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Vice Rector, Research & Innovation, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan
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Associate Professor of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan
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Senior Lecturer of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan
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Senior Lecturer of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan
Associate Professor of Philology, Faculty of Humanities & Pedagogy, Linguistics, Pedagogy, Turan International University , Namangan , Uzbekistan
Manufacturing systems that are technology-intensive have high interdependencies between financial decisions on investments, the change in production capacity, and operational efficiency. Traditional methods tend to look at financial and operational planning in isolation, resulting in poor performance of the system and poor use of resources. In order to overcome this shortcoming, this paper has suggested a combined techno-economic optimization framework, which models financial performance, production planning, technology-based capacity development, and energy efficiency together in a single mathematical expression. The manufacturing system is modeled in terms of a multi-period constrained optimization problem, in which the investment of technology, production output, capacity variation, and energy consumption are all optimized. A multi-objective function that combines financial and operational functions is formulated using diversity of weights, and an algorithm to find a solution is presented to achieve computational feasibility. The framework proposed is assessed by the numerical simulation in a 5-period planning horizon. Findings show that when there is a technology investment, capacity is incrementally expanded between 100 and 180 units at production levels that are viable. The integrated strategy has a total financial performance of 742.6 with a return on investment of 1.48 and average capacity utilization of 0.82. The energy efficiency is increasing to an average of 2.91, which shows that efforts are made to plan production considering energy efficiency. Sensitivity analysis also reveals that an increase in the technology gain coefficient will increase the Technical-Economic Performance Index to a maximum of 3.24, followed by a decreasing marginal gain. On the whole, the findings prove that the suggested framework offers a powerful and technologically efficient decision-support tool that can be applied to streamline financial and operational performance in technology-intensive production systems.
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