Design, bidding, and financing; procurement and construction; operations and asset management; and business model transformation are some of the areas where AI in construction has the potential to assist participants to realize value. Construction AI aids the sector in overcoming some of its most difficult difficulties, such as worker safety, labor shortages, and cost and schedule overruns.
Artificial intelligence (AI) in construction is becoming more ubiquitous in all aspects of the industry, from planning to construction.
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AI is being used by construction professionals to improve project efficiency and accuracy, monitor and track equipment usage and location, and a variety of other AI-driven applications.
According to Research and Markets, construction-related activities generate over $10 trillion in revenue each year, with that amount predicted to rise by 4.2 percent through 2023. AI is assisting in the expansion of the sector.
Use cases for AI in construction
The conceptualization, design and planning phases of a building project's lifecycle are crucial. They must run smoothly in order to complete any project on schedule, with high quality, and within budget. Designers, engineers, and architects spend a lot of time working on the building's design.
The process of producing design variations and checking the architectural statics and other parameters of the building takes a long period (e.g. compliance with building regulations, does the building fulfills all functional requirements, and so on).
There are several examples of projects collapsing owing to incorrect planning, particularly in huge construction projects such as infrastructure structures.
This is where generative design, a design exploration method based on artificial intelligence, comes into play. With access to a database of many previously built building plans, an AI-based system can produce design alternatives based on the information it acquires from the designs in the database.
Designers and engineers may easily enter design goals, as well as parameters like spatial requirements, performance, materials, cost limits, and more, into generative design tools.
The software then investigates all conceivable permutations of a solution, providing design alternatives that match all previously established requirements, thanks to artificial intelligence. The program then learns what is a better design option with each iteration, making it a stronger tool with each new project.
This is a significant advance over traditional scripting because it enables a far larger number of parameters and permutations to be explored. All the designer or engineer has to do is pick the most appealing design from the available options.
Because generative design allows people to instantly produce the most efficient designs depending on any parameters provided, it provides for faster, higher-quality, and less-expensive design and planning.
In addition to these benefits, generative design has the potential to boost creativity. For starters, it enables architects to discover previously unimaginable ways of designing forms and curves. Second, generative design can lead to design solutions that designers and engineers would not have considered otherwise.
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For decades, the construction industry's overall productivity output has been improving only slightly or not at all. One of the most prominent factors is the inefficiency of the building site's logistics.
First, shipments, rearrangements, downtimes, and the hunt for materials account for around one-third of the time spent on building sites. Second, construction projects frequently face difficulties as a result of construction delays. A major section of megaprojects are significantly delayed, over budget, or have other planning flaws.
For the enterprises participating in the construction process, all of these variables result in excessive costs.
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AI-based construction solutions can assist in a variety of ways during the construction process. Construction execution planning, update of construction sequences, and job management can all benefit from AI, as long as all stakeholders are kept up to date. Furthermore, AI has the potential to boost construction execution productivity.
Management of supply and facilities
Facility managers must continuously discover solutions to a variety of concerns, such as whether to replace or repair, whether to challenge an invoice or not, whether to act immediately or wait, and whether to buy replacement components right away or not. Facility managers must devote a significant amount of time to these decisions, which are based on massive volumes of data gathered during the project's lifecycle. This is both costly and error-prone.
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The massive volume of data collected over time makes it ideal for AI applications. This is already being used by some businesses. Data analytics can be done using AI-assisted tools to assist facility managers in taking preventive action.
For example, AI can detect parts of a building that are now unoccupied and turn off the heating, ventilation, and air conditioning in those areas, resulting in significant energy savings. Cleaning and unneeded upkeep for areas of the facility that aren't in use can also be eliminated.
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Construction Material Manufacturing and Distribution
AI can assist organizations in forecasting pricing for raw materials (sand, gravel, iron, etc.) and other input elements in procurement. To do so, AI will examine historical data as well as the evolution of other factors that influence the price of raw material, or even identify such linkages on its own.
After that, AI can forecast the price and pick the best time to buy. This may be linked to inventory data, allowing AI to factor in the stock of certain raw materials in its calculations and perform more efficient inventory management.
AI will make it possible to automate an increasing number of additional processes in the purchase-to-pay process. As previously said, AI can determine the requirement for a product and then place an order for it. Based on past data, it finds the best provider automatically (quality, punctuality, price, etc.). When AI receives an invoice, it verifies that it is correct before settling or declining it.
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The construction materials sector has almost realized all of its potential for improving the manufacturing process. With the current circumstances, there aren't many options for considerable efficiency improvements. AI could be the catalyst for the next big leap forward in terms of quality and efficiency.
Companies have the possibility to collect massive amounts of data generated during the manufacturing of construction materials (e.g. temperature, pressure, quality). Data from lasers, ultrasound examinations, cameras, thermometers, and other equipment may be included. Artificial intelligence may be used to assess data and derive actions from it, which can increase both the quality and efficiency of production.
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Reduce labor shortages in the construction industry
Construction firms may raise their production by up to 50% using AI-enhanced analytics, according to McKinsey & Company. This is fantastic news for construction companies that are having trouble finding enough human employees to complete their projects, and those companies are the rule rather than the exception.
Not only is it tough to locate laborers — CNN claims that the industry is short of more than one million workers in the United States — but it's also difficult to keep workers. The average monthly turnover rate in the construction industry is above 5%, according to the Bureau of Labor Statistics, compared to less than 4% across all industries.
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Project managers can use AI-powered robots like Boston Dynamics' Spot the Dog to identify real-time circumstances at many job sites, such as whether they should relocate personnel to different areas of the project or to new project sites entirely. The robot "dogs" keep an eye on construction sites throughout the day and at night to spot potential problems.
AI in the post-construction phase
Long after the work is finished, building managers can use AI. Advanced analytics and AI algorithms generate useful insights into the operation and performance of a building, bridge, roads, and nearly anything in the built environment by gathering information about a structure using sensors, drones, and other wireless technologies.
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This implies AI may be used to track the progression of issues, identify when preventative maintenance is required, and even direct human behavior for maximum security and safety.
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While an attempt has been made to provide high-level insight into the subject of artificial intelligence working as a deterrent for engineering and construction conflict causes, general adoption is improbable, and the focus will be on tiny pockets. To ensure minimal disruption, AI adoption will entail evaluating existing procedures and modifying them at a reasonable pace.
More importantly, AI is not what popular culture portrays it to be, and it is a fallacy to believe that AI will eventually replace humans and change construction processes. Given the intricacies of this sector, maximizing efficiency requires human intervention.
The most difficult challenge is to ensure that AI delivery is on par with human intelligence, which can only be accomplished by involving a wide range of industry professionals at various levels in the creation, maintenance, and error correction of applicable algorithms, as well as keeping them practically relevant.
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From the perspective of avoiding building disputes, AI has a lot of promise, and it's not hard to foresee a future when the quality of disputes improves. On the negative side, AI-related issues may result in uncertainty.