"A New Course in Statistical Process Control Integrating an Industrial Production Facility as The On-line Laboratory"

在传统的课堂环境中提供有意义的应用统计学习体验是提供制造工程或应用统计课程的学院和大学面临的困境。主要挑战之一是让所有学生成为积极的学习者。质量控制领域教育工作者面临的另一个挑战是让学生批判性地思考在大规模生产设施中的应用。这两个挑战都可以通过让学生有机会参与项目并向该领域的专业人士提出广泛的问题来解决。这一举措导致创建了统计过程控制（SPC）新课程，其中包括直接从工业赞助商运营的生产设施的工厂车间上传实时质量数据。位于赞助商站点的计算机将在几秒钟内以电子方式将数据传输到大学计算机实验室。学生将：(i) 学习如何从工厂上传当前质量数据，(ii) 完成四个为期数周的团队项目，以及 (iii) 进行口头演示并向教授和行业代表提交书面报告。本质上，每个学生都是行业质量控制团队的成员。该项目为工业界提供了与学术界分享其专业知识和数十亿美元设备投资的机会。由于良好的数据是应用统计课程的关键需求，因此所提出的解决方案为多个应用统计课程提供了负担得起的实时生产数据来源。此外，这种方法非常适合其他机构。该项目带来的工业界和学术界之间的合作氛围是新颖的。它将向学生展示如何应用统计数据来帮助提高美国工业在全球的竞争力。

Providing a meaningful applied statistics learning experience in a traditional classroom setting is a dilemma faced by colleges and universities that offer courses in manufacturing engineering or applied statistics. One of the major challenges is in engaging all students as active learners. Another challenge of educators in the quality control field is in getting students to think critically about applications at a full-scale production facility. Both of these challenges can be addressed by giving students an opportunity to participate in projects and to ask a broad range of questions to professionals in the field. This initiative is resulting in the creation of a new course in Statistical Process Control (SPC) that incorporates uploading real-time quality data directly from the factory floor of a production facility operated by an industrial sponsor. Computers located at the sponsor site will electronically transfer the data to a university computer laboratory in a matter of seconds. Students will: (i) be shown how to upload current quality data from the factory floor, (ii) complete four multi-week team projects, and (iii) make oral presentations and submit written reports to the professors and to industry representatives. Essentially, each student performs as a member of the quality control team for industry. This project represents an opportunity for industry to share their expertise and their billions of dollars in equipment investment with academia. Since good data is a critical need of applied statistics courses, the solution proposed offers an affordable source of real-time production data for several applied statistics courses. In addition, this approach is highly transportable to other institutions. The cooperative climate between industry and academia resulting from this project is novel. It will show students how to apply statistics to help make American industry competitive at a global level.