Machine Learning: 3 Things Construction & Manufacturing Have in Common

16 May 2023Architecture and Engineering, Computational Design, Construction, Data, Digital Transformation, innovation, ManufacturingFactory Design, Generative Design, Maintenance, quality, reality capture, risk mitigation, Safety

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Machine learning (ML) can help improve the jobs of people in a variety of industries, including construction and manufacturing.

A ProBuilder February 2022 blog article highlighted the ways ML can be used to help in the construction workplace.

graphic of purple and blue robotic hand touching an icon on a clear computer screen
Machine learning image: Shutterstock

Similarly, a Construction Dive article in March 2023 pointed out that technology can improve productivity in both construction and manufacturing.

ML requires that information about projects be collected and translated into usable data. A machine’s ability to provide insights improves as it is fed more information.


Find out more about machine learning in the free GRAITEC guide: “Ultimate Guide to Computational Design.” Download it today.


When it comes to the uses for ML, following are 3 things construction and manufacturing have in common:

1.     Improved Design – ML has the potential to improve the overall design of a building or a manufacturing facility. In construction, office buildings and custom spaces can be analyzed for frequency of use. This enables builders to anticipate needs and design accordingly in planning future buildings. In addition, the problem solving and pattern recognition of ML helps with generating design alternatives. In designing factory layouts, ML can help with better space utilization and lower utility costs. For both industries, ML can also assist with quality control, identifying potential design problems before proceeding with construction or manufacture.

2.     Predictive Analytics – ML can predict when maintenance is needed. Using predictive analytics, ML can track machinery usage and quantify how much time is left in the life of a piece of equipment. It can identify chokepoints and enable preventive actions before something jams or breaks and shuts down production. This can happen on a construction jobsite or on the manufacturing floor. Manufacturing does have the upper hand in this, since a sensor on one machine can monitor the production of many products. In construction, on the other hand, even on a small jobsite many more sensors and a larger investment would be needed to accomplish the same insights and data gathering. Fortunately, reality capture using video and still cameras can compensate and help the construction industry level up in its use of ML.

3.     Risk Mitigation – As reported by Engineering News-Record in 2017, image recognition software and machine learning can be combined to detect and flag safety hazards. That could be accomplished on a construction site or in a factory. ML enables companies to identify safe zones for workers. It can also help companies assess risk in terms of quality, materials expense and schedule so they can implement plans to mitigate that risk. A Trimble Constructible article in 2022 described robots that could autonomously capture 3D scans of construction sites and determine if sub-projects were falling behind and threatened to derail the schedule. The process will increasingly use machine learning in the future. Assessments that might take a person hours manually can be processed by a computer in just a few minutes.

As markets continue to put pressure on the construction and manufacturing industries to meet increased demand, it seems companies in both industries have a better chance of meeting those demands when ML is in the mix.


 

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