Literature Review on Vague Set Theory in Different Domains

Problem of decision making is a crucial task in every business. This decision making job is found very difficult when it is depends on the imprecise and vague environment, which is frequent in recent years. Vague sets are an extension of Fuzzy sets. In the fuzzy sets, each object is assigned a single value in the interval [0,1] reflecting its grade of membership. This single value does not allow a separation of evidence for membership and evidence against membership. Gau et al. proposed the notion of vague sets, where each object is characterized by two different membership functions: a true membership function and a false membership function. This kind of reasoning is also called interval membership, as opposed to point membership in the context of fuzzy sets. In this paper, reviews the related works on the decision making by using vague sets in different fields

Advanced Quantitative Risk Assessment of Offshore Gas Pipeline Systems

This research has reviewed the current status of offshore and marine safety. The major problems identified in the research are associated with risk modelling under circumstances where the lack of data or high level of uncertainty exists. This PhD research adopts an object-oriented approach, a natural and straightforward mechanism of organising information of the real world systems, to represent the Offshore Gas Supply Systems (OGSSs) at both the component and system levels. Then based on the object-oriented approach, frameworks of aggregative risk assessment and fault tree analysis are developed. Aggregative risk assessment is to evaluate the risk levels of components, subsystems, and the overall OGSS. Fault trees are then used to represent the cause-effect relationships for a specific risk in the system. Use of these two assessment frameworks can help decision makers to obtain comprehensive view of risks in the OGSS. In order to quantitatively evaluate the framework of aggregative risk, this thesis uses a fuzzy aggregative risk assessment method to determine the risk levels associated with components, subsystems, and the overall OGSS. The fuzzy aggregative risk assessment method is tailored to quantify the risk levels of components, subsystems, and the OGSS. The proposed method is able to identify the most critical subsystem in the OGSS. As soon as, the most critical subsystem is identified, Fuzzy Fault Tree Analysis (FFTA) is employed to quantitatively evaluate the cause-effect relationships for specific undesired event. These results can help risk analysts to select Risk Control Options (RCOs) for mitigating risks in an OGSS. It is not financially possible to employ all the selected RCOs. Therefore, it is necessary to rank and select the best RCO. A decision making method using the Fuzzy TOPSIS (FTOPSIS) is proposed to demonstrate the selection of the best RCOs to control the existing risks in the system. The developed models and frameworks can be integrated to formulate a platform which enables to facilitate risk assessment and safety management of OGSSs without jeopardising the efficiency of OGSSs operations in various situations where traditional risk assessment and safety management techniques cannot be effectively applied

Safety Analysis of different industries using Fuzzy AHP

In recent days, we march towards a new occupational health and safety era in which work cultures are directed towards positive safety values. It is predicted that the safety analysis techniques now in place are quite difficult to address the potential risks which weakens the era. A novel approach of analyzing different crucial criteria in different industrial sectors is analyzed carefully in this paper. In this unique approach, fuzzy AHP(Analytic Hierarchy Process) technique is applied to determine the respective weights of three main criteria and seventeen sub-criteria as a way of enriching the decision making process while in a dilemma. A survey was initiated in different industrial sectors to obtain reliable data for the research. The results shows that the main criteria ‘human safety’ acquired a weight of 72.5% while the respective weights of main criteria machine safety and work environment safety falls to 8.9% and 18.4%. The weight of the main criteria, human safety indicates that the sub-criteria such as eye protection, manual lifting, material handling practices, fire fighting drills, training and safety officers are implemented to a greater extent in most of the surveyed industries

Safety Analysis of different industries using Fuzzy AHP

In recent days, we march towards a new occupational health and safety era in which work cultures are directed towards positive safety values. It is predicted that the safety analysis techniques now in place are quite difficult to address the potential risks which weakens the era. A novel approach of analyzing different crucial criteria in different industrial sectors is analyzed carefully in this paper. In this unique approach, fuzzy AHP(Analytic Hierarchy Process) technique is applied to determine the respective weights of three main criteria and seventeen sub-criteria as a way of enriching the decision making process while in a dilemma. A survey was initiated in different industrial sectors to obtain reliable data for the research. The results shows that the main criteria ‘human safety’ acquired a weight of 72.5% while the respective weights of main criteria machine safety and work environment safety falls to 8.9% and 18.4%. The weight of the main criteria, human safety indicates that the sub-criteria such as eye protection, manual lifting, material handling practices, fire fighting drills, training and safety officers are implemented to a greater extent in most of the surveyed industries

Formal safety assessment of marine applications

This research has first established that it is based on multiple methodologies developed to tackle the areas of engineering cargo handling systems, both at port and on-board vessels, as well as in the area of organisational self-assessment. It continued in reviewing the current status and future aspects of marine safety assessment together with an examination of a few major accidents. The major problems identified in marine safety assessment in this research are associated with inappropriate treatment of uncertainty in data and human error issues during the risk modelling estimation process and the calculation of failure probabilities. Following the identification of the research needs, this thesis has developed several analytical models for the safety assessment of cargo handling systems and organisational assessment structure. Such models can be effectively integrated into a risk-based framework using the marine formal safety assessment, safety case concepts. Bayesian network (BN) and evidential reasoning (ER) approaches applicable to cargo handling engineering systems have been proposed for systematically and effectively addressing uncertainty due to randomness and vagueness in data respectively. ER test cases for both a vessel selection process and a comparison of the safety maturity of different organisations in terms of self-assessment have been produced within a domain in which main and sub criteria have been developed for assessment reasons a long with the combination of the proposed model with existing organisational models. BN test case for a Liquefied Petroleum Gas (LPG) reliquefaction plant has been produced within a cause-effect domain in which Bayes' theorem is the focal mechanism of inference processing. A methodology aiming in finding the probability of failure when having variables ruled by uncertainty is established using certain variable transformation methods through the First and Second order reliability methodologies. Form/Sorm produces a most likely failure point, which is demonstrated through the application at a port cargo handling crane system. The outcomes have the potential to facilitate the decision-making process in a risk-based framework. Finally, the results of the research are summarised and areas where further research is required to improve the developed methodologies are outlined

Multi-perspective evaluation of integrated active cooling systems using fuzzy decision making model

As global median temperatures continue to rise, the demand for active cooling systems (ACs) is increasing. These systems are particularly prevalent in developed countries for maintaining comfort during hot weather. Various ACs technologies are available, and assessing their performance in multi-perspective settings is necessary to determine the best option for intended usage. This requires an evaluation platform for assessment. This paper presents a novel multi-criteria decision-making (MCDM) model based on a new integrated 2-tuple linguistic Pythagorean fuzzy-weighted zero-inconsistency (2 TLP-FWZIC) and modified 2-tuple linguistic Pythagorean fuzzy multi-attributive border approximation area comparison (2TLPF-MABAC). The former is used to determine the importance of assessment criteria, while the latter is employed for selecting the optimal ACs using the obtained weights. The first-level weighting results reveal that performance criteria were predominantly favored for assessment, with ‘energy performance’ acquiring the most significant weight (0.2487) among all performance criteria. In terms of ACs selection results, among the 20 tested and assessed systems, the ‘geothermal borehole electricity-based ACs’ obtained the highest score value (0.1296), while the ‘window packaged electricity-based ACs’ had the lowest score (-0.0515). The robustness of the results was confirmed through sensitivity analysis

A review of applications of fuzzy sets to safety and reliability engineering

Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). In conventional PRA, failure data about components is required for the purposes of quantitative analysis. In practice, it is not always possible to fully obtain this data due to unavailability of primary observations and consequent scarcity of statistical data about the failure of components. To handle such situations, fuzzy set theory has been successfully used in novel PRA approaches for safety and reliability evaluation under conditions of uncertainty. This paper presents a review of fuzzy set theory based methodologies applied to safety and reliability engineering, which include fuzzy FTA, fuzzy FMEA, fuzzy ETA, fuzzy Bayesian networks, fuzzy Markov chains, and fuzzy Petri nets. Firstly, we describe relevant fundamentals of fuzzy set theory and then we review applications of fuzzy set theory to system safety and reliability analysis. The review shows the context in which each technique may be more appropriate and highlights the overall potential usefulness of fuzzy set theory in addressing uncertainty in safety and reliability engineering

Deciding a multicriteria decision-making (Mcdm) method to prioritize maintenance work orders of hydroelectric power plants

The current global competitive scenario and the increase in complexity and automation of equipment and systems demand better results from maintenance management in organizations. As maintenance resources are limited, prioritizing maintenance activities is essential to allocate them properly and to meet maintenance management objectives. In the face of these challenges, multicriteria decision-making (MCDM) methods are commonly used in organizations to support decision-making. Nevertheless, selecting a suitable MCDM method for maintenance planning can be complicated given the diversity of methods and their strengths and weaknesses. In this context, this paper proposes a novel knowledge-based method for deciding a multicriteria decision-making (MCDM) method to prioritize maintenance work orders of hydroelectric plants. As the main novel contribution, it translates the intrinsic characteristics of the main MCDM methods into questions related to maintenance planning to guide the recommendation of a suitable MCDM method for organizations through a decision tree diagram. This approach was applied to a maintenance case study of a hydroelectric power plant in order to demonstrate its use and contribute to its understanding. These findings contribute to maintenance management in selecting an MCDM method aligned with the context of its maintenance planning for the prioritization of maintenance work orders