Hydrocarbon Processing - December 2020 - 9

L. JENSEN, Fluor, Calgary, Alberta, Canada; and
J. SZCZEPANEK, Fluor, Gliwice, Poland

Business Trends

Why we value engineering data
In the 21st century, one cannot escape the concept of data.
Data is everywhere, and it is an integral part of people's professional and personal lives. Within the business markets in
which we operate, there are plenty of intriguing and fascinating
terms-such as Industry 4.0, Construction 4.0, digital twin, artificial intelligence, big data, integrated project delivery (IPD),
building information modeling (BIM), common data environment (CDE), virtual design and construction (VDC), Internet
of Things (IoT), Internet of Everything (IoE), radio frequency
identification (RFID), augmented and virtual reality (AR/VR),
point cloud and cloud storage. Fundamentally, all data management serves the same purpose of storing information and subsequently sharing or publishing this data to the intended recipients.
However, for successful data management, there are a few important questions that must be answered, including:
* What data is required?
* Which are the real engineering authoring tools?
* How can data be managed and used effectively?
* How can engineers achieve consistent data?
Looking back to ancient Egypt and the pyramids, modern
humanity does not fully understand how the Egyptians built
them or how they used and recorded the data that made the pyramids able to stand for so many centuries. This precise data and
knowledge are lost to the modern age under the shifting sands of
the passing millennia.
The previous generation of engineers used to say, " Engineering data ended two places after dot; the rest was the nonsignificant noise. " Today, engineers recognize that data is a
valuable commodity, with a similar intrinsic value as steel, concrete, cables, pipes and equipment. Engineers have historically
recognized the value of data; however, in years past, the practice of formatting and storing data on paper meant that subsequent data retrieval in the future could be a challenge. Backup
tapes and drives were stored offsite, and the effort to retrieve
information from a previous project was typically not worth
the time and effort to get it. Consequently, the data would be
recreated again and again. This rework increased project costs
and created a data glass ceiling that engineers could not break
through to make significant improvements. The more recent
breakthrough of having centralized, retrievable and standardized data is just what the industry needed.
The authors' company values engineering data and innovation throughout the lifecycle of a project. Digital transformation enables the company to integrate and organize data across
the lifecycle of the facility, which creates data harmony. The
company's data-centric execution strategy is based on three pillars: data collection, data quality and data management.
Data is consumed by several entities on a project. Some of

the data consumers are internal recipients, including personnel
in engineering disciplines and construction. The other major
consumer is the end user (i.e., the client). It is imperative to engage and work with the client to ensure that the data developed
by the project team aligns with the client's data requirements.
To this end, a company should place great value on matching
the client's expectations by engaging subject matter experts
(SMEs) with data management knowledge and experience to
ensure that this alignment is achieved.
What data is required? From a current industry perspective, there has been visible progress made since the National
Institute of Standards and Technology (NIST) published Cost
Analysis of Inadequate Interoperability in the U.S. Capital Facilities Industry in August 2004. Two concepts were developed:
BIM (2002) and IPD (2007), which focused on the integration
of data and on organizing a CDE across all lifecycle phases of
a facility. In 2019, the standard Capital Facilities Information
Handover Specification v1.4 standardized the specification of
information handover requirements between end-user clients
and engineering services companies.
For example, specific data is required to build a facility with
regard to engineering and construction requirements, and other
data is required to maintain and operate the facility after it is
built. Some of this data is utilized in multiple project lifecycle
phases, while other data is specific to a single phase. It is important for the creator and consumer to know the purpose of each
piece of data. If specific data is assigned to the wrong purpose,
it can have a significant impact on a phase of the facilities lifecycle. A company's data workflow should clearly define which
pieces of data are required to be produced and the identity of
the data consumer. This understanding is fundamental to how
a company should manage data on the projects that it executes.
Various data formats-such as the ISO 10303 Standard
for the Exchange of Product (STEP) data model, the Industry Foundation Classes (IFC) data format, and the CIMSteel
Integration Standards (CIS/2) data exchange format-are
commonly used in the industry. There is no easy way to build
a single, universal data format for all software developers and
the industry to utilize. BIM maturity levels describe shared collaboration based on the generated and exchanged data, as well
as on the environment (federated model, integrated database).
Instead of focusing on what data schema or format to exchange,
the key is to understand what data-down to the lowest level
of detail-is needed. Once that is obtained, personnel can map
the various data exchange methods.
According to lean construction, this excessive collection
of data could be called " information overload. " BIM standard
Hydrocarbon Processing | DECEMBER 2020

Hydrocarbon Processing - December 2020

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