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4. Life Cycle Assessment of Electrocoagulation Pilot Unit for Dairy Wastewater Treatment

Author

Ankoliya, Dipak, Raninga, Milan, Patel, Dhaval, Mudgal, Varsha, Vallamsetty, Prashanthi, Mudgal, Anurag, Sinha, Manish Kumar, Patel, Vivek K., Patel, Jatin, Choksi, Himanshu, Dey, Prasanta, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Lu, Xinzheng, Series Editor, Mudgal, Anurag, editor, Davies, Philip, editor, Kennedy, Maria, editor, Zaragoza, Guillermo, editor, and Park, Kiho, editor

Published
2024
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7. Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises.

Author

Dey, Prasanta Kumar, Chowdhury, Soumyadeb, Abadie, Amelie, Vann Yaroson, Emilia, and Sarkar, Sobhan

Subjects
SMALL business, SUPPLY chain management, SUPPLY chains, SUSTAINABILITY, STRUCTURAL equation modeling, PRODUCTION management (Manufacturing)
Abstract

Despite the exponential growth of artificial intelligence (AI) research in operations, supply chain, and productions management literature, empirical insights on how organisational behavioural mechanisms at the human–technology interface will facilitate AI adoption in small- and medium-sized enterprises (SMEs), and subsequent impact of the adoption on sustainable practices and supply chain resilience (SCR) is under-researched. To bridge these gaps, we integrate resource orchestration and knowledge-based view theoretical perspectives to develop a novel structural model examining antecedents to SCR and AI adoption, considering AI adoption as a pivot for facilitating SCR. The structural equation modelling technique was employed on the data collected from 280 Vietnamese manufacturing SMEs' operations managers. Our results demonstrate that leadership will drive AI adoption by creating a data-driven, digital and conducive culture, and strengthening employee skills and competencies. Furthermore, AI adoption positively influences CE practices, SC agility and risk management, which will help to achieve SCR. For managers, the importance of internal organisational employee-centric mechanisms to create value from AI adoption without impeding business value is highlighted. We reveal the enablers that will help in transforming SMEs to become resilient by deriving appropriate responses to unprecedented disruptions through data-driven decision-making leveraging AI adoption. [ABSTRACT FROM AUTHOR]

Published
2024
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19. A systematic literature review exploring and linking circular economy and sustainable development goals in the past three decades (1991–2022).

Author

Vann Yaroson, Emilia, Chowdhury, Soumyadeb, Mangla, Sachin Kumar, Dey, Prasanta, Chan, Felix T. S., and Roux, Melanie

Subjects
CIRCULAR economy, SUSTAINABLE development, KNOWLEDGE management, SUPPLY chain management, ORGANIZATIONAL performance, INTERNATIONAL trade
Abstract

Amid the escalating environmental crises and economic disparities, Circular Economy (CE) has garnered recognition as a pragmatic mechanism for achieving Sustainable Development Goals (SDGs). In response, several supply chain organisations are integrating CE strategies into their business operations and production processes. Despite these developments and since the introduction of Business Charter for Sustainable Development by the International Chamber of Commerce in 1991, the academic corpus comprehensively connecting CE research themes, catalysts, deterrents, practices with the SDGs has remained limited. To bridge this gap, we present a systematic literature review (SLR) of CE research in operations, supply chain and production management encompassing a time span of 31 years (January 1991 – June 2022), by sourcing, screening, and analysing articles obtained from multiple research databases. Our thematic coding analysis generated ten research themes, and subsequently linking them with relevant SDGs. Additionally, we interweaved CE catalysts and deterrents, establishing a connection with the SDGs. This is further enriched with CE strategies aimed at equipping business practitioners to enhance sustainable business performance and contributing to specific SDGs. Lastly, we delineate CE knowledge data management and priority actions frameworks to aid organisations to enhance employee capability and actively leverage digital technologies for implementing CE strategies. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Developing a plastic cycle toward circular economy practice

Author

Nguyen Tuyet T. A., Ta Yen T., and Dey Prasanta K.

Subjects
plastic cycle, io table, solid waste management, circular economy, vietnam, Chemistry, QD1-999
Abstract

This study develops a plastic cycle toward circular economy practice in Vietnam. First, we analyze inter-relationships between economic sectors and environmental issues concerning plastic waste in 2018. The research method integrates interdisciplinary balance with life cycle inventory, in which input–output (IO) table is both an econometric tool and original database to determine plastic IO between industries. As a result, over 60% of plastics after use was recycled for the production process (called recycled plastics) and nearly 40% of plastics after-use left the process (called disposed plastics). Within the recycled plastics, there was 10–15% of informal recycling collection from trade villages; within the disposed plastics, there was 13–18% unable to be collected and uncontrollably disposed to the environment. Then, we construct the plastic cycle, in which all the imported/domestic flows, single/multiple uses, and recycle/disposal flows are represented in proportional dimensions. This overall yet quantitative picture is an important data-driven basis for proposing plastic waste management solutions toward circular economy practice. As analyzed, the most challenge for waste management in Vietnam is to control single-use products (occupied 15.96% of total plastics) and indiscriminate waste in the environment (occupied 20.36% of total plastics). The case study for polyethylene terephthalate shows the need for expanding producer’s responsibilities to improve plastic recovery efficiency.

Published
2022
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44. Contributors

Author

Abdolghaffari, Amir Hossein, primary, Adhikari-Devkota, Anjana, additional, Ahmed, Salman, additional, Alhasani, Reem Hasaballah, additional, Alqarni, Mohammed, additional, Althobaiti, Norah A., additional, Alves, Renata de Sousa, additional, Arya, Rajeshwar K.K., additional, Asghari, Mohammad Hossein, additional, Azeemah, Chundoo B., additional, Azzopardi, Joseph I., additional, Baureek, Nawshin, additional, Behl, Tapan, additional, Belwal, Tarun, additional, Benmelouka, Amira Y., additional, Bhandari, Dhaka R., additional, Bisht, Dheeraj, additional, Bisht, Arti, additional, Blundell, Renald, additional, Blázovics, Anna, additional, Bouhenni, Hasna, additional, Braga, Jacqueline Ramos Machado, additional, Chafaa, Meriem, additional, Chatterjee, Sharmistha, additional, Chauhdary, Zunera, additional, Chen, Xiuping, additional, Chen, Lei, additional, Coy-Barrera, Ericsson, additional, Das, Abhishek K., additional, Devkota, Hari P., additional, Dey, Prasanta, additional, Dhariwal, Arasana, additional, Dilmar A., Sanaa, additional, Doukani, Koula, additional, Durgapal, Sumit, additional, Désiré A.-L., Daphne, additional, Ezzat, Shahira M., additional, Fakhri, Sajad, additional, Farzaei, Mohammad Hosein, additional, Fatimah-Tuz-Zohra, Joomun B., additional, Garg, Aakriti, additional, Ghosh, Noyel, additional, Ghosh, Sumit, additional, Gour, Jalaj K., additional, Gurgel, Daniel Cordeiro, additional, Hassani, Shokoufeh, additional, Hossain, Uday, additional, Hussein, Subratty A., additional, Iqbal, Shabnoor, additional, Jantwal, Arvind, additional, Jorge, Roberta Jeane Bezerra, additional, Joshi, Tanuj, additional, Juyal, Vijay, additional, Kaldate, Rahul, additional, Karatoprak, Gökçe Ş., additional, Karmakar, Arnab, additional, Khadaroo, S. Khatoon, additional, Khan, Haroon, additional, Khan, Abdul H., additional, Khan, Ziyad, additional, Kumar, Anoop, additional, Kumar, Prashant, additional, Kumar, Aadesh, additional, Kumar, Manish, additional, Kumar, Ankit, additional, Laxmi, Jankee T., additional, Lobine, Devina, additional, M. Irfaan, Meeajan, additional, Maggi, Filippo, additional, Mahdy, Nihal M. El, additional, Mahfouz, Marwa M., additional, Mahomoodally, Mohamad Fawzi, additional, Mandal, Ankita, additional, Marinho, Aline Diogo, additional, Maurya, Harikesh, additional, Miao, Lingchao, additional, Moloudizargari, Milad, additional, Momtaz, Saeideh, additional, Mujtaba Shah, Ghulam, additional, Nabavi, Seyed Mohammad, additional, Nabee, Nouzaifa, additional, Nogueira-Junior, Francisco Assis, additional, Nunes-Pinheiro, Diana Célia Sousa, additional, Pandey, Abhay K., additional, Patni, Kiran, additional, Patni, Pooja, additional, Patni, Lokesh, additional, Pratap, Vinay, additional, Rajpal, Govind, additional, Ramos, Márcia Maria Vieira, additional, Rana, Harvesh Kumar, additional, Rana, Mahendra, additional, Rana, Amita J., additional, Rasool, Shahid, additional, Rasul, Azhar, additional, Rasul, Akhtar, additional, Rosette M. A.-L., Elodie, additional, Sah, Archana N., additional, Salem, Mohamed A., additional, Sarkar, Kasturi, additional, Selles, Ammar S.M., additional, Shah, Muhammad Ajmal, additional, Shah, Ghulam Mujtaba, additional, Shah, Shahid, additional, Sharma, Ruchika, additional, Sil, Parames C., additional, Silva, Ana Sanches, additional, Silveira, João Alison de Moraes, additional, Singh, Amit Kumar, additional, Singh, Anita, additional, Singh, Manoj K., additional, Singh, Sushil Kumar, additional, Singh, Laxman, additional, Soudani, Leila, additional, Süntar, Ipek, additional, Tewari, Devesh, additional, Tiwari, Nidhi, additional, Ullah, Malik Saad, additional, Ullah, Hammad, additional, Upadhyay, Jyoti, additional, Vasconcelos, Mirele da Silveira, additional, Visvarma, Sandeep, additional, Xiao, Jianbo, additional, Xie, Yixi, additional, Yakıncı, Ömer F., additional, Yang, Li, additional, Zaynab, Toorabally B., additional, Zhang, Haolin, additional, da Silva Mendes, Francisco Rogênio, additional, de Melo, Dirce Fernandes, additional, de Paula, Paulo Carvalho, additional, de Siqueira Oliveira, Luciana, additional, de Sousa, Felipe Domingos, additional, de Souza, Tamiris de Fátima Goebel, additional, and Álvarez-Caballero, Juan M., additional

Published
2022
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45. A model for the optimal design of a supply chain network driven by stochastic fluctuations

Author

Petridis, Kostas, Chattopadhyay, Amit K., and Dey, Prasanta K.

Subjects
Mathematics - Optimization and Control, Physics - Physics and Society
Abstract

Supply chain optimization schemes have more often than not underplayed the role of inherent stochastic fluctuations in the associated variables. The present article focuses on the associated reengagement and correlated renormalization of supply chain predictions now with the inclusion of stochasticity induced fluctuations in the structure. With a processing production plant in mind that involves stochastically varying production and transportation costs both from the site to the plant as well as from the plant to the customer base, this article proves that the producer may benefit through better outlay in the form of higher sale prices with lowered optimized production costs only through a suitable selective choice of producers whose production cost probability density function abides a Pareto distribution. Lower the Pareto exponent, better is the supply chain prediction for cost optimization. On the other hand, other symmetric (normal) and asymmetric (lognormal) distributions lead to upscaled costs both in terms of inlays and outlays. While this is an averaged out statistics over large time regimes, transient features may still affect such probabilistic predictions and offset results. The predictions are shown to be in good harmony with model results shown., Comment: 25 pages, 7 figures, 1 table

Published
2015

46. Dynamics of Spatial Heterogeneity in Landfill - A Stochastic Analysis

Author

Chattopadhyay, Amit Kumar, Dey, Prasanta Kumar, and Ghosh, Sadhan Kumar

Subjects
Nonlinear Sciences - Adaptation and Self-Organizing Systems
Abstract

A landfill represents a complex and dynamically evolving structure that can be stochastically perturbed by exogenous factors. Both thermodynamic (equilibrium) and time varying (non-steady state) properties of a landfill are affected by spatially heterogenous and nonlinear subprocesses that combine with constraining initial and boundary conditions arising from the associated surroundings. While multiple approaches have been made to model landfill statistics by incorporating spatially dependent parameters on the one hand (data based approach) and continuum dynamical mass-balance equations on the other (equation based modelling), practically no attempt has been made to amalgamate these two approaches while also incorporating inherent stochastically induced fluctuations affecting the process overall. In this article, we will implement a minimalist scheme of modelling the time evolution of a realistic three dimensional landfill through a reaction-diffusion based approach, focusing on the coupled interactions of four key variables - solid mass density, hydrolysed mass density, acetogenic mass density and methanogenic mass density. In a marked departure from previous predictions, our results indicate that close to the linearly stable limit, the large time steady state properties, arising out of a series of complex coupled interactions between the stochastically driven variables, are scarcely affected by the biochemical growth-decay statistics. Our results clearly show that an equilibrium landfill structure relates to plant production times of approximately 20-30 years instead of the previous (incorrect) deterministic model predictions of 50 years and above., Comment: To be published in Applied Mathematical Modelling; 8 pages, 5 figures

Published
2015

50. Genomic plasticity associated with antimicrobial resistance in Vibrio cholerae

Author

Verma, Jyoti, Bag, Satyabrata, Saha, Bipasa, Kumar, Pawan, Ghosh, Tarini Shankar, Dayal, Mayanka, Senapati, Tarosi, Mehra, Seema, Dey, Prasanta, Desigamani, Anbumani, Kumar, Dhirendra, Rana, Preety, Kumar, Bhoj, Maiti, Tushar K., Sharma, Naresh C., Bhadra, Rupak K., Mutreja, Ankur, Nair, G. Balakrish, Ramamurthy, Thandavarayan, and Das, Bhabatosh

Published
2019

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