In modular construction—a type of industrialized construction—production planning is very important, as it is closely related to the project’s duration, quality, and sustainability. The constraints (production area, delivery due date) often differ for each project, yet production planning in modular construction has failed to change with the project characteristics. As a result, bottlenecks and construction delays are common problems seen in modular construction, which, in turn, decreases the production ratio, causing the production to be inefficient. To this end, this paper applied a prefabricated component in the modular production process. The paper developed a process analysis model considering constraint factors (production period, production area) to derive the optimal configuration of the prefabricated components in various alternatives. The developed analysis model was then applied to a virtual case to analyze the productivity improvement and select the optimal process. The optimal production process was derived by simulating the possible production planning within a limited production area and production timeline. The result of a simulation indicates that the production period has been halved by optimizing the process. Furthermore, by applying prefabricated components, the production efficiency was further increased because the existing linear production process’s bottleneck disappeared. The model is deemed to have the potential to optimize various production methods across production facilities or modular factories that simultaneously perform multiple projects.

Normal (typical) project duration is estimated at the initial stage of a renovation project and is an important reference for project control. However, its estimation has not been researched extensively owing to the complexity and uncertainties of renovation. Thus, a model was developed for predicting the duration of sustainable apartment renovation. Experts were asked to estimate a baseline schedule for extension-type renovation projects, factors that influence critical path activities, and the range of project durations considering these factors. An equation for estimating the duration of a renovation project was developed, and the range of project durations was derived using a MCS to reflect uncertainty. The proposed model was validated by applying it to actual cases. The case study shows that the model would be more suitable for complex renovation construction (i.e., more than two buildings or vertical extension). The model can be applied to various renovation projects and used as a reference for determining contract time. It can fill the knowledge gap of construction duration forecasting by adapting the concept of control activities to simplify the assessment of uncertainties in renovation of apartments, and can be applied for forecasting sustainable renovation time for other project types or in other locations.

Determining a reasonable construction time (RCT) is crucial in project planning and schedule management. Construction projects are exposed to the external environment, including rainfall, extreme temperatures, snowfall, and high wind speed, and the RCT should be evaluated considering these risks. The risks can be reflected by activity duration using nonworking days (NWDs). However, current construction planning and scheduling practices are ineffective for dealing with of NWD characteristics because working days (WDs) and NWDs are mixed in most schedule performance data used for schedule development. Activity durations estimated using historical performance data may not appropriately reflect the activity characteristics (work type, region, and work timing), leading to an unreasonable construction time for a project. Here, we propose an activity duration segmentation method (ADSM) for determining the RCT. The ADSM can evaluate the combined effects of weather factors according to work type and determine the operation rate, which depends on start date, work type, region, and activity duration. This leads to the separation of WDs and NWDs for determining the RCT. Case-based and comparative analyses were conducted to validate the proposed method. The mean absolute percentage error (MAPE), used to validate the ADSM, was 5.79%. The results of the present study show that NWDs can be determined by considering the characteristics of the various activities (e.g., sensitivities toward environmental conditions, start date) and the environmental conditions of the project (weather conditions at the project location, working hour patterns). The ADSM suggests an integrated framework for combining activity characteristics and project environmental conditions when determining NWDs of each activity. The ADSM can be used by project owners for determining the RCT or the contract time, which varies according to activity characteristics. Also, a construction scheduler can assess to what extent the construction schedule will be influenced by NWDs.