ENGINEERING TOOLS & METHODS
−− Assign factors −− Locate interactions −− Modification of standard orthogonal arrays −− Parameter design • Conducting The Experiment −− Trial data sheets −− Testing logistics & assignments −− Identification of trial results −− Sample size per trial −− Randomization −− Good and bad data sets • Analyzing And Interpreting Results −− Observation method −− Column effects method
This seminar covers the fundamentals required in planning, conducting, and analyzing orthogonal experiments, which are the major steps in the Design of Experiments (DOE) process. Emphasis is placed on the DOE process, which, if diligently followed will yield an effectively completed experiment. An introduction to parameter design is included. A short video introduces the experimental approach; the end of the session allows practice with the new methods in a hands-on workshop. For more advanced study, attend C0714 ANOVA for Design of Experiments. It is strongly recommended that any registrant attend a Basic Design of Experiments course prior to taking the advanced course. Learning Objectives By attending this seminar, you will be able to: • Choose appropriate factors and factor levels to effectively plan DOEs • Define an appropriate set of tests to evaluate the chosen factors and levels • Utilize appropriate randomization strategies and choose appropriate sample sizes for conducting tests for DOE • Utilize basic analytical methods to identify influential & non- influential factors in analyzing and interpreting DOE results • Set specification limits for all factors for effective performance and low cost Who Should Attend This seminar is designed for product and process design engineers, manufacturing engineers, quality engineers, testing and development engineers. Although it would be helpful, no statistical education or background is required for this course; only fundamental mathematical skills are necessary.
−− Plotting −− Ranking
−− Analyzing variability −− Factor classification −− Attribute data −− Interpreting experimental results −− Confirmation experiment • Experimental Workshop −− Popcorn experiment review −− Pendulum experiment
Instructor: Fee: $1415
Phillip J. Ross
1.3 CEUs
URL:
sae.org/learn/content/c0231/
Design of Experiments (DOE) for Engineers 2 Days | Classroom Seminar I.D.# C0406 Design of Experiments (DOE) is a methodology that can be effective for general problem-solving, as well as for improving or optimizing product design and manufacturing processes. Specific applications of DOE include identifying proper design dimensions and tolerances, achieving robust designs, generating predictive math models that describe physical system behavior, and determining ideal manufacturing settings. This seminar utilizes hands-on activities to help you learn the criteria for running a DOE, the requirements and pre-work necessary prior to DOE execution, and how to select the appropriate designed experiment type to run. You will experience setting up, running, and analyzing the results of simple-to-intermediate complexity, Full Factorial, Partial Factorial, and Response Surface experi- ments utilizing manual methods as well as a hands-on computer tool that facilitates experimental design and data analysis. You will also receive an overview of Robust DOE, including the Taguchi DOE Method.
Topical Outline • Design Of Experiments Background −− DOE definition −− DOE and Taguchi history −− DOE in the product life cycle −− Implementation strategy • Design Of Experiments Process −− Flowcharts −− Injection molding case study −− Water pump leak case study overview • Planning Phase −− State problem(s) −− State objective(s) −− Determine measurement method(s) −− Quality characteristic(s) −− Select factors −− Identify control and noise factors
−− Select levels of factors −− Select orthogonal array
55
3 ways to get a no-obligation price quote to deliver a course to your company: Call SAE Corporate Learning at +1.724.772.8529 | Fill out the online quote request at sae.org/corplearning | Email us at corplearn@sae.org
Made with FlippingBook Online newsletter