Table 1. Master Guide Sheet. This guide can be used to help plan and design an experiment. It serves as a checklist to improve experimentation and ensures that results are not corrupted for lack of careful planning. Note that it may not be possible to answer all questions completely. If convenient, use supplementary sheets for topics 4-8
1.Experimenter’s Name and Organization: Brief Title of Experiment:
2. Objectives of the experiment (should be unbiased, specific, measurable, and
of practical consequence):
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3. Relevant background on response and control variables: (a) theoretical relationships; (b) expert knowledge/experience; (c) previous experiments. Where does this experiment fit into the study of the process or system?:
4. List: (a) each response variable, (b) the normal response variable level at which the process runs, the distribution or range of normal operation, (c) the precision or range to which it can be measured (and how):
5. List: (a) each control variable, (b) the normal control variable level at which the process is run, and the distribution or range of normal operation, (c) the precision (s) or range to which it can be set (for the experiment, not ordinary plant operations) and the precision to which it can be measured, (d) the proposed control variable settings, and (e) the predicted effect (at least qualitative) that the settings will have on each response variable:
6. List: (a) each factor to be “held constant” in the experiment, (b) its desired level and allowable s or range of variation, (c) the precision or range to which it can measured (and how), (d) how it can be controlled, and (e) its expected impact, if any, on each of the responses:
7. List: (a) each nuisance factor (perhaps time-varying), (b) measurement precision, (c)strategy (e.g., blocking, randomization, or selection), and (d) anticipated effect:
8. List and label known or suspected interactions:
10. Give current design preferences, if any, and reasons for preference, including blocking and randomization:
11. If possible, propose analysis and presentation techniques, e.g., plots, ANOVA, regression, plots, t tests, etc.:
12. Who will be responsible for the coordination of the experiment? 13. Should trial runs be conducted? Why / why not?
9. List restrictions on the experiment, e.g., ease of changing control variables, methods of data acquisition, materials, duration, number of runs, type of experimental unit (need for a split-plot design), ¡°illegal¡± or irrelevant experimental regions, limits to randomization, run order, cost of changing a control variable setting, etc.:
An experiment is required to improve understanding of the manufacturing impellers on a CNC-machine that are used in a jet turbine engine. To achieve the desired performance objectives, it is necessary to produce parts with blade profiles that closely match the engineering specifications. The objective of the experiment was to study the effect of different tool vendors and machine set-up parameters on the dimensional variability of the parts produced by the CNC-machines.
Table 2. Beginning of Guide Sheet for CNC-Machining Study.
l.Experimenter’s Name and Organization: , Process Eng. Group Brief Title of Experiment: CNC Machining Study
2. Objectives of the experiment (should be unbiased, specific, measurable, and of practical consequence):
For machined titanium forgings, quantify the effects of tool vendor; shifts in a-axis, x- axis, y-axis, and z- axis; spindle speed; fixture height; feed rate; and spindle position on
the average and variability in blade profile for class X impellers, such as shown in
3. Relevant background on response and control variables: (a) theoretical relationships; (b) expert knowledge/experience; (c) previous experiments. Where does this experiment fit into the study of the process or system?
(a) Because of tool geometry, x-axis shifts would be expected to produce thinner blades, an undesirable
characteristic of the airfoil.
(b) This family of parts has been produced for over 10 years; historical experience indicates that externally
reground tools do not perform as well as those from the ¡°internal¡± vendor (our own regrind operation).
(c) Smith (1987) observed in an internal process engineering study that current spindle speeds and feed rates work well in producing parts that are at the nominal profile required by the engineering drawings
– but no study was done of the sensitivity to variations in set-up parameters.
Results of this experiment will be used to determine machine set-up parameters for impeller machining. A robust process is desirable; that is, on-target and low variability performance regardless of which tool vendor is used.
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