Optimization Techniques in Industrial Mathematics for Sustainable Manufacturing Systems

Md. Habijulla Fakir

Apr-May-Jun

Abstract
With environmental problems, limited resources, and global competition becoming more pressing, sustainable manufacturing is now a primary concern for the progress of the industrial sector. This study emphasizes the role of optimization techniques in industrial mathematics for improving the sustainability of manufacturing systems. It examines the applications of mathematical optimization, linear programming, operations research, simulation, and artificial intelligence for optimizing industrial production and managing resources. A qualitative and quantitative analytical method was used to test the optimization methods and their impact on production efficiency, waste minimization, energy savings, and supply chain management. The results show that industries using optimization models achieved significant improvements in operational efficiency, cost savings, energy management, and reduced environmental effects. In optimization-based systems, increases in production efficiency, reductions in industrial waste, reductions in energy consumption, and reductions in carbon emissions were 28%, 30%, 22%, and 27%, respectively. The study also highlights the development of AI-optimized and Industry 4.0 technologies for new manufacturing systems that are intelligent and adaptive. However, problems such as computational complexity, lack of technical knowledge, and budget constraints remain to be overcome. Finally, it is concluded that optimization techniques in industrial mathematics are crucial tools for achieving a sustainable manufacturing system and industrial competitiveness in today's global economy.

Keyword: Industrial Mathematics and Optimization Techniques, Sustainable Manufacturing, Industrial Linear Programming, Operations Research, Industry 4.0, and Artificial Intelligence

Research Area: Mathematics

Country: Bangladesh

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