Focus Areas

• Understanding of stacks and why do we need it
• Applications of stacks
• Product definition per design intent
• Loop diagram per dimensional objective or critical functional relationship to analyze
• Calculate nominal output and variational / tolerance out put
• Worst case tolerance calculation, WC
• Effect of dimensioning practices on tolerance variation
• Root Sum Square, RSS and Modified Root Sum Square, MRSS
• Empirical correction factors, Bender, Gilson, Gladman, and Greenwood
• Part stacks using bonus tolerance. Float and biased floats
• Exercises

Background

Manufacturing process, productivity and cost are often determined by component tolerances. If components are incorrectly toleranced, it leads to assembly problems. Too tight a tolerance leads to higher cost. Designers are expected to tolerance components optimally.

Dimensional variations in production parts accumulate or stack up statistically and propagate through an assembly kinematically, causing critical features of the finished product to vary. Such variations can cause costly problems, requiring extensive rework or scrapped parts. One of the effective tools for managing variations is Tolerance Analysis. Tolerance Analysis is a quantitative tool for predicting the accumulation of variation in an assembly by performing a stack-up analysis, reduces manufacturing costs by improving producibility and also enables design engineers to determine, how robust a design is at the drawing phase.

Keeping this in view, Indian Machine Tool Manufacturers' Association (IMTMA) is organizing a 2 day online training on Tolerance Stack-up Analysis.

Key Takeaways

• Understand stack-up analysis and why it is required in today’s design
• Analyse and optimize the designs for ease of manufacturing and assembly while keeping functionality intact
• Identify the critical tolerances which require tighter tolerance control or statistical process control, SPC
• Enlarge drawing tolerances and thereby reducing cost of design
• Develop robust design with low risk of failure

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