecycle performance through the integration of physics-based modeling and artificial intelligence or machine learning techniques. The effort aims to enhance accuracy in forecasting system behavior, optimize production workflows, and improve product reliability by creating dynamic, data-driven digital replicas of physical systems. This subcontract is issued under NAICS code 541690 and is solicited by the Department of Defense through its agency W6QK Acc Ccdc Sttc. The response deadline is May 22, 2026, with the solicitation posted on May 12, 2026. The place of performance and point of contact details are not specified, and no set-aside classification is indicated. Interested parties must submit proposals through the official SAM.gov portal before the deadline to be considered for award.

General Info

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

Agency

Department Of Defense → W6QK Acc Ccdc SttcView Agency

NAICS

541690 - Other Scientific and Technical Consulting ServicesView NAICS

Place of Performance

FL

Set-Aside

NONE

Documents

This scope was carved out of W912CG-26-S-AdvARTMDC-01.

The full solicitation package (2 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

DRAFT for Advance Manufacturing Applied Research & Technology Development Center (AdvMARTDC)

AI Contract Breakdown

Uniform Contract Format

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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
View Agency Profile
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.

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