Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey

Abstract

Predictive Maintenance 4.0 (PdM 4.0) showed a highly positive impact on chilled water system (CWS) maintenance. This research followed the recommendations of a systematic literature review (SLR), which was performed on PdM 4.0 applications for CWS at commercial buildings. Per the SLR, and to start making an excellent PdM 4.0 program, the faults and their frequencies must be identified. Therefore, this research constructed an industry survey, which went through a pilot study, and then shared it with 761 maintenance officers in different commercial buildings. The first goal of this survey is to verify the faults reported by SLR, explore more faults, and suggest a managerial solution for each fault. The second goal is to determine the minimum and maximum frequencies of faults occurrence, while the third goal is to verify selected operational parameters, in which their data can be used in smart buildings applications. A total of 304 responses are considered in this study, which identified additional faults and provided faults solutions for all CWS components. Based on the survey outcomes, justifiable frequencies are proposed, which can be used in creating the dataset of any machine learning model, and then to control the CWS performance.

Analysis of the Effect of Fabrication Failure Factors and Operational Failure Factors on Equipment Reliability Mediated by Maintenance Technology 4.0 with the Use of SEM (Structural Equation Modelling) Methods (Case Study of Genset Products at PT. XYZ)

“…Furthermore, H4 is accepted where operational damage factors directly influence the implementation activities of Maintenance Technology 4.0. This finding aligns with Almobarek et al (2022) and Jasiulewicz et al (2020). Then, H5 is accepted or not rejected, where equipment reliability in the field is significantly influenced directly by the application of Maintenance Technology 4.0, which aligns with research conducted (Jasiulewics et al, 2020).…”

Practical Applications of Model Predictive Control and Other Advanced Control Methods in the Built Environment: An Overview of the Special Issue

“…Almobarek et al [10] conducted an industry survey to complement the aforementioned systematic review outputs [9]. This survey targets the identification and frequencies of more operational faults and fault solutions for chilled water systems.…”

“…Ongoing efforts to improve models for indoor air temperature [3] and building energy loads [4] are and will remain essential to strengthening confidence in data-driven solutions. These solutions could be applied at various scales [1], from setpoint tracking [5] to the adjustment of building indoor conditions [6] and the optimization of heating and cooling system operations [6][7][8]10,11], with different levels of complexity, such as model-based controls [6,8], predictive control [7], and predictive maintenance [10,11].…”

Asset maintenance in Australian commercial buildings

“…When well-maintained buildings undergo refurbishment or repurposing projects, their asset values usually increase. Periodic upkeep and strategic upgrades improve an asset's marketplace appeal, drawing in new tenants and possibly raising property value (Almobarek et al, 2022). The relationship between regular consumption, renovation, and adaptive reuse highlights the potential financial gains from revitalisation initiatives.…”