Inflation has emerged as a significant economic challenge in Ethiopia, particularly in the Illu Abba Bor Zone, where its effects are profoundly felt by households and businesses alike. This study aims to identify and analyze the key determinants of inflation in this region using regression models. Data was collected from various sources, including government reports, economic databases, and household surveys, covering a range of variables such as money supply, consumer price index (CPI), agricultural output, exchange rates, and external economic factors.

The regression analysis revealed that several factors significantly influence inflation in Illu Abba Bor Zone. Notably, an increase in money supply was found to have a direct correlation with rising inflation rates, underscoring the impact of monetary policy in the region. Additionally, fluctuations in agricultural output emerged as critical determinants, highlighting the vulnerability of the local economy to agricultural productivity and climatic conditions. The study also identified the exchange rate and global commodity prices as significant external factors influencing inflationary trends.

The findings of this research provide valuable insights for policymakers and economic stakeholders, emphasizing the need for targeted economic interventions and sound monetary policies to mitigate inflationary pressures. By understanding the dynamics of inflation drivers specific to Illu Abba Bor Zone, this study contributes to the broader discourse on economic stability and sustainable development in Ethiopia. Future research should explore the long-term effects of these determinants on inflation and consider additional qualitative factors that may influence the region's economic landscape.

The advent of 3D printing technology has revolutionized manufacturing processes across various industries, offering unprecedented design freedom and customization capabilities. This study explores the critical interplay between polymers, precision, and surface topography in 3D printed structures. We investigate how different polymer materials, such as thermoplastics, elastomers, and composites, influence the dimensional accuracy and surface characteristics of printed objects. Through a series of experiments and analyses, we evaluate the effects of print parameters—such as layer height, print speed, and temperature—on the final quality of the printed surfaces.

We employ advanced measurement techniques, including scanning electron microscopy (SEM) and profilometry, to assess the surface roughness and topographical features of the printed specimens. Our findings reveal that the choice of polymer significantly affects both the precision of the prints and the resultant surface texture. Furthermore, we discuss how surface roughness can impact functional properties, such as adhesion, wear resistance, and aesthetic quality, emphasizing the importance of selecting appropriate materials and optimizing print settings to achieve desired outcomes.

Ultimately, this research contributes to the understanding of how polymer characteristics can be harnessed to enhance the performance and application of 3D printed structures, paving the way for innovations in fields such as biomedical engineering, aerospace, and consumer goods.