Integrating Experimental Design and Reliability for Multiple Stage Manufacturing of Multi-Scale Devices

这笔赠款提供资金，用于开发和分析特别适用于多阶段制造的基于统计的实验设计，并将这些设计与新产品开发的可靠性建模相结合。提出了多阶段分数析因分裂图(MSFFSP)设计的概念，以适应复杂的制造过程，其中需要对实验运行的随机化进行限制。具体地说，将导出MSFFSP设计的一般线性模型、设计目录和方差估计。这项工作将应用于包括凝胶浇注光刻在内的多阶段工艺，以制造用于微创手术的多功能钳剪(FS)器械。这种新的光刻工艺使用纳米颗粒使FS仪器同时具有纳米和微米尺度的特征。MSFFSP设计还将应用于光学显微镜的测量系统分析，该光学显微镜用于采集FS设备上的数据。结合FS设备开发，将识别、列举故障模式，并将其转换为可靠性数据。加速测试的概念将被用来缩短获取这些数据的时间，并将与MSFFSP设计相结合。MSFFSP分析将进行修改，以便正确分析可靠性数据，这些数据具有不同于工艺和产品数据的统计特征。如果成功，这项研究的结果将导致在保持设计效率的同时，减少在复杂的制造工艺中进行试验所需的试运行次数和设置。使用这些设计并将它们与可靠性测试集成到微纳制造研究的建模和生产中，将通过加快研发周期、延长实验预算并最终帮助创造更可靠、更坚固和更好性能的小规模产品来产生战略优势。这项工作不仅将推动实验设计领域的发展，而且还将扩大质量方法学推广到其他多阶段制造过程的潜力。

This grant provides funding to develop and analyze statistically-based experimental designs especially suited for multiple stage manufacturing, and to integrate these designs with reliability modeling for new product development. The concept of a multiple stage fractional factorial split plot (MSFFSP) design is proposed to accommodate complex manufacturing processes where restrictions on the randomization of experimental runs are required. Specifically, a general linear model, design catalogs, and variance estimates of the MSFFSP design will be derived. This work will be applied to a multiple stage process involving gel-casting lithography to manufacture a multifunctional forceps-scissors (FS) instrument for minimally invasive surgery. The novel lithography process uses nanoparticulates to impart the FS instrument with both nano- and micro- scale features. The MSFFSP design will also be applied in the measurement system analysis of an optical microscope, which is used to collect data on the FS device. In conjunction with the FS device development, failure modes will be identified, enumerated, and transformed into reliability data. The concept of accelerated testing will be used to shorten the time to acquire this data and will be integrated with MSFFSP design. The MSFFSP analysis will be modified in order to properly analyze the reliability data, which has different statistical characteristics than process and product data. If successful, the results of this research will lead to a reduction in the number of trial runs and settings required for experimentation in complex manufacturing processes with multiple stages while maintaining design efficiency. Using these designs and integrating them with reliability testing into modeling and production for micro- and nano-scale manufacturing research will yield strategic advantages by speeding the research and development cycle, stretching the experimental budget, and ultimately helping to create more reliable, robust, and better performing small-scale products. The proposed work will not only advance the field of experimental design, but also amplify the potential of quality methodologies to be extended for other multiple stage manufacturing processes.