ARTIFICIAL INTELLIGENCE: HOW WILL IT AFFECT CONSTRUCTION INDUSTRY

Below will explain how AI affects the construction industry.

Before site

Problem (design)

Do you know how many days exactly the designers and architects need to devote to design a building?

Time is more consuming and numerous workers and money are demanded, especially when checking the architectural statics and whether the building meets the building regulations and requirements.

There are many projects that have been delayed because of the inaccurate planning and clashes with utilities like construction of urban infrastructure.

How AI improve

• Help designers and architects to access database of past building plans

• Carry out the detection of clashes and allow changing of plans

• More efficient to choose the most desirable design

• Allow more parameters to be considered

• Higher quality and more precise design

• Software can learn and further improve from iteration

• Reduce the cost

• Reduce demand of workers

On construction site

Problem (progress)

One third of the time of delay was spent on transportation and searching for materials, also over 90% of projects are delayed. This delay and over budget of projects often happen in construction which will lead to low productivity.

How AI improve

• Detect possible clashes and errors of the construction progress automatically by comparing the digital twin of the building in the Building Information Modeling (BIM) cloud and the actual physical representation

• Robots and drones can be used for frequent image recording and 360 degree laser scans in construction sites to track instant progress of the physical building against the plan stored in the BIM cloud

• Perform automatic changes in the construction schedule in the BIM cloud due to possible delays

• Helps construction workers find tools faster with the use of the image recognition software

• Track instant progress in construction site

• Adjust the timeline effectively and allow different stage of workers react immediately

• Inform all stakeholders instantly and automatically, like manufacturers

• Perform troubleshooting at an early stage

• Reduce cost of correction in later stage (e.g. materials place in wrong place)

Problem (safety)

Fatal accidents caused by human errors will lead to high compensation cost and delay of projects. Total cost including direct medical cost and indirect cost like replacement of workers will be around 15K to 344K.

The above pie chart shows the different types of construction accidents. From Occupational Safety and Health Administration, 5,333 construction workers died in 2019, which indicates a serious safety issue in construction sites.

How AI improve

• Mitigate risks and reduce the number of accidents greatly with 70% more efficient

• Alarm staff when it detects improper gears and other possible safety hazards.

• Improves both the utilization of tools and productivity,

• Use the time of the construction workers and machinery more efficiently

• Increase 40% labour productivity

• Reduce 10% cost from budget

• Improve safety by 24/7 AI function

• Reduce 80% of compensation cost

AI has been trained to identify indicators of risk in photos, video and other project data, and even predicting accidents before they happened. For instance, danger zone alert and safety measures detection can be performed by AI to reduce accidents.

Problem (resource)

In construction sites, workers often perform tasks simultaneously while working a machine. This will cause a high rate of errors, lower efficiency and waste of resources.

A lot of time and effort will be taken for facility managers to make decisions, like replace or repair the tools and supply chain decisions, which is costly and easily leads to mistakes. Also, the resources are not allocated and used effectively as it is hard for operators to monitor.

How AI help

• Assist operators of heavy and mobile machinery at the construction site. Also, cameras can continuously observe the construction site and check potential clashes with people or objects, thus giving out warning before accidents happen.

• Helps collect a huge amount of data effectively and recommend possible action before potential problems happen.

• Simplify the use of heavy machinery, assist routine and repetitive tasks

• Order replacement parts automatically and predict the maintenance period in order to provide available resource on time and improve production capacity

• Reduces the total cost of ownership (including hardware and software acquisition and opportunity cost of training and other productivity losses)

• Enables operators to work faster and more precisely for more complicated and value adding tasks

• Increase productivity of mobile machinery by 60%

Problem(supply chain)

How AI improve

1. In procurement

1. Help companies forecast prices for raw materials and time of buying

2. Analyze data on past price development

3. Connected to data on inventory

4. Automate purchase-to pay process by choosing the most suitable sellers based on previous record

5. Help invoice checking

2. In marketing and sales

1. Helps company plan advertising budget

2. Provides personalized recommendations on price, quantity of offer

3. Help identify potential customers

3.In logistic

1. Helps further optimize transportation routes after every delivery

2. Increase efficiency by identifying best transportation routes based on time and cost etc

4. In customer service and after sales

1. Reduce the workload of staff by answering customer inquiries automatically

2. Reduce the cost

3. Increase productivity as workers can target on more complicated works