Armando Perez-Sanchez

This study proposes and validates a structured methodology based on Design for Six Sigma (DFSS) for sustainable product design, addressing the lack of standardization in the integration of design tools and the need to simultaneously consider qualitative, quantitative, and sustainability-related variables. The methodology integrates Voice of the Customer (VOC), Quality Function Deployment (QFD), Theory of Inventive Problem Solving (TRIZ), computer-aided design and engineering (CAD/CAE), and Design of Experiments (DOE) within a ten-stage framework combining the stages from DMADV (Define, Measure, Analyze, Design, Verify) and IDOV (Identify, Design, Optimize, Validate) approaches. The proposed method was applied to the design of a structural concrete block, considering performance variables such as weight, factor of safety, displacement, energy consumption, and carbon emissions. The results show that the integration of QFD enabled prioritization of customer requirements, while DOE and regression models identified significant factors and interactions. Multi-response optimization using desirability functions achieved a balanced solution, improving structural performance and sustainability indicators. In particular, a significant reduction in carbon emissions was achieved. Validation through simulation confirmed the consistency between predicted and observed results. The findings demonstrate that the proposed methodology provides a systematic and replicable approach for product design, improving decision-making and supporting the development of more sustainable products.

The energy transition in Baja California, a partially interconnected region with a high dependence on fossil fuels, faces the challenge of expanding generation capacity, modernizing electricity infrastructure, and addressing sustained demand growth. This study evaluates the feasibility of implementing a smart grid through a mixed-method approach that integrates stakeholder perceptions from the energy sector with techno-economic modeling of electricity scenarios. The methodology combines a questionnaire applied to regional energy experts with EnergyPLAN simulations to assess short- and long-term scenarios, including renewable generation expansion, battery energy storage, and the integration of electric vehicles under both conventional charging and vehicle-to-grid (V2G) schemes. The results indicate that the expansion of solar photovoltaic generation and the incorporation of energy storage help mitigate demand growth and improve the utilization of local energy resources. In particular, the smart charging V2G scenario shows, in the short term, a greater capacity to sustain regional energy autonomy and independence compared to other transport electrification scenarios, reducing the decline in electricity exports by 3%. In the long term, infrastructure expansion enables an increase in surplus electricity exports of up to 12%, strengthening system autonomy despite a 19% increase in imports. The mixed-method evaluation demonstrates that the energy transition in Baja California is feasible; however, its successful implementation will depend on the adoption of technological strategies supported by integrated policy frameworks that promote investment, innovation, and collaboration among public, academic, and private sectors.

3D printing using fused filament fabrication (FFF) has emerged as a key manufacturing tool due to its versatility, efficiency, and ability to produce complex geometries. However, ensuring consistent mechanical performance remains challenging, as reported properties often depend not only on process parameters but also on system-level characteristics of the printing platform. This study evaluates the tensile performance of PETG specimens fabricated using two open-frame FFF printers, treating the extrusion system architecture as an explicit experimental variable under controlled conditions: a Bowden-driven Ender 3 Pro and a direct-drive Insol Printer 4. ASTM D638 Type I specimens were printed at three raster orientations (0°, 45°, and 90°), with two replicates per condition (n = 2), using identical material, slicing parameters, and testing procedures. Build orientation dominated the tensile response, with 0° specimens exhibiting the highest strength and 90° the lowest. Beyond this established trend, a consistent printer-dependent difference was observed. At 0° orientation, the Insol Printer 4 reached a maximum ultimate tensile strength of 36.99 MPa, compared to 35.06 MPa for the Ender 3 Pro, representing an increase of approximately 5.5%. Similar trends were observed at 45°, while differences at 90° were less pronounced. Although the limited sample size restricts statistical generalization, these results provide controlled quantitative evidence that extrusion system architecture can influence PETG tensile performance alongside build orientation.

Atomic Layer Deposition (ALD) is a key thin-film fabrication technique that enables the growth of ultra-thin, conformal, and compositionally controlled layers for applications in nanoelectronics, optoelectronics, and energy devices. However, the high cost and operational complexity of commercial ALD systems limit their accessibility in academic and emerging research environments. In this work, a low-cost, automated thermal ALD system is designed, assembled, and experimentally validated for the deposition of zinc oxide (ZnO) thin films. The developed system enables precise control of precursor dosing, purge sequences, and substrate temperature via an integrated LabVIEW–Arduino control architecture, allowing reproducible and stable thin-film growth. The design allows the use of various precursors through high-precision three-way diaphragm valves. In addition, the system allows continuous purge gas flow in the reaction chamber, which enhances the drag velocity of the precursor gas, reducing dosage requirement, accelerating chamber saturation time and lowering the total consumption of precursors per deposition cycle. ZnO thin films were successfully grown on silicon and glass substrates at 200 °C using diethylzinc (DEZ) as the metal precursor and hydrogen peroxide (H₂O₂) as the oxidant. The process exhibited self-limiting growth characteristics typical of ALD, yielding a growth per cycle of approximately 0.8 Å. The deposited ZnO films exhibited optical transparency of 70–80% in the visible region, a refractive index of approximately 1.9, and an optical bandgap close to 3.4 eV, which are consistent with values reported for high-quality ZnO films grown in commercial ALD systems. These results demonstrate that the proposed low-cost platform is capable of producing functional ZnO thin films with properties comparable to those obtained with conventional commercial reactors. Overall, this work presents an accessible and scalable thermal ALD system that significantly reduces equipment costs while maintaining reliable process control and film quality, offering a practical framework for expanding thin-film research capabilities across microelectronics, optoelectronics, and nanotechnology laboratories.

Additive manufacturing via stereolithography (SLA) enables the fabrication of highly customized lattice structures, yet the interplay between geometry and graded density in defining mechanical behavior remains underexplored. This research investigates the mechanical behavior and failure mechanisms of cylindrical lattice structures considering uniform, linear, and quadratic density variations. Various configurations, including IsoTruss, face-centered cubic (FCC)-type cells, Kelvin structures, and Tet oct vertex centroid, were examined under a complete factorial design that allowed a thorough exploration of the interactions between lattice geometry and density variation. A 3D printer working with SLA was used to fabricate the models. For the analysis, a universal testing machine, following ASTM D638-22 Type I and ASTM D1621-16 standards, was used for tension and compression tests. For microstructural analysis and surface inspection, a scanning electron microscope and a digital microscope were used, respectively. Results indicate that the IsoTruss configuration with linear density excelled remarkably, achieving an impressive energy absorption of approximately 15 MJ/m³ before a 44% strain, in addition to presenting the most outstanding mechanical properties, with a modulus of elasticity of 613.97 MPa, a yield stress of 22.646 MPa, and a maximum stress of 49.193 MPa. On the other hand, the FCC configuration exhibited the lowest properties, indicating lower stiffness and mechanical strength in compression, with an average modulus of elasticity of 156.42 MPa, a yield stress of 5.991 MPa, and the lowest maximum stress of 14.476 MPa. The failure modes, which vary significantly among configurations, demonstrate the substantial influence of the lattice structure and density distribution on structural integrity, ranging from localized bending in IsoTruss to spalling in FCC and shear patterns in Kelvin. This study emphasizes the importance of selecting fabrication parameters and structural design accurately. This not only optimizes the mechanical properties of additively manufactured parts but also provides essential insights for the development of new advanced materials. Overall, the study demonstrates that both lattice geometry and density distribution play a crucial role in determining the structural integrity of additively manufactured materials.

The present research features an experimental comparative design and the objective of this work was to determine the susceptibility to microbiological contamination in fatty acid methyl esters (FAMEs) and the FAME–water interface of residual and refined lard, large volume simulating storage conditions as fuel supply chain, and to identify the microorganisms developed. The plates were seeded according to ASTM E-1259 and the instructions provided by the manufacturer of the Bushnell Haas agar. Microbiological growth was observed at the FAME–water interface of FAME obtained from residual lard. Using the MALDI-TOF mass spectrometry technique, Pseudomonas aeruginosa and Streptomyces violaceoruber bacteria were identified in the residual lard FAMEs, with the latter being previously reported in FAMEs. The implications of microorganism development on the physicochemical quality of FAMEs are significant, as it leads to an increase in the acid index, which may negatively impact metals by inducing corrosion. The refined lard FAMEs did not show any development of microorganisms. The present research concluded that residual lard tends to be more prone to microbiological attack if the conditions of water and temperature affect microbial growth. The findings will contribute to the knowledge base for a safer introduction of FAMEs into the biofuel matrix.

Global fossil fuel consumption, including diesel and gasoline, significantly contributes to emissions. Understanding emission percentages and types is critical. Alternative energies, like hydrogen mixed with gasoline, help mitigate emissions in sectors such as transport and energy. Hydrogen-gasoline blends in internal combustion engines improve the combustion process but require studying engine behavior and carbon footprint. This research designs a low-cost sensor network to monitor combustion emissions and provide reliable data for statistical comparison across vehicles. Two synchronized client–server software systems are proposed. The client software runs on an IoT development board (ESP32) and communicates with sensors via the ESP-NOW protocol to detect and collect gas data, transmitting it wirelessly to the web server. The server software provides a user-friendly interface for data control and visualization from a ground station. Tests used 100% Mexican gasoline (G100) and hydrogen-gasoline blends (GH) with a hydrogen cell electrolyte concentration of 0.0211 mL/gal (80 mL). A single vehicle followed the same route at 40–60 km/h, collecting data every 30 s over three trials. Results showed average reductions of 5% and 10% in CO and CO₂ emissions, respectively, with GH fuel.

The global consumption of fossil fuels such as diesel and gasoline represent a considerable per-centage of global emissions, it is important to know for sure the percentage and type of gas emitted, there are many alternative energies that mitigate the production of emissions in different sectors such as the transport sector and the energy sector. The percentage use of hydrogen mixed with gasoline in internal combustion engines is a viable alternative because it helps the com-bustion process, but it is necessary to know the behavior of the engine and determine the carbon footprint, to quantify the benefit of these actions it is necessary to design and implement a network of low-cost sensors that monitor the emissions produced during the combustion processes and provide reliable data that can be used to make a statistical comparison between vehicles. This research proposes two software systems of an architecture (client-server) working in a synchro-nized manner in order to collect and store information in a database. The first software works as the client and runs on an IoT development board called ESP32 in conjunction with esp32 ttgo and communication between both devices is done through the esp now protocol, this software estab-lishes the connection with the physical sensors to detect and collect gas information, the data is sent wirelessly to the web server, the second software works as a server in addition to providing a graphical interface for user control and data visualization from a ground station. The tests were carried out using 100% Mexican gasoline (G100) and a mixture of hydrogen fuel with gasoline (GH) for the hydrogen cell a concentration of 0.0211 ml / gal of electrolytes (80 ml) was used, the same route and vehicle were used at an average acceleration of 40 and 60 km / h, the data obtained are taken every 30 seconds, the process was repeated 3 times and an average emission reduction of 5% and 10% of CO and CO2 respectively was obtained with GH fuel.

Given the growing interest in manufacturing’s environmental effects, understanding the impact of improvement strategies on sustainability is critical. This study focuses on the implementation of Green Lean Six Sigma (GLSS) in the Mexican manufacturing sector, an area where research is limited, particularly concerning the barriers to successful outcomes. Through the development of a structural equation model using SPSS software,,version 25, 64-bit edition, key barriers such as lack of investment, insufficient participation, ineffective infrastructure, and lack of training were identified as the primary challenges to GLSS implementation. This study also highlights the interrelationships between these barriers and their influence on project success, emphasizing the role of insufficient participation as a critical mediating factor. This insight allows for a deeper understanding of how these obstacles affect the benefits of GLSS initiatives. The findings offer valuable guidance for researchers and practitioners, providing tools to enhance the effectiveness of GLSS implementation in the manufacturing industry. The study’s marginal contribution lies in its identification of key barriers and the introduction of insufficient participation as a mediating factor, offering a more comprehensive understanding of their impact on project success and contributing to improved GLSS adoption strategies.

Water supply represents a significant electrical load worldwide. The operation of inefficient pumps contributes to increased energy demand and carbon footprint. Current methods for evaluating industrial water pumps present technical and economic challenges that need to be addressed. For these reasons, we developed a practical and cost-effective virtual instrument called the Pumping Evaluation System (PES). The PES tool performs real-time monitoring of electrical, hydraulic, and efficiency data, as well as the Operating Characteristic (OC) curves. The PES tool was implemented on a vertical pump currently used by a municipal water distribution plant in Mexicali, Mexico. A comparative analysis between the experimental data and the manufacturer’s data revealed potential energy savings of 361,455 kWh/year (24.35%) and an equivalent carbon footprint reduction of 157,233 kg of CO_2eq/year if the old pump is replaced by a new one, which is the lowest cost alternative according to a Life Cycle Cost (LCC).