Construction Barge Performance Management - Artificial Intelligence Based Software

Abstract In the case of Offshore Construction through barges and construction works in general, whatever is the contracting strategy, one thing is common to all, which is human performance, this drives efficiency and makes the basis of all the development of Cost. There is a significant potential to enhance human efficiency. The project "CONSTRUCTION BARGE PERFORMANCE MANAGEMENT - ARTIFICIAL INTELLIGENCE BASED SOFTWARE" is development and implementation of AI/ML based software that analyzes components of human efficiency to identify training needs and establish targets for low performers to elevate their efficiency, thereby improving overall workforce efficiency and output. Huge data related to work requirements and workforce attributes is utilized by the software to suggest rational deployment of every worker at the most appropriate work location. In complex offshore construction, the gap between average and high productivity among workers is often due to lack of an effective work front. The software is designed to streamline work fronts, optimizing sequencing to shorten critical paths, attain effective work front and then balance the workforce with effective work front so derived. It analyzes non-productive time (NPT), suggests improvements and automates and eventually makes management autonomous. This approach aims to elevate productivity, pushing human efficiency and output to new heights. One of the major tools of this software is the point-based system to evaluate performance and skills. It generates points based on the skills and performance of the workforce to determine compensation. This system develops multi-skilled workers. The system identifies training needs and suggests appropriate courses. It also helps in identifying candidates for promotion by evaluating their performance and multiple skills, suggesting additional training or qualifications required for the next step in their career. Once the system is operated for one to two years it will have enough data to ensure fair compensation, identify training needs, fair promotions, improved behavioral based safety and effective counseling of workforce. Another important module of the software is deft handling of behavioral based safety data which aims to improve BBS and workers’ wellbeing. IoT cameras/sensors integrated with the system will be used in reducing HSE incidents and tracking and improving workers’ well-being.