{'fraction_non_alphanumeric': 0.02192448233861145, 'fraction_numerical': 0.0, 'mean_word_length': 4.748251748251748, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Root Cause Analysis of Process Faults Using Alarm Data

Alarm system is a vital component of industrial complexes and process plants. Once a fault occurs in a plant, some variables exceed their predetermined limits, which will trigger an alarm. However, because of immense interconnection between process variables, a fault might cause many alarms. This makes the task of finding the root cause fault difficult. One approach to find the root cause is to analyze time-trend of process data. This approach, however, is time and resource consuming and requires advanced infrastructure. In this paper, first the root cause analysis methods are reviewed. Then a technique is proposed to identify the root cause of a fault using alarm data only. The method is applied on the Tennessee Eastman process as a well-known benchmark.