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Sample Bearing Assembly

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Description: Try our tolerance calculator with this example

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Parts & Dimensions

1. Shaft

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Dimensions for Shaft:

Nominal	Type	Upper Tol.	Lower Tol.	Direction	Distribution	Notes	Actions
25.0000	Bilateral (+/-)	0.0250	0.0250	Positive (+)	Normal (Gaussian)	-	-

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Nominal value:

Tolerance type: Select how the tolerance is specified.

Upper tolerance: For Bilateral: + value. For Uni (0/+): + value. For Uni (-/0): 0.

Lower tolerance: For Bilateral: - value (enter as positive). For Uni (0/+): 0. For Uni (-/0): - value (enter as positive).

Direction: Is this dimension adding to (+) or subtracting from (-) the stack?

Distribution type: Statistical distribution for this dimension's tolerance.

Notes:

2. Bearing Inner Race

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Dimensions for Bearing Inner Race:

Nominal	Type	Upper Tol.	Lower Tol.	Direction	Distribution	Notes	Actions
25.0500	Bilateral (+/-)	0.0130	0.0130	Negative (-)	Normal (Gaussian)	-	-

Add Dimension to Bearing Inner Race

Nominal value:

Tolerance type: Select how the tolerance is specified.

Upper tolerance: For Bilateral: + value. For Uni (0/+): + value. For Uni (-/0): 0.

Lower tolerance: For Bilateral: - value (enter as positive). For Uni (0/+): 0. For Uni (-/0): - value (enter as positive).

Direction: Is this dimension adding to (+) or subtracting from (-) the stack?

Distribution type: Statistical distribution for this dimension's tolerance.

Notes:

3. Housing

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Dimensions for Housing:

Nominal	Type	Upper Tol.	Lower Tol.	Direction	Distribution	Notes	Actions
10.0000	Bilateral (+/-)	0.1000	0.1000	Positive (+)	Normal (Gaussian)	-	-

Add Dimension to Housing

Nominal value:

Tolerance type: Select how the tolerance is specified.

Upper tolerance: For Bilateral: + value. For Uni (0/+): + value. For Uni (-/0): 0.

Lower tolerance: For Bilateral: - value (enter as positive). For Uni (0/+): 0. For Uni (-/0): - value (enter as positive).

Direction: Is this dimension adding to (+) or subtracting from (-) the stack?

Distribution type: Statistical distribution for this dimension's tolerance.

Notes:

Calculation Results

Worst-Case Analysis

Assembly Nominal: 9.9500

Max Limit (Upper): 10.0880

Min Limit (Lower): 9.8120

Worst-Case Total Range: ±0.1380

Statistical (RSS) Analysis

Assembly Mean (Nominal): 9.9500

Sigma Level (k): 3

Combined RSS Tolerance (1σ): 0.0346

Statistical Upper Limit (3σ): 10.0539

Statistical Lower Limit (3σ): 9.8461

Statistical Total Range (3σ): ±0.1039

Terminology Guide

📖 Want the complete glossary? Visit our comprehensive tolerance calculator terminology guide for detailed explanations of all tolerance analysis terms.

LSL (Lower Specification Limit): The minimum acceptable value for a product or process measurement.
USL (Upper Specification Limit): The maximum acceptable value for a product or process measurement.
Nominal (Target): The ideal or target value for a dimension or assembly.
Worst-Case Min/Max: The extreme possible assembly values if all dimensions are at their smallest or largest limits simultaneously.
Worst-Case Total Range: The difference between the Worst-Case Max and Worst-Case Min limits.
RSS (Root Sum Squares): A statistical method to combine individual tolerances, assuming they are independent and normally distributed. Calculated as the square root of the sum of the squares of individual tolerances (or their equivalents).
Combined RSS Tolerance (1σ): The resulting standard deviation (1 sigma) of the assembly based on the RSS method. Represents the expected variation if each part's tolerance is its 1-sigma value.
Statistical Mean (RSS): The average value of the assembly expected from an RSS analysis, typically equal to the nominal assembly dimension.
Statistical Limits (kσ): The range around the statistical mean (e.g., +/- 3σ or +/- kσ) that is expected to contain a certain percentage of all assemblies. 'k' is the sigma level.
Monte Carlo Simulation: A computational technique that uses random sampling to simulate the behavior of a complex system, providing a distribution of possible outcomes.
Cpk (Process Capability Index): A measure of how well a process is centered within its specification limits and how variable it is. Higher Cpk values indicate a more capable process. Cpk = min((USL - Mean) / 3σ, (Mean - LSL) / 3σ).
Sigma Level (Quality Level): Indicates how many standard deviations fit between the process mean and the nearest specification limit. A "k-sigma process" (e.g., 3-sigma or 6-sigma) refers to this. For RSS results, 'k' is the multiplier for the combined RSS tolerance to determine statistical limits.