ANALYSIS
Minimize the J-curve Effect in Manufacturing Derek DeGeest DeGeest Corporation - Tea, South Dakota (SD) – United States
derek@degeestmfg.com
You may have heard the term “J-Curve” from the world of investing, but it’s a concept that applies to anything – even manufacturing. The J-Curve explains the often mistaken expectations to the more common initial negative effects of implementing new technology or processes before it eventually leads to increased productivity, efficiency, and profitability. The concept is named after the letter “J,” as the curve typically dips down initially before rising sharply. It’s useful to demonstrate the effects of an action over a period of time. Put bluntly, it shows that change will make things temporarily worse before they get better, which is completely normal and expected. But as the saying goes, “No pain, no gain.” This article will explain the impacts of the J-Curve effect and provide tips on how to make this initial phase of decline much softer so you can get to the benefits phase quicker.
A
ny time you make a process or
After making initial weld programs and starting
up our tolerances.
technology change in manufacturing,
production, we found ourselves reworking
Tackling these variables one at a time initially
you’ll most likely experience a gap in
many parts. In this case, the painful variable
decreased our production. It would have been
expectation on your journey from your current
was adjusting our company-wide processes
faster and easier to scrap this new robotic
state to your desired state. This gap is the
from the adaptability of a manual welder to
welding machine along with the required new
J-Curve effect. It happens because this new
the precision and repeatability required for a
processes and go back to our old manual
variable will affect other things. At DeGeest, we
robotic welder. We had to increase the quality
methods. Instead, we fought through the
experienced the J-Curve when we added our
of our fabrication processes, improve our
J-Curve and are now running fully automated
first welding robot.
fixtures, review tack procedures, and tighten
robotic welding jobs and producing more parts more efficiently than ever before. Another example is the addition of Lesta robots to the paint line at DeGeest. Adding the adaptable self-learning automation was great in theory, but there weren’t quality and consistency checks and balances in place to make it a smooth transition. After experiencing another decline in production, we resisted the temptation to go back to manual finishing. Instead, we came together and worked on identifying variables that affected our new automation and created processes and programs to take advantage of this new technology. While it’s true that adding a Lesta robot will result in Day One Finishing (meaning you will be finishing robotically the first day after installation), it’s important to be realistic about initial production goals due to the adaptation
© DeGeest Corporation
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N. 85 - JANUARY/FEBRUARY 2024 - international PAINT&COATING magazine
required for new technology, also known as