Danijela Tadic

An evaluation of quality goals by using fuzzy AHP and fuzzy TOPSIS methodology

There is no defined methodological approach that would rank the quality goals of a process in uncertain environments, which is one of the basic problems in process management. In this paper, the considered problem is stated as a multi-criteria decision problem. The criteria present performances which are defined by the knowledge and experience of the decision makers. The fuzzy rating weights of each pair of the considered criteria and uncertain criteria values for the defined quality goals are described by linguistic expressions which are modeled by triangular fuzzy numbers. The weights vector of criteria is calculated by the fuzzy Analytic Hierarchical Process AHP. The extension of the fuzzy Technique for Order Preference by Similarity to Ideal Solution TOPSIS is applied to rank quality goals. The proposed model is illustrated by an example.

New integrated approach to the problem of ranking and supplier selection under uncertainties

The problem of ranking and supplier selection in the uncertain environment is part of a purchasing plan and its relationship has a critical effect on the competitive advantage (high-quality products at lower cost with higher customer satisfaction) of each industrial organization. The considered problem can be stated as a multicriteria decision problem which includes both quantitative and qualitative criteria. The criteria present supplier performances which are defined by the purchasing Management Team depending on the size of industrial organizations and on production type. In this paper, the Management Team, using European Union (EU) recommendations, made a choice of criteria for supplier evaluation. The fuzzy rating weights of each pair of the considered criteria and uncertain criteria values are described by linguistic expressions which are modelled by triangular fuzzy numbers. The fuzzy extent approach for the synthetic extent values of the pairwise comparison for handling fuzzy analytic hierarchical process (AHP) is used to calculate the weight vector. The extension of the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is applied to rank the suppliers. The proposed model is illustrated by an example. It is shown that the developed model is highly suitable as a decision-making tool for reaching decisions about supplier selection.

Evaluation and Ranking of Organizational Resilience Factors by Using a Two-Step Fuzzy AHP and Fuzzy TOPSIS

We presented a novel fuzzy multicriteria decision making approach to evaluate and rank organizational resilience factors with respect to user preference orders. Due to vagueness of the decision data, the precise numerical data are inadequate for real-life business situations. Human judgements can be expressed by linguistic expressions which are modeled by fuzzy sets. The complexity of the considered problem calls for analytic methods rather than intuitive decisions. Two fuzzy multi-criteria methods are proposed for solving the treated problem: Fuzzy Analytic Hierarchical Process (FAHP) is applied to determine the relative importance of business processes and the relative importance of organizational resilience factors under each business process, and an extension of the fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) is applied to rank the organizational resilience factors. With respect to complexity and the type of considered management problem, we introduce a modified fuzzy decision matrix. The proposed algorithm has efficiently been applied in the assessment of organizational resilience factors to small and medium enterprises of the process industry.

An assessment of distance learning laboratory objectives for control engineering education

The concept of web laboratories with remotely controlled laboratory set ups or virtual laboratories with different simulations have an important role in engineering education and training. This paper presents an evaluation of the fundamental objectives of laboratories for distance education, comparing the effectiveness of a remotely controlled approach versus simulations. The results and analysis show that students prefer remotely controlled laboratories compared to simulation labs. The results show that remotely controlled laboratories better fulfill objectives important for laboratory exercises.

The evaluation and ranking of medical device suppliers by using fuzzy topsis methodology

The aim of this study is to propose a fuzzy multi-criteria decision-making approach (MCDM) to evaluate suppliers of one kind of medical device with respect to numerous criteria, simultaneously taking into account the type of each criteria and its relative importance. Two fuzzy MCDM methods are proposed for solving the treated problem. In the first step, the fuzzy pair-wise comparison matrix of the relative importance of criteria is constructed. The weight vector is calculated by using the developed procedure, and in the second step, the fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) is applied in order to rank possible suppliers of the considered kind of medical device. The rank is obtained using the process of fuzzy number comparison. A case study with real-life data is presented to verify the proposed method.

A fuzzy model for assessing risk of occupational safety in the processing industry

Abstract Managing occupational safety in any kind of industry, especially in processing, is very important and complex. This paper develops a new method for occupational risk assessment in the presence of uncertainties. Uncertain values of hazardous factors and consequence frequencies are described with linguistic expressions defined by a safety management team. They are modeled with fuzzy sets. Consequence severities depend on current hazardous factors, and their values are calculated with the proposed procedure. The proposed model is tested with real-life data from fruit processing firms in Central Serbia.

A new fuzzy model for determining risk level on the workplaces in manufacturing small and medium enterprises

Crucial part of the reduction and prevention of workplace injuries and maintaining occupational safety and health system takes risk assessment model, which appears as one of the most important. Frequent advances in all fields cause changes in risk assessment models in relation to the traditional approach. This article is focused on providing reliable assessment tool that will enable suitable and easy usage of methodology for risk evaluation in the workplaces in manufacturing small and medium enterprises. For that purpose, three groups of factors are introduced and their hierarchical structures are defined. Pre-defined linguistic expressions are used to describe relative importance of factors, sub-factors and values of sub-factors. Fuzzy set theory is used for modeling of existing uncertainties. The levels of identified risks are given by exact way, using fuzzy logic. The proposed model is tested with real-life data from manufacturing small and medium enterprises.

The evaluation and improvement of process quality by using the fuzzy sets theory and genetic algorithm approach

The performance evaluation of business processes in uncertain environments has important consequences for investors, stakeholders and has critical importance for the improvement of business processes, which is one of the requirements of ISO 9001. In this paper, a new fuzzy model is proposed for evaluation and improvement of process quality. The fuzzy ratings of the Key Performance Indicators (KPIs) are stated as fuzzy pair-wise comparison matrices (by analogy to the AHP framework). By using the developed procedure, the fuzzy weights of KPIs are given. The KPI values are based on the assessment of decision makers. The developed solution, based on the genetic algorithm approach, is presented and tested on data from 53 Serbian manufacturing SMEs. The presented solution enables quality assessment of a purchasing process, the fuzzy ranking of KPIs, the selection of critical KPIs by using an exact approach, optimization and the provision of the basis for successful improvement of purchasing

A model of the assessment and optimisation of production process quality using the fuzzy sets and genetic algorithm approach

In this paper, the production process is decomposed for typical manufacturing small and medium sized enterprises (SMEs) and the metrics of the defined sub processes, based on the requirements of ISO 9001:2008, are developed. The weight values of production process performance indicators are defined, using the experience of decision makers from the analysed manufacturing SMEs, and calculated using the fuzzy set approach. Finally, the developed solution, based on the genetic algorithm approach, is presented and tested on data from 112 Serbian manufacturing SMEs. The presented solution enables quality assessment of a production process, the ranking of indicators, optimisation and provides the basis for successful improvement of the production process quality. [Received 13 April 2013; Revised 7 October 2013; Accepted 5 November 2013]

Organisational resilience in a cloud-based enterprise in a supply chain: a challenge for innovative SMEs

The main idea of the paper is to analyse the organisational resilience potential of enterprises that may be modelled as a non-cloud enterprise or modelled from the perspective of being a cloud-based enterprise in a supply chain. In this manner, the model of an organisation is presented as a network of business processes. Organisational resilience factors (RFs) are assessed on the level of each business process and the overall level of organisational resilience potential is obtained for each organisation. The level of organisational resilience potential in these organisations is assessed when the enterprise is modelled, in the first place, as a non-cloud enterprise and also modelled from the perspective of being a cloud-based enterprise in a supply chain. In this way, the level of organisational resilience potential may be compared and analysed, which is a significant benchmark starting point for this research and practice domain.