Yazar "Gangadhari, Rajan Kumar" seçeneğine göre listele

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    Breaking barriers toward a net-zero economy
    (Wiley, 2023) Gangadhari, Rajan Kumar; Karadayi-Usta, Saliha; Lim, Weng Marc
    Following The Paris Agreement and United Nations Sustainable Development Goals (SDGs), a significant number of nations globally have pledged to achieve net-zero emissions by 2050. The goal is to lower emissions while emphasizing economically and socially sustainable practices. To meet these sustainable development targets, some countries have introduced industry-specific roadmaps, showing how nations can systematically allocate resources to attain net zero, which includes balancing energy and production needs with existing energy sources. Such a transformation will inevitably encounter obstacles, particularly in reducing reliance on non-renewable fuels and mitigating existing emissions. This study focuses on identifying these impediments to achieving a net-zero economy. Utilizing the novel concept of plithogenic sets, the study examines the interdependent relationships among various barriers, providing insights into navigating these constraints. The findings reveal external, economic, and policy and framework obstacles and their subsequent impact on organizational and technological challenges that must be surmounted to reach net-zero status.
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    Navigating the new normal: Redefining N95 respirator design with an integrated text mining and quality function deployment-based optimization model
    (Pergamon-Elsevier Science Ltd, 2024) Gangadhari, Rajan Kumar; Tarei, Pradeep Kumar; Chand, Pushpendu; Rabiee, Meysam; Delen, Dursun
    The global surge in demand during the pandemic led to a proliferation of substandard surgical N95 respirators, particularly in the e-commerce market, due to a lack of regulatory standards. In the post-pandemic era, the essential role of these respirators in protecting against airborne hazards and infectious agents persists. Addressing the need for standardized design and manufacturing processes, this research proposes a three-phased integrated decision-making framework. Firstly, text-mining algorithms analyze online consumer reviews to identify critical characteristics of surgical N95 respirators. Subsequently, a spherical-fuzzy-based quality function deployment assesses manufacturing capabilities in alignment with consumer requirements. The final phase utilizes Mixed Integer Non-linear Programming to optimize utility and select the most effective design, considering both technical specifications and consumer needs. The proposed framework is validated through a case study, revealing technical characteristics crucial for organizations in product development. The findings not only offer insights into the technical aspects of N95 respirators but also recommend essential product characteristic tests during manufacturing and certification. This information is vital for educating consumers and guiding companies in the effective use and development of Surgical N95 respirators in the post-pandemic landscape, addressing the challenges posed by inferior and counterfeit products.