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，以提供对计算机数控机床（CNC），增材制造（AM）/3D打印机，计算机控制的设备和复杂工程系统的深入停机时间减少分析。该项目的结果将影响大量的美国数控制造设施（超过19，000家数控商店）以及数千家计算机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提高服务质量来最大限度地减少系统停机时间。使用数学方程、算法以及可视化方法和工具对这些方法进行分析和量化。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，如机器人和协作机器人（协作机器人），有几个复杂的计算机控制，网络设备/仪器，需要专业的质量服务，以避免停机和故障。这个I-Corps项目的基础上，技术的发展，为定量，利用质量相关关键性能指标（KPI）的预测方法和工具，其可以在计算机数控机器（CNC）、增材制造（AM）/3D打印机的服务操作期间被测量、校准和实施，和复杂的工程系统。 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。所采用的方法不是以系统工程为重点，而是以财务会计为重点，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。正在开发的技术是基于可量化的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。该奖项反映了NSF的法定使命，通过使用基金会的知识价值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.