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This paper aims to explore the potential capabilities of the application of computing features (CFs) in resolving the most common issues that adversely affect performance in architecture, engineering and construction (AEC) projects.

Through a comprehensive review of the literature, 10 most significant CFs were identified. Also, the 15 most prevalent issues in AEC projects (AECIs), for which computers can provide remedial solutions, were determined and categorized into three phases of design, construction and operation. Potential impacts of each CF on handling AECIs in each of the three stages were assessed based on experts’ perceptions.

CFs are ranked based on their potential on solving the identified AECIs. So too, the order of the most common AECIs is provided in terms of their disposition for being solved by CFs. In this regard, findings reveal that the most effective CF in addressing AECIs is “artificial intelligence” and the most solvable AECI by using CFs is “increased costs and poor budgeting.” Furthermore, the most appropriate CF to handle each AECI is specified, as a result of which, it is inferred CFs are more effective in handling operation-related issues, compared to design, construction phases.

The results can provide a profound insight into software/tool selection based on features that enable technological tools and programs to handle AECIs in the three major phases of projects. Moreover, technology providers and vendors are provided with a benchmark to supply products according to the demands of the AEC industry. The study provides a readily available point of reference for practitioners in selecting various CFs for handling common AECIs that affect their projects.

A large body of research is available on the evaluation of various computer-based technologies and tools. Nevertheless, little, if any, study exists that explores the potential of underlying CFs of these technologies in addressing endemic problems across various stages of AEC projects. This study is one of the first in its kind that shifts to exploring various CFs, as the main enablers of computer technologies, establish links between these CFs and common issues of projects and assesses the potential of various CFs in addressing common problems of construction projects.

Prompt and effective responses to incompatibilities between as-designed and as-built drawings prevent cost and time overruns and material waste. This paper aims to provide an efficient framework to handle mismatches between these two models with the least negative impact on the whole project.

First, 11 most frequent mismatches were identified through questionnaires. Also, the respondents were asked to determine the mismatches’ roots and solutions and the impact of applying solutions on the whole project. Afterward, the process to present the optimum solution to one of these mismatches was modeled. After running the application programming interface developed in Navisworks software, decision-makers access a form, showing mismatches, their causes and solutions, as well as the solutions’ effect. To finalize the optimal solution, a platform was provided on whether to accept the system solution or to propose an alternative.

To empirically validate the reliability of the proposed framework, two projects were investigated. Two different approaches to dealing with the same mismatch occurred in these projects were compared in terms of time, cost and material required. The results showed that addressing the mismatches through the proposed framework can efficiently enhance time, cost and material consumption, in comparison with the traditional approach.

There is currently no building information modeling-based holistic framework for managing mismatches between as-designed and as-built drawings. The results of this research can help contractors to make the best decision, saving project resources, when setting about a mismatch during construction.