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Article
Publication date: 1 March 2006

David Oloke, David J. Edwards, Bruce Wright and Peter E.D. Love

Effective management and utilisation of plant history data can considerably improve plant and equipment performance. This rationale underpins statistical and mathematical…

Abstract

Effective management and utilisation of plant history data can considerably improve plant and equipment performance. This rationale underpins statistical and mathematical models for exploiting plant management data more efficiently, but industry has been slow to adopt these models. Reasons proffered for this include: a perception of models being too complex and time consuming; and an inability of their being able to account for dynamism inherent within data sets. To help address this situation, this research developed and tested a web‐based data capture and information management system. Specifically, the system represents integration of a web‐enabled relational database management system (RDBMS) with a model base management system (MBMS). The RDBMS captures historical data from geographically dispersed plant sites, while the MBMS hosts a set of (Autoregressive Integrated Moving Average – ARIMA) time series models to predict plant breakdown. Using a sample of plant history file data, the system and ARIMA predictive capacity were tested. As a measure of model error, the Mean Absolute Deviation (MAD) ranged between 5.34 and 11.07 per cent for the plant items used in the test. The Root Mean Square Error (RMSE) values also showed similar trends, with the prediction model yielding the highest value of 29.79 per cent. The paper concludes with direction for future work, which includes refining the Graphical User Interface (GUI) and developing a Knowledge Based Management System (KBMS) to interface with the RDBMS.

Details

Journal of Engineering, Design and Technology, vol. 4 no. 1
Type: Research Article
ISSN: 1726-0531

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Article
Publication date: 1 February 2003

David A. Oloke, David J. Edwards and Tony A. Thorpe

Construction plant breakdown affects projects by prolonging duration and increasing costs. Therefore, prediction of plant breakdown, as a precursor to conducting timely…

Abstract

Construction plant breakdown affects projects by prolonging duration and increasing costs. Therefore, prediction of plant breakdown, as a precursor to conducting timely maintenance works, cannot be underestimated. This paper thus sought to develop a model for predicting plant breakdown time from a sequence of discrete plant breakdown measurements that follow non‐random orders. An ARIMA (1,1,0) model was constructed following experimentation with exponential smoothening. The model utilised breakdown observations obtained from six wheeled loaders that had operated a total of 14,467 hours spread over a 300‐week period. The performance statistics revealed MAD and RMSE of 5.03 and 5.33 percent respectively illustrating that the derived time series model is accurate in modelling the dependent variable. Also, the F‐statistics from the ANOVA showed that the type and frequency of fault occurrence as a predictor variable is significant on the model's performance at the five percent level. Future work seeks to consider a more in depth multivariate time series analyses and compare/contrast the results of such against other deterministic modelling techniques.

Details

Journal of Engineering, Design and Technology, vol. 1 no. 2
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 28 January 2020

David Oloke

Abstract

Details

International Journal of Building Pathology and Adaptation, vol. 39 no. 1
Type: Research Article
ISSN: 2398-4708

Article
Publication date: 26 January 2021

Dahiru Abdullahi, Suresh Renukappa, Subashini Suresh and David Oloke

Despite the abundant renewable energy potential in the Nigeria, the power-sector stakeholder has not paid attention to the prospect of the natural resources that can be…

Abstract

Purpose

Despite the abundant renewable energy potential in the Nigeria, the power-sector stakeholder has not paid attention to the prospect of the natural resources that can be accrued when it is properly harnessed. Although a very negligible fraction of the population has invested in solar photovoltaics (PVs) for home solution, the initiative was only made public commercialised under the public-private partnership (PPP) and the objectives of the Power Sector Reform Act. 2005. It is, therefore, aimed to investigate the causes and insight of the barriers that are responsible for the slow implementation of the solar energy initiative in the Nigeria.

Design/methodology/approach

An empirical study was performed in the Nigeria. The study was conducted qualitatively, through semi-structured face-to-face interviews of 25 participants. The interviews were recorded, transcribed, interpreted, coded, categorised into themes and analysed by content analysis.

Findings

The study reveals technological, financial, political and social barriers have been the reason for slowing down solar energy development in Nigeria. While the technical barrier is a challenge to the solar energy implementation, socio-cultural issues have also been an obstacle to the implementation process. It is suggested that, the stakeholders of the initiative endeavour to proffer sustainable policies to enable public and private promoters to be able to generate and distribute electricity through solar PV and to complement the inadequate conventional electricity sources from the grids.

Originality/value

The paper provides a richer insight into the understanding and awareness of barriers for implementing solar energy strategies in Nigeria.

Details

Smart and Sustainable Built Environment, vol. 11 no. 3
Type: Research Article
ISSN: 2046-6099

Keywords

Article
Publication date: 11 May 2020

Tochukwu Moses, David Heesom and David Oloke

The purpose of this paper is to report on primary research findings that sought to investigate and analyse salient issues on the implementation of 5D building information…

2201

Abstract

Purpose

The purpose of this paper is to report on primary research findings that sought to investigate and analyse salient issues on the implementation of 5D building information modelling (BIM) from the UK contractors’ perspective. Previous research and efforts have predominantly focussed on the use of technologies for cost estimation and quantity takeoff within a more traditional-led procurement, with a paucity of research focussing on how 5D BIM could facilitate costing within contractor-led procurement. This study fills this current knowledge gap and enhances the understanding of the specific costing challenges faced by contractors in contractor-led projects, leading to the development of 5D framework for use in future projects.

Design/methodology/approach

To develop a fully detailed understanding of the challenges and issues being faced in this regard, a phenomenological, qualitative-based study was undertaken through interviews involving 21 participants from UK-wide construction organisations. A thematic data analytical process was applied to the data to derive key issues, and this was then used to inform the development of a 5D-BIM costing framework.

Findings

Multi-disciplinary findings reveal a range of issues faced by contractors when implementing 5D BIM. These exist at strategic, operational and technological levels which require addressing successful implementation of 5D BIM on contractor-led projects adhering to Level 2 BIM standards. These findings cut across the range of stakeholders on contractor-led projects. Ultimately, the findings suggest strong commitment and leadership from organisational management are required to facilitate cost savings and generate accurate cost information.

Practical implications

This study highlights key issues for any party seeking to effectively deploy 5D BIM on a contractor-led construction project. A considerable cultural shift towards automating and digitising cost functions virtually, stronger collaborative working relationship relative to costing in design development, construction practice, maintenance and operation is required.

Originality/value

By analysing findings from primary research data, the work concludes with the development of a 5D BIM costing framework to support contractor-led projects which can be implemented to ensure that 5D BIM is successfully implemented.

Details

Journal of Engineering, Design and Technology , vol. 18 no. 6
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 18 October 2021

John Peter Cooney, David Oloke and Louis Gyoh

This study aims to demonstrate the possibility of showing the functionality of complex microbial groups, within ancient structures within a process of refurbishment on a…

Abstract

Purpose

This study aims to demonstrate the possibility of showing the functionality of complex microbial groups, within ancient structures within a process of refurbishment on a heritage building information modelling (BIM) platform.

Design/methodology/approach

Both a qualitative and qualitative research method will be used throughout, as observational and scientific results will be obtained and collated. This path being; phenomena – acquisition tools – storage – analysis tools – literature. Using this methodology, one pilot study within the scope of demolition and refurbishment, using suitable methods of collecting and managing data (structural or otherwise), will be used and generated by various software and applications. The principle methods used for the identification of such micro-organisms will incorporate a polymerase chain reaction method (PCR), to amplify DNA and to identify any or all spores present. The BIM/historical BIM (HBIM) process will be used to create a remotely-based survey to obtain and collate data using a laser scanner to produce a three-dimensional point cloud model to evaluate and deduce the condition, make-up and stature of the monument. A documentation management system will be devised to enable the development of plain language questions and an exchange information requirement, to identify such documentation required to enable safe refurbishment and to give health and safety guidance. Four data sampling extractions will be conducted, two for each site, within the research, for each of the periods being assessed, that being the Norman and Tudor areas of the monument.

Findings

From laboratory PCR analysis, results show a conclusive presence of micro-organism groups and will be represented within a hierarchical classification, from kingdom to species.

Originality/value

The BIM/HBIM process will highlight results in a graphical form to show data collected, particularly within the PCR application. It will also create standardisation and availability for such data from ancient monuments to make available all data stored, as such analysis becomes substantially important to enable the production of data sets for comparison, from within the framework of this research.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 6 April 2022

AbdurRaheem A. Yakub, Kamalahasan Achu, Hishamuddin Mohd Ali and Rohaya Abdul Jalil

There are a plethora of putative influencing variables available in the literature for modelling real estate prices using AI. Their choice tends to differ from one…

Abstract

Purpose

There are a plethora of putative influencing variables available in the literature for modelling real estate prices using AI. Their choice tends to differ from one researcher to the other, consequently leading to subjectivity in the selection process. Thus, there is a need to seek the viewpoint of practitioners on the applicability and level of significance of these academically established variables.

Design/methodology/approach

Using the Delphi technique, this study collated and structured the 35 underlying micro- and macroeconomic parameters derived from literature and eight variables suggested by 11 selected real estate experts. The experts ranked these variables in order of influence using a seven-point Likert scale with a reasonable consensus during the fourth round (Kendall's W = 0.7418).

Findings

The study discovered that 16 variables are very influential with seven being extremely influential. These extremely influential variables include flexibility, adaptability of design, accessibility to the building, the size of office spaces, quality of construction, state of repairs, expected capital growth and proximity to volatile areas.

Practical implications

The results of this study improve the quality of data available to valuers towards a fortified price prediction for investors, and thereby, restoring the valuers' credibility and integrity.

Originality/value

The “volatility level of an area”, which was revealed as a distinct factor in the survey is used to add to current knowledge concerning office price. Hence, this study offers real estate practitioners and researchers valuable knowledge on the critical variables that must be considered in AI-based price modelling.

Details

Property Management, vol. 40 no. 5
Type: Research Article
ISSN: 0263-7472

Keywords

Article
Publication date: 27 June 2022

Gholamreza Dehdasht, M. Salim Ferwati, Saeed Reza Mohandes, Luai El-Sabek and David John Edwards

Proper identification of the key motivating factors (or key drivers) is needed to ensure successful adaption and implementation of the lean concept for construction…

Abstract

Purpose

Proper identification of the key motivating factors (or key drivers) is needed to ensure successful adaption and implementation of the lean concept for construction projects. However, there lacks a study investigating the complex interrelationships existing among the key drivers contributing to Sustainable and Successful Lean Construction (SSLC) implementation for such projects. To address this shortcoming, this study aims to uncover the main critical key drivers towards the implementation of SSLC for the very first time by capturing the complexity of this vexing problem.

Design/methodology/approach

In this study, a new hybrid framework is developed through the integration of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Social Network Analysis (SNA). The novel developed framework is called the DSNA approach.

Findings

Considering the case of Malaysian construction projects, the developed DSNA gives the following major outcomes: (1) Most important critical key drivers are seen to be optimization, continuous improvement, and, improve company culture, and (2) For SSLC adoption, the critical drivers impacting other key drivers are seen to be “improve teamwork”, “reduce leadership conflict”, and “improve company culture”, thereby demanding more attention.

Practical implications

The outcomes of this study give insight for decisions and policymakers in the construction industry regarding critical key drivers and their complex interrelationships towards the further adoption of SSLC, promoting the sustainability paradigm within the respective sector.

Originality/value

This paper not only presents a list of critical drivers and the corresponding association among them towards SSLC adoption, but also proposes DSNA as a novel approach for uncovering the complex interrelationship existing in an intricate problem, improving the intricate process of decision-making.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 31 August 2022

Maria Unuigbe, Sambo Lyson Zulu and David Johnston

Challenges to energy access in Nigeria have resulted in the widespread use of fossil fuel generating sets (generators) despite its renewable energy (RE) potential. Given…

Abstract

Purpose

Challenges to energy access in Nigeria have resulted in the widespread use of fossil fuel generating sets (generators) despite its renewable energy (RE) potential. Given the climate crisis, combined with the country's rapid population growth and expected rise in energy and building demand, transitioning to low-carbon electricity using REs like solar photovoltaic (PV) presents opportunities beyond securing its energy future. While PV use is growing in Nigeria, this is focused on the residential sector despite the identification of the commercial sector as a high energy consumer and a key platform for its integration. In line with this, this research aims to investigates the challenges to energy transitioning from generators to solar PV in commercial buildings.

Design/methodology/approach

A qualitative approach in line with grounded theory was adopted using in-depth face-to-face interviews with industry experts.

Findings

Two distinct but interrelated categories emerged: being held captive and being a saviour that represented a duality of systems, and/or processes formed the core category “Hostage Syndrome”. The core category (theory) was generated based on the explanations and expressions by participants about their concerns, interests, and the conditions under which they operate. The findings reveal the value attributed to generators beyond an operational role and the adjustments or mechanisms adopted by building professionals during their practice. It suggests a sphere of influence beyond the obvious financial and/or institutional aspects, as determining factors to what is viewed as sustainable which will be key to transitioning to REs.

Originality/value

This paper provides new and in-depth insight into understanding the conditions under which building professionals operate associated with their interpretations of “being sustainable”. The study highlights the need to consider psychological and cultural factors in the development of interventions, strategies and/or policies to support RE transition, particularly towards achieving a sustainable construction industry.

Details

Built Environment Project and Asset Management, vol. 13 no. 1
Type: Research Article
ISSN: 2044-124X

Keywords

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