A Systematic Approach to Planning for a Designed Industrial

Different sponse variables 1 measurable 1 categories

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: actors -~ Figure 5. Different sponse Variables. 1 measurable 1 Categories of Factors Affecting Re- 4.2 Current Ability Use (col. 2) to Measure and Set (col. 3) With control variables, there is an additional consideration rarely mentioned in the literature. The experimentation team not only needs to know how measurements will be obtained and the precision of measurement, a,,,, but also how the control variable settings will be obtained and “setting error,” E,. These different types of deviation from the ideal have different effects on experimentation. Large 0, will mean that either errors-in-variables methods will have to be used (e.g., methods that will allow estimation of bias in effects estimates) or, alternatively, many samples will have to be collected for measurement during experimentation to get an acceptably small a,,,lfi, especially if IE,Jis also large. If IE,~ large, traditional, is class-variable-based analysis of variance will have to TECHNOMETRICS, FEBRUARY 1993, VOL. 35, NO. 1 DAVID E. COLEMAN AND DOUGLAS Table 3. Control Control variable (units) Normal level and range x-axis shift* (inches) y-axis shift* (inches) z-axis shift* (inches) Tool vendor O--.020 inches O-.020 inches O--.020 inches Internal, external a-axis shift* (degrees) Spindle speed (% of nominal) O--.030 O-.025 Variables Measurement precision and setting errorhow known? .OOl inches (experience) .OOl inches (experience) .OOl inches (experience) - Difference /1 0, .015 inches Difference 7 ? Difference 7 degrees 0, .030 degrees External is more variable Unknown 90%. 110% None? ,002 inches (guess1 -1% (indicator on control panel) 0, .015 inches Unknown 90%, 110% None? .OOl degrees go-110% inches be replaced by regression analysis. The result of large setting variation may be unwanted aliasing, greater prediction error, violation of experiment constraints, and difficulty conducting split-plot analyses. Often, one finds that a, = [es/, such as when the measurement system is part of a controller, and equilibrium conditions can be achieved. Measurement precision and set...
View Full Document

Ask a homework question - tutors are online