Saroj Kumar Dash

Bio: Saroj Kumar Dash is an academic researcher. The author has contributed to research in topics: Municipal solid waste. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

Haar FCM with DEMATEL Technique to Analyze the Solid Waste Management

Abstract: An interesting attempt is taken to form a hybrid model by integrating Fuzzy Cognitive Map (FCM), the Delphi Method, and the DEMATEL method through the Haar ranking of Hexagonal Fuzzy Number. To examine this model, the problem of solid waste management is taken. Solid waste arises from human and animal activities can generate major health problems and horrible living environment when they are not dumped of safely and appropriately. The proper disposal of solid waste helps to reduce the terrible impacts on both human health and environment to sustain economic growth and better quality of life. Therefore, this present study analyzes the solid waste management through the Haar FCM with DEMATEL technique.

Modelling the Barriers to Sustainable Waste Management in the Plastic-Manufacturing Industry: An Emerging Economy Perspective

Abstract: Sustainable waste management (SWM) is an important goal for the plastic manufacturing industry, which is aiming toward enhancing its economic, environmental, and social sustainability in recent years. However, plastic manufacturing industries in developing countries like Bangladesh are yet to establish efficient SWM systems despite the amount of solid plastic waste continually rising across all sectors. This paper investigates the underexplored barriers to implementing SWM in the Bangladeshi plastic industry. First, it employs the Delphi method to identify the 16 most relevant barriers to SWM through a literature review and expert feedback. Then, using an integrated grey theory and decision-making trial and evaluation laboratory (DEMATEL) method-based framework, it evaluates these 16 barriers to examine their interrelationships in the context of emerging economies. The findings show that the five most significant barriers are as follows: lack of awareness of and knowledge about plastic waste disposal, lack of compliant waste management, lack of a sense of environmental responsibility on the part of manufacturers, lack of systematic waste collection and effective dumping-ground utilization and lack of proper environmental policies, legislations, and regulations. This study presents valuable insights that can deeply contribute to the literature on SWM, enabling scholars, policymakers, and industrial managers to practice sustainability more effectively in the plastic manufacturing industry.

Haar and Yager’s Ranking Methods for Intuitionistic Dense Fuzzy Set

Abstract: The world is full of uncertainties. To deal with the uncertain nature mathematically, fuzzy set came into being. Fuzzy set was then extended to intuitionistic fuzzy set where the set itself contains its membership, non-membership and its hesitancy. When the entire components converge at a crisp numberin a set as n→ ∞, dense fuzzy set was identified. Thus, by introducing dense fuzzy set into the field of intuitionistic set theory, intuitionistic dense fuzzy set was introduced. In this present study, an effort has been made in ranking an intuitionistic dense fuzzy set. Ranking plays a vital role in fuzzy decision making problems and in numerous fuzzy applications. Ranking a fuzzy tuples is not as easy as an ascending order ranking. There are numerous methods for ranking a fuzzy number. But in all the cases it is found that, they end up in giving unsatisfactory results due to the complexity of the problem in one way or the other. Thus, this paper paves a way in finding a ranking method for the intuitionistic dense fuzzy set by means of Haar ranking and Yager’s ranking. Numerical examples are given and Cauchy’s sequence has been utilized for better illustration.

An integrated intuitionistic dense fuzzy Entropy-COPRAS-WASPAS approach for manufacturing robot selection

Abstract: Manufacturing robots are used for industrial purposes. Robots used for manufacturing purpose have the power to create products from raw materials and are capable of operating endlessly even in lights-out situations for continuous production. Manufacturing robots can be used in applications like arc welding, spot welding, materials handling, machine tending, painting, machine cutting and so on. Selecting a robot for a given application is complex. However, robot selection is used in selecting a suitable robot for the preferred output with specific application ability. In recent years, many authors used multi-criteria decision-making methods to select a robot that meets the need. This study presents a hybrid model by integrating complex proportional assessment (COPRAS) with the weighted aggregates sum product assessment (WASPAS) methods in intuitionistic dense fuzzy set to select a manufacturing robot for a particular application. Intuitionistic dense fuzzy entropy is used in calculating the weights for the criteria and intuitionistic dense fuzzy COPRAS and WASPAS are used in ranking the best alternatives where in the optimum types of robots are obtained. Here, intuitionistic dense fuzzy sets are used as it is capable of dealing with the intangible factors while selecting a robot. On the basis of the manufacturing robot selection, two comparisons are given. First, the results are compared with various λ values between 0 and 1 and second the results are compared with the fuzzy set, intuitionistic fuzzy set and the dense fuzzy set to show the effectiveness of the proposed methodology with the intuitionistic dense fuzzy set.