scholarly journals On the optimization of maintenance storage cost in industry a fuzzy logic application

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jean Khalil ◽  
Ashraf W. Labib
Keyword(s):  
Fuzzy Logic ◽  
Positive Impact ◽  
Spare Parts ◽  
Batch Size ◽  
Content Type ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Industrial Maintenance ◽  
Chronic Problem ◽  
Limited Sensitivity

PurposeThe purpose of this paper is to construct a fuzzy logic model that acts as a decision support system to minimize inventory-related costs in the field of industrial maintenance. Achieving a balance between the unavailability and over-storage of spare parts is a problem with potentially significant consequences. That significance increases proportionally with the ever-increasing challenge of reducing overall cost. Either scenario can result in substantial financial losses because of the interruption of production or the costs of tied-up capital, also called the “solidification of capital.” Moreover, there is that additional problem of the expiry of parts on the shelf.Design/methodology/approachThe proposed approach relies on inputs from experts with consideration for incompleteness and inaccuracy. Two levels of decision are considered simultaneously. The first is whether a part should be stored or ordered when needed. The second involves comparing suppliers with their batch-size offers based on user-determined criteria. A mathematical model is developed in parallel for validation.FindingsThe results indicate that the fuzzy logic approach is accurate and satisfactory for this application and that it is advantageous because of its limited sensitivity to the inaccuracy and/or incompleteness of data. In addition, the approach is practical because it requires minimal user effort.Originality/valueTo the best of the authors’ knowledge, the exploitation of fuzzy-logic altogether with limited sensitivity experts' inputs were never combined for the solution of this particular problem; however, this approach's positive impact is expected to be highly significant in solving a chronic problem in industry.

scholarly journals Supply chain risk assessment approach for process quality risks

2017 ◽  
Vol 34 (7) ◽  
pp. 940-954 ◽  
Author(s):  
Abhijeet Ghadge ◽  
Xie Fang ◽  
Samir Dani ◽  
Jiju Antony
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Supply Chain ◽  
Failure Modes ◽  
Design Stage ◽  
Security Risks ◽  
Content Type ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Purpose The purpose of this paper is to proactively analyse and mitigate the root causes of the product and security risks. The case study approach examines the effectiveness of the fuzzy logic approach for assessing the product and process-related failure modes within global supply chain context. Design/methodology/approach The case study of a Printed Circuit Board Company in China is used as a platform for conducting the research. Using data triangulation, the data are collected and analyzed through interviews, questionnaires, expert opinions and quantitative modelling for some interesting insights. Findings Fuzzy logic approach for failure mode and effect analysis (FMEA) provides a structured approach for understanding complex behaviour of failure modes and their associated risks for products and processes. Today’s managers should conduct robust risk assessment during the design stage to avoid product safety and security risks such as recalls. Research limitations/implications The research is based on the single case study and multiple cases from different industry sectors may provide some additional insights. Originality/value The study attempts to mitigate the root causes of product and processes using fuzzy approach to FMEA in supply chain network.

Evaluation of agility in supply chains: a case study of an Indian manufacturing organization

2017 ◽  
Vol 28 (2) ◽  
pp. 212-231 ◽  
Author(s):  
Bharat Singh Patel ◽  
Cherian Samuel ◽  
S.K. Sharma
Keyword(s):  
Fuzzy Logic ◽  
Supply Chain ◽  
Human Perception ◽  
North India ◽  
Scoring Method ◽  
Content Type ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Manufacturing Organization

Purpose The purpose of this paper is to report a case study carried out to assess the agility and identify obstacles to agility in a supply chain. A human perception-based framework is used for the calculation of agility. The case study was carried out in a North India-based manufacturing organization. Design/methodology/approach In this study, the concept of a multi-grade fuzzy logic approach is used. Using this concept, the overall agility index has been determined. The fuzzy logic approach has been used to overcome the disadvantages such as impreciseness and vagueness using a scoring method. Findings From the analysis, it is observed that the organization on which the study was performed is “very agile.” After evaluating the agility level, the fuzzy performance importance index is calculated, which helps to identify the barriers of agility in the supply chain. These barriers help decision makers to implement appropriate improvement measures for improving agility level. Overall, 11 barriers were identified in the study. Research limitations/implications Managers of the contemporary manufacturing organization have to measure the agility level of the organization and identify barriers to agility in order to survive in a competitive environment. The obstacles identified in this study are used to improve the performance of the organization. The enterprise should improve on the weak areas in order to achieve the highest agility level. Originality/value The agile supply chain (ASC) enablers proposed by previous researchers are not sufficient for the evaluation of agility of a supply chain. There are a few more ASC enablers such as customer satisfaction, flexibility and adaptability that also play a vital role in making a supply chain agile. Adding these three ASC enablers, a total of seven ASC enablers along with their attributes are being considered for the development of a conceptual model.

An integrated Delphi – fuzzy logic approach for measuring supply chain resilience: an illustrative case from manufacturing industry

2019 ◽  
Vol 23 (3) ◽  
pp. 350-375 ◽  
Author(s):  
Siva Kumar ◽  
Ramesh Anbanandam
Keyword(s):  
Fuzzy Logic ◽  
Supply Chain ◽  
Manufacturing Industry ◽  
Illustrative Case ◽  
Organizational Relationships ◽  
Content Type ◽  
Management Culture ◽  
Resilience Index ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Purpose Growth in a number of the supply chain (SC) disruptions threatens the enterprises globally. Earlier studies and reports say that many organizations go out of businesses within two or three years after they experience a major disruption. Therefore, companies in today’s volatile business arena need to possess the necessary resilience level to combat supply china disruptions. This is even more important for organizations of developing nations, which are constantly struggling to gain the advantages of globalization and to grab the new opportunities. Thus, this paper aims to help organizations understand their SC resilience level through a framework. Design/methodology/approach The methodology comprises integrated Delphi – fuzzy logic approach in identifying formative elements of SC resilience from a diverse resilience related body of knowledge and distinguish key obstacles of SC resilience based on their performance level. Findings Findings reveal that SC flexibility components such as sourcing, manufacturing and logistic flexibility are the major contributors of SC resilience index of case organization. Similarly, lack of risk management culture, inter-organizational relationships, information sharing and integration of SC stakeholders are the major inhibitors of resilience. Thus, the organization needs to overcome these identified obstacles to enhance their SC resilience level. Practical implications Present study offers a novel focus of research on SC resilience measurement that is significant for understanding the level of immunity enterprises possess to unanticipated SC interruptions, and the ability to bounce back after an unforeseen event. Originality/value This paper proposes an integrated Delphi – fuzzy logic framework for measuring SC resilience. In doing so, the study identifies key potential inhibitors of SC resilience of the case company under study.

Benchmarking fuzzy logic and ANFIS approaches for leanness evaluation in an Indian SME

2017 ◽  
Vol 24 (4) ◽  
pp. 973-993 ◽  
Author(s):  
Rohit Agrawal ◽  
P. Asokan ◽  
S. Vinodh
Keyword(s):  
Fuzzy Logic ◽  
Lean Manufacturing ◽  
Fuzzy Inference ◽  
Evaluation Model ◽  
Medium Size ◽  
Inference System ◽  
Content Type ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Leanness Evaluation

Purpose The purpose of this paper is to present a study that is focused on application of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS) approaches for leanness evaluation in an Indian small- and medium-size enterprise (SME). Design/methodology/approach Lean manufacturing concepts are being adopted by SMEs to sustain in the competitive manufacturing landscape. Performance of lean system needs to be assessed using appropriate methods. A model for measuring lean performance is proposed with five enablers, 30 criteria and 90 attributes. Leanness index is computed using fuzzy logic approach and benchmarked with ANFIS approach. Findings Leanness index computed using fuzzy logic approach is found to be (4.47, 5.97, 7.55) and that of ANFIS approach is found to be 5.84 to facilitate benchmarking of leanness evaluation. After finding weaker areas, certain improvement initiatives are being deployed. Research limitations/implications The developed model for leanness evaluation has been test implemented in an SME. In future, the model could be test implemented in several SMEs. Practical implications A case study conducted in an SME involved in heavy engineering fabrication is presented. Therefore, the inferences derived from the study has practical propensity. Originality/value The development of leanness evaluation model for SMEs and deployment in an industrial scenario are the original contributions of the authors.

Managing the humanitarian supply chain: a fuzzy logic approach

2017 ◽  
Vol 8 (5) ◽  
pp. 521-536 ◽  
Author(s):  
Kunal K. Ganguly ◽  
R.K. Padhy ◽  
Siddharth Shankar Rai
Keyword(s):  
Fuzzy Logic ◽  
Supply Chain ◽  
Inventory Management ◽  
Humanitarian Relief ◽  
Content Type ◽  
Disaster Situation ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Humanitarian Supply Chain ◽  
The Relationship

Purpose Humanitarian supply chain management (HSCM) in today’s environment faces the challenges such as information availability, inventory management, collaboration, logistics related issues and preparedness. The purpose of this paper is to evaluate the HSCM performance, considering the consequences in terms of operation, recovery and responsiveness based on the fuzzy estimates of the components presented. Design/methodology/approach In the study, triangulation approach was adapted for collecting data and developing a hierarchical structure for humanitarian supply chain performance assessment. The relationships between HSCM performance and its suddenness and required preparedness are depicted by cause and effect diagrams. The concepts of fuzzy association and fuzzy composition are applied to identify relationships. Findings In the hierarchy presented, the performance in a disaster situation, preparedness and suddenness of the situation and factors that influence the above are modeled. The taxonomy is developed for describing the relationship between factors, their likelihoods and impacts to achieve consistent quantification. Research limitations/implications The study considers case studies from Indian conditions; however, conditions in other countries and their practices for the disaster management may vary to certain extent. Practical implications A methodology presented for evaluating the exposures in considering the consequences in terms of responsiveness, operations, recovery, mitigation and emergency response. The study may help the humanitarian relief practitioners to understand the insights of the disaster situations using the proposed framework. Originality/value A common language for describing the different factors of HSCM is presented, which includes terms for quantifying likelihoods and impacts. The concept of fuzzy association and fuzzy composition has been applied to identify relationships between sources and consequences on HSCM performance. The use of descriptive linguistic variables is ensured through the implementation of fuzzy logic.

Benchmarking agility assessment approaches: a case study

2015 ◽  
Vol 22 (1) ◽  
pp. 2-17 ◽  
Author(s):  
S. Vinodh ◽  
S Aravindraj
Keyword(s):  
Fuzzy Logic ◽  
Design Methodology ◽  
Content Type ◽  
Agility Assessment ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Manufacturing Organization ◽  
Case Organization ◽  
Practical Implications

Purpose – The purpose of this paper is to benchmark the assessment approaches of agility in a manufacturing organization. Design/methodology/approach – The criteria for agility assessment were identified comprehensively based on literature review. The agility assessment was done using Multi Grade Fuzzy and Fuzzy logic approaches, and the results were benchmarked. Findings – Based on Multi Grade Fuzzy approach, the agility index was found to be 6.6; Fuzzy logic approach reveals the agility index as (5.37, 6.91, 8.45) which indicated the case organization is agile. The gaps were identified from both the approaches and the results were corroborated. Research limitations/implications – In the present study, Multi Grade Fuzzy and Fuzzy logic approaches were only benchmarked. Also, the benchmarking exercise was done only in one manufacturing organization. Practical implications – The benchmarking study was conducted in a manufacturing organization. The practitioners’ views were gathered and they were involved in the study to substantiate the practical validity. Originality/value – The benchmarking study between two approaches for agility assessment was found to be original and adds value to the agility assessment field.

Assessment of readiness level for implementing lean six sigma in healthcare organization using fuzzy logic approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
V. Vaishnavi ◽  
M. Suresh
Keyword(s):  
Fuzzy Logic ◽  
Conceptual Model ◽  
Six Sigma ◽  
Healthcare Organization ◽  
Lean Six Sigma ◽  
Medium Size ◽  
Content Type ◽  
Readiness Level ◽  
Fuzzy Logic Approach ◽  
Logic Approach

Purpose Lean Six Sigma (LSS) is a widely accepted business improvement methodology in healthcare, which aims to improve operations and quality and reduce cost, medical errors and waiting time by combing the principles of lean thinking with Six Sigma methodologies. To implement LSS successfully in healthcare organizations it is necessary to know the readiness level before starting the change process. Thus, the purpose of this paper is to assess the readiness level for the implementation of LSS in healthcare using a fuzzy logic approach. Design/methodology/approach The current study uses a fuzzy logic approach to develop an assessment model for readiness to implement LSS. The conceptual model for readiness is developed with 5 enablers, 16 criteria and 48 attributes identified from the literature review. The current study does the study in a medium-size hospital from India. Findings The fuzzy readiness for implementation of LSS index (FRLSSI) and fuzzy performance importance index (FPII) are calculated to identify the readiness level for the implementation of LSS in the case hospital. The FRLSSI is computed as average ready with (3.30, 5.06 and 6.83) and the FPII computed helps to identify 15 weaker attributes from 48 attributes. Research limitations/implications The current study uses only one hospital for study. In the future, the model can be tested in many hospitals. Practical implications The current study would be used by the managers of a healthcare organization to identify the readiness level of their organization to implement LSS. The proposed model is based on the identification of enablers, criteria and attributes to assess the readiness level of a healthcare organization and it helps to improve the readiness level to implement LSS effectively. Originality/value The present study contributes to the knowledge of readiness for the implementation of LSS in a healthcare organization. The conceptual model is developed for assessing the readiness level of a healthcare organization and it helps to improve the readiness level for successful implementation of LSS. Weaker attributes are identified and necessary corrective actions should be taken by the management to improve the readiness. The continuation of the assessment readiness model over a period of time would help to improve the readiness level of healthcare for the implementation of LSS.

Leanness evaluation in health-care organizations using fuzzy logic approach

2020 ◽  
Vol 28 (6) ◽  
pp. 1201-1225 ◽  
Author(s):  
M. Suresh ◽  
V. Vaishnavi ◽  
Rajesh D. Pai
Keyword(s):  
Health Care ◽  
Fuzzy Logic ◽  
Health Care Organizations ◽  
Health Care Organization ◽  
Point Of View ◽  
Care Organization ◽  
Content Type ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Leanness Evaluation

Purpose Lean practices are one of the fundamental practices adopted by health-care organizations to improve service quality and to reduce cost. In this context, the measurement of leanness in health-care organizations has become imperative. The purpose of this study is to measure the leanness of a hospital using fuzzy logic. Design/methodology/approach The design of the research includes two major steps. First, the identification of enablers, criteria and attributes of leanness constitutes the measures of assessment. Second, the above measures in the case hospital are assessed by using fuzzy logic approach. Findings This study suggests that leanness assessment is essential to identify the current lean capability of a health-care organization. This would help the health-care organizations to improve their lean performance further. The findings of the study suggest that the leanness of the case hospital is “Lean” (fuzzy range: 5.61, 7.24 and 8.91). Practical implications This study brings in three important implications from managerial point of view. First, it helps the management to assess the current level of leanness of the hospital. Second, it identifies the attributes that prevent the organization from being more lean. Third, it provides suggestive measures to address the weaker attributes and enables the enhancement of lean performance further. Originality/value The leanness assessment framework developed in the hospital operations is found to be original, and it adds value to the leanness assessment in health-care operations.

Measuring pro-poor growth: a comparative study and a fuzzy logic-based method

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rami Haj Kacem ◽  
Saoussen Bel Hadj Kacem
Keyword(s):  
Fuzzy Logic ◽  
Comparative Study ◽  
Critical Evaluation ◽  
Fundamental Principle ◽  
Poor Growth ◽  
Content Type ◽  
Growth Measurement ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Global Growth

PurposeThis paper has two purposes. The first is to provide a critical evaluation of current methods of measuring monetary versus non-monetary pro-poor growth. The second is to propose an alternative method based on the fuzzy logic aggregation approach, which allows including both monetary and non-monetary indicators simultaneously for measuring the “global pro-poor growth”.Design/methodology/approachThe methodology that we propose is based on the fuzzy logic approach to aggregate both monetary and non-monetary indicators simultaneously and thus to calculate the “Global Welfare Index”. This index will be considered as the main global wellbeing indicator based on which a “Global Growth Incidence Curve” is constructed to analyze the pro-poor growth. 10; Also, an application of the main previous procedures for measuring monetary vs non-monetary pro-poor growth is presented to compare their results and to discuss their advantages and limitations.FindingsEmpirical validation using Tunisian data reveals that on one hand, results of the pro-poor growth analysis are very sensitive to the used measurement method and may lead to different conclusions. On the other hand, our alternative procedure may provide a more appropriate analysis of pro-poor growth given that it takes into consideration the multidimensional aspect of poverty while remaining faithful to the fundamental principle of pro-poor growth measurement.Originality/valueThe proposed method for constructing the “Global Growth Incidence Curve” is original given that it presents a new procedure to take into account both monetary and non-monetary indicators simultaneously, which allows having a more global view of the phenomenon. Also, the comparative study of the different proposed methods in the literature of measuring pro-poor growth is useful to identify their limitations and advantages.

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