Development of computational tools for criticality analysis of process systems, utilizing Industrial IOTs
T. Theodosiadis-Thomaidis(1), G. Panagopoulou(2) and S. Pistikopoulos(3)
1. Future Technology Systems sa, Greece
2. Pangaea R&D IKE, Greece
3. Chemical Engineering, Director, Texas A&M Energy Institute, Texas
keywords: Computational algorithm; Effective Risk Assessment; Fault Trees, FMEA; Directed Functional AND/OR Logic Digraphs; NASA’s Fault-Tree Diagnosis System FTDS; Flexibility; Reliability; Criticality; Process Systems; Predictive Maintenance; Industrial-IoTs
Traditional sensitivity analysis based on reliability models, such as logic-tree or fault-tree analysis, together with existing FMEA techniques, are powerful and well established methods for the identification of critical parts of equipment / events affecting the system functionality and safety.
However, they share a common limitation since they do not explicitly take into account process models and process interactions; this may overestimate the real system efficiency and provide misleading information regarding rating critical components or events. PANGAEA R&D presents a uniform framework, computational tools and algorithms for criticality analysis of process systems, which embodies:
–system logic via Directed Functional Logic Digraphs – DFLD/ Fault-Tree Diagnosis System FTDS,
–explicit process and safety models, equipment reliability data and occurrence probabilities of external events/utilizing sets of data collected via Industrial IoTs.
The criticality analysis framework is used as a guide for improvements towards safer and more efficient systems design and/or condition-based maintenance activities whereas the proposed computational toolset is based considering process and equipment interactions, equipment failure, stochastic process variations and external events related to process operations and safety.
Important extensions are also presented for the use of such criticality analysis tools for safety and maintenance considerations.
A module for rating all the equipment, operations and events according to the associated criticality index is utilized, coupled with a condition based maintenance framework for enhancing overall system efficiency and safety.
The computational tools and the algorithms are demonstrated via case studies. The developed software and methodology utilizes valuable sets of information yielding from dedicated Industrial-IoTs in order to rank the criticality importance of the parts / subsystems / systems / events and then to propose a maintenance / safety policy which fulfills certain efficiency and safety targets.
Criticality Analysis of Process Systems
The objective of the criticality analysis module is to identify the relative importance of equipment (un)availability (or other external events affecting the process operations) over a time horizon by taking into account process interactions, reliability models, parameter variations and operational characteristics of a process system.
Criticality analysis comprises:
• Size reduction of the system state space,
• Translation of process flow-sheet into DFLD(automatic generation of fault-trees/n-order cut sets);
• Estimation of state probabilities as a function of time and system’s efficiency; Estimation of a system criticality index as a function of time;
• Estimation of a combined flexibility-reliability-criticality index for each part of equipment or event;
• Criticality based maintenance scenarios.