Productivity is today one of the most important aspects of a business, the productivity concept not only implies higher profits, but use their resources efficiently, based on the purpose or goal of the organization. One of the most important resources is the human resource, which is why when talking about productivity, it is vital to consider the environment or workspace in which the operators perform. Ergonomics talk is talk of a tool for increasing productivity, as this, to bring the physical conditions of the work area, allows workers feel more comfortable and the risk is diminished by poor posture, resulting an increase in production since the worker gets healthier and safer working conditions. In the northern state of Veracruz, Mexico, is located a company Ironmonger industry and construction, which has about 376 people. It has been found that operators do not have the area right job, so a study was done through the RULA (Rapid Upper Limb Assessment) method for the assessment of risk by maintaining inadequate by the poor design of workspace views. The Rula method provides a useful tool for evaluating working postures that may create a risk tool, however when you have a large number of workers, this process becomes tedious. Fuzzy Logic is an extension of traditional logic, but uses similar concepts belonging to the human way of thinking, the concept of fuzzy logic was introduced by LA Zadeh in 1965, who described that Fuzzy logic does not use exact values as 1 or 0 but if you use values between 0 and 1 (inclusive) that may indicate intermediate values. The use of fuzzy logic in this case study aims to minimize the valuation work for every operator with Rula method, indicating, through fuzzy sets, the levels of risk that may arise in representative areas of the Hardware Store in where work is carried out with similar positions, regardless of the area from which it comes. Allowing this, assign values to assess accurately if no or a risk index

This study summarizes advancements in life cycle assessment (LCA) that enhance our understanding of environmental sustainability in milk production and processing. A systematic review of 84 papers published between 2018 and 2024 was conducted to highlight the topics and the main methodological elements that can aid in prioritizing interventions from an environmental standpoint. The findings indicate that the most discussed topics include farming management strategies, mitigation approaches, and livestock management. Limited attention was given to the circular economy, energy efficiency, milk production and consumption, and feed management. In the goal and scope phase, only 36 studies followed a standard LCA methodology, while 53 took a comparative approach and 32 a descriptive one. In the inventory analysis phase, 23% relied solely on modeled data, 72% on experimental data, and 56 studies used IPCC guidelines for emission factors. For impact assessment, the main categories addressed were global warming potential, eutrophication potential, and acidification potential, with ReCiPe being the most commonly used method. Importantly, more than half of the studies did not conduct uncertainty or sensitivity analyses; only 27% performed sensitivity analyses and 12% performed uncertainty analyses. The review offers insights for advocates of LCA and suggests future research directions.

This paper combines the use of two tools: Failure Mode and Effect Analysis (FMEA) and Fuzzy Logic (FL), to evaluate the functionality of a quantifier prototype of Methane gas (CH₄) and Carbon Dioxide (CO₂), developed specifically to measure the emissions generated by cattle. Unlike previously reported models for the same purpose, this device reduces damage to the integrity of the animal and does not interfere with the activities of livestock in their development medium. FMEA and FL are used to validate the device’s functionality, which involves identifying possible failure modes that represent a more significant impact on the operation and prevent the prototype from fulfilling the function for which it was created. As a result, this document presents the development of an intelligent fuzzy system type Mamdani, supported in the Fuzzy Inference System Toolbox of MatLabR2018b^®, for generating a risk priority index. A Fuzzy FMEA model was obtained to validate the prototype for measuring Methane and Carbon Dioxide emissions, which allows considering this prototype as a reliable alternative for the reliable measurement of these gases. This study was necessary as a complementary part in the validation of the design of the prototype quantifier of CH₄ and CO₂ emissions. The methods used (classic FMEA and Fuzzy FMEA) to evaluate the RPN show asymmetric graphs due to data disparity. Values in the classical method are mostly lower than the Mamdani model results due to the description of the criteria with which it is evaluated.

Mexico is the world’s third largest consumer of Polyethylene Terephthalate (PET), only preceded by the United States and China. PET is commonly used in plastic containers such as beverage bottles and food packaging. It can be argued that the main problem regarding pollution generated by PET waste lies in the lack of appropriate solid waste management. The decision regarding facility location is the central issue in solid waste management. A mixed integer linear programming model of the capacitated facility location problem is proposed and then a genetic algorithm is designed to optimize the model. The problem is described as follows: given the quantities of PET generated in the northern region of Veracruz, Mexico, by considering five cities and each as a single generation source, a collection center has to be selected among a set of pre-identified locations in the town of Tempoal, Veracruz; in order to serve a set of demand points in the re-use market; demands are assumed to be uncertain. The aim is to minimize the system’s overall cost.

Constructed wetlands (CWs) have emerged as effective nature-based solutions (NbS) for the treatment of industrial dairy wastewater (DWW), which is characterized by high organic loads, elevated nutrient concentrations, and pronounced operational variability. Despite increasing implementation, quantitative engineering evidence supporting design optimization and scalability remains fragmented. Herein, we present a semi-quantitative synthesis of CW performance for DWW treatment, explicitly linking hydraulic and operational parameters with pollutant removal efficiencies. A systematic review of 38 peer-reviewed studies published between 1995 and 2025 was conducted in accordance with PRISMA 2020 guidelines. Treatment performance was normalized and evaluated as a function of hydraulic retention time (HRT), organic loading rate (OLR), system configuration, and climatic context. The results demonstrate that hybrid CWs combining vertical and horizontal subsurface flow most frequently achieved COD and BOD₅ removal efficiencies exceeding 90% when operated within an observed operating envelope, typically including HRT ranges of 4–8 h (VSSF; n = 4) and 3–7 days (HSSF; n = 14), and OLR values below 30 g COD m⁻² d⁻¹ (n = 7, among studies reporting OLR). Operation outside this operating envelope was generally associated with reduced treatment stability and an increased likelihood of operational constraints (e.g., clogging). Substrate porosity, vegetation diversity, and climate further modulated long-term performance and system resilience. Based on the consolidated evidence, this review suggests transferable operational design envelopes and configuration-specific implementation pathways that translate empirical findings into practical engineering guidance, supporting the scalable adoption of CWs as low-energy NbS for decentralized and sustainable DWW management.