METODOLOGI SIX SIGMA PERTEMUAN 5 MEASURE PHASE OLEH: EMELIA SARI
Overview Objectives of the Measure Phase include identifying process performance measures and setting their targets according to the VOC data The current process is evaluated against the targets The gap between current and target performance provides the Six Sigma team with priorities and direction for further analysis
Activities of the Measure Phase Determine appropriate process performance measurements, such as timeliness and accuracy measures, from an understanding of the customer and business CTQs. Measure baseline sigma levels, which is current performance against the target process performance measure, in order to determine the capability of the current process to meet customer CTQs. This is referred to as gap analysis.
Activities of the Measure Phase (2) Define and measure process defects. Develop a detailed process map of the current process. Conduct best practices and benchmark research results, including how the current process is performing against best practices. Identify the process inputs (critical X’s) and outputs (critical Y’s) and their relationship to each other.
The Most Common Six Sigma Tools Used During the Measure Phase Process maps Check sheets Pareto charts Cause-and-effect Histograms Control charts Statistical techniques
Types of Measures One of the first steps in the Measure Phase is to define the performance measures from the customer’s perspective For cycle time reduction projects, it is logical to start with measuring the current cycle time of the process against customer timeliness requirements.
For general improvement projects, defining appropriate measures may be a little more difficult The three types of measurements needed are output, process, and input measures The Input-Process-Output components of the S-I-P-O-C diagram from the Define Phase are useful in identifying these measures
Input, Process, and Output Measures Expressed as Critical X’s and Y’s
Measurement Data Types Measurement data are categorized as either continuous or discrete Continuous data, also called variable data, are based on a continuum of numbers, such as heights, weights, times, and dollars Discrete data, also called attribute data, are based on counts or classes, such as proportions, defects, yes/no or pass/fail, A, B, C, D Grades or a 5-point survey scale