scholarly journals BIM Based Time Management Among Construction Contractors in Turkey

2021 ◽  
Author(s):  
Ayşen Saraç Çıracıoğlu ◽  
Hakan Yaman
Keyword(s):  
Time Management ◽  
Construction Projects ◽  
Critical Role ◽  
Scheduling Problems ◽  
Project Schedule ◽  
Structured Interviews ◽  
Planning And Scheduling ◽  
Construction Companies ◽  
Planning Department ◽  
Industrialised Countries

In both developing and industrialised countries, due to numerous time-related problems of construction projects, BIM-based time management, 4D BIM, plays an increasingly critical role within the industry. This study investigates the planning and scheduling problems, BIM application level, and BIM-based scheduling implementation by the lead construction companies in Turkey. Despite the critical importance of the planning department in construction companies, the planning and BIM integration levels have scarcely been investigated from the contractor perspective in Turkey. This paper presents the outcomes of 16 semi-structured interviews (SSI) with managers of the leading Turkish contractors selected from 100 of ENR’s 2019 Top 250 International Contractors list; a list of issues are outlined. The current situation escalates problems like tendering with missing project documents, examining 2D project drawings while scheduling, fragmentation, project manager’s reluctance to use and follow the project schedule, issues with updating the schedule as per construction improvements and quantities, and a lack of investment for BIM implementation. The research findings, ultimately, aim to help contractors improve their processes. Although this study’s findings are obtained from interviews with lead Turkish contractors, it is not limited in terms of geographic context since the interviewed contractors work worldwide.

An empirical study on non-physical waste factors in the construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Charles Igwe ◽  
Fuzhan Nasiri ◽  
Amin Hammad
Keyword(s):  
Developing Countries ◽  
Empirical Study ◽  
Construction Projects ◽  
Severity Index ◽  
Structured Interviews ◽  
Planning And Scheduling ◽  
Content Type ◽  
Normality Test ◽  
Importance Index ◽  
Human Material

PurposeThis study highlights the findings of an empirical study to investigate waste factors (WFs) affecting the performance and delivery of construction projects in developing countries. The objectives of this study are to identify non-physical WFs in developing nations and rank the identified factors based on their degree of influence on the key performance indicators (KPIs) of cost, quality and time.Design/methodology/approachIn total, 34 WFs were identified through a detailed literature review and consolidated using semi-structured interviews with construction practitioners. The statistical analysis involved a normality test using the Shapiro–Wilk test to determine if sample data have been drawn from a normally distributed population, ranking the WFs using the Frequency Index (FI), Severity Index (SI) and Importance Index (IMPI), ranking the WFs based on their effect on the project KPIs of cost, quality and time, and identify clustering structures for the identified WFs to using factor analysis (FA).FindingsThe results revealed ineffective planning and scheduling, rework/repair of defective work and resource quality problems (human, material and equipment) as the three most important WFs affecting construction projects. The factor analyses showed that WFs can be grouped into five interrelated components, suggesting the need for integrated and holistic strategies to overcome the identified WF.Practical implicationsUnderstanding the effects of WFs on construction projects is a first step towards designing holistic solutions to ensuring projects deliver value to the clients and other stakeholders. The findings of this study provide direction to construction practitioners on where to focus appropriate strategies to manage the identified WFs effectively and, therefore, improve the productivity of construction projects.Originality/valueThis study provides the first holistic analysis of WFs affecting the productivity of construction projects in developing countries.

scholarly journals Comparative Study of Pipeline Deliverables using Deterministic and Stochastic Models

2019 ◽  
Vol 4 (1) ◽  
pp. 115-122
Author(s):  
Ernest Oria Ihendeson ◽  
Awajiogak A Ujile ◽  
Anthony K. Leol
Keyword(s):  
Stochastic Model ◽  
Construction Projects ◽  
Deterministic Model ◽  
Critical Path ◽  
Project Schedule ◽  
Construction Time ◽  
Planning And Scheduling ◽  
Pipeline Construction ◽  
Stochastic Duration ◽  
Model Variable

This study aim to proffer solution to the factors causing delay is pipeline construction project deliverables, it compared deterministic model (variable with certainty) and stochastic model (variable with uncertainty), with Six (6) planned project schedules of Brownfield Energy Service Limited for pipeline construction. Time assigned to critical activities, identified from a network analysis, with the aid of the Critical Path Method, expected mean time, both deterministic and stochastic duration was calculated. Program Evaluation Review Techniques (PERT), the variance and standard deviation of the critical activities were also calculated. The probability of completion of a project within a given period was gotten with PERT. Comparing the results for deterministic duration 60 days to 79 days, which is 50% compared to 64%. It was concluded that stochastic model is preferable when scheduling and executing pipeline construction projects, because uncertainties are factored into the planning and scheduling process including delays. Delays during execution stage, occurs mainly due to community related issues, equipment failures, change in job scope and work- men antics but not limited to these. This study advocates elimination of causes of delay, especially before and during project execution phase. It also suggested that every project schedule should follow an order of precedents, prerequisite, and management involvement and cooperation at all stages of the project

scholarly journals Strategic framework for implementing smart devices in the construction industry

2021 ◽  
Vol 21 (2) ◽  
pp. 218-243
Author(s):  
Manuel Alexander Silverio-Fernández ◽  
Suresh Renukappa ◽  
Subashini Suresh
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
Success Factors ◽  
High Rate ◽  
Smart Devices ◽  
Structured Interviews ◽  
Content Type ◽  
Strategic Framework ◽  
Construction Companies ◽  
The Uk

Purpose The decentralisation of information and high rate of mobile content access in the construction industry provide an ideal scenario for improvement of processes via the implementation of the paradigm of the Internet of Things (IoT). Smart devices are considered as the objects interconnected in the IoT; therefore, they play a fundamental role in the digital transformation of the construction industry. Currently, there is a lack of guidelines regarding the implementation of smart devices for digitalisation in the construction industry. Consequently, this paper aims to provide a set of guidelines for implementing smart devices in the construction industry. Design/methodology/approach An empirical study was performed in the UK and the Dominican Republic (DR). Following a systematic approach, qualitative data collection and analysis was performed based on semi-structured interviews involving professionals from construction companies in the UK and the DR. Interviews were recorded and subsequently transcribed using Microsoft Word and exported to the software NVivo, where the software was used to find common thematic nodes across all interviews. Findings The findings encompass drivers, challenges and critical success factors (CSFs) for implementing smart devices in construction project. For both countries, the top five CSFs were leadership, staff training, culture, technology awareness and cost of implementation. These findings were used to develop a strategic framework for implementing smart devices in construction companies. The framework establishes the actors, elements and actions to be considered by construction companies when implementing smart devices. Originality/value This paper provides a richer insight into the understanding and awareness of implementing smart devices. A strategic framework for implementing smart devices in the construction industry and providing guidelines for adopting smart devices in construction projects was developed and validated. This study provides a better understanding of the key factors to be considered by construction companies when embedding smart devices into their projects.

scholarly journals Construction delays: a case study in the Brazilian Amazon

2017 ◽  
Vol 17 (3) ◽  
pp. 167-181 ◽  
Author(s):  
Luiz Mauricio Furtado Maués ◽  
Wylliam Bessa Santana ◽  
Paulo Cerqueira dos Santos ◽  
Renato Martins das Neves ◽  
André Augusto Azevedo Montenegro Duarte
Keyword(s):  
Factor Analysis ◽  
Construction Projects ◽  
City Planning ◽  
Brazilian Amazon ◽  
Construction Time ◽  
Construction Companies ◽  
Industrial Sectors ◽  
Planning Department ◽  
The Government

Abstract he construction industry is one of the industrial sectors with the lowest rates of fulfilment of contract deadlines, especially in developing countries. This fact has been the focus of considerable discussions seeking to identify the causes of the delays. The main purpose of this paper is to use factor analysis to identify the factors that are correlated with delay, contemplating exclusively residential real estate projects and using a city in the Brazilian Amazon as a case study. Based on the database from the government agency that authorises constructions in the city of Belém (City Planning Department - Secretaria Municipal de Urbanismo, SEURB) and data from construction companies, the study investigated 274 construction projects from the past 11 years. Factor analysis and work with the variables that can be identified and measured in the initial phase of the project, i.e., during the feasibility study, demonstrate that the physical characteristics of the apartments and the construction project are the primary causes for variations in construction delays; these causes have not yet been reported in the literature. We hope that the results of this study will contribute to more consistent forecasting of construction time, minimising the risk of delays.

scholarly journals Implementation Phase Safety System for Minimising Construction Project Waste

Buildings ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 25 ◽  
Author(s):  
Kamal Mahfuth ◽  
Amara Loulizi ◽  
Khalid Al Hallaq ◽  
Bassam A. Tayeh
Keyword(s):  
Construction Projects ◽  
Safety System ◽  
Waste Materials ◽  
Safety Factors ◽  
Structured Interviews ◽  
Implementation Phase ◽  
Construction Companies ◽  
Positive Effects ◽  
Importance Index ◽  
Safety Considerations

The construction sector is a key component of a nation’s gross domestic product, but its inherent nature results in potentially dangerous conditions that affect the safety of all workers on construction projects (CPs). Therefore, the original idea of the research is to determine the relationship between safety system (SS) during the implementation phase (IPh) of CPs and the minimisation of waste (materials, time and cost). Achieving a lean construction work requires suitable planning, safety considerations and waste resource minimisation throughout the project cycle. This research aims to identify and rank the safety factors during the IPh of a CP, which will have positive effects on minimising waste. Information and data were gathered from the existing literature and the structured interviews and questionnaire survey conducted among 111 randomly selected construction companies. Questionnaire results were evaluated using statistical tools, such as hypothesis testing, analysis of variance and linear regression. This research identified and ranked 24 important safety factors with positive effects on minimising waste in CPs during IPh. The seven most important safety factors that should be considered to minimise material, time and cost wastage are as follows: handling, management, external factors, workers, procurement, site condition and appropriate scaffolding for SS. The best linear model was developed on the basis of the importance index of the identified factors. This model can predict the minimisation of waste (materials, time and cost) in CPs by using SS. Thus, the safety criteria and SS should be used during IPh to minimise waste on the basis of the developed model.

MITIGATING CONSTRUCTION PROJECT SCHEDULE OVERRUNS

2016 ◽  
Vol 3 (2) ◽  
Author(s):  
Mulenga Mukuka ◽  
Clinton Aigbavboa ◽  
Wellington Thwala
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
Construction Project ◽  
Project Planning ◽  
The Body ◽  
Mitigation Measures ◽  
Primary Data ◽  
Project Schedule ◽  
Gauteng Province ◽  
Planning And Scheduling

There are many factors that contribute to the causes of schedule overruns in construction projects. This ranges from factors inherent in the technology and its management, to those resulting from the physical, social, and financial environment. Schedule overruns can give rise to disruption of work and loss of productivity, late completion of project, increased time related costs and third party claims and abandonment or termination of contract. Schedule overruns are costly and often result in disputes and claims. Hence, the need to identify mitigation measures of construction projects overruns that will bring about the timely delivery of construction projects. This paper assesses the measures to mitigate against construction projects schedule overruns in the Gauteng Province construction industry in South African. The data used in this paper were derived from both primary and secondary sources. The primary data were collected through a questionnaire distributed to construction professionals in the study area. Data received from the questionnaires were analyzed using descriptive statistics procedures. Findings revealed that proper project planning and scheduling, effective strategic planning, site management and supervision, amongst others, were the major mitigation measures of construction projects schedule overruns in the Gauteng Province of South Africa. This study contributes to the body of knowledge on the subject of the measures of mitigating against construction project schedule overruns in the Gauteng Province construction industry.

scholarly journals Data Analytics of Production Cycle Time for Offsite Construction Projects

2019 ◽  
pp. 25-32
Author(s):  
Angat Pal Singh Bhatia ◽  
Sanghyeok Han ◽  
Osama Moselhi ◽  
Zhen Lei ◽  
Claudio Raimondi
Keyword(s):  
Construction Industry ◽  
Cycle Time ◽  
Construction Projects ◽  
Production Cycle ◽  
Linear Regression Models ◽  
Project Schedule ◽  
Work Station ◽  
Construction Companies ◽  
Design Specifications ◽  
Productivity Data

Offsite construction has been widely used in the construction industry. The process improves productivity that leads to shortened project schedule and lower budget. Over the decades, offsite construction industry has continuously evolved with the aspects of management and technology. However, offsite construction companies still have various challenges such as accurately obtaining productivity metrics, which helps in production planning. These challenges result from lack of understanding the process itself because of high variation of wall panel design specifications along with high variability of cycle time at each work station. To solve the problem, productivity data needs to be collected in context to offsite construction. In this paper, a time study was conducted in one of Alberta’s-based offsite construction factory. From the collected data and product design specifications, multiple linear regression models were developed to represent the actual work station time. The comparison between actual collected duration and modeled duration for assembly station demonstrate its accuracy that ranges from 80 -99%. In the near future, findings will be used for simulation to forecast factory production and optimize the utilization of the resources.

The Role of Software in Construction Management

2021 ◽  
pp. 69-97
Keyword(s):  
Project Management ◽  
Project Scheduling ◽  
Construction Management ◽  
Construction Projects ◽  
Planning And Scheduling ◽  
Management Software ◽  
Construction Engineering ◽  
Construction Companies ◽  
Software Market

Civil construction projects not only need to be executed on time; these also require that budgetary overruns are not allowed to take place needlessly. The traditional constraints involving time, quality, and money must always be paid close attention for a project to be considered commercial and engineering success. In this chapter, the authors discuss the role of project management software and the various commercial options available in the software market for entrepreneurs, engineers, and project planners to explore. They also discuss the need for activity codes and project scheduling types and the significance of these in civil construction engineering. The importance of planning and scheduling cannot be overestimated in a world where competition is high and civil construction companies often find themselves on razor's edge to stay afloat and remain profitable.

scholarly journals The Use of Project Time Management Processes and the Schedule Performance of Construction Projects in Mexico

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Rómel G. Solís-Carcaño ◽  
Gilberto A. Corona-Suárez ◽  
Aldo J. García-Ibarra
Keyword(s):  
Time Management ◽  
Construction Projects ◽  
Statistical Dependence ◽  
School Construction ◽  
Project Schedule ◽  
Public Agency ◽  
Management Processes ◽  
Timely Completion ◽  
Schedule Performance ◽  
Controlling Processes

Delays have been frequently reported as the cause of several conflicts that affect the different parties involved in construction projects. Project Time Management (PTM) includes a number of planning and controlling processes that are recommended for complying with requirements related to project time. The study reported in this paper aimed at assessing the use of PTM processes and its relation with project schedule performance (i.e., timely completion). Seven PTM processes and seventy-seven tasks associated with them were identified from the literature that is globally relevant to project management. The study included the assessment of fourteen school construction projects executed by a public agency in the Yucatan Peninsula, Mexico. These projects were monitored during the construction phase in order to measure two different variables: the use of processes related to PTM (i.e., schedule planning and controlling processes) and the project schedule performance. For each of these projects a Use Index was obtained for assessing the first variable, while the Schedule Performance Index and the Schedule Variance were computed to assess the second one. The results demonstrated there is statistical dependence between these two variables. Most of the projects that attained timely completion also made a greater use of the PTM processes.

scholarly journals A Novel Load Forecasting Approach Based on Smart Meter Data Using Advance Preprocessing and Hybrid Deep Learning

2021 ◽  
Vol 11 (6) ◽  
pp. 2742
Author(s):  
Fatih Ünal ◽  
Abdulaziz Almalaq ◽  
Sami Ekici
Keyword(s):  
Deep Learning ◽  
Energy Consumption ◽  
Prediction Models ◽  
Short Term Memory ◽  
Critical Role ◽  
Load Forecasting ◽  
Unified Framework ◽  
Short Term ◽  
Planning And Scheduling ◽  
Short Term Load Forecasting

Short-term load forecasting models play a critical role in distribution companies in making effective decisions in their planning and scheduling for production and load balancing. Unlike aggregated load forecasting at the distribution level or substations, forecasting load profiles of many end-users at the customer-level, thanks to smart meters, is a complicated problem due to the high variability and uncertainty of load consumptions as well as customer privacy issues. In terms of customers’ short-term load forecasting, these models include a high level of nonlinearity between input data and output predictions, demanding more robustness, higher prediction accuracy, and generalizability. In this paper, we develop an advanced preprocessing technique coupled with a hybrid sequential learning-based energy forecasting model that employs a convolution neural network (CNN) and bidirectional long short-term memory (BLSTM) within a unified framework for accurate energy consumption prediction. The energy consumption outliers and feature clustering are extracted at the advanced preprocessing stage. The novel hybrid deep learning approach based on data features coding and decoding is implemented in the prediction stage. The proposed approach is tested and validated using real-world datasets in Turkey, and the results outperformed the traditional prediction models compared in this paper.

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