In today’s complicated world, the quality professional is faced with an increasing array of differing methods to solve problems and improve processes. Advertisements shout to the prospective buyer that this software will make their dreams come true – guaranteed! Best selling books are written that extol the virtues of special techniques and then proceed to take you down such a complicated path that it’s difficult to perceive if you’re going in the right direction. Many improvement programs within organizations fail just because they are too complicated and no one quite knows how to proceed or what the results mean at the end.
Life doesn’t have to be full of complications. If the full blown version of an improvement program is introduced and not understood, the result may well be that no improvements happen, yet employee’s time is taken up because they still think something is supposed to happen. The improvement teams stay together and have “sometimes meetings” because they don’t have the permission of management to quit, but are able to throw attention off of their non-results by identifying progress as “ongoing”. This is not a good situation for anyone. The management team is fooling itself by not monitoring the team progress (or lack of) properly and not identifying that a possible time and money pit has been created. The employees feel inadequate because they can’t come up with a success and are keeping out of trouble by standing still. Don’t underestimate the power of these complete programs. If implemented properly with appropriate support and training, they can offer a tremendous amount of payback over time. The trouble is that many improvement techniques are introduced without the high-end support structure that is needed, and just end up sucking resources from the company and frustrating everyone involved.
Make Life Easier
Whenever you feel yourself deluged by the complications of introducing a particular improvement subject, sit back for a minute and ask yourself several questions.
Design of Experiment
A good example of a complicated improvement technique that can be downsized, broken into critical components, and made available even to the line operator, is Design of Experiments (DOE). DOE’s come in many formats and gained a great height of awareness with the introduction of the Taguchi method in the latter part of the 20th century. DOE is used when other methods to improve processes such as Statistical Process Control (SPC) have been exhausted. DOE’s allow a team to see how the different parameters of a process affect a given result that they would like to improve (ex: defects, inefficiencies). These experiments also allow the team to see if interactions exist between the different critical parameters of the process such as temperature, speed, pressure, etc.
GenichiTaguchi was an engineer and statistician who developed a methodology for applying statistics to improve the quality of manufactured goods. Although experimentation to establish how different process parameters affected each other and come up with a holistic combination was not new, creating special production runs to involve all possible combinations was time consuming and expensive. Taguchi made DOE’s simpler by introducing a new methodology and philosophy, including the use of a Loss Function to decide when a process needed to be optimized. He advised engineers to look only at the critical process parameters rather than all of them, and to not look at interactions at all unless they felt compelled to. This enabled organizations to reduce the amount of experiment runs they had to make from thousands down to less than twenty with a comparable result. Even Taguchi’s simplified methods, however, were interspersed with complicated mathematical formulas and functions such that would scare off the layman technician and floor operators. Many DOE’s were created within organizations that had erroneous results that couldn’t be explained because the coordinator didn’t understand the critical concepts behind the DOE techniques.
DOE Made Easy
Go back to the basics. With Design of Experiments we can further the philosophy of Taguchi by making it even easier to understand how to make a successful designed experiment that everyone can understand – without complicated mathematics and expensive software. We can do this by defining a DOE as a series of critical steps in a process, with the end result being an improvement in the “Effect” being studied.