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Sam Golan

Innovation

Supply Chain Innovation Begins With Interpretation

Leveraging automated GD&T

Published: Tuesday, September 4, 2018 - 11:02

Technological innovations on all fronts are evolving quickly and are developed, manufactured, and sold worldwide in aerospace, medical device, communications, automotive, and many other industry segments. It’s hard to keep up with these breakthroughs because they are growing exponentially. But despite all the technological innovations, one critical issue has persisted since the first industrial revolution during the mid-1800s: the engineering, manufacturing, and quality “interpretation” by companies’ suppliers, whether internal or external.

For many years geometric dimensioning and tolerancing (GD&T) has been the engineering, manufacturing, and quality processes language. The origin of GD&T has been credited to Stanley Parker, who worked at the Royal Torpedo Factory in Alexandria, Scotland. Parker started to develop the concept in 1938, and for nearly 20 years he added more into the language, culminating in his last book, Drawings and Dimensions (Pitman, 1956).

GD&T is an exact language that enables design engineers to “say what they mean” on a drawing. In theory, a GD&T document should carry the same meaning to everyone. Design and manufacturing use the language to interpret the design intent and to determine the right manufacturing approach. Quality control and inspection use GD&T language to interpret proper setup, part inspection, and verification. In reality, though, the language is complex enough that even within internal departments, two engineers who work together may not realize they are misreading or misapplying GD&T symbols. When it comes to outside suppliers, this misinterpretation has an exponentially negative impact. In addition to making parts that don’t match the design intent, it can delay the entire assembly of a product.

Today, a single car has about 40,000 parts, and future models—electric and autonomous—will double this number. In comparison, the Boeing 787 Dreamliner has about 2.3 million parts (counting every part down to the smallest screw). Around the world, hundreds of thousands suppliers are ranked by tiers and produce these parts. Millions of parts are manufactured daily; they are made of numerous raw materials and have different manufacturing and inspection processes.

Readiness for Industry 4.0

The complexity of today’s global supply chain introduces new business needs that are far more demanding than what present systems can fulfill; they are definitely not ready for the imminent arrival of Industry 4.0. Currently, the solutions available at OEM levels and for higher tiers suffer from a lack of capabilities and focus on metadata rather than content, which is the most critical part in communicating with the supply chain. Current solutions require manual data entry and other labor-intensive processes by OEMs. The manufacturing and quality systems at lower supply chain tiers include multiple software solutions that produce many forms, documents, standards, analyses, and reports. These data may not even be stored in databases but in fragmented file systems, which represents much greater complexity and vulnerability within the supply chain. This disjointed and outdated solution creates many difficulties, including a lack of internal and external collaboration and communication, and significant lack of alignment. It currently provides minimal value to organizations, particularly for their quality processes, improvements, competitiveness, error prevention, cost reduction, delivery time, and budgets.

Currently, manufacturing supply chains within any given industry are lacking a crucial capability: preventing supply chain interpretation. Given that more than 80 percent of supply chains use 2D prints for manufacturing, this is a critical oversight. Additionally, supply chains lack the ability to automatically and securely manage quality requirements directly from a file  or other digital content, and seamlessly communicate, manage, and integrate with the supply chain from the bidding stage through designing, manufacturing, engineering changes, to delivery on time, within quality parameters, and on budget.

In mid-2016, 60 years after Parker’s last book was published, High QA presented a solution that enables OEMs and suppliers to collaborate seamlessly by using common GD&T language without the need for manual interpretation. Based on High QA’s optical manufacturing and quality characteristics recognition (OMCQR) platform technology, in combination with artificial intelligence and a quality and manufacturing “dictionary,” the solution addresses industries’ need for accurate manufacturing and quality data as they move forward into Industry 4.0.

High QA will be exhibiting at IMTS 2018 in Chicago starting on Sept. 10. Look for us in booth No. 135314.

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About The Author

Sam Golan’s picture

Sam Golan

Sam Golan is the founder and CEO of HighQA enterprise quality management systems. He has more than 25 years of continuous success in building, leading, and managing multinational organizations and expanding them internationally. Among the numerous software companies he has developed through all stages across a range of industries include Cmatron (Currently 3D Systems) and Enovia/Dassault Systèmes. HighQA Quality 4.0 enables manufacturers to automate their entire internal and external manufacturing and quality processes, there by eliminating user errors, managing corrective and preventive measures, and significantly improving customer satisfaction.

Comments

GD&T Dictionary - Automated or Otherwise

Unfortunately a common language is of very little use to illiterates.  Too many engineers today cannot communicate in complete sentences - either verbally or in writing, let alone speak a common technical language.  Several years ago, a licensed PE working for Federal Highways demanded that my office enforce exact placement of concrete reinforcement based on their measurement of elements in a drawing that was clearly marked "Not to Scale" and where the only dimension given was a minimum depth of cover. 

When a second PE working for my agency concurred with the Fed's determination, I inquired about tolerances for deviation.  I was told that we were to accept "zero" tolerance.  I inquired futher as to what was meant by zero.  The engineer looked at me quizzically and asked what did I mean.  I explained about standard tolerances and said that we needed to define zero in terms of the number of significant digits we wanted to use to define the tolerance.  The engineer got very red in the face, slammed their fists onto the conference table and screamed that "zero meant zero".  So we interpreted that to mean that they wanted 0" giving us a standard tolerance of +/- 0.5" where the previous defined tolerance for these units was .25" -going to show that you get what you pay for all around.