## 1 _Editorial_  
### Reliability Techniques in Engineering Projects  
**[PERSON] 1,*(c)**, [PERSON] 2(c), [PERSON] 1(c) and [PERSON] 1(c)**  
In engineering projects, reliability is conceived as physical equipment's ability to function without failure. Thus, reliability can be described as a system's ability to operate under the design conditions for a determined period of time [1]. From the perspective of safety, reliability analyses aim to quantify the probability of system failure and its protective barriers [2]. Reliability planning [3] is required for high-quality engineering projects from the early stages of system design [4, 5]. Probabilistic design for reliability allows for a comparison of the strength of a component with the stress it will be subjected to in different environments [6]. Failures are hierarchically linked according to the system architecture, and a failure mode, in turn, may cause failures in a higher-level subsystem or be the result of a failure of a lower-level component [7]. Reliability is associated with all project lifecycle stages. Starting with the customer's requirements and specifications, installation, operation, and maintenance are critical aspects that affect the reliability of systems. Thus, no matter how well a system has been installed, maintained and operated, if it was designed with inherently low reliability, it will remain unstable until redesigned. Quality typically focuses on preventing defects during the warranty phase, while reliability is concerned with preventing failures during the lifespan of the product or system, from commissioning through operation to decommissioning [8]. Condition-based maintenance (CBM), also known as predictive maintenance, focuses on monitoring relevant parameters to empirically determine the percentage of service life that is consumed [9]. Operational reliability in engineering projects can be substantially increased by improvements in system design and the selection of more suitable parts and materials based on different reliability techniques and tools. Furthermore, some practices can improve reliability concerning manufacturing, assembly, shipping and handling, operation, maintenance and repair [10]. Before undertaking any design work, it is essential to specify the reliability and maintainability objectives of the product, i.e., a design trade-off between reliability and maintainability is necessary, since the more reliable the product, the less maintenance it needs [11, 12]. Various tools can be used to analyze the reliability of an engineering project: Markov chains [13], machine learning [14], and Cox [15], etc. [16, 17, 18]. This Special Issue of _Applied Science_ features new research and cutting-edge technologies related to reliability techniques in engineering projects. It includes research focused on: maintenance, reliability techniques, reliability prediction, design for reliability, failure modes, design for maintainability, facility and building design, the reliability-centred maintenance and improvement statistics-based approach, reliability testing, reliability modelling, maintenance 4.0, accelerated testing fail-safe design, detectability and common causes of failure, and built-in redundancy. A total of eight contributions have been published in this Special Issue of _Applied Science_. In the first contribution, [PERSON] et al. identified the performance degradation characterization parameters by analyzing the storage degradation mechanism of the aerospace electromagnetic relay (AEMR) to build a storage degradation model and analyze the AEMR failure criterion conditions and degradation characterization parameters. The margin equation is then combined with the storage degradation model, and the uncertainties of the model parameters are quantified to complete the AEMR belief reliability model. From the analysis of the model parameter uncertainty, they found that aerospace batch relay storage reliability is mainly affected by the initial release time [19].