Management of daily progress in a construction project of multiple apartment buildings
- Authors
- Yang, Yong Cheol; Park, Chan Jung; Kim, Ju Hyung; Kim, Jae Jun
- Issue Date
- Mar-2007
- Publisher
- ASCE
- Keywords
- Budgets; Buildings, residential; Construction management; Information systems; Korea; Scheduling
- Citation
- Journal of Construction Engineering and Management, v.133, no.3, pp.242 - 253
- Indexed
- SCOPUS
- Journal Title
- Journal of Construction Engineering and Management
- Volume
- 133
- Number
- 3
- Start Page
- 242
- End Page
- 253
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/180358
- DOI
- 10.1061/(ASCE)0733-9364(2007)133:3(242)
- ISSN
- 0733-9364
- Abstract
- This paper presents the methods used and a case study of a project management system (PMS) to manage daily progress in the construction of multiple apartment buildings in South Korea. A dilemma encountered in previous research in the field of progress management is that efforts to enhance data accuracy cause the data handling workload to soar. A main feature of the method presented by the writers for calculating the budgeted cost work schedule is to allocate the project budget into control attributes, activities, and tasks that are defined in a work-packaging model, according to daily weight value. The method offers enhanced practicability by reducing data-handling workloads while not sacrificing the rationale of progress management. The work-packaging model is designed to enable project managers to acquire and process data for progress management at various levels of detail. The budgeted cost of work performed is measured daily at the tasks level using the earning percentage rate from daily work reports. The implementation of PMS focuses on functions to distribute the budget according to daily weight values and acquire the earning percentage from the daily work report. The PMS was applied to a construction project of 54 apartment buildings in South Korea. The case study of its use shows that company headquarters and managers in the field can acquire data for progress management without additional data-handling workloads, and can analyze the progress daily at various levels of detail.
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