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How to Reduce Manufacturing Variation with Red X

Reducing Manufacturing Variation: its Not as easy as it sounds

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.

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.

The Problem that Never Goes Away

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. 

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. 

A Beacon of Hope

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 a Strategy Diagram to understand what nonrandom patterns exist in the manufacturing process, tools like Isoplot or Stage 0 Component Search to evaluate measurement systems and ensure that the observed variation was not coming from the measurement system itself, tools like Multi-Vari, Concentration Diagram, Component Search, Operations Search, or Event to Energy Transform to converge on a suspect root cause by eliminating possible causes that could be shown to be insignificant with regards to the large variation of the population, and tools like B vs W 6 Pack or 5 Penny tests to finally confirm the suspected root cause as the true Red X causing the variation in manufacturing. 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. 

Finding the Root Cause

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. 

Confirmation of the Root Cause

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.  

Just Scratching the Surface

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. 

About the Author

DIRECTOR OF TRAINING SERVICES
Matt Peterson

While earning bachelor’s and master’s degrees in mechanical engineering from Clemson University, Matt worked extensively in engineering design research, most notably with BMW. He began his career as an instructor at Clemson University. From there, he went into the automotive industry, where he became a Red X Master working on a range of complex problems from component manufacturing suppliers to vehicle level problems. Matt joined Shainin in 2017, and has since become a renowned problem solver, coach, and instructor across Shainin’s different methodologies with experience across many industries, including automotive, aerospace, medical devices, and commercial and consumer products. 

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Dorian Awards Criteria

Team Project Awards

Product Development
PROJECT OF THE YEAR

This category recognizes technical problems solved during product development and launch. These projects typically have small sample sizes to work with. Product development begins the lifecycle of a product. Projects that win this award will demonstrate:

  • Potential impact of the problem.
  • Effective use of the Shainin Red X® tools to uncover the root cause.
  • The timeline of resolution from initial discovery to solution implemented. 
  • Explanation of lessons learned and how to use this knowledge in the future.

Dorian Awards Criteria

Team Project Awards

Field Reliability
PROJECT OF THE YEAR

Field failures impact more than just your bottom line. This category is dedicated to projects that focus on field issues such as ‘No Trouble Found’, fatigue failures, and other destructive or malfunction events. Projects that win this award will demonstrate:

  • Initial impact of the problem.
  • Creative and effective use of the Shainin Red X® tools to uncover the root cause.
  • Speed and efficiency in resolving the issue.  
  • Impact of resolving the problem.

Dorian Awards Criteria

Team Project Awards

PLANT MANUFACTURING
PROJECT OF THE YEAR

Manufacturing is a world all its own. With the fast-moving pace, the speed of solving problems matters. The Plant Manufacturing Project of the Year Award recognizes projects that resolve complex problems in ongoing production which impact the end user, company bottom line, production quality rates, and the like. Projects that win this award will demonstrate:

  • Technical difficulty or complexity in resolving the issue.
  • Creative and effective use of the Shainin Red X® tools to uncover the root cause.
  • How the solution or information discovered was leveraged.
  • Timeline for resolving the issue.
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John Abrahamian

Executive VP - Problem Solving

John Abrahamian is a highly respected problem solver as well as an expert in the field of Lean manufacturing, with a career spanning over three decades. Throughout his career, John has become renowned for his innovative approach to problem-solving and his unwavering dedication to customer satisfaction. 
  
After receiving his BS in Mechanical Engineering from the University of Connecticut in 1985, John began his career as a design and development engineer at Pratt & Whitney. It was during this time that his interest in problem-solving first emerged. By 1994, John had become a Continuous Improvement Manager at the company. During his tenure, John led Pratt & Whitney’s efforts in Lean manufacturing and Value Engineering. 
  
In 1990, John began pursuing his MBA in Operations Management, where he was first introduced to the concept of Lean manufacturing, and this influenced the direction of his career. In 1996, he was encouraged by his Pratt & Whitney team to take Shainin Red X training, building on his Lean manufacturing efforts. This training proved to be a turning point in John’s career, igniting his passion for problem-solving and setting him on a path to becoming one of the industry’s most respected experts. 
  
In 1998, John joined Shainin, where he has spent the last 25 years pursuing his passion for problem-solving. During his time here, John has developed innovative approaches to problem-solving, having received a US Patent for a problem-solving method. He also integrated function analysis into Shainin methods, seeding what would ultimately become Resilient Engineering.  
  
Despite his busy schedule, John still finds time to pursue his hobbies, which include golfing, stand-up paddleboarding, and skeet shooting. He especially enjoys traveling with his wife and spending time with family, including his three grandsons. 
  
Having the opportunity to work in a wide variety of industries, experiencing different cultures and meeting new and interesting people gives John the kind of job satisfaction that makes him grateful to be in this field of work. He truly enjoys creating meaningful relationships with his customers and inspiring ordinary engineers to become extraordinary problem solvers. 

Dorian Awards Criteria

Red X® Master of the Year Award

The Red X® Master of the Year Award is for leaders with a Red X® Master Certification who have increased the impact of problem solving using Shainin technologies within their organization. To be considered for this award, the submission must meet the following criteria:

  • Applies leadership skills to expand the impact of Shainin technologies within the organization.
  • Results include projects that made a significant impact improving business performance.
  • The number of individuals coached to certification.

Dorian Awards Criteria

Team Project Awards

This category of awards is for project teams who have demonstrated outstanding application of Shainin methodologies in solving complex problems within their company.

To be considered for this award, the submission must meet the following criteria:

  • Speed and efficiency of the problem solved
  • Technical difficulty and complexity of the problem solved
  • Project impact and leverage across the organization
  • Creative use of Shainin technologies
  • Clarity of the project documentation