FACTORIAL DESIGN OF EXPERIMENTS FOR LABORATORIES INCORPORATING ENGINEERING MATERIALS

摘要

Engineering laboratory experiments that involve materials and/or material properties are often designed to establish a level of specification and implementation methodology. Often these laboratory experiments are developed for well defined systems in controlled environments to take advantage of limited resources (i.e., materials, testing supplies, laboratory space, time, etc.). Material systems that incorporate a dependence on more that one parameter for processing and subsequent characterization pose a significant problem in that the experiment designer may not possess the information to identify the key parameters that influence the critical properties sought after. The ultimate goal is for the student experimental designer to predict parameters and properties based on a limited number of experiments or available data. The proposed methodology in this paper describes a general full factorial design for experiments involving the processing of materials for characterization used in undergraduate mechanics and materials laboratories. This Factorial Design Analysis (FDA) approach facilitates a 'between-participants' design analysis that includes more than one independent variable, and has the advantage over a simple randomized design in that one can test the effect of more than one independent variable and the interactive effect of the various independent variables. The method is validated for the optimization of the boundary conditions that influence the material properties of electrodeposited metals. Specifically, a 2~k factorial statistical analysis is conducted, analyzed, and a mathematical model derived, to describe how the electrolytes' boundary conditions influence the mechanical properties of electrodeposited nickel-iron (Ni_(80)Fe_(20)). Results include the students' full factorial design of experiments for an upper-level undergraduate engineering materials laboratory and an assessment of the laboratory experience.