Soft computing approach to construction performance prediction and diagnosis

2008 ◽  
Vol 35 (8) ◽  
pp. 764-776 ◽  
Author(s):  
Manjula Dissanayake ◽  
Aminah Robinson Fayek
Keyword(s):  
Soft Computing ◽  
Construction Projects ◽  
Field Measurements ◽  
Performance Measure ◽  
Related Factors ◽  
Fast Tracking ◽  
Subjective Assessments ◽  
Project Complexity ◽  
Systematic Methodology ◽  
Computing Approach

Increasing project complexity and greater levels of fast-tracking on construction projects make the need for quickly detecting and diagnosing a deviation in a construction performance measure from its planned value a challenging task. In such a rapidly changing environment, timely detection of deviations is critical so that the most effective corrective actions can be taken. This paper presents an integrated model that is capable of predicting and diagnosing construction performance deviations based on a combination of field measurements and subjective assessments of performance-related factors. The proposed system is based on the synergistic integration of the soft computing approaches of fuzzy set theory, neural networks, and genetic algorithms. A systematic methodology to elicit and represent qualitative construction performance knowledge from a group of experts is presented. The essential features of the model are described in detail and are implemented in a computer system called XCOPE (explaining construction performance).

scholarly journals ASSESSING PROCUREMENT IRREGULARITIES IN THE SUPPLY-CHAIN OF GHANAIAN CONSTRUCTION PROJECTS: A SOFT-COMPUTING APPROACH

2020 ◽  
Vol 26 (1) ◽  
pp. 66-82
Author(s):  
Emmanuel Kingsford Owusu ◽  
Albert P. C. Chan ◽  
M. Reza Hosseini ◽  
Bahareh Nikmehr
Keyword(s):  
Soft Computing ◽  
Construction Projects ◽  
Decision Makers ◽  
Fuzzy Synthetic Evaluation ◽  
Factor Analyses ◽  
Computing Technique ◽  
Probabilistic Sampling ◽  
Policy Making Process ◽  
Soft Computing Technique ◽  
Computing Approach

This study examines procurement irregularities, as one of the most unexplored threats in the procurement process of construction projects. It also tests the suppositions associated with the contributions of irregularities to corruption in construction procurement. An expert survey is conducted with 62 construction-related practitioners selected via non-probabilistic sampling in the context of a Ghana, to assess the criticalities of the irregularities. Eighteen irregularities were identified within the context selected for this study. A soft computing technique known as the Fuzzy Synthetic Evaluation (FSE) method is employed to examine the identified irregularities. Other relevant techniques including factor analyses, normalization, and descriptive tools are employed to factorize the identified irregularities and test the hypotheses. Out of the 18 irregularities, 11 were revealed to be critical. The findings reveal that the top three irregularities were: payments for uncompleted works, sourcing of proforma invoices from the same supplier and the lack of proper coordination among key departments. Moreover, four constructs were developed using the identified measurement items. They are administrative-specific, procedural, compliance and contract monitoring irregularities. Out of the four, the topmost critical construct turns out to be compliance irregularities. Theoretically, this study advances the scholarship of construction by shedding lights on the irregularities associated with the procurement processes of construction projects. It also contributes to an in-depth understanding of the noted irregularities. In practical terms, this study contributes to the procurement planning and policy-making process, it assists decision makers in putting in place measures to prevent or extirpate the likelihood of any of the irregularities’ occurrences.

SOFT COMPUTING APPROACH TO DETECT FAULT IN INDUCTION MOTOR

2018 ◽  
Vol 12 (2) ◽  
pp. 6
Author(s):  
SEKHAR PUHAN PRATAP ◽  
BEHERA SUDARSAN ◽  
◽  
Keyword(s):  
Induction Motor ◽  
Soft Computing ◽  
Computing Approach

scholarly journals A Soft Computing Approach to Crack Detection and Impact Source Identification with Field-Programmable Gate Array Implementation

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Arati M. Dixit ◽  
Harpreet Singh
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Inference System ◽  
Source Identification ◽  
Field Programmable Gate Array ◽  
Crack Detection ◽  
Fuzzy Inference ◽  
Inference System ◽  
Field Programmable ◽  
Computing Approach

The real-time nondestructive testing (NDT) for crack detection and impact source identification (CDISI) has attracted the researchers from diverse areas. This is apparent from the current work in the literature. CDISI has usually been performed by visual assessment of waveforms generated by a standard data acquisition system. In this paper we suggest an automation of CDISI for metal armor plates using a soft computing approach by developing a fuzzy inference system to effectively deal with this problem. It is also advantageous to develop a chip that can contribute towards real time CDISI. The objective of this paper is to report on efforts to develop an automated CDISI procedure and to formulate a technique such that the proposed method can be easily implemented on a chip. The CDISI fuzzy inference system is developed using MATLAB’s fuzzy logic toolbox. A VLSI circuit for CDISI is developed on basis of fuzzy logic model using Verilog, a hardware description language (HDL). The Xilinx ISE WebPACK9.1i is used for design, synthesis, implementation, and verification. The CDISI field-programmable gate array (FPGA) implementation is done using Xilinx’s Spartan 3 FPGA. SynaptiCAD’s Verilog Simulators—VeriLogger PRO and ModelSim—are used as the software simulation and debug environment.

Empirically validating five propositions regarding 3D visualizations for subsurface utility projects

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mechiel van Manen ◽  
Léon olde Scholtenhuis ◽  
Hans Voordijk
Keyword(s):  
Construction Projects ◽  
3D Visualization ◽  
Three Dimensional ◽  
Urban Environments ◽  
Content Type ◽  
Complexity Level ◽  
Daily Work ◽  
Complex Projects ◽  
Project Complexity ◽  
Multiple Case

PurposeThis study aims to empirically validate five propositions about the benefits of three-dimensional (3D) visualizations for the management of subsurface utility projects. Specifically, the authors validate whether benefits from 3D in the literature of building construction project management also apply to subsurface utility projects and map them using a taxonomy of project complexity levels.Design/methodology/approachA multiple case study of three utility construction projects was carried out during which the first author was involved in the daily work practices at a utility contractor. 3D visualizations of existing project models were developed, and design and construction meetings were conducted. Practitioners' interactions with and reflections on these 3D visualizations were noted. Observational data from the three project types were matched with the five propositions to determine where benefits of 3D visualizations manifested themselves.FindingsPractitioners found that 3D visualizations had most merit in crowded urban environments when constructing rigid pipelines. All propositions were validated and evaluated as beneficial in subsurface utility projects of complexity level C3. It is shown that in urban projects with rigid pipelines (project with the highest complexity level), 3D visualization prevents misunderstanding or misinterpretations and increases efficiency of coordination. It is recommended to implement 3D visualization approaches in such complex projectsOriginality/valueThere is only limited evidence on the value 3D visualizations in managing utility projects. This study contributes rich empirical evidence on this value based on a six-month observation period at a subsurface contractor. Their merit was assessed by associating 3D approaches with project complexity levels, which may help utility contractors in strategically implementing 3D applications.

Factors affecting the delivery of optimum health and safety on construction projects during the covid-19 pandemic in Zimbabwe

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Benviolent Chigara ◽  
Tirivavi Moyo
Keyword(s):  
Factor Analysis ◽  
Construction Projects ◽  
Health And Safety ◽  
Project Managers ◽  
Small Sample ◽  
Related Factors ◽  
Content Type ◽  
Factors Affecting ◽  
Related Risk ◽  
Monitoring And Enforcement

Purpose The purpose of this study was to investigate the perceptions of construction professionals relative to factors that affect the delivery of optimum health and safety (H&S) on construction projects during the COVID-19 pandemic. Design/methodology/approach The study adopted a quantitative design which entailed the distribution of a web-based questionnaire among construction professionals, namely, architects, construction/project managers, engineers, H&S managers and quantity surveyors working for contractors and construction consultants in Zimbabwe. The data were analysed with descriptive and inferential statistics. Factor analysis was used to reveal interrelated significant sets of factors affecting the delivery of optimum H&S. Findings Factor analysis revealed nine components/factors: change and innovation-related, monitoring and enforcement-related, production-related, access to information and health service-related, on-site facilities and welfare-related, risk assessment and mitigation-related, job security and funding-related, cost-related and COVID-19 risk perception-related factors as the significant factors affecting the delivery of optimum H&S during the COVID-19 pandemic in Zimbabwe. Research limitations/implications The results highlighted the need for social dialogue among construction stakeholders to support initiatives that will enhance the delivery of H&S on construction projects. Construction stakeholders may find the results useful in highlighting the areas that need improvement to protect workers’ H&S during the pandemic. However, the small sample limits the generalisability of the results to construction sectors in other regions. Originality/value The study investigated factors affecting the delivery of optimum H&S during the COVID-19 to inform interventions to enhance H&S.

Modeling and Analysis of Surface Roughness with Statistical and Soft Computing Approach

2021 ◽  
Vol 106 ◽  
pp. 109-115
Author(s):  
L.B. Abhang ◽  
M. Hameedullah
Keyword(s):  
Surface Roughness ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Prediction Models ◽  
Tool Geometry ◽  
Modeling And Analysis ◽  
Empirical Prediction ◽  
Lathe Machine ◽  
Carbide Inserts ◽  
Computing Approach

The objective of this study focuses on developing empirical prediction models using response regression analysis and fuzzy-logic. These models latter can be used to predict surface roughness according to technological variables. The values of surface roughness produced by these models are compared with experimental results. Experimental investigation has been carried out by using scientific composite factorial design on precision lathe machine with tungsten carbide inserts. Surface roughness measured at end of each experimental trial (three times), to get the effect of machining conditions and tool geometry on the surface finish values. Research showed that soft computing fuzzy logic model developed produces smaller error and has satisfactory results as compared to response regression model during machining.

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