Benjamin Reese, on Jan 23, 2018 10:41:09 AM
Benjamin Reese, on Aug 10, 2017 9:02:00 AM
SOVA is a method of applying variation analysis as part of the design and manufacturing process to drive robust design in order to reduce costs in manufacturing.
Developed in the late 90's and early 2000's and documented in the book "Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes" (Jianjun Shi, 2006, CRC Press, ISBN 1420003909), it forms a basis for many of the programs DCS provides for customers and is similar to many process established by leading manufacturers in the automotive and aerospace industries.
Benjamin Reese, on Aug 9, 2017 11:20:48 AM
In a typical assembly process, dimensional variation is affected by tolerances (including component and operationinduced tolerances) and operations. Tolerance Analysis is focused on tolerances and assumes operations are known. Dimensional Variation Analysis analyzes both tolerances and operations. For example, operation sequence or operation type is an analysis topic for Dimensional Variation Analysis.
Benjamin Reese, on Jun 27, 2016 1:52:18 PM
Now available on the DCS Community, the DE Focus article series highlights useful features and functions in 3DCS, as well as discussing strategy, dimensional management and GD&T.
Benjamin Reese, on Feb 2, 2015 3:32:00 PM
How do you know your results are accurate? Here are some methods of calculating your Confidence Interval
Dimensional Control Systems 3DCS® is a variation analysis tool that uses Monte Carlo simulation to predict the results of a set of measurements [Dimensional Engineering News, June 2009]. After a variation model is built in 3DCS®, a Monte Carlo simulation can be performed to provide the following statistics:
Descriptive statistics - calculations made directly from the sample data such as mean, minimum, maximum, standard deviation, percentage out-of-spec, confidence intervals, etc.
Inferential statistics – estimations based on a curve-fitting algorithm such as estimated low, estimated high, estimated percentage out-of-spec, etc.