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Donald Jasurda

Metrology

Using Closed-Loop Dimensional Control Systems

An ounce of prevention, in engineering terms

Published: Thursday, September 30, 2010 - 05:30

The value of ongoing maintenance and prevention is no secret. We know we can save a lot of anguish and money by taking preventive actions today and every day to avoid major problems later. This principle also applies to the quality of the products designed each day by engineers.

The “healthiest,” most successful automotive and aerospace companies use tools early and often to address dimensional engineering problems before they occur. This prevents problems that others may not discover until manufacturing or—worse—until their end-customer experiences them as quality issues.

Ask the right questions at the right time

When it comes to quality, everything starts in design. It’s important to ask the following questions as early as possible in the process:

• Is your quality process in control?

• Is it linked to your program objectives?

• Are your product and process requirements tightly defined and traceable?

• Are there any process considerations being made for dimensional objectives?

• Does your build strategy help you meet your design for Six Sigma (DFSS) objectives?

• Are you going to make your launch schedule—without staff overtime or other unplanned costs?

Define your dimensional engineering process

Most quality problems are the result of a poor definition of requirements, an improper allocation of tolerances, or the lack of early specification validation. The case for a well-defined dimensional engineering process is well established as a proven tool for effective process development.

Many leading original equipment manufacturers (OEMs) in aerospace, automotive, and other industries use dimensional engineering software to drive variation analysis as part of a world-class quality process. The software provided by Dimensional Control Systems (DCS), for example, enables users to validate manufactured components, regardless of where or how they are manufactured. By using 3-D data, sophisticated measurements, visual simulation, and testing, engineers can quickly pinpoint problems and perform root cause analyses to solve problems, thus avoiding the need to chase problems through their build-process steps. The illustration in figure 1 outlines the dimensional engineering process.

Figure 1: Dimensional engineering process

With DCS software, engineers are empowered to analyze tolerance stack-ups and their effects on overall assembly. They can address, with precision, three key questions that drive the perceived quality of every product:

• Do things fit together as intended?

• Does the product look like it is supposed to look?

• Does the product function as intended?

 

To answer these questions, engineers view how assemblies fit together, and then adjust tolerances or properties to better achieve their goals. For example, they can use visual simulation to identify flush and gap misalignment, part interference, hole winking, and related issues. There is no other way engineers could predict these problems because they can’t be seen in standard computer-aided design (CAD) or computer-aided manufacturing (CAM) views.

Most critical assembled components in nearly all automotive vehicles and aircraft built today are subjected to 3-D model-based tolerance analysis. Engineers use variation analysis tools to understand dimensional fit characteristics and quality status before they start the build process. Variation analysis is also used in production monitoring and early-stage, low-volume prototype development.

Using tolerance analysis enables leading OEMs to achieve robust and repeatable fabrication and assembly processes for complex, often large, assembled products. This results in shorter launch cycles, improved process capabilities, reduced scrap, and less production downtime.

The closed-loop system

A comprehensive dimensional engineering process enables fit, finish, and function to be analyzed. Multiple solutions can be tried through visual simulation, then validated through automated as-built reporting. This closed-loop system drives product quality all the way from design engineering to production. The system looks like the illustration in figure 2:

Figure 2: A closed-loop, dimensional engineering system

A closed-loop variation analysis system enables engineers to correlate theoretical tolerance analysis results produced during simulation to actual as-built results determined at other stages of the quality process. Based on correlations, the as-designed simulation parameters can be validated or adjusted to more closely align to production process capabilities.

Additionally, a closed-loop system enables best practices to be validated, captured, and reused on future programs for engineering simulation and manufacturing. Leading OEMs are beginning to use closed-loop systems to improve their program efficiency as they continually face tighter and tighter development cycles and budgets. The intelligence they gather through this system helps them discover ways to reuse existing and proven manufacturing process elements and modularized tooling on new and redesign programs, which saves time and cost.

Those OEMs that use a closed-loop variation analysis as a critical part of their quality program are truly able to experience the benefits of an “ounce of prevention.”

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About The Author

Donald Jasurda’s picture

Donald Jasurda

Donald Jasurda has more than 30 years of engineering process improvement experience in the automotive, aerospace, medical device, and machinery industries where he worked on leading-edge projects ranging from mechanical artificial heart valves to composite commercial aircrafts, wind power generation and most recently, electric vehicles. Jasurda is the vice president of sales at Dimensional Control Systems Inc. (DCS), where he leads the sales and process transformation teams. DCS is a global provider of dimensional engineering consulting services and 3-D tolerance analysis and quality assurance software solutions that fully support the entire product life cycle.