Risk analysis for clean and sustainable production in a urea fertilizer industry

Abstract

Purpose The purpose of this paper is to develop a fuzzy methodology approaches based framework for carrying the risk analysis of a real industrial system of a urea fertilizer industry located in northern part of India. Design/methodology/approach Petri Net approach was applied for representing the series-parallel arrangement of the considered system. Various failure causes related to different subsystems or equipment of the considered system were listed under FMEA approach and their Risk Priority Number was tabulated. Further, to overcome the drawbacks of traditional FMEA approach in risk ranking fuzzy FMEA and grey relation analysis (GRA) approaches were applied within traditional FMEA approach and the ranking results were compared for better and effective decision making of risky components. Findings The proposed framework has overcome the drawbacks of tradition FMEA approach in an effective and efficient manner. Causes AC7, CL3, ST2, DR3 and NR3 of centrifugal compressor, hot heat exchanger, ammonia convertor reactor, cold condenser and ammonia separator have been identified as the most critical failure causes of the considered system. Originality/value The proposed framework has been tested with its application on an ammonia synthesis system of the considered process industry. The risk ranking results would be highly useful in developing a planned maintenance policy for the considered system which further results in improving the system availability.

Information Security Risk Management of Research Information Systems: A hybrid approach of Fuzzy FMEA, AHP, TOPSIS and Shannon Entropy

“…Implementation of risk management systems based on FMEA is experienced in manufacturing and projected systems in previous studies (Wu et al, 2015;Panchal, 2018).On the other hand risk assessment in information systems recently is a state of the artwork (Aldini et al, 2017;De Gusamu et al, 2016). Also considering wellapplied approaches in risk assessment such as FMEA in information systems are rarely studied.…”

“…Information security management has undertaken the task of implementing and monitoring the organization's security system which finally must try to keep the system always up to date (Panchal et al 2018). The purpose of information security management in an organization is to preserve capital in the face of any threat and to achieve this goal required a comprehensive and integrated program.…”

Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement—Intuitionistic Fuzzy Sets and Genetic Algorithm Approach

“…The development of theories of mathematics, such as the theory of fuzzy sets [13], has enabled these linguistic terms to be presented quantitatively in a sufficiently good way. In the literature, there are a large number of papers in which the relative importance of RFs and its values are modeled by: (i) type 1 fuzzy sets [26][27][28], (ii) the interval type 2 fuzzy numbers [10,29,30], and (iii) intuitionistic fuzzy sets [31][32][33]. The intuitionistic fuzzy set using two characteristic membership functions expressing the degree of membership and the degree of non-membership of elements of the universal set.…”

Total risk evaluation framework

“…In addition, the authors emphasize a remarkable shift toward integrated methods for ranking failure modes when aiming at accurate risk evaluation. For instance, fuzzy evidential reasoning is integrated with grey theory (Chang et al, 1999;Liu et al, 2011), fuzzy TOPSIS (technique for order preference by similarity to ideal solution) with fuzzy AHP (Kutlu and Ekmekçio glu, 2012) and VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) or EDAS (evaluation based on distance from average solution) (Panchal et al, 2019c) with fuzzy logic Panchal et al, 2019b;Panchal and Srivastava, 2019) and grey techniques (Panchal and Kumar, 2016;Panchal et al, 2018b;Panchal and Srivastava, 2019). There is a trend toward using more than one method to enhance the efficacy and empirical validity of risk evaluation results (Liu et al, 2013).…”