AIAG Close on Data Swap

The different computer-generated product data systems used by auto makers and suppliers waste $1.4 billion annually in North America and $20 billion globally, says the Automotive Industry Action Group (AIAG).

The non-profit automotive trade organization based in Southfield, MI, ran a pilot program in August using new technology that allows OEMs and suppliers to share previously incompatible “meta-data,” which is any data used to aid the identification, description and location of networked electronic resources.

AIAG received a 2-year, $300,000 federal grant from the National Institute for Standardization of Technology (NIST) for the project, which uses Web-based applications to translate information across differing formats to make it compatible with different data-management systems.

Currently, computer-generated product data is difficult or impossible to read on any system except for the one on which it was created. Auto makers use computer-aided design software from SDRC, CATIA and Unigraphics, but the industry never has been able to get the systems to speak the same computer language. The AIAG study is a significant step forward.

“We've proven that there's a cure for ‘cancer’ in the laboratory, now it's up to the industry to take it from where we are,” says Akram Yunas, program manager for AIAG's pilot project. “The next six months are going to be devoted to a full-blown rollout globally. The push for industry support and implementation starts now.”

Participants include Ford Motor Co., Renault SA, Siemens VDO Automotive Corp., Johnson Controls Inc., TRW Automotive, EDS, Parametric Technology Corp. (PTC) and MatrixOne Inc.

Yunas says that although the pilot program still is in the research and development phase, Ford already has emphasized the importance of data sharing in its corporate policy.

The increasingly global economy calls for a standard format of data sharing among automotive-related companies, says Nick Andreou, engineering group manager for General Motors Corp.'s General Assembly Engineering and Manufacturing Math Modeling.