I-Corps: Quantifiable Service Quality Firmware System

这个i-Corps项目的更广泛的影响/商业潜力是开发技术，为计算机数控机床(CNCS)、附加制造(AM)/3D打印机、计算机控制的家电和复杂的工程系统提供深入的停机时间减少分析。该项目的结果将影响到非常多的美国数控制造设施(超过1.9万家数控商店)以及数千家电脑控制的家电维修公司，每年为该行业节省数百万美元。该项目的商业潜力是通过改进服务质量将系统停机时间降至最低。使用数学方程、算法以及可视化方法和工具对这些方法组进行分析和量化。研究结果还将对制造设施和其他复杂的工程系统产生影响，如机器人和Cobot(协作机器人)，这些设备/仪器具有多个复杂的计算机控制的、联网的设备/仪器，需要专业的质量服务以避免停机和故障。该i-Corps项目基于定量、预测方法和工具的技术开发，这些方法和工具利用与质量相关的关键性能指标(KPI)，可以在计算机数控机床(CNCS)、附加制造(AM)/3D打印机和复杂工程系统的服务操作期间进行测量、校准和执行。目前，没有任何方法或工具可用于预测所提供服务的有效性或成功程度或风险。所使用的方法不是以系统工程为重点的，而是财务会计，可能包括也可能不包括历史数据报告，以表明所提供的以工程为重点的服务的状况。正在开发的技术基于可量化的以服务质量为重点的关键流程/绩效指标(KPI)，使用数学模型、算法和多媒体软件可视化方法。这使用户能够量化产品/过程质量服务的水平。此外，该平台可用于量化和预测产品质量服务作为一项指标。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is to develop technology to provide an in-depth downtime reduction analysis of computer-numerical controlled machines (CNCs), Additive Manufacturing (AM)/3D printing machines, computer-controlled appliances and complex engineered systems. The results of this project will affect a very large number of US CNC manufacturing facilities (over 19,000 CNC shops) as well as thousands of computer-controlled appliance repair companies, saving millions of dollars annually for the industry. The commercial potential of the project is is to minimize system downtime using service quality improvements. These groups of methods are analyzed and quantified using mathematical equations, algorithms, as well as visualization methods and tools. The results also will have an impact on manufacturing facilities and other complex engineered systems, such as robots, and cobots (collaborative robots), that have several complex computer-controlled, networked devices/instruments that need professional quality service to avoid downtime and failure.This I-Corps project based on the development of technology for quantitative, predictive methods and tools that utilize quality-related key performance indicators (KPIs), that can be measured, calibrated, and enforced during service operations in computer-numerical controlled machines (CNCs), additive manufacturing (AM)/3D printing machines, and complex engineered systems. Currently, there is no method or tool available for predicting the effectiveness or the level of success or risk of the services provided. The methods utilized are not systems engineering-focused, but rather financial accounting, and may or may not include reports of historical data to indicate the status of engineering-focused services provided. The technology under development is based on quantifiable service quality-focused key process/performance indicators (KPIs), using mathematical models, algorithms, and multimedia software visualization methods. This enables users to quantify levels of product/process quality service. In addition, the platform may be used to quantify and predict the product quality service as an index.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.