A Big Data and FMEA-based construction quality risk evaluation model considering project schedule for Shanghai apartment projects

Abstract

Purpose The purpose of this paper is to mine information on the construction process of previous projects to develop a construction plan that meets both quality requirements and schedule constraints. Design/methodology/approach This paper uses a failure mode and effect analysis to evaluate the construction quality of 311 apartments in Shanghai. The authors also evaluate construction-scheduling control using the earned value management technique and implement an artificial neural network to correlate the results. The authors then develop a quality risk and schedule correlation model based on Big Data. The model can predict the relationship between the planned schedule and the project quality risk using multiple variables such as the number of layers, the schedule performance index and budget costs. Findings The methodology offers an innovative approach for assessment on the relationship between quality risk and project schedule. The authors have also built a multiple regression analysis model for comparative purposes with the model. The results show that the proposed model can better describe the relationship. The model can provide a quantitative quality risk value that changes with the planned schedule, as well as help project managers to understand the relationship between quality risk and project scheduling more accurately. Research limitations/implications The research approach only focuses on quality risk under the impact of scheduling. Future efforts might focus on developing a model that connects failure models with project schedules and costs in order to improve the effort of quality management. Practical implications The model based on Big Data in this paper is developed using real projects and reflects the relationship between project quality risk and scheduling in real environments. The created application provides support for project managers to develop and adjust quality plans and schedules, thereby reducing deviations in quality and scheduling objectives. Originality/value The authors make full use of historical project data from the perspective of both quality and schedule management, and provide a novel method to intelligently and objectively analyze the relationship between quality risk and scheduling.

Applying a new systematic fuzzy FMEA technique for risk management in light steel frame systems

“…Considering some modifications in the FMEA formulation, Seifi Azad Mard et al (2017) introduced a novel approach for risk evaluation of occupational outcomes. There are several other researches about implementation of FMEA in the construction industry that can be found in Chin et al (2009), Gargama and Chaturvedi (2011), Liu et al (2019), Ma and Wu (2019).…”

Development of Cost and Schedule Data Integration Algorithm Based on Big Data Technology

“…While data-driven analytics has been widely introduced in the building sector, the adoption of big data technology has been low [2]. Ma and Wu [18] used big data to develop a construction schedule evaluation model in terms of project risk. The proposed model is based on EVMS [12] and addressed cost and schedule data only for three types of activities at a single level.…”

A hybrid risk prioritization approach in construction projects using failure mode and effective analysis

“…AHP and fuzzy logic are used to find the relative weights of RPN components. (Ma and Wu, 2019) presented a big data and FMEA-based construction quality risk evaluation model considering project schedule for Shanghai apartment projects. The model used a new approach for assessment on the relationship between quality risk and project schedule.…”