PLC failure program analysis and countermeasure research

The reliability of Programmable Logic Controller (PLC) systems is critical for the safe and efficient operation of oil and gas pipelines. These systems, which control various components such as valve houses, station and yard technology, oil pump control, and fire gas systems, face significant challenges due to the gradual accumulation of failure programs over time and through system updates. This paper investigates the causes of PLC failure programs, emphasizing their hidden nature and the resulting system overcrowding, resource consumption, decreased operational efficiency, and potential risks to safety and reliability. Drawing on a decade of practical experience in failure prevention, the study analyzed data from 8720 points across different control components. The proposed measures, which include enhancing management systems, standardizing workflows, and improving personnel competencies, resulted in significant reductions in failure rates: 25% for valve house switching values, 30% for station and yard technology switching values, 20% for analog quantities, 28% for oil pump control switching values, 22% for analog quantities, and 18% for fire gas systems. Overall, these measures led to a 26% average reduction in system overcrowding and a 22% increase in operational efficiency. The study highlights the importance of systematic management and continuous improvement in maintaining the reliability of PLC systems, providing a framework for enhancing the stability and safety of national oil and gas pipeline networks.

Authors

Institutions

Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1117/12.3055464
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PLC failure program analysis and countermeasure research

Pan Wang
Risk and Safety Analysis
article

PLC failure program analysis and countermeasure research

Pan Wang
article en

Abstract

The reliability of Programmable Logic Controller (PLC) systems is critical for the safe and efficient operation of oil and gas pipelines. These systems, which control various components such as valve houses, station and yard technology, oil pump control, and fire gas systems, face significant challenges due to the gradual accumulation of failure programs over time and through system updates. This paper investigates the causes of PLC failure programs, emphasizing their hidden nature and the resulting system overcrowding, resource consumption, decreased operational efficiency, and potential risks to safety and reliability. Drawing on a decade of practical experience in failure prevention, the study analyzed data from 8720 points across different control components. The proposed measures, which include enhancing management systems, standardizing workflows, and improving personnel competencies, resulted in significant reductions in failure rates: 25% for valve house switching values, 30% for station and yard technology switching values, 20% for analog quantities, 28% for oil pump control switching values, 22% for analog quantities, and 18% for fire gas systems. Overall, these measures led to a 26% average reduction in system overcrowding and a 22% increase in operational efficiency. The study highlights the importance of systematic management and continuous improvement in maintaining the reliability of PLC systems, providing a framework for enhancing the stability and safety of national oil and gas pipeline networks.

Oil and Gas Center (CN)
Openalex Percentile: Top 77%
Risk and Safety Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.