Asset Operation Detection Based on Fuzzy Logic and Phase Portrait

This article proposes a novel asset operation detection (AOD) solution by applying the fuzzy logic reasoning concept to the phase portraits (PPs) of time series data. Around the benefits of business insight and climate impact, we firstly provide relevant context to highlight the importance of asset operation features and necessity for efficient operation detection algorithms in the facility management industry. Then we will review several existing approaches for detecting asset operations and discuss their advantages and disadvantages. With these concerns in mind, we come to the operation detection solution proposed in this research, explaining the technical idea and mentioning two approaches regarding the algorithm inputs: physical phases and derivative phases. All the proposed analysis will be based on a real-case industrial dishwasher. Finally, we will come back to the benefits in terms of business insight and climate impact to showcase the application of detected operational features.