How to Reduce Manufacturing Variation with Red X / 如何使用 Red X 方法减少制造变异

Throughout his career, Marcus was no stranger to success. He was an excellent student, graduating with honors. In his first job after graduation, he quickly gained recognition as a promising young engineer within his organization and was rewarded with promotions and expanding responsibilities.

Marcus在其职业经历中对成功并不陌生。他是一名优秀的学生，以优异的成绩毕业。在毕业后的第一份工作中，他作为一名极具潜力的年轻工程师迅速崭露头角，并获得了晋升和更广泛的工作职责。

With broadening responsibilities, Marcus began to realize that while solving problems in the past had been easy, the more complicated problems he faced were proving to be more difficult. Throughout his academic career, he was always able to find the correct answer, and there was always a correct answer. In the real world, though, he quickly realized that many problems do not have only one right answer, and the problems are open-ended. Regardless, he was determined to find a way to get to an answer and felt confident in his ability to do so.

随着职责的不断扩展，Marcus开始意识到，虽然过去解决问题相对容易，但他现在面临的复杂问题实际上愈发棘手。在他的学习生涯中，他总是能够找到正确答案，而且总有一个正确答案。然而在现实世界中，他很快意识到多数问题并非只有一个正确答案，问题往往是开放性的。尽管如此，他决心找到解决问题的方法，并对自己的能力充满信心。

One specific problem gave him quite a bit of trouble. Marcus had been assigned a project to find what was causing variation in the results of an in-process leak test for one of his company's flagship products. The problem had plagued the organization for years. There were lots of theories, but no results. Eager for the opportunity and confident in his abilities, Marcus gladly agreed to take on the project, and set to work trying to understand all the nuances of this product and the leak test process.

有一个具体问题给他带来了不少麻烦。Marcus被指派了一个项目，为其公司的一个旗舰产品寻找造成过程泄漏测试结果变异的原因。此问题已经困扰公司多年。理论众多，但没有结果。Marcus渴望得到这个机会，并对自己的能力充满信心，他欣然同意接手这个项目，并开始努力了解该产品和泄漏测试过程的所有细微差别。

The weeks turned into months, and Marcus was still struggling to find the cause of the leak test variation. The tools he had learned throughout his career, though critical to his success so far, were not yielding the same results now. Marcus could classify the capability of the process using the statistical methods he knew, he could describe the theoretical workings of the product and the leak test machine thanks to his courses in thermodynamics, fluid mechanics, machine design, and others. Even still, he was no closer to finding the cause of this leak test variation. He needed a new approach.

数周甚至数月过去了，Marcus 仍在努力寻找泄漏测试变异的原因。虽然他在职业生涯中学到的问题解决工具对他迄今为止的成功至关重要，但现在却无法产生同样的结果。Marcus可以使用他所掌握的统计方法对工艺能力进行分类，他可以利用热力学、流体力学、机械设计等课程对产品和泄漏测试机器的理论工作原理进行描述。尽管如此，他仍然无法找到泄漏测试变异的原因。他需要一种新的方法。

While discussing the issue with one of his colleagues, Leslie, Marcus learned about Red X. Leslie explained to Marcus that she had already solved several manufacturing variation problems using tools like:

在与同事Leslie讨论这个问题时，Marcus了解到了 Red X。Leslie向Marcus解释说，她已经使用某些工具解决了一些制造变异问题：

The best part – Leslie had solved these complex problems in a fraction of the time that Marcus had spent trying to solve the leak test variation problem.

最棒的是，Leslie只用了Marcus解决泄漏测试变异问题的一小部分时间，就解决了这些复杂的问题。

Empowered with the knowledge of this new strategy and toolset for problem solving, Marcus convinced his organization to invest in his problem-solving abilities. Marcus was trained in Red X problem solving, and with the help of his coach, was able to approach the leak test problem with a new perspective. Rather than focusing on how everything was supposed to work, he focused on the difference between the best and worst performing parts. With this new strategy, and with the application of Component Search, he quickly realized that almost all of the variation in the leak test results could be traced to a single component. When he compared the suspect components, he quickly noticed that the high leak rate parts had obvious porosity, and the low leak parts did not. When he presented the findings, he received swift pushback. Previous attempts at solving this problem had noted the porosity that Marcus had found. However, this porosity was eliminated as a possible root cause by the previous teams because it was deemed within the specifications for the component in question.

掌握了解决问题的新策略和工具集后，Marcus 说服他的组织对他解决问题的能力进行投资。Marcus 接受了 Red X 问题解决培训，并在教练的帮助下，以全新的视角解决了泄漏测试问题。他不再关注一切应该如何运作，而是关注性能最好和最差的零部件之间的差异。有了这一新策略，再加上组件搜索的应用，他很快就意识到，泄漏测试结果中几乎所有的变异都可以追溯到一个组件。当他对嫌疑零件进行比较时，很快发现高泄漏率零件有明显的气孔，而低泄漏率零件则没有。当他提出这一发现时，迅速遭到了反对。此前的团队尝试解决这个问题时也注意到了Marcus发现的气孔。然而，这些气孔被他们排除在可能的根本原因之外，因为他们认为这些气孔符合相关零件的规格要求。

Undeterred, and motivated by the evidence he had gathered already, Marcus conducted a B vs W Six Pack confirmation test which proved with 95% statistical confidence that the porosity he had found, in spec or not, was in fact the cause of the leak test variation. He again presented the results, and explained that while yes, the visible porosity on the surface of the component was within the print specification, what the previous teams had failed to realize is that the porosity created a leak path through the component entirely, causing the high leak value. Armed with the proof from his confirmation test, Marcus was able to convince the team to modify the print for this component to eliminate the porosity problem, and the performance of the leak rate station improved significantly because of the change.

Marcus没有气馁，在他已经收集到的证据的推动下，他进行了一次 B vs W 6 Pack 验证试验，以 95% 的统计置信度证明，他发现的气孔，无论是否符合规格要求，实际上都是造成泄漏测试变异的原因。他再次展示了结果，并解释说，虽然组件表面可见的气孔符合图纸规格，但此前的团队没有意识到的是，这些气孔在组件中完全形成了一条泄漏通道，从而导致了高泄漏值。有了验证试验的证据，Marcus得以说服团队修改该组件的图纸，消除了气孔问题，高泄漏率工站的表现也因这一变更而得到显著改善。

While Marcus had succeeded in his initial goals of learning a new way to solve problems and employing that knowledge to solve the problem at hand, as he reflected on what he had learned, he realized that there was much more to learn and many more problems to solve. Marcus recognized that his past successes were an excellent foundation, but he needed to continue to expand his problem-solving knowledge to prepare himself to solve any problem that may come his way in the future.

虽然Marcus成功地实现了他最初的目标，即学习一种新的问题解决方法，并利用这些知识来解决手头的问题，但当他反思自己所学内容时，他意识到，自己要学的不止是皮毛，要解决的难题也远不止眼前这些。Marcus意识到，他过去的成功为他奠定了坚实的基础，但他仍需不断拓展自己的问题解决知识，为解决未来可能遇到的任何问题做好准备。

Matt received his BS and MS in Mechanical Engineering from Clemson University and spent years in engineering design research, most notably at BMW. His career started as an instructor at Clemson University. He then moved to the automotive industry as a Red X Master, working on complex problems ranging from component manufacturing to complete vehicles. Matt joined Shainin in 2017 and has since become a well-known problem solver, coach, and instructor in different Shainin methodologies with experience spanning automotive, aerospace, medical devices, commercial, and consumer goods industries.

Matt在克莱姆森大学(Clemson University)获得机械工程学士和硕士学位后，在工程设计研究领域深耕多年，其中最知名的是宝马公司(BMW)。他的职业生涯始于克莱姆森大学的讲师。之后，他进入汽车行业，成为一名 Red X Master，研究从零部件制造到整车的一系列复杂问题。Matt于 2017 年加入谢宁，自此成为谢宁不同方法论领域的知名问题解决者、教练和讲师，拥有横跨汽车、航空航天、医疗设备、商业和消费品等多个行业的经验。