Modelling the Barriers to Circular Economy Practices in the Indian State of Tamil Nadu in Managing E-Wastes to Achieve Green Environment

Owing to a heightened necessity, the consumption rate of electronic items has increased exponentially in recent decades, resulting in huge quantities of electronic waste (e-waste). Though increasing e-waste has many adverse impacts, it also provides an ample opportunity of recover value from the waste through circular economy (CE) practices. However, the adoption to CE practices is jeopardised by myriad barriers. This paper wishes to identify and evaluate the barriers that hamper CE practices in e-waste management. First, 30 barriers to the adoption of CE practices in India e-waste management are identified by reviewing the existing literature and conformed using experts’ inputs. Furthermore, based on the experts’ opinion, the thirty barriers are categorised into social, economic, and environmental categories. An integrated multi-criteria decision-making (MCDM) framework of fuzzy decision-making trial and evaluation laboratories (FDEMATEL) and fuzzy analytic network processes (FANP) is employed to understand the causal interrelationship and also to rank the barriers. Uncertainty about the profitability of the circular economy (E9), insufficient market demand (E6), lack of successful circular business model (E5), shortage of high-quality recycling materials (E4), and lack of adequate technology (EN6) have been identified as the top five barriers to the incorporation of CE practice in e-waste management. Out of these 30 barriers, 12 come under the cause group and 18 come under the effect group. Understanding the causal interrelationship and prioritization of barriers provide better insight into the barriers. This study offers some managerial implications that could assist industrial practitioners and policymakers

AI-driven techniques for controlling the metal melting production: a review, processes, enabling technologies, solutions, and research challenges

Artificial Intelligence has left no stone unturned, and mechanical engineering is one of its biggest consumers. Such technological advancements in metal melting can help in process simplification, hazard reduction, human involvement reduction & lesser process time. Implementing the AI models in the melting technology will ultimately help various industries, i.e., Foundry, Architecture, Jewelry Industry, etc. This review extensively sheds light on Artificial Intelligence models implemented in metal melting processes or the metal melting aspect, alongside explaining additive manufacturing as a competitor to the current melting processes and its advances in metal melting and AI implementations

3rd National Conference on Image Processing, Computing, Communication, Networking and Data Analytics

This volume contains contributed articles presented in the conference NCICCNDA 2018, organized by the Department of Computer Science and Engineering, GSSS Institute of Engineering and Technology for Women, Mysore, Karnataka (India) on 28th April 2018