Service quality management under risk prioritization and imprecise information: a hybrid fuzzy approach DOI
Swarup Mukherjee, Anupam De,

Supriyo Roy

et al.

The TQM Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

Purpose Conventional risk prioritization methods rely on crisp inputs but struggle with imprecise data and hesitancy, resulting in inaccurate assessments that affect service information quality performance monitoring. This study proposes a fuzzy data-driven model for under information. Design/methodology/approach Enterprise management is crucial management, ensuring effective identification, assessment mitigation of risks impacting delivery customer satisfaction. paper multi-criteria involving multiple decision-makers. It introduces hybrid method combining intuitionistic hesitant group decision-making to assess better prioritize based decision-maker preferences. Findings The proposed improves business operations by efficiently representing uncertain traditional frameworks. helps identify potential advance enhances control over operations, enabling organizations benchmark best practices. Accordingly, acquire background knowledge their quality. This, turn, management. Research limitations/implications Despite the advantages models prioritization, such as mimicking human reasoning more accurately, complexity can hinder adoption. intricate computational steps may deter shop-floor managers who prefer straightforward conventional RPN approach, which easier understand implement. However, while developing require effort, its benefits become apparent time. Once developed, be integrated into software applications, allowing decision-makers use it easily. integration simplifies computations leading informed improved long term. Practical implications robust framework integrating expertise, reliable outputs enhance strategic decisions operational efficiency. Originality/value We validate approach at an steel plant’s process, covering broad areas domain. To our knowledge, no exists existing literature attempting explore efficacy practices prime sectors like steel. study’s novelty backed this validation experiment, indicates effectiveness results obtained from multi-attribute methodology practical. model’s outcome substantially adds value current significantly affects

Language: Английский

Risk prioritization in manufacturing processes: a hybrid approach to group decision-making under hesitation DOI
Wauires Ribeiro de Magalhães, Francisco Rodrigues Lima

Benchmarking An International Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Purpose This article aims to propose a model support the assessment and prioritization of risk in manufacturing processes. Design/methodology/approach The integrates failure modes effects analysis (FMEA) criteria with evaluation procedures new hesitant fuzzy linguistic-technique for Order Preference by Similarity Ideal Solution (HFL-TOPSIS) variation. A case study evaluating wiring harness assembly process demonstrated model's applicability. sensitivity was performed verify effect variation weights assigned decision-makers (DMs). Findings mode (FM) ranking FM4 > FM9 FM17 FM2>FM8>FM12 FM16 FM19 FM11 FM3>FM18 FM15 FM13 FM10 FM14 FM7 FM1 FM5 FM6. These outcomes suggest that “stripping length less than specified” top priority among 19 FMs evaluated. Sensitivity tests DMs’ on FMs. comparison FMEA HFL-TOPSIS demonstrates greater capacity discriminate levels priority, as it identifies total compared 9 other approaches. Practical implications adoption proposed can drive substantial improvements management practices across industries, provided organization has decision-making team experienced FMEA. Therefore, this approach promotes continuous improvement operations ensures mitigation actions effectively address critical Originality/value is first accounts DMs' hesitation defining through linguistic expressions. Additionally, addresses uncertainty when assessing opinions considers multiple factors affect these prioritization.

Language: Английский

Citations

0
Risk prioritization in enterprise supply chains: application of fuzzy analytic hierarchy process DOI
Swarup Mukherjee, Anupam De,

Supriyo Roy

et al.

Business Process Management Journal, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

Purpose The study aims to develop a robust, fuzzy, data-driven ERM model that incorporates the decision-makers’ varied levels of expertise and relative importance risk factors. Design/methodology/approach presents robust multi-criteria fuzzy integrates inputs from multiple decision-makers enhance prioritization in supply chain operations. It employs triangular numbers normalize decision-maker weights uses AHP determine criteria weights. Risks are evaluated using linguistic terms, such as FMEA, followed by weighted aggregation. Finally, defuzzification generates priority for ranking risks. Findings This approach enhances user-friendliness promotes greater acceptance, making particularly suitable implementation typical steel plant settings, which may be extendable general industry with modifications parameters on “case-to-case” basis. Research limitations/implications Due its advanced calculations multi-step processes, framework’s complexity deter adoption, especially organizations unfamiliar logic. Implementation demands specialized training or software support, posing challenges smaller enterprises. Customization specific industrial contexts requires substantial resources, adoption difficult resource-constrained organizations. Practical implications proposed framework delivers more nuanced management integrating imprecise information leveraging diverse expertise. contribution broadens knowledge, within context complex, multi-tiered risks, advancing beyond traditional linear perspectives literature. Originality/value is novel terms successful validation under environment combined FMEA.

Language: Английский

Citations

0
An Analytical Risk Mitigation Framework for Steel Fabrication Supply Chains Using Fuzzy Inference and House of Risk DOI Creative Commons
Fadillah Ramadhan, Agus Mansur, Nashrullah Setiawan

et al.

Supply Chain Analytics, Journal Year: 2025, Volume and Issue: unknown, P. 100122 - 100122

Published: April 1, 2025

Language: Английский

Citations

0
Service quality management under risk prioritization and imprecise information: a hybrid fuzzy approach DOI
Swarup Mukherjee, Anupam De,

Supriyo Roy

et al.

The TQM Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

Purpose Conventional risk prioritization methods rely on crisp inputs but struggle with imprecise data and hesitancy, resulting in inaccurate assessments that affect service information quality performance monitoring. This study proposes a fuzzy data-driven model for under information. Design/methodology/approach Enterprise management is crucial management, ensuring effective identification, assessment mitigation of risks impacting delivery customer satisfaction. paper multi-criteria involving multiple decision-makers. It introduces hybrid method combining intuitionistic hesitant group decision-making to assess better prioritize based decision-maker preferences. Findings The proposed improves business operations by efficiently representing uncertain traditional frameworks. helps identify potential advance enhances control over operations, enabling organizations benchmark best practices. Accordingly, acquire background knowledge their quality. This, turn, management. Research limitations/implications Despite the advantages models prioritization, such as mimicking human reasoning more accurately, complexity can hinder adoption. intricate computational steps may deter shop-floor managers who prefer straightforward conventional RPN approach, which easier understand implement. However, while developing require effort, its benefits become apparent time. Once developed, be integrated into software applications, allowing decision-makers use it easily. integration simplifies computations leading informed improved long term. Practical implications robust framework integrating expertise, reliable outputs enhance strategic decisions operational efficiency. Originality/value We validate approach at an steel plant’s process, covering broad areas domain. To our knowledge, no exists existing literature attempting explore efficacy practices prime sectors like steel. study’s novelty backed this validation experiment, indicates effectiveness results obtained from multi-attribute methodology practical. model’s outcome substantially adds value current significantly affects

Language: Английский

Citations

1