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The agreed-upon operational contingency cost is a key element of maintenance contracts, especially for the Natural Gas Reduction and Metering Stations. Disputes, claims, and failure to fulfil contractual obligations often stem from poor estimation of the risks associated with contingency costs. Currently, there are no standard rules or methods for companies to estimate these costs. As a result, some practices rely on rough estimates as a percentage of the total contract value without conducting any risk analysis. Others base their estimates on opinions from subject matter experts. This paper addresses the issue of improper contingency cost estimation by: 1) identifying the most influential factors affecting the value of maintenance contracts in the natural gas sector, and 2) developing a fuzzy logic risk analysis model to predict contingency costs based on the specific circumstances of contract signing. The effectiveness of this approach was validated through a real case study of an existing natural gas maintenance contract in Egypt. The results revealed that the most impactful factors were economic, contractual, operational, construction, and regulatory risks, while market and legal risks had the least impact. In addition, the findings show that the proposed model predicts the contingency cost with nearly 94.69% accuracy.

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