Engineering systems must function effectively whilst maintaining reliability in service. Predicting maintenance costs and asset availability raises varying degrees of uncertainty from multiple sources. Previous reviews in this domain have assessed cost uncertainty and estimation for the entire life cycle. This paper presents a systematic review to investigate existing methodologies and challenges in uncertainty quantification, aggregation and forecasting for modern engineering systems through their in-service life. Approaches to forecast uncertainty here are hindered chiefly by data quality of available data, experience and knowledge. A total of 107 papers were analysed to answer three research questions based on the scope, through which two core research gaps were identified. An integrated combination of identified approaches will enhance rigour in uncertainty assessment and forecasting. This review contributes a systematic identification and assessment of current practices in uncertainty quantification and scientific methodologies to quantify, aggregate and forecast quantitative and qualitative uncertainties to better understand their impact on cost and availability to aid decision making throughout the in-service phase.

工程系统必须有效运行，同时保持服务可靠性。预测维护成本和资产可用性会从多个方面提高不同程度的不确定性。该领域的先前评论已经评估了整个生命周期的成本不确定性和估计。本文提供了系统的综述，以研究现代工程系统在使用寿命中不确定性量化，汇总和预测方面的现有方法和挑战。此处预测不确定性的方法主要受到可用数据，经验和知识的数据质量的阻碍。共对107篇论文进行了分析，根据范围回答了三个研究问题，从而确定了两个核心研究空白。已识别方法的综合组合将提高不确定性评估和预测的严格性。此项审查有助于系统地识别和评估不确定性量化和科学方法中的当前实践，以量化，汇总和预测定量和定性不确定性，以更好地了解其对成本和可用性的影响，从而有助于整个服务阶段的决策。