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Exploring the nature of nonconformities : the development of a procedure that classifies construction project nonconformities into risks and non-risks

Wit, M.J.G. de (2014) Exploring the nature of nonconformities : the development of a procedure that classifies construction project nonconformities into risks and non-risks.

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Abstract:During construction projects, many nonconformities occur. A nonconformity is a non-compliance of a requirement. Often rework is necessary to correct the nonconformity and ensure that is complied with the requirements. Therefore, these nonconformities increase the costs of construction projects and thus construction contractors often strive to eliminate them. This research was conducted at one of these contractors: BAM Infra. Two problems were identified at contractor BAM. First, BAM developed a risk database in which risk data of finished construction projects is collected to be used as input for future projects. However, risk data of unidentified occurred risks is not included in this database and BAM does not know what unidentified risks occur. Second, BAM strives to eliminate their nonconformities, in order to eliminate nonconformities, insight in the nature of nonconformities is necessary and BAM does not have this insight. While combining both problems, classifying nonconformities into risks and non-risks can contribute to a solution of both problems. It can provide insight into the nature of nonconformities and the nonconformities that are classified as risk can be unidentified risks and included in the database. Therefore, in this research a procedure is developed that determines in a few simple steps whether a nonconformity is a risk or not. The main question of this research is hence: What procedure can be developed in order to classify nonconformities into risk and non-risk? This procedure can be used by many contractors to obtain insight in the nature of nonconformities. Moreover, it can be used by contractors to identify unidentified occurred risks. These risks can be included in a database to be used as input at future projects. In addition, this research contributes to the gap in literature by a new approach to classify nonconformities with a risk management perspective. Method First, a theoretical procedure was developed using the results of a literature study. This procedure was empirically tested on samples of documented construction project nonconformities. The insights obtained during these tests were used to adjust the procedure, resulting in an empirically tested procedure. This procedure was tested on the nonconformities of four construction projects. Two types of tests were performed, reliability and validity tests. The reliability tests were performed to obtain insight in whether the procedure provides comparable results when performed by two persons of the same nonconformities. The unreliability is considered to be high if the percentage of disagreement is higher than 15%. The reliability tests were performed on a sample of 100 nonconformities of two projects. During the validity tests all documented nonconformities of three projects were analysed, the results were used to obtain the validity of the procedure and determine the results of the procedure. The validity shows whether the results of the procedure are the expected results. Moreover, these tests were used to obtain the results of the procedure. The procedure The procedure consists of three main steps, which are divided into sub-steps. Figure 1 shows an overview of the procedure and appendix 1 shows the final procedure. The first step determines if a nonconformity is a risk or not and consists of four simple questions that need to be answered for each nonconformity. The second step selects the nonconformities that are risks and concludes if these risks were identified. The third and last step answers the question why the unidentified risks were not-identified in advance. This data can be used to improve the risk identification of future projects. The nonconformities that are non-risks can be managed by improving standard processes, while the nonconformities that are risks can be approached through risk management. Risk Non-risk Identified risk Unidentified risk Reasons for non-identification Risk management Improving standard processes Step 1 Step 2 Step 3 Figure 1 Overview procedure Testing the procedure The reliability results of the second project show an unreliability of the sub-steps of step one between 10% and 34%. When looking at the validity, the nonconformities that are risks are both identified and unidentified risks. The results of the three analysed projects show that the nonconformities that are not risks are on average 85% of the total impact. Eliminating these nonconformities that are no risks can lower the costs of projects by 1,2%. A total amount of 32 unidentified risks were identified out of 2116 nonconformities, of these risks the reasons for non-identification show no patterns. Conclusions and recommendations It can be concluded that the reliability of the procedure is low, the unreliability is higher than 15% for some of the steps. The unreliability can be explained by the low quality of the data that was used as input. The documented information did not contain clear information of the nonconformities, leaving space for interpretation. If the procedure is implemented, it is recommended to perform the first step of the procedure during the project directly after nonconformity occurred. Additional information is then available, by the responsible person. In contrast, the validity is sufficient. The risks are in fact risks. However, it was not validated whether the non-risks are in fact non-risks. Further research can be performed to test this. The results provide insight into the nature of nonconformities and the nonconformities that are risks can be included in a risk database. Because relatively few unidentified risks were identified it is recommended to perform the procedure at more and different types of projects. For BAM it is recommended to focus on the improvement of standard processes, since the category with the highest impact are these risks. Thus, the developed procedure classifies nonconformities into risks and non-risks. It can be used to provide insight into the nature of nonconformities. It also identifies unidentified risks that can be included in a database. It provides a new approach of classifying nonconformities. In order to successfully implement the procedure within the organisation, it is recommended for BAM to improve the way nonconformities are documented. It was determined during the research that nonconformities were not always documented completely; this could have affected the results of the results. The improvements should therefore result in clear unambiguous descriptions of nonconformities.
Item Type:Essay (Master)
Clients:
BAM Infraconsult, Gouda, the Netherlands
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering and Management MSc (60026)
Link to this item:http://purl.utwente.nl/essays/66452
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