scholarly journals Research on Optimization of Big Data Construction Engineering Quality Management Based on RNN-LSTM

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Daopeng Wang ◽  
Jifei Fan ◽  
Hanliang Fu ◽  
Bing Zhang
Keyword(s):  
Big Data ◽  
Quality Management ◽  
Information Integration ◽  
Construction Project ◽  
Maintenance Phase ◽  
Practical Significance ◽  
Future Research ◽  
Integration Technology ◽  
Project Quality ◽  
Business Data

Construction industry is the largest data industry, but with the lowest degree of datamation. With the development and maturity of BIM information integration technology, this backward situation will be completely changed. Different business data from a construction phase and operation and a maintenance phase will be collected to add value to the data. As the BIM information integration technology matures, different business data from the design phase to the construction phase are integrated. Because BIM integrates massive, repeated, and unordered feature text data, we first use integrated BIM data as a basis to perform data cleansing and text segmentation on text big data, making the integrated data a “clean and orderly” valuable data. Then, with the aid of word cloud visualization and cluster analysis, the associations between data structures are tapped, and the integrated unstructured data is converted into structured data. Finally, the RNN-LSTM network was used to predict the quality problems of steel bars, formworks, concrete, cast-in-place structures, and masonry in the construction project and to pinpoint the occurrence of quality problems in the implementation of the project. Through the example verification, the algorithm proposed in this paper can effectively reduce the incidence of construction project quality problems, and it has a promotion. And it is of great practical significance to improving quality management of construction projects and provides new ideas and methods for future research on the construction project quality problem.

scholarly journals Big data, technology capability and construction project quality: a cross-level investigation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Linhua Sang ◽  
Mingchuan Yu ◽  
Han Lin ◽  
Zixin Zhang ◽  
Ruoyu Jin
Keyword(s):  
Big Data ◽  
Quality Improvement ◽  
Project Management ◽  
Construction Project ◽  
Short Time Interval ◽  
Quality Performance ◽  
Content Type ◽  
Project Quality ◽  
Technology Capability ◽  
The Relationship

PurposeEmbracing big data has been at the forefront of research for project management. Although there is a consensus that the adoption of big data has significantly positive impact on project performance, far less is known about how this innovative information technology becomes an effective driver of construction project quality improvement. This study aims to better understand the mechanism and conditions under which big data can effectively improve project quality performance.Design/methodology/approachAdopting Chinese construction enterprises as samples, the theoretical framework proposed in this paper is verified by the empirical results of the two-level hierarchical linear model. The moderated mediation analysis is also conducted to test the hypotheses. Finally, the empirical findings are validated by a comparative case study.FindingsThe results show that big data facilitates the development of technology capability, which further produces remarkable quality performance. That is, a project team's technology capability acts as a mediator in the relationship between organizational adaptability of big data and predictive analytics and project quality performance. It is also observed that two types of project team interdependence (goal and task interdependence) positively moderate the mediation effect.Research limitations/implicationsThe questionnaire study from China only represents the relationship within a short time interval in the current context. Future studies should apply longitudinal designs to properly test the causality and use multiple data sources to ensure the validity and robustness of the conclusions.Practical implicationsThe value of big data in terms of quality improvement could not be determined in a vacuum; it also depends on the internal capability development and elaborate design of project governance.Originality/valueThis study provides an extension of the existing big data studies and fuels the ongoing debate on its actual outcomes in project management. It not only clarifies the direct effect of big data on project quality improvement but also identifies the mechanism and conditions under which the adoption of big data can play an effective role.

PRACTICES FOR PROJECT QUALITY MANAGEMENT SYSTEMS (PQMS) IN CONSTRUCTION PROJECT

2015 ◽  
Vol 77 (26) ◽  
Author(s):  
Nursyamimi Shaari ◽  
Mat Naim Abdullah @ Mohd Asmoni ◽  
Muhamad Amir Afiq Lokman ◽  
Hamdi Abdul Hamid ◽  
Abdul Hakim Mohammed
Keyword(s):  
Quality Management ◽  
Management System ◽  
Quality Management System ◽  
Construction Project ◽  
Education And Training ◽  
Success Factor ◽  
Research Approach ◽  
Successful Implementation ◽  
Project Quality ◽  
And Training

Due to the importance of the quality management system implementation in construction project, the current study was conducted to identify the set of Project Quality Management System (PQMS) practices for its successful implementation in construction field through a systematic review of literature. Critical success factor (CSF) to implement PQMS in construction project were stated as ‘Client Commitment’, Measurement and Improvement’, ‘Integration of quality Plan’, ‘Education and Training’, Teamwork and Communication’ and ‘Use of ICT’. However, these CSF need to be explored more in terms of its practices and there is an urgent need. A research approach was carried out on the selected papers published between 2004 and 2014. An appropriate database was chosen and seven research papers were identified through a screening process and reviewed for this study. There are 20 important practices in PQMS were identified and has been categorized into six CSF namely; Client’s Commitment (5 practices); Integration of Quality Plan (3 practices); Education and Training (3 practices); Measurement and Improvement (4 practices); Teamwork and Communication (3 practices) and the use of ICT (2 practices).This paper concluded with a numbers of recommendations for  future researchers to discuss, develop, and work upon in order to achieve better precision and generalization

scholarly journals Modeling and Querying Business Data with Artifact Lifecycle

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Danfeng Zhao ◽  
Wei Zhao ◽  
Le Sun ◽  
Dongmei Huang
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
High Volume ◽  
Future Research ◽  
Data Partition ◽  
User Interest ◽  
Transmission Cost ◽  
Minimum Number ◽  
Business Data ◽  
Partition Method

Business data has been one of the current and future research frontiers, with such big data characteristics as high-volume, high-velocity, high-privacy, and so forth. Most corporations view their business data as a valuable asset and make efforts on the development and optimal utilization on these data. Unfortunately, data management technology at present has been lagging behind the requirements of business big data era. Based on previous business process knowledge, a lifecycle of business data is modeled to achieve consistent description between the data and processes. On this basis, a business data partition method based on user interest is proposed which aims to get minimum number of interferential tuples. Then, to balance data privacy and data transmission cost, our strategy is to explore techniques to execute SQL queries over encrypted business data, split the computations of queries across the server and the client, and optimize the queries with syntax tree. Finally, an instance is provided to verify the usefulness and availability of the proposed method.

Construction Project Quality Evaluation System from Lean Construction Perspective

2014 ◽  
Vol 687-691 ◽  
pp. 4438-4441 ◽  
Author(s):  
Yu Hai Miao
Keyword(s):  
Quality Management ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Construction Project ◽  
Lean Construction ◽  
Living Standards ◽  
High Quality ◽  
Project Quality ◽  
Quality Evaluation System

With economic development and improvement of living standards, people are increasingly demanding high-quality building products. However, due to the drawbacks of traditional quality management methods, it leads to a lot of problems in construction quality management, which affect the quality of the construction project, and even pose a threat to people's lives and property. Construction project quality evaluation system from lean construction perspective in this paper can effectively improve the current situation.

scholarly journals RESEARCH ON THE MAKER TEACHER MOBILE TRAINING PLATFORM BASED ON BIG DATA ANALYSIS

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 343-348
Author(s):  
Z. H. Jiang
Keyword(s):  
Professional Development ◽  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Practical Significance ◽  
Future Research ◽  
Space Module ◽  
Space Design ◽  
Evaluation Feedback ◽  
Feedback Module

Abstract. In the era of "Internet +" and Big Data, it is of great practical significance on how to build a training platform that accurately matches the professional development of maker teachers, and to carry out personalized mobile training for maker teachers under the Big Data analysis technology. The construction of the maker teacher mobile training platform, based on the big data analysis technology, is designed to explore the personalized needs of maker teachers in professional development. It introduces a new concept of MOOC and community space design to build the maker mobile training platform framework structure, which contains three layers: application layer, service layer, and data layer. It designs five functional modules: diagnostic demand analysis module, personalized service customization module, online maker course module, seminar space module, and evaluation feedback module. The case analysis of the platform and its application effect shows that the maker teacher mobile training platform based on big data analysis has obvious effects on professional development for teachers and can provide reference for future research on related topics.

Study on the Quality Management of Construction Enterprise

2013 ◽  
Vol 639-640 ◽  
pp. 1281-1284
Author(s):  
Sen Zhi Ren ◽  
Guo Jing He
Keyword(s):  
Quality Management ◽  
Construction Project ◽  
Internal Quality ◽  
High Quality ◽  
Construction Enterprise ◽  
Construction Enterprises ◽  
Project Quality ◽  
Survival And Development

Quality management was the key to the survival and development of construction enterprises. This paper discussed the construction enterprises should carry on the quality management at two levels of the internal quality management of construction enterprises and their construction project quality management, that could make construction enterprises to embark on a high-quality and efficient development road.

scholarly journals Simulation-Based Fuzzy Logic Approach to Assessing the Effect of Project Quality Management on Construction Performance

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Gilberto A. Corona-Suárez ◽  
Simaan M. AbouRizk ◽  
Stanislav Karapetrovic
Keyword(s):  
Fuzzy Logic ◽  
Quality Management ◽  
Causal Structure ◽  
Discrete Event ◽  
Construction Project ◽  
Simulation Models ◽  
Simulation Approach ◽  
Factors Affecting ◽  
Project Quality ◽  
Fuzzy Logic Approach

This paper reports the development of an approach to integrate the appropriate modeling techniques for estimating the effect of project quality management (PQM) on construction performance. This modeling approach features a causal structure that depicts the interaction among the PQM factors affecting quality performance in a given construction operation. In addition, it makes use of fuzzy sets and fuzzy logic in order to incorporate the subjectivity and uncertainty implicit in the performance assessment of these PQM factors to discrete-event simulation models. The outcome is a simulation approach that allows experimenting with different performance levels of the PQM practices implemented in a construction project and obtaining the corresponding productivity estimates of the construction operations. These estimates are intended to facilitate the decision making regarding the improvement of a PQM system implemented in a construction project. A case study is used to demonstrate the usefulness of the proposed simulation approach for evaluating diverse performance improvement alternatives for a PQM system.

A Systematic Literature Review of the EFQM Excellence Model from 1991 to 2019

1970 ◽  
Vol 2 (2) ◽  
pp. 11-15
Author(s):  
Muhammad Yousaf ◽  
Petr Bris
Keyword(s):  
Quality Management ◽  
Data Collection ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Quantitative Research ◽  
Web Of Science ◽  
State Of The Art ◽  
Future Research ◽  
European Foundation ◽  
The Subject

A systematic literature review (SLR) from 1991 to 2019 is carried out about EFQM (European Foundation for Quality Management) excellence model in this paper. The aim of the paper is to present state of the art in quantitative research on the EFQM excellence model that will guide future research lines in this field. The articles were searched with the help of six strings and these six strings were executed in three popular databases i.e. Scopus, Web of Science, and Science Direct. Around 584 peer-reviewed articles examined, which are directly linked with the subject of quantitative research on the EFQM excellence model. About 108 papers were chosen finally, then the purpose, data collection, conclusion, contributions, and type of quantitative of the selected papers are discussed and analyzed briefly in this study. Thus, this study identifies the focus areas of the researchers and knowledge gaps in empirical quantitative literature on the EFQM excellence model. This article also presents the lines of future research.

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