The fourth industrial revolution is the current and developing environment in which disruptive technologies and trends such as the Internet of Things, robotics, virtual reality and artificial intelligence are changing the way we live and work. It is not only about smart and connected machines and systems but also the innovations that result from interdependencies among different technologies at an incredible speed. That’s my takeaway from Klaus Schwab’s The Fourth Industrial Revolution. So, how can these technologies be applied to drive improved quality performance in the construction industry?
Quality planning:Virtual reality (VR) technology provides construction project owners a virtual space that reflect the architect’s design and gives them a chance to ‘see’ the space before the construction work begins. This is a great opportunity for the owners to confirm that the designed space meets what’s in their minds early in the design phase so that all other supporting teams can better plan their work. The team, which including architect, general contractor, trade partners, and suppliers would have stronger alignment on what the owners’ expectations are and can better work together to bring the owners vision to life. This clarity has the most impact in the aesthetic aspect of quality requirements rather than how everything comes together in the space or the function of the space. VR sessions can also be easy opportunities to gather feedback throughout the life of the project so appropriate changes can be identified and made with minimal disruption for all parties involved. Drones can be used to survey the land and capture necessary data to help the team plan the work in much less time than traditional methods. This data capture eliminates much of the human error that can occur in the surveying process. Building Information Model (BIM) is the virtual prototype used by the team to plan the work and have immersive reviews of design constructability. When BIM is used in virtual design in construction, that helps to better inform decision makers on different means and methods that can lead to higher predictability of time, cost and quality of the project, product, and/or customer value.
It is not only about smart and connected machines and systems but also the innovations that result from interdependencies among different technologies at an incredible speed
Computational Design (CD) technologies can help teams model building performance in changing environments like airflow, temperature distribution, chemical substance concentration distributions, etc. Computational design tools allow teams to make informed decisions much earlier in the design process and can help select materials that would mitigate one of quality biggest challenge area - moisture intrusion.
Quality inspection to confirm that everything is as it should be per the requirements.
Drones can also be used throughout the building process to collect data and do quality control checks against the building information model and/or specification requirements. This set of data along with photos and videos on a drone with mounted camera can be used to capture ‘record’ of the quality workmanship. Robots can be deployed 24X7 as inspectors. An example would be the Quality Inspection & Assessment Robot (QuicaBot) that AS online video shows, it uses laser and scanner to perform inspection against a model. The scanner maps and navigates building and inspect walls. The camera can spot poorly installed tile by using infrared imaging and can detect cracks in the wall. This inspection data is gathered and uploaded into the cloud system so we can retrieve records when we need them.
As noted earlier, it is the interdependencies among different technologies that would bring greater value to an organization than each individual technology alone. This is the case for Quality Management System, which is intended to drive continual improvement. For instance, all the information models and data captured by different technologies like drones and robots, can feed through analytics tools and be used in a couple ways to drive improved quality performance. First, the organization’s lessons learned can be pushed out to the project team near real-time to share recent knowledge and experience and to trigger appropriate actions within each individual project. Then, these analytics tool can also provide reports that show pattern of known and emerging quality risks so that focused teams can be deployed to investigate and define actions to drive improved performance across the company.
Another example of interdependencies is leveraging VR capability to help us grow ‘builders.’ We can bring team members together to a shared virtual space, modeled with a 360 ̊ camera to walk with a subject matter expert through a construction space to learn how to identify quality deficiencies in various work scope and practice in this virtual world without the expense of travel or needing to build a physical mock up for learning.
With the large volume of data that we are collecting which includes open issues, requests for information, change orders, design review action items, observed quality deficiencies through either inspection and/or feedback from team members and warranty work orders, machine learning can wade through all this data across the company, identify the most critical risk factors from a quality perspective needing immediate attention and send alert the appropriate team members to help them focus on what needs their attention that day without human intervention. To ensure that the machine has a strong foundation to learn, it’s critical that the quality of the data feeding the machine is good to start out and remain good as it goes forward.