A comparative outline for quantifying risk ratings in occupational health and safety risk assessment

The concept of risk assessment has been introduced as an examination of safety in the workplace to enable assessments as to whether sufficient precautions have been taken or if more should be done to prevent potential harm. Hazardous industries have faced serious fatalities related to work, workplaces, and workers as a consequence of their high-risk processes. Therefore, in this work, a novel and comparative methodology for quantifying risk ratings in occupational health and safety risk assessment is proposed. A 5 x 5 risk matrix is initially determined, and the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) method is then applied to rank identified hazards. As a novelty to the knowledge, two parameters of the 5 x 5 matrix method, likelihood and severity, are subjectively assessed by occupational health and safety experts, and then importance levels for these parameters are determined using the Pythagorean fuzzy analytic hierarchy process (PFAHP). In the proposed approach, analysts use linguistic terms and Pythagorean fuzzy sets, which provide greater independence in their evaluations. An outline that enables comparison of the results of this study with the circumcenter of centroids method and the fuzzy AHP-fuzzy VIKOR integrated method in quantifying risk ratings is also provided. In order to present the practicality of this work, a case study in an underground copper and zinc mine is carried out. (C) 2018 Elsevier Ltd. All rights reserved.No sponso

AHP-TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis

Risk analysis (RA) contains several methodologies that object to ensure the protection and safety of occupational stakeholders. Multi attribute decision-making (MADM) is one of the most important RA methodologies that is applied to several areas from manufacturing to information technology. With the widespread use of computer networks and the Internet, information security has become very important. Information security is vital as institutions are mostly dependent on information, technology, and systems. This requires a comprehensive and effective implementation of information security RA. Analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are commonly used MADM methods and recently used for RA. In this study, a new RA methodology is proposed based on AHP-TOPSIS integration extended with Pythagorean fuzzy sets. AHP strengthened by interval-valued Pythagorean fuzzy numbers is used to weigh risk parameters with expert judgment. Then, TOPSIS with Pythagorean fuzzy numbers is used to prioritize previously identified risks. A comparison of the proposed approach with three approaches (classical RA method, Pythagorean fuzzy VIKOR and Pythagorean fuzzy MOORA) is also provided. To illustrate the feasibility and practicality of the proposed approach, a case study for information security RA in corrugated cardboard sector is executed.No sponso

A multi criteria decision making methodology based novel model for supplier selection

Supplier selection and measurement of supplier performance are multi-criteria decision making (MCDM) problems and have strategic importance for all industries. The study contains analyzed factors that are affecting the process of the supply chain concerning supplier performance. Supplier performance measures is a tool to determine whether suppliers are doing their job as expected. The importance of supplier performance measurement should not be underestimated due to direct and indirect productivity-related consequences. Supplier evaluation is a complex multiple criteria decision-making problem that is affected by several conflicting factors. Therefore, the measurement of supplier performance has been becoming crucial and critical throughout the world. The purpose of this paper is to investigate the MCDM methods and propose a novel method to check how the performance of suppliers is being measured using three different methods. Qualification and final selection of the supplier can be done with a proposed novel model. In the study, the criteria are weighted with the Analytical Hierarchy Process, while TOPSIS and VIKOR methods are used to evaluate and rank the suppliers. Evaluating supplier performance, derive the importance of the main criteria and sub-criteria applied in decision-matrix to sort the suppliers according to the measurement of supplier performance criteria.No sponso

A comparative analysis of breast cancer detection and diagnosis using data visualization and machine learning applications

In the developing world, cancer death is one of the major problems for humankind. Even though there are many ways to prevent it before happening, some cancer types still do not have any treatment. One of the most common cancer types is breast cancer, and early diagnosis is the most important thing in its treatment. Accurate diagnosis is one of the most important processes in breast cancer treatment. In the literature, there are many studies about predicting the type of breast tumors. In this research paper, data about breast cancer tumors from Dr. William H. Walberg of the University of Wisconsin Hospital were used for making predictions on breast tumor types. Data visualization and machine learning techniques including logistic regression, k-nearest neighbors, support vector machine, naïve Bayes, decision tree, random forest, and rotation forest were applied to this dataset. R, Minitab, and Python were chosen to be applied to these machine learning techniques and visualization. The paper aimed to make a comparative analysis using data visualization and machine learning applications for breast cancer detection and diagnosis. Diagnostic performances of applications were comparable for detecting breast cancers. Data visualization and machine learning techniques can provide significant benefits and impact cancer detection in the decision-making process. In this paper, different machine learning and data mining techniques for the detection of breast cancer were proposed. Results obtained with the logistic regression model with all features included showed the highest classification accuracy (98.1%), and the proposed approach revealed the enhancement in accuracy performances. These results indicated the potential to open new opportunities in the detection of breast cancer.No sponso

Eğitim yapılarında güneş panellerinin kullanımlarının değerlendirilmesi ve mimari tasarıma etkisi

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A modified failure modes and effects analysis using interval-valued spherical fuzzy extension of TOPSIS method: case study in a marble manufacturing facility

Failure modes and effects analysis (FMEA) is a commonly used step-by-step approach to assess potential failures existing in a product or process design. In this paper, a modified FMEA model based on an interval-valued spherical fuzzy extension of technique for order preference by similarity to ideal solution (IVSF-TOPSIS) is proposed to cope with drawbacks of the traditional risk priority number (RPN) computation. Spherical fuzzy sets are the integration of Pythagorean fuzzy sets and neutrosophic sets. They provide more freedom to experts in decision making by including the degree of membership, non-membership, and hesitation of fuzzy sets. Therefore, initially, TOPSIS is merged with a special branch of spherical sets ‘‘interval-valued spherical fuzzy sets’’ to determine priorities of emerged failures. As a novelty to traditional RPN of FMEA, three parameters called cost, prevention, and effectiveness in addition to the existed parameters of severity, occurrence and detection are attached to the proposed approach. Weights of these parameters are determined via an interval-valued spherical weighted arithmetic mean operator (IVSWAM). As a demonstration, a case study in a marble manufacturing facility is provided to show the applicability of the novel model. Results show that the most crucial failure modes concern with the maintenance and repairing works of the factory and the lack of technical periodic checks of lifting vehicles regarding ‘‘block area: crane’’ failures. Some comparative and validation studies are also performed to test the solidity of the approach.No sponso

Occupational health, safety and environmental risk assessment in textile production industry through a Bayesian BWM-VIKOR approach

Occupational risk assessment (ORA) is a process that consists of evaluating, ranking, and classifying the hazards and associated risks arising in any workplace from the viewpoint of occupational health and safety. Many ORA methods have been proposed in the literature, from a single independent expert to participatory methodologies made by group decision and simple to complex ones. In this paper, a holistic ORA is presented, which uses two important multi-attribute decision methods named Bayesian Best-Worst Method (Bayesian BWM) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Bayesian BWM is used to determine the importance weights of six different assessment criteria, which are the probability of hazardous event (P), frequency (F), severity (S), detectability (D), cost (C) and sensitivity not to use personal protective equipment (SNP). Since the classical BWM finds solution to the weights of a number of criteria from only one expert’s judgment, Bayesian BWM is preferred in this paper (1) to enable participation of a group of experts, (2) to aggregate the preferences of these multiple experts into consensus without loss of information and (3) to follow a probabilistic way for solving the ORA problem. The hazards are then ranked by VIKOR. The approach is implemented in the ORA process of a textile production plant. Results of risk analysis showed that electricity hazard and associated risks constitute the highest risk ratings. These hazards arise from the product, process, human and working environment. The associated risks are evaluated, prioritized, and detailed control measures are proposed. This study made comparisons with the classical BWM-VIKOR approach to demonstrate the proposed approach’s difference and practicality. Results can also help practitioners and risk analysts in formulating the improvement measures to increase the overall safety of the working environment further.No sponso

İnsani yardım tedarik zinciri depo yer seçimi: ÇKKV metodolojisi temelli bir örnek olay incelemesi

"Disaster" is a general name given to events that cause physical, economic, and social losses for people that will disrupt the functioning of a community or society. Disasters that occur largely or completely beyond the control of people cause a mass loss of life and property. Turkey is in one of the most effective earthquake zones which is the Mediterranean-Alpine-Himalayan belt. Almost, every 5 years, one big earthquake is happened and causes loss of life and property. Disaster management requires complex logistic activities and it is an unpredictable marketplace, they must be managed appropriately to achieve faster and more efficient results. In this study, evaluation of the factors which is affecting the location selection of the humanitarian supply chain warehouses (HSCW) at the local and regional levels is done with multi-criteria decision making (MCDM) based methods. Main and subcriteria weights are Main criteria and subcriteria were calculated with AHP. The ranking of criteria and alternatives was carried out with the TOPSIS method. In this study, AHP-TOPSIS integrated criteria assessment is conducted for the HSCW selection problem. This study intends to explore the humanitarian supply chain warehouse selection problem and evaluate criteria to improve humanitarian supply chain management and location selection implementation."Afet", bir topluluğun veya toplumun işleyişini bozacak kişiler için fiziksel, ekonomik ve sosyal kayıplara neden olan olaylara verilen genel bir addır. Büyük ölçüde veya tamamen insanların kontrolü dışında meydana gelen afetler, kitlesel can ve mal kaybına neden olur. Türkiye, Akdeniz-Alp-Himalaya kuşağı olan en etkili deprem bölgelerinden biridir. Neredeyse her 5 yılda bir büyük bir deprem meydana gelir ve can ve mal kaybına neden olur. Afet yönetimi, karmaşık lojistik faaliyetler gerektirir ve öngörülemeyen bir pazardır, daha hızlı ve daha verimli sonuçlar elde etmek için uygun şekilde yönetilmeleri gerekir. Bu çalışmada, insani yardım tedarik zinciri depolarının (HSCW) yerel ve bölgesel düzeydeki lokasyon seçimini etkileyen faktörlerin değerlendirilmesi, çok kriterli karar verme (MCDM) tabanlı yöntemlerle yapılmıştır. Temel ve alt kriter ağırlıkları Ana kriterler olup, alt kriterler AHP ile hesaplanmıştır. Kriter ve alternatiflerin sıralaması TOPSIS yöntemi ile yapıldı.No sponso

Occupational Risk Assessment for Flight Schools: A 3,4-Quasirung Fuzzy Multi-Criteria Decision Making-Based Approach

The concept of occupational risk assessment is related to the analysis and prioritization of the hazards arising in a production or service facility and the risks associated with these hazards; risk assessment considers occupational health and safety (OHS). Elimination or reduction to an acceptable level of analyzed risks, which is a systematic and proactive process, is then put into action. Although fuzzy logic-related decision models related to the assessment of these risks have been developed and applied a lot in the literature, there is an opportunity to develop novel occupational risk assessment models depending on the development of new fuzzy logic extensions. The 3,4-quasirung fuzzy set (3,4-QFS) is a new type of fuzzy set theory emerged as an extension of the Pythagorean fuzzy sets and Fermatean fuzzy sets. In this approach, the sum of the cube of the degree of membership and the fourth power of the degree of non-membership must be less than or equal to 1. Since this new approach has a wider space, it can express uncertain information in a more flexible and exhaustive way. This makes this type of fuzzy set applicable in addressing many problems in multi-criteria decision making (MCDM). In this study, an occupational risk assessment approach based on 3,4-quasirung fuzzy MCDM is presented. Within the scope of the study, the hazards pertaining to the flight and ground training, training management, administrative and facilities in a flight school were assessed and prioritized. The results of existing studies were tested, and we considered both Pythagorean and Fermatean fuzzy aggregation operators. In addition, by an innovative sensitivity analysis, the effect of major changes in the weight of each risk parameter on the final priority score and ranking of the hazards was evaluated. The outcomes of this study are beneficial for OHS decision-makers by highlighting the most prioritized hazards causing serious occupational accidents in flights schools as part of aviation industry. The approach can also be suggested and adapted for production and service science environments where their occupational health & safety are highly required

Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA

improving their operations with a view to human health and environmental awareness. Many methods with different rationales have been existed in the literature to prioritize hazards according to their risk levels and to mitigate their consequences. In this study, a new model is developed for occupational risk assessment by merging two well-known multicriteria decision-making methods named best and worst method (BWM) and multi attribute ideal real comparative analysis (MAIRCA) under fuzzy environment. The proposed model differentiates from other similar models by three aspects. First, it considers severity of a hazard and its associated risk from the human and environmental riskiness perspectives. Secondly, it applies fuzzy BWM (F-BWM) to calculate the relative importance of three risk factors named as ‘‘probability, frequency and severity’’ of traditional Fine–Kinney method. Thirdly, it applies fuzzy MAIRCA (F-MAIRCA) to rank hazards according to their risk level using importance values obtained by F-BWM. To show applicability of the approach, a case study of risk assessment in a marble factory is fulfilled. Additionally, a number of validation studies including benchmarking analysis with fuzzy VIKOR and fuzzy TOPSIS methods; a sensitivity analysis by varying importance weights of risk factors are carried out to highlight the solidity of the proposed approach.No sponso