Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/11727/4809

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Author: search.filters.author.Can, Gulin Feryal

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    A new multidimensional process type FMEA approach: Defense and aerospace industry application
    (2022) Uslu, Tugce; Can, Gulin Feryal; Delice, Elif Kilic
    Purpose: Failure Modes and Effects Analysis (FMEA), one of the most used methods in the literature, is a powerful risk assessment tool. However, it has many weaknesses that need to be improved. In this study, in order to increase the efficiency of using FMEA; a new multidimensional process type FMEA (MDPT-FMEA) approach is proposed. Theory and Methods: The MDPT-FMEA approach consists of three stages. At the first stage, Entropy, Preference Selection Index (PSI) and Criteria Importance through Inter-criteria Correlation (CRITIC) methods were used in the weighting of the risk criteria (RC). The different criteria weights obtained from these three different weighting methods were combined using the geometric mean operator and the integrated (final) weights were calculated. In the second stage, Evaluation based on Distance from Average Solution (EDAS), Combinative Distance-based Assessment (CODAS), Complex Proportional Assessment (COPRAS) to prioritize failure modes (FMs) were used. In the third stage, different FM priorities obtained from these three different ranking methods were combined using the Technique of Precise Order (TPOP) method. Results: The proposed MDPT-FMEA approach has been applied in a company operating in the defense and aerospace industry to evaluate the process-based FMs that may arise. In this study, different perspectives of different weighting and ranking methods are reflected in final criteria weights and final FM rankings. Conclusion: For the first time, different weighting and different ranking methods are combined in FMEA. As a result of the Spearman Correlation Coefficient calculation, the validity of both of the final criteria weights obtained and the final FM rankings were discussed.
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    A novel aggregated multiple criteria decision-making approach to evaluate the physical workload of workers
    (2021) Ekinci, Elmas Burcu Mamak; Can, Gulin Feryal; AAE-4242-2020
    Physical workload (PWL) is a measure of the physical resources consumed by a worker while performing a task. Analyzing the PWL of workers can aid experts in identifying workers whose working conditions should be improved. Identifying workers who are exposed to the highest PWL is essential for task continuity and occupational health. In this study, a new approach is proposed to prioritize workers according to their PWL levels. In the proposed approach, multiple criteria decision-making techniques are used because different factors can affect PWL levels. Eight criteria, that is, standard time, frequency of working posture, heart rate, the risk level of posture, noise level, lighting intensity, rest period, and perceived workload level are considered. In the evaluation process, criteria weights are computed using entropy considering measurements of the eight criteria for each worker. Using these weights in multiobjective optimization by simple ratio analysis, multiobjective optimization by ratio analysis, and multiattributive ideal-real comparative analysis methods, workers are ranked according to their PWL levels. The final order of workers is determined by aggregating different rankings obtained from these three methods, using the technique of precise order preference method. This study presents original research that can potentially contribute to the literature by considering different perspectives offered by various methods for PWL evaluation. It focuses on several different criteria by performing real measurements and subsequently ranking workers based on the aggregation of these measurements.
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    A FMEA based novel intuitionistic fuzzy approach proposal: Intuitionistic fuzzy advance MCDM and mathematical modeling integration
    (2021) Yener, Yelda; Can, Gulin Feryal
    This study proposes a novel three-stage intuitionistic fuzzy risk assessment (RA) approach based on Failure Modes and Effects Analysis (FMEA). In this study, it was paid attention for considering real constraints of firms such as capital, time etc. to prevent nan-fatal failure modes (FMs), interactions between FMs and risk level similarities created by risk factors (RFs). At the first stage of the proposed approach, RFs' weights are computed by a new intuitionistic fuzzy weighting method considering similarities between RFs for risk levels that they can create. At the second stage, Modified Intuitionistic Fuzzy Multi Attribute Border Approximation Area (MIF-MABAC) including interactions between FMs is used to determine the rankings of FMs by using Extended Haussdorff distance function. At the third stage, two intuitionistic fuzzy mathematical models are established to show the effect of the real constraints of the firm to identify the risk types (RTs) that must be avoided primarily. It was seen that the first model gives the same ranking results with the MIF-MABAC. Additionally, when including the real constraints, the first model can give the more suitable results than the second model. The results obtained from the first model show that experts' assessments and mathematical modeling identify the same FMs for preventing primarily. This study is the first one to suggest a new RA approach that reflects the real constraints of the firms to RA. Additionally, this is the first study that models' interactions between FMs and risk level similarities created by RFs.
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    Occupational health and safety performance evaluation of countries based on MAIRCA
    (2020) Can, Gulin Feryal; Kiran, Muzaffer Bertan
    Purpose The purpose of this paper is to develop an approach to compare occupational health and safety (OHS) performances of countries. Additionally, another aim is to debate the impacts of using recorded data and ratios for OHS performance evaluations. Design/methodology/approach The number of fatal accidents (NFAs), fatal accident rates (FARs), numbers of lost days (NLDs) and accident severity rates (ASRs) are determined as main criteria and six economic activity areas (EAAs) are considered as sub-criteria. Two different initial decision matrices are used as the initial decision matrix, the first of which consists of recorded data of countries related to NFAs and NLDs, and the second consists of FAR and ASR values as ratios. Importance weights of main and sub-criteria regarding the recorded data and ratios are determined using four different weighting ways. Countries are ranked via utilizing Multi-Attributive Ideal-Real Comparative Analysis considering two different initial decision matrices. Findings It can be stated that an evaluation based on ratios for comparison of OHS performance provides more realistic results. Additionally, increasing the effect of the FAR values using the 6,000 equivalent lost days factor is also important in terms of differentiating the data of the countries in question. Originality/value To the best of the authors' knowledge, there is no study in literature that discusses the ranking of countries by means of recorded data and ratios considering different criteria. Additionally, this study is a first in terms of the number of countries evaluated and the comparison of these countries according to their respective EAAs.
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    Six sigma project prioritization and selection: a multi-criteria decision making approach in healthcare industry
    (2020) Pakdil, Fatma; Toktas, Pelin; Can, Gulin Feryal
    Purpose The purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM) methods in healthcare organizations. This study addresses a particular gap in implementing a systematic methodology for Six Sigma project prioritization and selection in the healthcare industry. Design/methodology/approach This study develops a methodology in which alternate Six Sigma projects are prioritized and selected using a modified Kemeny median indicator rank accordance (KEMIRA-M), an MCDM method based on a case study in healthcare organizations. The case study was hypothetically developed in the healthcare industry and presented to demonstrate the proposed framework's applicability and validity for future decision-makers who will take place in Six Sigma project selection processes. Findings The study reveals that the Six Sigma project prioritized by KEMIRA-M assign the highest ranks to patient satisfaction, revenue enhancement and sigma level benefit criteria, while resource utilization and process cycle time receive the lowest rank. Practical implications The methodology developed in this paper proposes an MCDM-based approach for practitioners to prioritize and select Six Sigma projects in the healthcare industry. The findings regarding patient satisfaction and revenue enhancement mesh with the current trends that dominate and regulate the industry. KEMIRA-M provides flexibility for Six Sigma project selection and uses multiple criteria in two-criteria groups, simultaneously. In this study, a more objective KEMIRA-M method was suggested by implementing two different ranking-based weighting approaches. Originality/value This is the first study that implements KEMIRA-M in Six Sigma project prioritization and selection process in the healthcare industry. To overcome previous KEMIRA-M shortcomings, two ranking based weighting approaches were proposed to form a weighting procedure of KEMIRA-M. As the first implementation of the KEMIRA-M weighting procedure, the criteria weighting procedure of the KEMIRA-M method was developed using two different weighting methods based on ranking. The study provides decision-makers with a methodology that considers both benefit and cost type criteria for alternates and gives importance to experts' rankings related to criteria and the performance values of alternates for criteria.
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    Universal usability evaluation by using an integrated fuzzy multi criteria decision making approach
    (2019) Can, Gulin Feryal; Demirok, Seda
    Purpose The purpose of this paper is to propose an integrated fuzzy approach to determine important universal usability problems (UUPs) by providing experts who behave like real users and to establish a work plan to correct the most important ones. Design/methodology/approach In this study, a fuzzy multi-criteria decision-making approach with three stages is proposed for the evaluation of universal usability. At the first stage, UUPs are identified by performing modified heuristic evaluation, and severity rating of each problem is determined by experts. At the second stage, critical problems are specified by applying the fuzzy Delphi considering these severity ratings. At the third stage, Fuzzy Decision Making Trial and Evaluation Laboratory approach is applied to prioritize critical problems as sub and main criteria. An illustrative example related to emergency service is performed to apply the proposed approach. Findings Results showed that the elevator button design, the elevator emergency button design and the position of the floor signboard are the first three problems that should be primarily improved as sub-criteria. In terms of main criteria, equitable use, simple and intuitive use, and perceptible information are the first three main criteria that should be improve in emergency service. Originality/value This study is original in terms of methodology and providing a new perspective for building design evaluation. The results can help the designers to see the UUPs in buildings, to focus the most important UUPs and to establish improvement ranking. These advantages provide time and cost-effective design improvement actions.
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    Stochastic KEMIRA-M Approach with Consistent Weightings
    (2019) Toktas, Pelin; Can, Gulin Feryal
    This study proposes an advanced Modified KEmeny Median Indicator Rank Accordance (KEMIRA-M) approach based on stochastic evaluation process considering consistent weights to improve effective usage of KEMIRA-M. In the proposed approach, tasks related to the decision issue are performed by decision makers to ensure the understanding sufficiency of alternatives in terms of criteria more clearly. The weighting procedure of Analytic Hierarchy Process (AHP) is implemented in a stochastic manner benefited from discrete uniform distribution to provide obtaining consistent criteria weights considering median priority components. Therefore, different trials including different number of replications that shows the number of decision makers are performed and the most consistent weightings are determined for each trial in the stochastic process. In this way, the dependency to the limited numbers of decision makers and to determine criteria weights in a heuristic manner in KEMIRA-M is prevented. Additionally, the effect of the number of decision makers on criteria weightings and alternatives' ranking process is shown. To obtain the most consistent weighting results, this stochastic process is utilized until acquiring approximate consistency ratios. The proposed stochastic KEMIRA-M approach is utilized to rank nine shopping malls (SMs) in Ankara in terms of technical criteria (TC) and universal design criteria (UDC). It was seen from the ranking results that the first SM (SM1) is the best one.
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    Image processing based rapid upper limb assessment method
    (2017) Can, Gulin Feryal; Figlali, Nilgun
    Occupational Musculoskeletal System Disorders (OMSDs) are disorders that inflict a great deal of economical burden on enterprises and nations, decrease quality, productivity and cause inability to sustain livings of employees. One of the most important factor that cause OMSDs is working posture. In literature, there are various methods for determining risk levels of working postures. In this study because of its common usage, Rapid Upper Limb Assessment Method (RULA) that identfies hazard level created by working postures on employees' upper limb musculoskeletal health is selected for improving with image processing systems. It is necassary to improve RULA's performance due to complications stemming from its implementation method based on observation, lack of information on the best duration of observation, subjectivity on results and extensive analysis time etc. For compansate these requirements a modified method is proposed in this study named as Advanced RULA (ARULA). Reliability and validity analysis are implemented statistically for ARULA. As a result, ARULA is recommended as a practical tool for analyzing risk levels of working postures for tasks that contain intensive usage of upper extremity.