Treffer: Optimizing Manufacturing Processes through Advanced Process Engineering Techniques: A Case Study of Energy Efficiency, Waste Reduction, and Environmental Sustainability: Review.

Manufacturing processes has evolved over the last century with the incorporation of a lot of new concepts. The industry as today is faced with a growing demand for higher quality products, tailored to specifications, energy efficient processes, ecofriendly processes and increased process sophistication with fewer human operations and much reliance on artificial intelligence. Thus, there is so much reliance on technology, science, innovation, interdisciplinary research and development (R&D) to either develop advanced manufacturing processes or optimize the existing processes to achieve the desired goals. In this review study, emphasis is placed on the various advanced process engineering techniques for optimizing manufacturing processes. Advanced process engineering techniques encompass a range of methodologies and tools used to optimize and improve industrial processes across various fields, including chemical engineering, manufacturing, pharmaceuticals, and biotechnology. These techniques leverage on advanced computational methods, data analysis, optimization algorithms, and innovative approaches to enhance process efficiency, reduce costs, minimize waste, and ensure product quality. Optimizing energy use in industry contributes to sustainable engineering by conserving resources, reducing emissions, and promoting renewable usage, thus aligning with the global need for sustainable development. Thus, from studies reviewed, process simulation using Aspen HYSIS was adopted in optimizing the energy efficiency in SIBUR Petrochemical Company, and it resulted in the recovery of over 25% of the overall energy consumption, and an IRR greater than 25%. Other studies revealed that the implementation of Just-in-time inventory (JIT) methodology results in waste reduction. Lastly, a study shows that the adoption of eco-design strategies or characteristic in a manufacturing process, influences enterprise sustainability innovativeness. [ABSTRACT FROM AUTHOR]

Copyright of FUPRE Journal of Scientific & Industrial Research is the property of FUPRE Journal of Scientific & Industrial Research and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)