SBIR/STTR Research Award

Optimal Production Planning, Sourcing, Distribution and Routing for Complex Energy Intensive Manufacturing Companies Using High Performance Computing

Award identifier bc4c390afd4c821204ffd73d00b5c3966e840ca5f2777748022cd2e7dd6f4903Awarding agency Department of Energy

Award amount

$1,000,000

Program and phase

SBIR · Phase II

Award year

2014

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
OPTIMAL SOLUTIONS INC
Proposal award date
2014-04-08
Contract end date
2016-04-07
UEI
MNRUWLRAW7T6
Solicitation number
DE-FOA-0001019
Topic code
02a

Research abstract

Todays approaches to production planning and inventory management in a distribution network for large industrial gases and chemicals manufacturers are based on static snap-shot data and are not suitable for real-time use in tactical demand fulfillment. Companies have yet to harness the potential of powerful new computing technologies to find solutions for energy and other costly inefficiencies persisting in their supply chains many of which must be solved in real-time. This project addresses DOEs interest in turnkey solutions advancing the use of HPC in manufacturing and is intended to result in increased supply chain efficiency, reduced costs, and job creation. The overall objective is to develop a next generation production planning and distribution optimization algorithm together with a data-integration platform to provide timely and accurate data required for the optimization model. We take a two-pronged approach to address the problem: (1) leverage HPC technology to parallelize and rapidly solve the production planning and distribution problem and (2) leverage Big Data technology on a HPC platform to address the required data-integration. Phase I R & amp;D resulted in (1) a comprehensive model formulation that provides vehicle routing, production optimization and inventory optimization simultaneously and (2) a Big Data analytics framework to support the generation of the required input data. We demonstrated that using HPC, we can achieve 1080- times faster performance (vs. non-HPC implementation) without loss of optimality, thus proving feasibility of our innovation. We used industrial data and benchmarking to prove optimality and scalability. Our results were reviewed by several prospective customers and we received encouraging feedback (see support letters). We plan to build on the formulations and the test-bed created in Phase I and improve our algorithms. Our research activities will also focus on overcoming challenges including scalability of the solution, data security, and total cost of ownership. Our target is to be ready by the end of Phase II with a prototype turnkey application running on a hosted-HPC infrastructure, which allows us to start commercialization of our product as a service over the Internet to a variety of customers. Commercial Applications and Other Benefits: The envisioned software system will be used to obtain optimal production planning and distribution at multi-product, multi-depot manufacturing companies which utilize many fleets of vehicles. It is expected to result in significant efficiencies and reductions in energy and other operating costs. It is intended to increase the global competitiveness of the U.S. manufacturing sector and result in job creation.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

11 SBIR/STTR records share this UEI (2012–2025). Reported award amounts total $5,511,428. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Energy, Department of Agriculture, Department of Defense, National Science Foundation

Agency intelligence

Department of Energy

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