Jim Kinter, Chair, Zachry
Tedd Weitzman – Southern Company
Ioannis Brilakis – Cambrige University
Craig Larson – Oracle
Deb McNeil - Dow Chemical
Sonali Singh – ASD Global
Tom Sawyer – ENR
Larry Daniels – Eastman Chemical
Duane Toaves – Emerson
Rayan Jreije - CCC
Maggie Brown – Crossrail
Chris Lalka - ExxonMobil
Awards presented at the CETI Awards Gala on April 5, 2016:
Fluor Corporation with AMECO and PERI Integrated Scaffolding Solution for North West Redwater Sturgeon Refinery
Fluor Corporation is providing engineering, procurement, fabrication and construction (EPFC) for the North West Redwater (NWR) Sturgeon Refinery project in Alberta, Canada. Once complete, the facility will convert bitumen blend into premium ultra-low sulphur diesel, diluents, and other products. Situated in a high-cost labor market, direct construction efficiency and productivity was a major concern for the owner and for Fluor. The project team identified scaffolding, which can account for 20 to 40 percent of direct labor costs on a large scale industrial facility project, as an opportunity area for significant cost reduction through application of an innovative approach. To address this challenge, Fluor, in partnership with equipment subsidiary AMECO and German scaffolding company PERI, developed and implemented an Integrated Scaffolding Solution that drives a step change in efficient scaffolding execution compared to traditional “design-as-you-build” approaches. Fluor’s Integrated Scaffolding Solution makes scaffolding an integral part of the detailed design development. The approach incorporates highly efficient assembly sequencing as a key driver of design, including the attachment and support connections for scaffolding that are integral to the structural steel design and fabrication. To maximize value, Fluor’s solution utilizes PERI, an engineered scaffold system, which allows for maximized assembly at grade with reduced support from grade. This promotes ease of access on the project and site-wide productivity enhancement beyond just the scaffold assembly itself. A turnkey solution, Fluor’s scaffolding program includes 3D design, logistics, and distribution expertise as well as field execution expertise, whereby scaffolds are identified and designed in the 3D model during the project’s design phase before construction in the field, as is traditionally done. This enables visualization of where the scaffolding will be placed in a module, vessel, or elsewhere on the site, as well as the ability to build the scaffolding system in a way to accommodate construction elements, such as electrical trays or piping which helps eliminate rework. Other advantages provided by Fluor’s Integrated Scaffolding Solution include reduced site congestion (due to having less scaffold supports at ground level), improved measurement and reporting of scaffold material on site, and accurate logistics planning and sequencing.
CCC King Hussein Cancer Center (KHCC)
The King Hussein Cancer Center (KHCC) Construction Project is considered a small size project compared to the CCC portfolio but the complexity is rated very high due to the complications that usually accompany fully-equipped hospital fit-ups. The challenge of delivering a hospital in 730 calendar days, places KHCCC on a fast track that dictates meticulous coordination between a large number of subcontractors including medical equipment and furniture suppliers. The decision to introduce culture changing Lean methodologies and emerging 3D technologies was challenged by the fact that the smaller the construction project, the less resources and margin there are to experiment with. Nevertheless, the KHCC project team took the Lean challenge and audaciously implemented the full fledge C3D LEAN (© CCT Intl. 2004 - 2016) Project Controls System. C3D LEAN empowered the engineers to identify Open Fronts through Front-End-Loading (FEL). FEL ensures that work orders are only issued after requirements are met and checked (such as engineering drawings availability, resource availability, material availability special constraints, and clearance from other crews). Once applied, the C3D LEAN methodology results in a laminar flow of work minimizing turbulence and optimizing time, cost, and safety performance. The results exceeded all expectations and materialized into a fully operational 3D LEAN based room completion system. This was done by keeping the project on track and making it a remarkable success story. C3D LEAN sequencing facilitated the detection of optimal contracts assignment. It also helped with coordination between subcontractors and optimized the storage space management. The automation of the subcontractor invoice approvals and the payment certificates for the owner came as a by-product. All in all, it has been proven that LEAN Project controls boosts the efficiency of project delivery, reduces usage of unneeded resources, increases profit, and reduces safety hazards on site to a minimum. In addition to the direct benefits, the indirect long-term benefit was breaking down the cultural barrier and reducing resistance to change for CCC as well as other EPC contractors. Another indirect benefit was the rich and well-organized information model handed over for O&M. The project team set the example that a persistent team, if endorsed with the appropriate automation tools, can and will make the difference and achieve LEAN construction targets.
Costain and The University of Reading GIS in the Visualisation of Biodiversity as an Early Planning and Mitigation Tool
As land planners attempt to mitigate irreversible damages to the environment in order to avoid net loss to biodiversity, the potential “silver bullet” of conservation in planning, biodiversity offsetting, is expensive and sometimes ineffective. Therefore, the pressure is on innovation and technology to reduce impacts to the wider environment during large infrastructure development by becoming aware of the surrounding environment from the start of a project. The overall aim of this engineering doctoral project was to use GIS to develop a prototype model as an early planning solution to inform or avoid the future use of biodiversity offsetting. The test site was Section 2 of the A465 road widening in Wales. The three-stage tool gives an indication of potential ecological restraints that could affect the time and cost of the project. Stage One displays and identifies the conservation designations and governing bodies, such as national parks, sites of special scientific interest, or areas of outstanding natural beauty. Stage Two detects any EU protected species that have previously been recorded within 5km of the site and Stage Three uses an analysis of landscape metrics and habitat requirements of EU protected species present on site. So far, the outputs, in the current form of 2D maps, have been used effectively by the company through the bid-writing process on other projects to establish awareness of the surrounding environment. The model is going to be tested further on other linear asset sites. In addition it will be shown to environmental advisors while testing other visualisation tools for effectiveness, such as the CAVE at the University of Reading, and virtual reality using Oculus Rift. As the tool from this project becomes more widely used, it will have more potential to revolutionise biodiversity policies and procedures for large infrastructure development within the UK. The commercial benefits from this project are immense. Over time, the tool from this project will be used throughout the life cycle of a project, enabling customers to gain the maximum benefit from their biodiversity offsetting. In addition, this work on biodiversity mapping has the potential to influence and inform construction projects, from feeding into feasibility studies and concept design to informing the construction and restoration processes, ensuring that impacts on the local environment are minimized and helping deliver a net positive gain in biodiversity.
ProjectAtlas Parkland Med-Surg Clinic
The Parkland Medical Surgery (Med-Surg) Clinic is a 5-story, 227,000 square foot. outpatient medical facility located in Dallas, Texas and scheduled for completion in July 2016. Its 171 exam rooms and 12 treatment rooms will support the brand-new 2 million square foot Parkland Replacement Hospital with Urology, Neurology, ENT, Radiology, Imaging, Cardiac Rehabilitation, Pre-Anesthesia and Surgical Exam services. The Med-Surg Clinic is also connected with the adjacent acute care hospital via a pedestrian bridge on the second level and a subgrade service tunnel. The project will be the last building in a multi-billion dollar, decade long re-envisioning of the Parkland Health & Hospital System campus – the largest single-phase healthcare construction project in the United States. The project is made more complex by the fact that more than 75 different companies were involved, including a joint-venture team from Rogers-O’Brien Construction (RO) and JE Dunn. From the beginning the team knew there would be challenges collecting and organizing information. The RO team volunteered to lead document management, having been successful on past projects. As the project progressed, the team realized that traditional paper processes, while digitized, wouldn’t be good enough and instead opted to test a new software application called Project Atlas. The software platform effectively allowed the team to piece together project information and see the project in its entirety rather than 1/6th of a floor at a time. Additionally, the team utilized Redpoint Positioning, a real-time location services (RTLS) solution that allowed users to pin-point their exact location within the project. These two technologies combined created a friendly and error-free experience when viewing project drawings, similar to using Google Maps to navigate a city map. The result was quick access to current information without having to dig through hundreds of pages of data.
BaseStone Digital Redline Review
Construction job sites run on data that can, when collected and utilized effectively, reduce construction time, cost, errors and rework. The Costain-Skanska Joint Venture used a redlining tool (BaseStone) in three different trials. The trials began by comparing the redline drawing review process and the requirements of Crossrail for redline outputs. Two trials were conducted over a period of 5 weeks. BaseStone was used for redline drawing generation and Snagging at Eastbourne Terrace (Crossrail’s Paddington site run by CSJV). The use of BaseStone was expanded into a design review trial with Alstom, TSO and Costain Joint Venture (ATC). Crossrail then produced a Six Sigma report to verify efficiency gains.Redline tools are widely deployed throughout the industry. This particular project represented a more complex and holistic application of this technology. This project demonstrated the viability of a common user interface and integration with the user’s current document management system (Enterprise Bridge). In providing one platform for data capture, import and export this technology enabled standard data exchange. By understanding common workflow requirements and subsequently creating accessible information to ensure "right people/right time" data delivery efficiency was increased and participant learning curve was decreased. The technology, coupled with revisions in work process, enabled improvements in efficiency and effectiveness for redline reviews. The trial project proves the concept and can be applied to all capital projects. The project helped drive the adoption of BIM by improving data accessibility and demonstrating the value of that data. BIM tools provide a data driven opportunity for innovation in work process. The trials were proof of concept and moved the needle for effective data management. The accomplishment links directly to Fiatech Productivity Advancement Targets. The project demonstrates the effective transformation of field data collected into integrated business intelligence.
Precyse Technologies, Inc with AECOM Olmsted Dam Project
Managing and maintaining high value equipment is an operational imperative for EPC firms and companies engaged in large scale heavy construction. AECOM needed a solution to identify, locate, and monitor vital engine statistics for more than 330 vehicle, pieces of heavy equipment, and vessels at the Olmsted Dam construction site in Illinois. This state-of-the-art multi-billion dollar project is one of the largest civil works projects undertaken by the United States Army Corps of Engineers (USACE). AECOM needed a solution, requiring only minimal infrastructure, which would fully cover the expansive site’s land and water work areas. All of the assets needing to be identified, located and monitored were located outside, with some on the lower decks of tugs. Engine statistics needed to be collected approximately every six hours and reports needed to be provided on a weekly basis. The PrecyseTech proprietary IIoT solution, Industrial IoT, was implemented utilizing various patented location, communication and sensor technologies. Automating the collection of information minimized the need for workers to manually interact with these assets thus reducing the risk of personal injury such as slips, trips and falls. The process involved establishing a wireless network infrastructure to cover the entire dam. Vehicle agents were installed on each vessel and connected to the engines via CAN bus interface. As a result, current location, odometer readings (mileage), sudden impact and engine run time were acquired in real-time and reported to the system. Empowered with remote management capabilities, AECOM reduced operating and maintenance costs while it enhanced capabilities to responsively support construction operations.
Stefania C. Radopoulou, University of Cambridge Automated Detection of Road Defects for Enhanced Pavement Condition Assessment
The American Society of Civil Engineers has graded the country’s road infrastructure a “D”, which reveals its poor conditions due to insufficient data, information gaps, and poor quality of pre-collected road condition data. The objective of Stefania C. Radopoulou’s project at the University of Cambridge is to create a novel framework that, when combined with low cost vehicle sensors into a system, is able to detect the type, location, and severity of defects and damages on road assets for condition assessment purposes. The proposed method utilizes existing rear-view parking cameras and GPS sensors on modern day cars, accelerometers, and odometers. The method can automatically detect and assess road defects to assist road owners with maintenance decisions while minimizing the time spent on manual collection methods. Detected defects are registered into a database for inspectors to further investigate. This technology addresses the operations & maintenance of aging infrastructure. It enables a safe, secure, and continuously optimized system to assist road owners in the decision making process of infrastructure maintenance. The system is a cost-effective solution in comparison to current methods and allows for operational maintenance of the roadways within the performance envelope while providing near real-time condition assessment, assisting in the prediction of problems, i.e. fixing defects before they become “dangerous”, and enhancing life cycle performance of roadways. Stefania is currently a PhD candidate in the Department of Engineering at the University of Cambridge in Cambridge, UK. She has a BEng-MEng in Civil Engineering and a MSc in Engineering Project Management from the Aristotle University of Thessaloniki in Greece and a MSc in Transportation from the Massachusetts Institute of Technology in Cambridge, MA. Her PhD research is in the areas of computer vision, image processing and machine learning where she has made significant contributions in the field of computing for civil engineering practices.
Vineet R. Kamat
Dr. Kamat’s research in real-time visualization experimentally demonstrated that the real-time operations monitoring that incorporates proximity sensing and collision detection algorithms has the potential to significantly improve the safety and productivity of visibility-constrained construction processes such as urban excavation and crane operations. This research led to twleve Invention Disclosures, four Patents, and has had a significant impact on professional practice. The work also spawned a start-up company named Perception Analytics and Robotics LLC (PeARL) that is focused on the design and deployment of automation technologies for construction and maintenance of capital facilities and has been commercializing technologies developed in his research. Dr. Kamat’s research has led to strong collaborations with industry partners and government laboratories that include Turner, Skanska, Walbridge, Eagle Excavation, DTE Energy, Walsh Group, Miss Dig System, Mitsubishi Electric Research Laboratories, Michigan Department of Transportation (MDOT), California Department of Transportation (CalTrans), US Army Corps of Engineers Construction Engineering Research Laboratory, and the National Institute of Standards and Technology (NIST). Dr. Kamat has also established strong research collaborations with national and international institutions that include Purdue University and Hanyang University (Korea). Innovations and patented technologies developed in Dr. Kamat’s research are also being commercialized by a start-up company named Perception Analytics and Robotics LLC (PeARL) for the excavation and heavy lifting markets. His research has provided a new theoretical foundation for innovations in construction automation and robotics by outlining key differences between civil engineering and other automated disciplines. It has reduced the time and cost of constructed facilities through the use of visual simulation for planning and experimentation prior to actual construction. In particular, the research that developed augmented reality methods for subsurface utility visualization led to a new excavator-utility collision avoidance technology that is currently being used by contractors for subsurface utility detection during excavation. The research that developed semantic object recognition methods has been transferred to Mitsubishi Electric Research Laboratories for commercialization in civil infrastructure archival and maintenance applications. The research that developed context-aware infrastructure visualization methods has been transferred to the Michigan Department of Transportation for highway bridge condition assessment. Dr. Vineet R. Kamat, a Professor and John L. Tishman Faculty Scholar at the University of Michigan, received a Ph.D. in Civil Engineering at Virginia Polytechnic Institute and State University in 2003; a MS in Civil Engineering at Virginia Polytechnic Institute and State University in 2000; and a BE degree in Civil Engineering from Goa University in India in 1998.
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