Nowadays automation plays an important role in various industries. A collection of algorithms, robots, and software has altered the traditional approaches in various fields. Contemporary robots provide human beings with many crucial services in which accuracy is of prime importance. For instance, robots can take and carryout orders in Amazon warehouse, fold clothes at a Berkeley lab, and slice the meat at supermarkets with the required precision. Artificial Intelligence (AI) and Machine Learning (ML) can defeat champions in different competitions. As expected, the construction industry has greatly benefited from the ongoing automation movement.
(Fig1. Use of genetic algorithm on Ali Al-Sabah Military Academy design process. Left: Overall bird’s eye view of campus. Right: Image of window design generated by genetic algorithm.)
There is a wide variety of engineering software with various levels of complexity that are used in modeling, analysis, design, and drafting procedures. These range from SAP and ETABS for finite element structural design of building structures, to HYSIS, an optimization chemical and process design software in the oil and gas industry. Depending on the complexity of the project, design drawings could be developed by a simple drafting software (such as AutoCAD) to a highly sophisticated 3d modeling BIM software with an interactive database that is capable of working from different engineering disciplines simultaneously with defined authentication levels.
As this trend continues, software developers are continuously trying to predict and fulfill their users’ current and future demands. Consequently, engineering software is growing in size and complexity. One of the important barriers to this growth is the hardware configuration that determines its efficiency and speed in running a program. In recent years, innovators have come up with new ideas to overcome this barrier. What if the performance of the software becomes independent of the user’s hardware? Is it possible to run a complicated multidisciplinary software on a user’s mobile application? These questions led to the creation of web service applications and cloud-based software in which a giant software would be installed on a powerful server, but its functionalities could be reached by any platform and device, via web requests.
Another trend in the development of computer-aided engineering software is to combine similar or related services. As a case in point, the BIM environment has been developed by combining 3D modeling capability with information management services that handle material properties such as weight, color, dimensions, cost, environmental footprint, etc. Revit as a powerful BIM software, for example, can analyze and design structures or can conduct a life-cycle energy analysis by using add-ins, such as Tally. BOCAD as another example has been recognized as a shop drawing software for a long period of time, but has been recently combined with AVEVA to create a comprehensive structural module in its collection of integrated multidisciplinary engineering and design solutions. This trend has been helping developers to create one-stop-shop solutions that fulfills users’ various needs with different levels of complexity. This integration has overcome interoperability problems when exchanging data between various platforms, eliminated many blind spots, and improved productivity and constructability of sophisticated projects.
(Fig2. BIM model built-in Digital Project in collaboration with Gehry Technologies)
While this integration trend is occurring across various disciplines in the construction industry, it has also been realized that it is impossible to come up with software solutions that can cover all engineering problems. Therefore, on an individual level, large-scale companies are trying to develop customized tools that match their specific needs. It involves creating macros or developing new software to improve their productivity, reduce their errors, unite their engineering procedures, decrease their used man-hour, ensure the constructability of their product, reduce Technical Queries (TQ) from constructors, lower the material consumed and the waste produced, and deliver a stable and integrated service for clients. As a result, these companies have improved their success rate in commercial bids, due to lower man-hour and higher productivity. Such tools and software are always custom-made and apply only to the specific needs of their corresponding organizations.
In sustainable construction practice, automation is paving the way for more interoperable computation in the design, construction, and operation of green projects. There is a variety of engineering applications developed to help implement sustainable solutions in green buildings. Countless customized software applications are designed to gather information and buildup material databases to conduct energy analysis and life-cycle assessment for green building projects. The next generation of green building automation solutions would provide cloud services and wireless command systems which can learn and update whole systems based on the latest standards and material inventories, as well as the data collected from previous experiences during various phases of the life-cycle of a project. Future sustainable buildings will be highly intelligent and would be assessed in real-time during design, construction, and operation.
Andia, A., & Spiegelhalter, T. (2014). Post-parametric automation in design and construction. Artech House.
Manrique, J. D., Al-Hussein, M., Bouferguene, A., & Nasseri, R. (2015). Automated generation of shop drawings in residential construction. Automation in Construction, 55, 15-24.