Multi-criterion analysis based on integrated process-risk optimization

Derradji, Rima; Hamzi, Rachida

doi:10.1108/jedt-08-2019-0201

Cited by 6 publications

(6 citation statements)

References 20 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, the authors of [36] presented a fuzzy multi-criteria decision approach in the selection of a sustainable risk management strategy. Similarly, [37] used a multicriteria assessment system when choosing the method of operational risk management, and [38] performed a multi-criterion analysis based on integrated process-risk optimization. The sum of the partial orders 9 14…”

Section: Complex Evaluation Of Investment Variantsmentioning

confidence: 99%

Optimization of the Automated Production Process Using Software Simulation Tools

2023

View full text Add to dashboard Cite

The purpose of this article is to point out the need to use software simulation tools in industrial practice to optimize the production process and assess the economic effectiveness of investment, including risk. The goal of the research is to find an optimal investment variant to ensure an increase in the production volume of at least 50% and to achieve the maximum economic efficiency of the investment, even considering the risk. The article presents a comprehensive approach that enables the achievement of the set research goal. The selection of the optimal version of the investment is carried out in three steps. Firstly, the versions of the investment variants are assessed from the production point of view using the program Tecnomatix Plant Simulation. Subsequently, the versions of the investment variants are assessed from an economic point of view and from a risk point of view. Economic efficiency is assessed using the financial criteria net present value (NPV), profitability index (PI), and discounted payback period (DPP), and risk analysis is carried out using Monte Carlo simulations. Finally, the accepted outputs are evaluated overall using a multi-criteria method, namely the method of partial order.

show abstract

Section: Complex Evaluation Of Investment Variantsmentioning

confidence: 99%

Optimization of the Automated Production Process Using Software Simulation Tools

2023

View full text Add to dashboard Cite

show abstract

“…The current crisis in the market environment has forced businesses to operate more agilely to develop the necessary knowledge and skills and acquire the skills required in financial and investment decision-making. Day and Schoemaker (2019) and other authors (Fabianova, 2019;Ključnikov, 2022;Oulehlova, 2021;Derradji, 2020) emphasize three dynamic capabilities for managing uncertainty and risk: perceiving change earlier than competitors, taking advantage of opportunities more effectively and transforming the business as needed.…”

Section: Entrepreneurship and Sustainability Issuesmentioning

confidence: 99%

Risk factors' prediction model for the investment evaluation

Tobisova,

Seňová,

Rozenberg

2023

JESI

View full text Add to dashboard Cite

The article deals with the issue of increasing the competitiveness of enterprises and their long-term sustainability based on the efficiency of investment processes. Implementing new approaches to the company's decision-making processes will allow companies to overcome the pitfalls of the market environment created by the post-COVID period and the current energy crisis that has affected the world markets after the conflict between Ukraine and Russia. The article aims to verify the application of the methodology for increasing the competitiveness of enterprises based on the use of a model creating a fusion of traditional and sophisticated tools. The analyses carried out are based on the investment decisions of a real company operating in the Slovak Republic's territory in the production and supply of security products. Mathematical modelling and Monte Carlo simulation are based on the company's accounting and operational financial outputs (profit and loss statement, balance sheet). The methodology is based on mathematical modelling through static traditional financial approaches and their verification through sensitivity analysis, regression analysis and Monte Carlo simulation based on distributional distributions of risk factors. The output is the assessment of risk factors and their significance for the criterion value Net Present Value (NPV).

show abstract

“…2. Conventional failure mode effect and criticality analysis method for criticality evaluation In FMECA, the RPN is acquired by multiplication of three inputs, frequency of occurrence (F), severity and non-detection, as follows (Derradji and Hamzi, 2020):…”

Section: New Criticality Assessmentmentioning

confidence: 99%

“…In FMECA, the RPN is acquired by multiplication of three inputs, frequency of occurrence (F), severity and non-detection, as follows (Derradji and Hamzi, 2020): …”

Section: Conventional Failure Mode Effect and Criticality Analysis Me...mentioning

confidence: 99%

Failure mode, effects and criticality analysis improvement by using new criticality assessment and prioritization based approach

Chakhrit

Chennoufi

2021

JEDT

View full text Add to dashboard Cite

Purpose This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios. Design/methodology/approach To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method. Findings This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method. Originality/value This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.

show abstract

Multi-criterion analysis based on integrated process-risk optimization

Cited by 6 publications

References 20 publications

Optimization of the Automated Production Process Using Software Simulation Tools

Optimization of the Automated Production Process Using Software Simulation Tools

Risk factors' prediction model for the investment evaluation

Failure mode, effects and criticality analysis improvement by using new criticality assessment and prioritization based approach

Contact Info

Product

Resources

About