Revolutionary Methods for Problem Solving


Sladky Jr., John   (1991, ASQC)   Working Smarter, Inc., Manchester, PA

Annual Quality Congress, Milwaukee WI    Vol. 45    No. 0
QICID: 9607    May 1991    pp. 64-70
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Article Abstract

This article explores several approaches to continuously improve manufacturing process and product quality. The article states that the Statistical Process Control (SPC) approach to problem solving is outdated and obsolete. This premise led author to look for other tools that would be more reliable than SPC techniques and more cost-effective than Taguchi Orthagonal Arrays or classical fractional factorial experiments.

Statistical Process Engineering (SPE) methods address seven technical categories: (1) Measurement Effectiveness; (2) Problem-Cause Isolation; (3) Systematic Variation Reduction; (4) Testing and Proving the Answer; (5) Process Optimization; (6) Defect Prevention; and (7) Quality Safeguards. SPE techniques are flexible, efficient, and simple; their main advantage is that they are applicable to any situation and do not require complex statistical scenarios.

The Multi-Vari Study method uses five steps to collect current and accurate information: (1) always collect NEW data; (2) plot the information on the diagram; (3) separate the components of variation; (4) identify patterns of variation; and (5) analyze the results. The main advantage of the Multi-Vari Study is that it shows which components contribute to the most variation.

These methods are effective for manufacturing companies of all sizes. The ability to reduce the problem-solving process from years to months is one of the greatest benefits of using SPE techniques and the Multi-Vari Study method.


Manufacturing,Multi-vari studies,Problem solving,Statistical process control (SPC),Statistical Process Engineering (SPE),Variation,Cause and effect diagram

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