How to Meet the Dimensional Engineering Challenges Inherent in Increased Automation

Engineers across many manufacturing industries are faced with dimensional engineering challenges as their organizations increase the use of automation on the plant floor.

A critical part of the engineers’ dimensional engineering process involves verifying that the parts being produced meet the tolerances and dimensional specifications they’ve outlined. Yet, cycle time reductions resulting from increased automation have limited the windows of time they have to confirm these “as-built” measurements.

This is where having a comprehensive closed-loop dimensional engineering process in place is not only desirable, but necessary.

Closed-Loop Solutions

In a closed-loop dimensional engineering process, dimensional quality data reports are generated as the product enters preproduction and initial runs begin. Engineers refer to the reports and check key points to ensure that measurement plans for the detail parts are being followed and that end-products achieve the quality targets expected based on the results of all prior steps in the dimensional engineering process. With these results, they are able to quickly conduct root-cause analyses of quality issues as they arise. If the end-products are not achieving the quality expected, engineers can “loop back” to find out where problems originated and initiate corrective actions as needed.

This closed loop approach is referred to as such because it closes the product lifecycle management loop and allows engineers to apply world-class dimensional engineering to their products from start to finish, a critical component of an overall quality program.

While there are many dimensional engineering tools on the market today, few provide meaningful, measurement-based data all the way across the product lifecycle, through the production phase. And even fewer can function well in an automation environment with tight cycle times.

 

Dimensional Control Systems’ software tools (3DCS and GDM) are among the few that function well in a highly automated event. They provide comprehensive virtual simulation and analyses of variation and tolerances in product design from the initial product development and into production, ensuring that the value of the dimensional analysis is maintained across the full product lifecycle, regardless of cycle time.

 

The 3DCS software tool is a CAD-based tolerance analysis solution for predicting the amounts of part and process variation and identifying their sources. It allows manufacturers to thoroughly appraise design, fabrication and assembly robustness by quickly evaluating embedded Geometric Dimensioning & Tolerancing (GD&T), assembly tooling and build sequencing – all well ahead of production release.  The 3DCS tool uses a Monte Carlo random number generator to randomly select points, (representing random production builds) within each tolerance and distribution, one sampling at a time. The tolerance simulation identifies areas of concern, potential failure rates, and statistical results for each measurement, such as percent out of specification.  A sensitivity analysis then looks at each tolerance as it relates to each measurement, and it identifies the percentage contribution or affect on each measurement. 

 

Based on the output of 3DCS, measurement plans are created with GDM. The plans define which critical-to-quality characteristics are to be inspected for dimensional variability.  GDM is a quality data management reporting and monitoring system, which allows users and managers to review and control their processes from anywhere in the world.  By providing real-time analysis of measured quality data, trends can be detected and potential problems rectified well before parts or assemblies start to fail more traditional quality checks.  For the first time it will be possible to ‘close the loop’ from manufacturing back to design, providing real feedback for engineers, directly improving overall product quality.

 

By relying on these virtual simulations and feeding measurement inspection data back into the tolerance model, engineers can quickly pinpoint issues and perform corrective actions -- avoiding the need to chase problems through their build process by trial and error.

An Example

In a typical application of 3DCS to a product design, the engineer identifies key points within its design that it wants to control closely. For example, key points typically exist where a door fits to a body or a hood interfaces with the headlamp or fender. All parties involved focus on holding these points precisely as the design moves into manufacturing.

While 3DCS can predict and show through virtual simulation the variation of hundreds of features with corresponding measurement points in the design stage, these vast amount of data would be too cumbersome to interpret, and root-cause analyze, for the plant floor engineers in a highly automated environment.

In this environment, the number of points they can actually check must be limited in order to meet their tight cycle-time requirements, and or measurement cell/tooling budget restrictions. When measurements of key points are taken through automated in-line inspection devices, the number of points that can be checked at each manufacturing cell are far fewer than the limits often applied in manual processes.

 

For example, a manual process on a coordinate measurement machine, or CMM, can easily measure 300-plus points over a couple of hours. To optimize this process for an automated inline application, a 90 percent reduction in points is required. 

 

To meet the constraints of the faster cycle times associated with increased automation, many engineers use the Advanced Analyzer Optimizer (AAO) feature of 3DCS. This feature compares the hundreds of focal features identified through the 3DCS core functions then further sorts them to identify those that have the very highest influence on the overall quality of the product. This process gives engineering and quality to tools to effectively and efficiently identify critical features and plant floor quality tooling requirements. 

 

In Practice

America’s premium truck manufacturer, Peterbilt, is one of the companies that can speak to the value of the 3DCS approach. The company has been using 3DCS tools to manage dimensional quality throughout the design process for many years. As it moves more heavily into inline automated process, the company is pleased to be able to extend the value of dimensional engineering more fully into the production environment.

 

As its use of automation increases, the company believes that having agile dimensional engineering tools built into its quality processes will help it continue to meet quality and cost goals while speeding its product turnaround times.

 

The flexibility of 3DCS enables Peterbilt engineers to continue to use the power of a closed-loop dimensional engineering approach to identify the key points that most affect the fit, function and finish of their products-- even as the allowable number of points is reduced

About Dimensional Control Systems

Dimensional Control Systems Inc. (DCS) is a world-class experienced provider of dimensional engineering software solutions and consulting services. Established in 1994, DCS is a privately held company with partners and customers around the world.  Leading organizations like Airbus, BMW, Boeing, Chrysler, Daimler AG, Embraer, General Motors, Herman Miller, IBM, Lockheed Martin, Volkswagen, and many major tier-one and tier-two suppliers use DCS solutions to optimize product design and manufacturing processes, improve quality, and reduce program cost and timing. DCS’ 3D tolerance analysis and quality assurance software applications fully support the entire product quality lifecycle. 

 For more information, see www.3dcs.com.

 

 



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