As industrial assets are becoming increasingly complex, connected and smart, they are radically transforming a number of industries including construction. Within the construction industry, the impact of this transformation will be the most profound in equipment operations and worker safety. This will require construction executives to rethink and reimagine how they manage, operate and maintain physical assets. There are two major reasons for this disruption.
Today's construction equipment, from bulldozers to forklifts, remotely collect data from onboard computers (e.g., hours, usage patterns) and sensors (e.g., temperature, vibration) and are critical to understanding operation status and prediction failure. As an example, the same bulldozer will function and fail differently in a desert compared to a highly humid tropical environment.
Operators of this modernized equipment are using data to execute both conditioned based maintenance (CBM) and predictive maintenance. This new operating model puts the onus on manufacturers to provide more information about bill materials, which parts will fail first and under what conditions, and which parts are most critical to equipment function. This is all needed to accomplish both CBM and predictive maintenance. Additional detail, combined with equipment usage data, is essential to creating new predictive models for how equipment should be monitored, maintained and repaired. As a result, this will reduce equipment downtime, avoid over-maintenance and improve overall costs.
According to the Occupational Safety and Health Administration, 1 in 10 construction workers are injured every year with a significant number being attributed to equipment contact. What was once perceived as risk inherent to workers in the construction industry can now be mitigated, or completely eliminated, by the availability of sensors, cameras and AI modeling. For example, sensors today are being employed to assess workers’ biological data (e.g., assessing fatigue).
Additionally, equipment is being integrated with sensors that assess the cognitive ability of machine operators before they can use equipment. By employing cameras in vehicles, combined with the power of AI-based algorithms, heavy equipment will be able to determine if an operator is potentially impaired before allowing the equipment to operate, or even assess if the operator is distracted in any way (e.g., looking at a cell phone instead of the controls). Some companies may consider the use of VO2 or passive alcohol sensors to determine if an operator might be under the influence, or simple cognitive tests to determine if an operator is too fatigued to safely operate a piece of machinery. These developments not only ensure a safer work environment for employees, but also stand to protect employers from risk.
These scenarios are underpinned by three increasingly critical technologies:
While these disruptive technologies will undoubtedly pose new challenges, despite upending traditional operational models and transforming the relationship between man and machine, they’re ultimately for the better. By embracing key technological underpinnings, construction executives will be able to reduce many of the significant risks and costs, which ultimately ensures a smarter and safer construction industry.
Written by {{author.AuthorName}} - {{author.AuthorPosition}}, {{author.Company}} {{author.Company}} Contact Info: {{author.OfficePhone}} , {{author.EmailAddress}}
{{comment.Text}}