SBIR Phase I: OptimizerAero - A robust production scheduling optimizer for aerospace manufacturers

Award ID: 2036546

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be in making US manufacturing base more competitive. The aerospace supply chain contains thousands of less digitally sophisticated Small and Medium Enterprise (SME) manufacturers. The SMEs constitute a vast aerospace supply base across the country and have largely remained unaffected by the advances in operations research. Consequently, local manufacturers compete unfavorably with those in low-cost countries. While the computing power and speed of optimization techniques have increased to a point where one could now solve large-scale industry problems in real time, little attention has been given to the many modeling decisions that need to be made to accurately capture the complexities of real factory physics into a prescriptive mathematical model. This project will develop of a plug-and-play software for SMEs this estimated $850 M market that will improve efficiency along the entire supply chain. The resulting solution is expected to be a production optimizer that can be implemented in less than two weeks at any SME aerospace manufacturer using their existing data streams. Use of digital technologies and operations research advances embodied in this project will ultimately play an appreciable role in bringing outsourced manufacturing back to the United States. The proposed project will advance translation of powerful optimization tools in production planning and execution. The proposed contributions include 1) a hierarchical approach that allows for planning and scheduling at different timescales, 2) computational improvements to classic operations models to incorporate real-time issues such as incomplete orders, carryover of production and continuation of setup activities across periods, 3) the design of algorithms to adapt the shops data to the different timescales while preserving model accuracy, 4) the analysis of the impact of planning horizon, time period choice and objective coefficients, as well as the creation of systematic schemes to determine their best value to meet user needs, and 5) the development of heuristics for quick re-optimization to respond to small deviations from the plan. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ela Mirowski