{"id":3468,"date":"2023-05-10T09:13:51","date_gmt":"2023-05-10T08:13:51","guid":{"rendered":"https:\/\/naska.ai\/?p=3468"},"modified":"2023-05-10T09:16:17","modified_gmt":"2023-05-10T08:16:17","slug":"unravelling-the-complexities-of-construction-embracing-ai-and-automation-for-improved-quality-and-profitability","status":"publish","type":"post","link":"https:\/\/naska.ai\/unravelling-the-complexities-of-construction-embracing-ai-and-automation-for-improved-quality-and-profitability\/","title":{"rendered":"Unravelling the Complexities of Construction: Embracing AI and Automation for Improved Quality and Profitability"},"content":{"rendered":"\n

In an age where technology continues to disrupt and reshape various industries, the construction sector benefits immensely from embracing innovation. With the intricate interplay of numerous elements, such as materials, people, logistics, and budgets, project managers face mounting challenges in ensuring quality control and progress tracking. But what if AI and automation could revolutionize construction processes, leading to better outcomes and increased profitability?<\/p>\n\n\n\n

In this article, we’ll dive into the complexities of the construction industry and explore how artificial intelligence (AI) and machine learning can transform how we approach project management, resource allocation, and quality assurance. Join us as we uncover the potential of AI-driven solutions to redefine the construction landscape and lay the groundwork for a smarter, more efficient, and sustainable future.<\/p>\n\n\n\n

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A decentralized and constantly evolving construction project<\/figcaption><\/figure>\n<\/figure>\n\n\n\n

The Complex World of Construction<\/strong><\/p>\n\n\n\n

Construction projects involve assembling hundreds of thousands of elements, including materials, people, logistics, plans, and budgets. These components interact in time and space, operating at different levels of granularity and frequencies, making it challenging to manually track the quality and progress of the built structure on a construction site.<\/p>\n\n\n\n

Manually tracking and verifying elements on a construction site is a near-impossible task, leaving projects vulnerable to errors that can have catastrophic downstream effects. For example, steel defects delayed the GMHBA Stadium redevelopment<\/a>, while missed deadlines by contractors led to the postponement of Spurs’ new football stadium<\/a>. Implementing a robust quality control system is crucial for avoiding such consequences.<\/p>\n\n\n\n

Furthermore, the Building Information Model (BIM) is a living document on construction sites, with multiple decentralized teams referencing and updating it throughout the project lifecycle. This constant interaction further intensifies the complexity of the construction process.<\/p>\n\n\n\n

Smart Automation and Reality Capture<\/strong><\/p>\n\n\n\n

Smart automation enables project managers to simplify the problem of validating work by comparing the as-designed BIM to the as-built structure through reality capture techniques, such as laser scanning.<\/p>\n\n\n\n

Since construction sites are open systems, reality capture is susceptible to different kinds of un-modeled real-world noise like ambient weather conditions, lighting changes, and clutter. The complexity inherent in the system poses a significant challenge to implementing BIM-based process control on construction sites.<\/p>\n\n\n\n

Despite these challenges, effective BIM-based construction process control is essential to ensure quality and avoid catastrophic downstream consequences like rework and delays that result in schedule and budget overruns.<\/p>\n\n\n\n

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BIM-based construction process control<\/figcaption><\/figure>\n<\/figure>\n\n\n\n

Tackling the Automation Problem with AI and Machine Learning<\/strong><\/p>\n\n\n\n

To address the automation challenge in construction, which involves identifying and verifying numerous elements amidst noisy and incomplete data, the industry can leverage the power of machine learning and artificial intelligence-based technologies to make this problem tractable. These advanced tools can simplify the seemingly impossible problem of finding “needles in a dirty haystack” or “needles in a scrap metal yard.”<\/p>\n\n\n\n

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