The main objective of this research study is to optimize the printing parameters that can be used in the FDM (fusion deposition modeling) production method to obtain the lowest production time and best printing parameter of PLA (polylactic acid) filament with the tensile test. The printing parameter that can be used in FDM machines such as extruder temperature, bed temperature, layer height, printing speed, travel speed, infill, and shell count is taken into account for optimization. In addition, the tensile specimens from ASTM (American Society for Testing and Materials) D638 standard were manufactured by PLA filament with the above‐modified printing parameters. The best printing parameters for PLA products were found by the time recorded during production and tensile test results after production. Thus, through this research, one can find the best PLA filament printing parameters and their timing.

The mass production and consumption of plastics have serious effects on the environment, human health, and livelihood. Hence, global efforts to reduce plastic generation must be realized. This study aimed to determine the prevalence of microplastics in mangrove sediments of Cabadbaran, Buenavista, and Nasipit in Butuan Bay, Philippines. Seventy-two (72) microplastic particles were extracted from mangrove sediments dominated by fibrous type (71%) and blue (35%) as the most common color. Attenuated total reflectance–Fourier transform infrared (ATR–FTIR) spectroscopy was used to assess the polymer type of microplastics. Results reveal a total of six polymer types including high-density polyethylene, low-density polyethylene, polyethylene terephthalate, ethylene-vinyl acetate, polyamide, and polypropylene, with the latter comprising 39% of samples, the highest among the extracted particles. Overall, Nasipit (71.1/kg) obtained the highest microplastic density followed by Buenavista (48.9/kg) and Cabadbaran (40.0/kg). These data will serve as a piece of baseline information in crafting important environmental policies to address plastic pollution issues in the area. Long-term studies are recommended to better understand, monitor, and prevent further microplastic pollution in Butuan Bay.

A straightforward approach to recycle waste expanded polystyrene (EPS) foam to produce polystyrene (PS) microfibers using the improvised centrifugal spinning technique is demonstrated in this work. A typical benchtop centrifuge was improvised and used as a centrifugal spinning device. The obtained PS microfibers were characterized for their potential application for oil adsorption. Fourier transform infrared spectroscopy results revealed similarity on the transmission bands of EPS foam and PS microfibers suggesting the preservation of the EPS foam’s chemical composition after the centrifugal spinning process. Scanning electron microscopy displayed well-defined fibers with an average diameter of 3.14 ± 0.59 μm. At the same time, energy dispersive X-ray spectroscopy revealed the presence of carbon and oxygen as the primary components of the fibers. Contact angle (θ_CA) measurements showed the more enhanced hydrophobicity of the PS microfiber (θ_CA= 100.2 ± 1.3°) compared to the untreated EPS foam (θ_CA= 92.9 ± 3.5°). The PS microfiber also displayed better oleophilicity compared to EPS foam. Finally, the fabricated PS microfibers demonstrated promising potential for oil removal in water with a calculated sorption capacity value of about 15.5 g/g even at a very short contact time. The fabricated PS fiber from the waste EPS foam may provide valuable insights into the valorization of polymeric waste materials for environmental and other related applications.

Innovative technologies enable businesses to stay competitive in marketplace while also increasing profits in manufacturing of nanocomposites for water treatment. Aforementioned driving factors resulted in adoption of a number of innovative technologies, and no other trend has had a greater impact in recent years than Industry 4.0. Industry 4.0 is a comprehensive term that encompasses data management, manufacturing competitiveness, manufacturing processes, and efficiency. The term “Industry 4.0” refers to a group of key enabler technologies, such as cyber physical models, Internet of Things (IoT), artificial intelligence (AI), and big data analytics, including embedded devices which are all significant components to the mechanized and digitized industrial environments. AI approaches have been used for water treatment processes as well as desalination in recent years for optimizing the process along with providing realistic answers to water scarcity and water pollution‐related issues. AI applications have been used to predict and minimize water treatment process operational costs by lowering costs and optimizing chemical utilization. Several AI models are successful and accurate in predicting effectiveness of various adsorbents used in the removal process of a variety of contaminants from water. To identify the current level of research and future development prospects of smart manufacturing, this study uses a comprehensive literature review technique for manufacturing sustainability of nanocomposite fabrication for water treatment applications. The model provided will help to create a baseline for AI and hybrid models in the water treatment and wastewater management sectors, allowing for the increased performance and innovative growth. It will serve to provide the framework and give guidance for researchers interested in creating superior nanocomposites for waste and fresh water treatment and management using Industry 4.0. This study looks at a variety of AI approaches as well as how they may be used in water treatment, with an emphasis on pollutant adsorption. This assessment also identified certain obstacles and research gaps in the field of AI applications in water treatment processes.