Reasoning Mechanism for Construction Nonconformance Root-Cause Analysis

Battikha, Mireille

doi:10.1061/(asce)0733-9364(2008)134:4(280)

Cited by 22 publications

(21 citation statements)

References 10 publications

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“…In fact, non-conformance occurs when the finished state of a project and/or its components deviate from established requirements, and decisions must be made regarding acceptance and/or rectification (Battikha, 2008). However, Watt (1999) considers that "defect is the term used to define a failing or shortcoming in the function, performance, statutory or user requirements of a building, and might manifest itself within the structure, fabric, services or other facilities of the affected building".…”

Section: Rework In Constructionmentioning

confidence: 99%

Factors Affecting Rework Costs in Construction

Forcada

Gangolells

Casals

et al. 2017

J. Constr. Eng. Manage.

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Rework adversely impacts the performance of building projects. In this study, data were analyzed from 788 construction incidents in 40 Spanish building projects to determine the influence of project and managerial characteristics on rework costs. Finally, regression analysis was used to understand the relationship between the contributing factors, and to determine a model for rework prediction.Interestingly, the rework prediction model showed that only the original contract value (OCV) and the project location in relation to the company's headquarters contribute to the regression model. The Project type, the Type of organization, the Type of contract and the original contract duration (OCD) which represents the magnitude and complexity of a project, were represented by the OCV. This model for rework prediction based on original project conditions enables strategies to be put in place prior to the start of construction, to minimize uncertainties and reduce the impact on project cost and schedule, and thus improve productivity.

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Section: Rework In Constructionmentioning

confidence: 99%

Factors Affecting Rework Costs in Construction

Forcada

Gangolells

Casals

et al. 2017

J. Constr. Eng. Manage.

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“…Moreover, though several authors have empirically determined the significance of the effect of quality management practices on quality performance [47][48][49][50][51], other ones have reasoned on the indirect path through which such effect is accomplished [43,46,52,53]. The approach reported in this paper follows the reasoning mechanism proposed by Battikha [53] to identify and analyze the root causes of nonconformities. In this case, parting from the information usually found in quality management information systems, it is acknowledged that disruptions occurring during the execution of construction activities are caused by nonconformities in the management system implemented for attaining quality performance in construction projects.…”

Section: Modeling the Effect Of Pqm On Productivitymentioning

confidence: 99%

“…This path assumes that, depending on the performance of PQM practices, nonconformance events may occur during the execution of the project, which eventually may cause disruptions that will affect productivity in construction activities. Following Battikha's [53] approach to simplify the identification of patterns indicating the occurrence of nonconformance during project execution, this modeling approach also classifies nonconformance according to the process requirements with which they are related; for instance, as illustrated in Figure 1, delayed deliveries and inaccurate and out-of-specification deliveries are nonconformance events related to material supply.…”

Section: Modeling the Effect Of Pqm On Productivitymentioning

confidence: 99%

“…Therefore, it makes sense to group them into categories representing the nature of a given number of nonconformance events. As said before, the proposed model has adopted Battikha's [53] approach to integrate different types of nonconformance into categories depicting requirements to accomplish activities in a given project. For instance, as illustrated in Figure 1, some of these requirements include material supply, equipment, design information, and supervision.…”

Section: Nonconformance Events Causing Disruptionsmentioning

confidence: 99%

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

Corona-Suárez

AbouRizk

Karapetrović

2014

Journal of Quality and Reliability Engineering

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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.

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“…Soibelman and Kim (2002) and Kim, Soibelman, and Grobler (2008) use Knowledge Discovery in Databases (KDD), a data analysis process, to identify main factors of construction delays using statistical measurements and a decision tree based machine learning algorithm. Other methods like regression models (Lucko and Mitchell 2010), pattern analysis (Battikha 2008), and automatic hierarchical classification method (Caldas and Soibelman 2003) have also been used to mine construction project documents with the goal of identifying improved management strategies.…”

Section: Introductionmentioning

confidence: 99%

Construction schedule simulation for improved project planning: Activity criticality index assessment

Tang¹,

Mukherjee

Onder

2013

2013 Winter Simulations Conference (WSC)

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The objective of this paper is to illustrate the application of construction schedule simulation during the planning phase of a construction project. Schedule simulations can be used to develop risk informed schedules that support improved contingency planning. This paper discusses the challenges underlying construction schedule simulation, and how they can be addressed by an interactive simulation platform such as the Interactive Construction Decision-Making Aid (ICDMA). Further, the paper uses ICDMA during the planning process, for a case study, to identify the activities in a project that are most likely to change criticality during the construction process. Current scheduling techniques such as the Critical Path Method (CPM) are capable of identifying critical activities, but they cannot be used to assess the likelihood of alternative critical paths emerging during construction due to unexpected disruptions in the as-planned schedule. The research illustrates the usefulness of construction simulation in supporting the scheduling process.

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Reasoning Mechanism for Construction Nonconformance Root-Cause Analysis

Cited by 22 publications

References 10 publications

Factors Affecting Rework Costs in Construction

Factors Affecting Rework Costs in Construction

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

Construction schedule simulation for improved project planning: Activity criticality index assessment

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