ABSTRACT
Modular construction has been implemented to achieve shorter project duration, lower cost, and higher productivity for construction projects. This option is especially helpful to reduce on-site activities and interaction under and after COVID impact. However, additional planning and support in engineering, procurement, and delivery are required to facilitate modular construction. Unreliable prefabrication and delivery can deteriorate subsequent activity productivity and overall project performance. This research aims to develop an automatic incentive—penalty enforcement system for modular construction based on the situation awareness of delivery tracking. The research selected a high-rise residential project in Singapore as a case study. The project used modular construction for making and installing 120 Prefabricated Bathroom Units. Based on the empirical data of delivery, on-site lifting, and installation, we built STROBOSCOPE simulation models to understand the impact on productivity and schedule from five scenarios at various delivery reliability levels of the Prefabricated Bathroom Units. Smart Contract rules were developed based on the impact. A Blockchain platform was established so that once a real-time delivery is identified and the information is entered into the Smart Contract, the associated incentive or penalty can be triggered instantly. The Smart Contract based incentive—penalty enforcement system will be beneficial for construction projects to monitor and track modular delivery, motivate reliable supply, reduce payment disputes, and improve productivity. © 2023, Canadian Society for Civil Engineering.
ABSTRACT
The project "Language guidance tool for improving language knowledge"(LanGuide) is supported by the Erasmus+ program Strategic Partnerships for Higher Education. The project duration is 36 months. The coordinating institution is the University of Primorska, and the partner institutions are Mälardalen University, the University of Castilla - La Mancha, Transilvania University of Braov, and two Croatian universities - the University of Zadar, and the University of Rijeka. The main aim of the project is to build an open access students/teachers/administrative staff centered mobile app for improving language knowledge. To achieve the goal, the first phase of the project is concerned with the development of a universal methodology for the preparation of language exercises focused on language for specific purposes. In the second phase, the methodology is applied in the preparation of language resources for six languages in four LSP fields at different levels of difficulty. Appropriate IT tools are developed simultaneously with the preparation of exercises. Finally, the developed tools and resources are evaluated through two rounds of user testing. This paper first describes the motivation behind the project proposal. Next, each of the four intellectual outputs and activities carried out within the project are described. Finally, challenges such as the one brought about by the pandemic of COVID-19 are highlighted. © 2022 Croatian Society MIPRO.
ABSTRACT
Despite the impact of the COVID-19 pandemic in 2020-21, the digital economy remains solid and sustainable. This trend continues to drive massive demand for Information Technology (IT) projects. Underestimated costs and time are considered one of the most critical IT project risks that directly impact a project's success or failure. Currently, there is a lack of models, tools, and techniques capable of effectively predicting cost and duration. This study aims to find a solution to enhance prediction capability by using a machine learning (ML) model. An experiment was conducted comparing the performance of each ML model utilizing three distinct datasets and fourteen different models against six performance indicators. The results indicated the existence of a highly reliable, effective, consistent, and accurate ML model with a significant degree of augmentation compared to conventional predictive project management tools and techniques. © 2022 IEEE.
ABSTRACT
Modular construction has been implemented to achieve shorter project duration, lower cost, and higher productivity for construction projects. This option is especially helpful to reduce on-site activities and interaction under and after COVID impact. However, additional planning and support in engineering, procurement, and delivery are required to facilitate modular construction. Unreliable prefabrication and delivery can deteriorate subsequent activity productivity and overall project performance. This research aims to develop an automatic incentive—penalty enforcement system for modular construction based on the situation awareness of delivery tracking. The research selected a high-rise residential project in Singapore as a case study. The project used modular construction for making and installing 120 Prefabricated Bathroom Units. Based on the empirical data of delivery, on-site lifting, and installation, we built STROBOSCOPE simulation models to understand the impact on productivity and schedule from five scenarios at various delivery reliability levels of the Prefabricated Bathroom Units. Smart Contract rules were developed based on the impact. A Blockchain platform was established so that once a real-time delivery is identified and the information is entered into the Smart Contract, the associated incentive or penalty can be triggered instantly. The Smart Contract based incentive—penalty enforcement system will be beneficial for construction projects to monitor and track modular delivery, motivate reliable supply, reduce payment disputes, and improve productivity. © 2023, Canadian Society for Civil Engineering.