# Failure Modes in Electricity and Telecommunication Facilities in Dwellings in Spain
###### Abstract
Notwithstanding, they did not take into account the incidence of faults reported by building owners. The widespread occurrence of faults and errors leads to economic and time deviations in construction projects that must be reduced [16]. Therefore, experience-based learning can help to minimize faults and their consequences [17]. Learning from faults is a beneficial process in engineering and business environments [18; 19] and can be leveraged to build knowledge. [PERSON] and [PERSON] [20] studied the critical factors contributing to construction fault in Yemen. They ranked 62 factors including, among others, poor construction management and frequent changes in design. [PERSON] et al. [21] conducted a questionnaire survey to evaluate the frequency of quality faults. The research revealed that quality faults are caused by defaults by workers, inadequate checking procedures, incomplete construction site surveys, inaccurate design work, fraud of construction companies, and inefficient cooperation between different departments. Other authors applied different techniques to analyze the fault mode of building components. For example, [PERSON] et al. [22] applied Markov chains to determine the most appropriate maintenance period for roofs by analyzing a comprehensive fault database. [PERSON] and [PERSON] [23] analyzed construction projects of 18 houses drawn from Dundee City Council's housing stock by applying fault mode and effects analysis (FMEA) under a Reliability Centered Maintenance (RCM) approach. A comparative analysis of condition survey, FMEA, and RCM were provided to assess the benefits of applying RCM to an existing building stock. [PERSON] et al. [24] determined the risks of structural faults by using fault mode effects and criticality analysis (FMECA) to establish a methodology for managing these faults. [PERSON] and [PERSON] [25] explored the relations between defect types and quality inspection grades of public construction projects in Taiwan using data mining and fuzzy logic. A classification of 499 defect types was created on the basis of 17,648 defects from a sample of 990 construction projects. [PERSON] et al. [26] conducted a fault detection analysis using data mining techniques for a set of smart office buildings using pattern recognition techniques together with outlier detection methods. This paper studies the faults in electricity and telecommunications installations in dwellings based on complaints registered by their owners. No papers dealing with faults of these two domestic installations has been found after reviewing the international scientific references. Related investigations are focused on analyzing surveys and not events that have taken place. This fact makes this research a novelty in the field of forensic engineering. This research aims to shed light on the most common faults in the electrical and telecommunications installations of dwellings that lead to owners filing court action and then reducing the costs due to these processes. However, research into construction faults usually analyses buildings that are dependent on each other (i.e., they belong to the same construction company or developer), which can lead to somewhat biased results. In our case, no parameter can link one work with another, ensuring independence. The aim of this work is to identify the most common incidences in electricity and telecommunications facilities and to propose a methodology to identify the weak points in the building process that lead to user dissatisfaction, non-quality costs, complaints, and judicial filings during a building's service life. The results obtained from this research contribute to improving the quality of construction. Knowing the typology and probability of occurrence of this type of fault allows professionals in the sector to be aware of the most recurrent faults and to solve and/or prevent them at the design stage. Additionally, government decision-makers will be able to adapt legislation to avoid the most frequent faults.