AVEVA.NET enabled Woodside to consolidate schematics and all engineering data in one, easily accessible PLM system that takes new employees about an hour and a half to learn.
Woodside Energy, one of the largest publicly traded oil and gas companies headquartered in Australia, traces its origins back to 1953, the year after the first oil was discovered Down Under. That proud industrial history also comes with a burdensome legacy known as engineering legacy data.
Company archives, amounting to decades of project data, comprise paper documents, microfilm, Microstation files, AutoCAD files, piping and instrumentation schematics, and maintenance records scattered across several repositories in both corporate and outside (service providers’) document management systems. At one point, Woodside’s engineering data management team supported more than 250 applications, many homegrown, that required new hires an estimated 20 hours to learn.
In 2004, after an extensive evaluation process, Woodside chose AVEVA.NET, an ISO15926-compliant PLM system, as a single source. Today, new employees get trained in a limited number of core applications (AVEVA’s VNET and SAP among them), reducing the training time to 1.5 hours. All Woodside assets are now accessible via a standard VNET portal, allowing Woodside to train its employees once.
Second Time Around
Dave Coppin, AVEVA’s executive VP for AVEVA.NET solutions, was among those who first went to Woodside Energy to bid on the project.
“That was actually Woodside’s second attempt at [consolidation],” said Coppin. “A similar undertaking was made in 2001. It was an IT-led initiative, meant to change everything overnight—the Big Bang approach.” That project fizzled out at the end of the dot-com boom and by the end of 2003, Woodside ws ready for another crack at information management. According to Coppin, “[Woodside’s] engineering group was having difficulty controlling the large number of applications that wouldn’t talk to one another.”
This time, Woodside and AVEVA implemented the changes in various phases, not all at once. The project was to be led by engineering, not IT as in previous attempts. Coppin recalled, “It was not just about putting in an information backbone but about installing an integrated engineering solution based on modern technologies.”
With electronic data, more data doesn’t necessarily mean better data. “Data quality was a major issue,” recalled Richard Harris, Woodside’s engineering data management technical authority and team leader.
Typically, Woodside collects process maps, engineering libraries, and metadata: facility codes, system codes, document types, relevant disciplines, and so on, all reduced to a series of alphanumeric codes.
“But it’s difficult to associate intelligence with numbers,” said Bill Van Butzelaar, Woodside’s business improvement manager. “We want to put intelligence back into metadata.“
Product Lifecycle vs. Asset Lifecycle
Though AVEVA sometimes refers to its technologies as product lifecycle management, using the same three-letter acronym employed by Dassult Systemes, PTC, and Siemens PLM Software, AVEVA’s specialty may more accurately be described as asset lifecycle management.
“With product lifecycle management, you’re dealing with a product during its manufacturing stages,” clarified Dave Coppin, AVEVA’s executive VP for AVEVA.NET solutions. “Asset lifecycle management is the control and management of all the data in an operating facility. Not many [asset lifecycles] start from inception, but it could start from there, all the way to decommissioning.” For AVEVA, “asset” primarily means data from power plants, marine facilities, and oil and gas refineries. —KW
Employees used to juggle nine different metadata profiles, most of them comprising noncritical engineering information. AVEVA.NET helped drive Woodside toward a single metadata profile.
With the introduction to VNET, Woodside began its transition from traditional 2D data paradigm to digital archival system. Not only did it result in substantial savings, but it also enabled reuse of engineering data in new projects and in repurposing assets.
In the oil and gas industry, plant components—pipes, valves, cables, machinery, and plant areas, to name but a few—are marked with tags, or unique identifiers that explain their locations, maintenance records, purposes, and functions. The more complex the site, the greater the number of tags. There’s a direct correlation between the volume of tags involved in a new plant and the price Woodside must pay to fix inaccurate and inconsistent data when an EPC (engineering, procurement, and construction) firm hands over the finished facility.
“We knew that, historically, the cost of a post-handover data manipulation and cleansing team would cost about eight times more than having the project source that required data prior to handover,” said van Butzelaar. Typically, each capital project handover cost Woodside about $3 million, depending on the project scope.
But the streamlined data structure imposed by AVEVA.NET changed that. Recently, a new facility (dubbed Woodside Angel Project, constructed in Singapore) was completed. It was used as benchmark for the success of the EDM project handover strategy. The cost to Woodside was $250,000, a significant drop from the previous bills.
More to Come
Looking ahead to 2012, Woodside plans to use its media gallery to monitor its sites, to photographically keep track of sections and machinery that are shut down, in repair, or operating as normal.
These site photos may even let contractors issue quotes without costly site visits. They also reduce time in the field. “Some of these are high-risk areas, so we don’t really want crews to be there if they don’t have to,” noted van Butzelaar.
As part of the project, AVEVA helped Woodside migrate its existing data into the AVEVA.NET environment. “If the data is electronic—3D models, AutoCAD files, intelligent PDFs, databases, Excel, Word, those types of documents—then it’s very easy to do,” said AVEVA’s Coppin.
When dealing with unintelligent documents—paper documents that have been scanned and converted to PDF, for example—AVEVA uses optical character recognition features, then compares the text to 3D models and master data repositories.
Kenneth Wong writes about technology, its innovative use, and its implications. One of DE’s MCAD/PLM experts, he writes DE’s Virtual Desktop blog at deskeng.com/virtual_desktop/.