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

SBIR 第一阶段：OptimizerAero - 面向航空航天制造商的强大生产调度优化器

• 批准号: 2036546
• 负责人: Vivek Saxena
• 金额: $ 24.9万
• 依托单位: ADVISORY AEROSPACE OSC LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2022-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2036546&HistoricalAwards=false
• 关键词: SBIR; Phase; OptimizerAero; robust; production

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 shop’s 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.

小企业创新研究 (SBIR) 第一阶段项目的更广泛影响将是使美国制造基地更具竞争力。航空航天供应链包含数千家数字化程度较低的中小企业 (SME) 制造商。中小企业构成了全国范围内庞大的航空航天供应基地，并且基本上没有受到运筹学进步的影响。因此，当地制造商在与低成本国家制造商的竞争中处于不利地位。虽然优化技术的计算能力和速度已经提高到可以实时解决大规模工业问题的程度，但很少有人关注需要做出的许多建模决策，这些决策需要将真实工厂物理的复杂性准确地捕获到规定的数学模型中。 该项目将为中小企业开发一款即插即用软件，该市场估计价值 8.5 亿美元，将提高整个供应链的效率。由此产生的解决方案预计将成为一个生产优化器，可以在任何中小企业航空航天制造商使用现有数据流的情况下在不到两周的时间内实施。 该项目所体现的数字技术和运筹学进步的使用最终将在将外包制造带回美国方面发挥重要作用。拟议的项目将推动生产规划和执行中强大的优化工具的转化。提议的贡献包括 1) 允许在不同时间尺度进行规划和调度的分层方法，2) 对经典运营模型的计算改进，以纳入实时问题，例如不完整订单、生产结转和跨期间设置活动的延续，3) 算法设计，使车间数据适应不同时间尺度，同时保持模型准确性，4) 分析规划范围、时间段选择和目标的影响 系数，以及创建系统方案以确定其最佳价值以满足用户需求，以及 5) 开发启发式方法以快速重新优化以应对与计划的微小偏差。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。