THE MODEL OF IDENTIFICATION OF THE PROBLEM MAIN CAUSE SET OF VARIATION

The term Lean has been widely used in today's product manufacturing and service delivery environments. In its fundamental nature the Lean Philosophy continuously strives for elimination of any kind of waste that exists in such environments. There are six basic strategies [1] related to the Lean Philosophy: Workplace Safety & Order & Cleanliness, JIT production, Six Sigma Quality, Empowered Teams, Visual Management and Pursuit of Perfection. On the journey of sustaining the lean supporting strategies there are many problems, or opportunities as Lean Practitioners call them. The value of some strategies highly depends on the efficiency of the problem solving techniques used to overcome the emerging issues. JIT production is difficult to imagine without a system that supports a high level of operational readiness with equipment uptime above 98%. Six Sigma level of quality, even when built into a product or system design, still undergoes the challenges of day to day operations and the variability brought with it. This variability is the source of waste and lean systems culture strives for continuous reduction of it. Empowered Teams properly trained to recognize the real cause of the problems and their Pursuit of Perfection culture are one of the corner stones of Lean Philosophy sustainability. Their ability to work with Problem Solvers and understand the difference between the "cure of the symptoms" approach versus "problem root cause identification" is one of the distinctions between Lean and Mass operations. Among the series of Statistical Engineering To ols this paper will show one of the techniques that proved to be powerful in the identification of the Set of Variation that contains the Main Cause of the new problems that arise in daily operations. This technique is called Multi - Vari. Multi - Vari is th e statistical engineering method used to analyze the set of data acquired in an organized manner. The set could be analyzed graphically or analytically. There are two basic applications of this method: (1) Determine statistically the homogeneity of the data distribution [2] and (2)Identify the critical set of variation that contains the assignable cause of the variation. This paper will focus on the second application of this method which gives the greatest return on investment in day to day operations in different working environments. Presented vision of the Multi - Vari method and application example should help readers to understand the essence, evaluate the value of this method and identify a potential for application in their areas of expertise.