| Abstract |
The present research examines a wide range of civil engineering projects across India, each providing a distinct platform for investigating quality management, automation techniques, and improvement activities using artificial intelligence (AI) techniques. The study covers projects demonstrating the variety of India’s civil engineering undertakings, from the Smart City Mission to the Mumbai Metro Line 3 and the Chennai-Madurai Expressway. The adoption of quality management techniques, including ISO 9001 Certification, Lean Construction, Six Sigma, Building Information Modeling (BIM), and Total Quality Management (TQM), is evaluated in the projects. In this case study, experimental datasets and employed AI techniques such as Artificial Neural Networks (ANN) are used to predict accurate outcomes. It was also observed that more variation in the regression coefficient (R2) and errors (MSE) from 1 to 5 hidden layer nodes. While hidden layer nodes 6 to 10 performed stable outcomes. Out of them, hidden layer node 9 performed best of the best regression coefficient (R2 = 99.4%) with minimum error (MSE = 0.04). The comple investigation of the outcomes indicating towards the suitability of the existing model as an important one for accurately predicting the UCS. A thorough framework for improving quality management in Indian civil engineering projects is the research’s final product, and it offers insightful information to industry stakeholders. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. |
