Natural Language Processing Model for Managing Maintenance Requests in Buildings

Abstract

In recent years, facility management (FM) has adopted many computer technology solutions for building maintenance, such as building information modelling (BIM) and computerized maintenance management systems (CMMS). However, maintenance requests management in buildings remains a manual and a time-consuming process that depends on human management. In this paper, a machine-learning algorithm based on natural language processing (NLP) is proposed to classify maintenance requests. This algorithm aims to assist the FM teams in managing day-to-day maintenance activities. A healthcare facility is addressed as a case study in this work. Ten-year maintenance records from the facility contributed to the design and development of the algorithm. Multiple NLP methods were used in this study, and the results reveal that the NLP model can classify work requests with an average accuracy of 78%. Furthermore, NLP methods have proven to be effective for managing unstructured text data.

Predictive Maintenance in Building Facilities: A Machine Learning-Based Approach

“…Long short-term memory is a variant of the artificial recurrent neural network (RNN) architecture, which is a type of artificial neural network designed to process sequential data as time series data and text and speech data [ 44 ]. LSTM and RNNs in general are capable of capturing long-term dependencies in a sequence.…”

“…This means they can capture information about the past of the sequence. Thanks to this characteristic, LSTM are widely used in multiple applications including natural language processing applications [ 44 ], forecasting time series [ 35 ], and anomaly detection [ 30 , 45 ].…”

“…Furthermore, autoencoders are flexible methods that require less hand engineering work and can be adapted to several applications. Moreover, the choice of LSTM layers is justified because they are designed to process sequential data such as time-series [ 44 ], which is the case of the majority of the installations monitoring data (temperature, vibration, and energy consumption, etc.).…”

Application of Building Information Modelling (BIM) in the Health Monitoring and Maintenance Process: A Systematic Review

“…Many studies focused on healthcare facility management with some technologies such as AR or using 2D plans for creating BIM models and energy simulation which needs more examination related to modeling curved surfaces and envelope geometry [ 88 , 89 , 90 , 91 , 92 , 93 ]. Recently, the purpose of time-saving during the FM process for healthcare facilities, attracted scientists to utilize an algorithm through Natural Language Processing (NLP) to reduce human management problems [ 94 ].…”

“…The future agenda in this category consists of improving the plug-in for using with different components models [ 129 ], reducing the impacts of environment on facility maintenance process [ 82 ], improve the PIM through using maintenance information of technical components [ 68 ], using various approaches to gather and share data for increasing automation among processes [ 83 ], considering the capacities of VR environment for reviewing designs [ 104 ], control energy conservation for mechanical, electrical, and plumbing systems [ 128 ], integrating BIM and VR technologies for controlling distance and time among sites [ 86 ], facility management with historical and current data of sensor technologies for controlling energy consumption [ 75 ], conducting various dataset to test NLP for FM [ 94 ].…”