ENGINEERING TOOLS AND METHODS
• 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.
• Institutionalizing DFM+A in Your Organization −− How DFM+A fits in with other strategies −− Lessons learned from other companies −− Ideal workplace implementation plan • Video Presentation on Goal Setting (time permitting) • Wrap Up • Course Evaluation
Instructor: Fee: $1595
Kevin Zielinski
1.3 CEUs
URL:
sae.org/learn/content/92047/
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 −− 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
Design of Experiments - Basic Simplified Taguchi 2 Days | Classroom Seminar (Available for Private Delivery Only) I.D.# C0231 Design of Experiments is a statistically based, structured approach to product or process improvement that will quickly yield significant increases in product quality and subsequent decreases in cost. Products and processes can be designed to function with less variation and with less sensitivity to environmental factors or customer usage. While still maintaining high quality from a customer’s viewpoint, products and processes can utilize lower cost materials and methods. Specifications can be opened-up with wider tolerances while still maintaining high quality for customers. In summary, products and processes can be designed and developed in shorter times to reduce costs and become more competitive in the marketplace from a delivery and profit standpoint. 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
−− Plotting −− Ranking
−− Analyzing variability −− Factor classification −− Attribute data −− Interpreting experimental results −− Confirmation experiment
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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
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