Problem Description

When building new refineries oil and gas companies engage engineers to design the refinary. The design is typically captured in a schematic drawing. These schematic drawings contain components such as pipes, fittings, valves and instruments. Prior to building a refinary a bill of materials is estimated from the schematic drawing. This is a manual process called a "take-off", where a civil engineer aggregates relevant components. The extraction of relevant components is not just a matter of lookup, it involves the application of complex domain rules. A typical process is as follows:

• A collection of schematic drawings, some of which stretch across multiple PDF documents, is submitted for cost estimation
• A team of cost estimators manually reviews the drawings and extracts a summary of materials used
• The extracted bill of materials is uploaded into an engineering system for cost estimation
• The cost estimation system generates a final cost estimate

The entire process is costly since it involves a manual review. It is slow and also error-prone. When reviewing schematic drawings across multiple pdf documents, it is easy miss something.

Reliancy Solution

We used Intelligent Process Automation to semi-automate what cost estimators do. The intent was to provide an assistive technology rather than to replace cost estimators. The solution consisted of the following steps:

• Study Of Cost Estimator Thought Processes

  Our first step was to thoroughly study how cost estimators do their take-offs. We categorized scenarios into those that are simpler and those that are more complex in nature.

• Implementation of Computer Vision Detection System

  A computer vision system was built to interpret a schematic drawing and to convert it into a usable digital representation.

• Implementation of Automation Logic

  Given the inferred digital representation of a schematic drawing we automated about 90% of the cost estimation process. Our focus was on simpler more managable scenarios. The complex and rare scenarios we left for the cost estimator to address.

• Flagging of Sub-Tasks That Require Human Review

  A system was built to flag areas of the schematic drawing where our automation could not be done with a high degree of certaintly. Once the processing was done the cost estimator was expected to manually inspect the flagged areas.

Impact

Our solution significantly improved the process of cost-estimation:

• Improved Speed of Processing

  Previously it took a civil engineer an entire day to process approximately 8 drawings. With the Reliancy system 100 engineering drawings can be processed and reviewed for accuracy within 60 min.

• Improved Quality

  Providing an assistive technology helped cost estimators reduce and catch errors. Manually processing huge drawings which might not even fit on a single page is a non-trivial task for a human.

• Improved Profitability

  The increase in efficiency allowed cost estimators to significantly increase their output and cut costs. From a business standpoint this translates to improved competitiveness.