The purpose of this research article is to provide a comprehensive method of evaluation for public transportation. In this sense, this study considers transport lines that offer in Ciudad Juárez, Chihuahua. Hence, this study presents a description of the public transport system as part of the literature review. Likewise, the document describes an appropriate model based on the more outstanding publications about urban mobility and public transportation for passengers. Nevertheless, it is based on the Pythagorean Fuzzy combinative distance-based assessment (CODAS) to analyze and evaluate the alternatives through criteria that define general performance. Thus, the integration of these methods provides an adequate methodology for decision-making concerning urban planning and mobility to detect and improve the performance of criteria not considered within sustainable urban mobility plans. Results show how the applied approach can work as a powerful tool for the appraisal of the transport service. Finally, the results give relevant information to the local authority of the transport management of Ciudad Juarez to do improvements focused on the user.

The purpose of this research article is to develop a hybridization between the Failure Mode and Effect Analysis (FMEA) method and the Combinative Distance-Based Assessment (CODAS) method under Pythagorean Fuzzy environment. The traditional FMEA procedure is based on the multiplication between the parameters of severity, occurrence, and detectability where everyone has equal relative importance; therefore, different combinations of these parameters can generate the same result creating uncertainty in the analysis. In this mode, the hybridization proposed in this research deal with relative importance of each parameter; in the fact to have a more suitable combination which consider the level of knowledge of the experts in the assessment. Finally, a numerical case was carried out concerning the public transportation service to validate our proposal; the results show that 31 failure modes and potential risks can be evaluated using user perceptions, a dominant with high level of knowledge about the public transportation service and an apprentice or common user, as team of experts and exploiting the subjectivity of the information in a mathematical model. Also, we compare the results with a variation of the proposed model with the multi-criteria method multi-objective optimization method by relationship analysis (MOORA); it was observed that the convergence of the failure modes depends on the nature of the mathematical model even under the same conditions at the start.

Lean Manufacturing has become, in recent years, one of the most important philosophies for improving production and organizational systems. The literature shows that Hesitant Fuzzy Linguistic Terms Sets (HFLTSs) are highly capable of manipulating the uncertainty that the judgments made by evaluators carry and that they are subject to their perception, especially when used in combination with multicriteria decision making (MCDM) for the measurement of indicators in this type of system, as well as their general performance. However, it is still of interest to researchers to develop techniques and instruments that facilitate the measurement of the results obtained after applying this philosophy in organizations. This article proposes a model for the evaluation of the Lean Manufacturing performance through the Analytic Hierarchy Process (AHP) and Dimensional Analysis (DA) using HFLTSs. The results obtained show that the proposed model is a solid tool for the evaluation of Lean Manufacturing systems from a different perspective and that it can be integrated into the issuance of evaluations in a better way by considering human subjectivity. At the same time, it offers a strategy to create priorities in the action plans that Lean system managers propose after evaluating. However, it is important to apply the proposed model to multiple organizations and analyze the results obtained to maximize its benefits.

En este artículo se aborda la investigación realizada en una planta de Ciudad Juárez, Chihuahua, México, donde se trabajan diferentes modelos de tablillas electrónicas para el control de diversas partes y accesorios automotrices. Ahí se identificó una oportunidad de mejora, ya que se estaban generando defectos de bolas y burbujas de soldadura en las tablillas, creando un daño latente y aumento en los costos de producción. Se implementó la metodología Seis Sigma y su herramienta DMAIC en seis diferentes diseños de experimentos con una máquina de inspección de rayos X y un software que procesa las imágenes. Se modificaron diversos parámetros en la etapa de soldeo y, finalmente, se encontró que las tablillas de un proveedor chino causaban el defecto debido la rugosidad en orificios (through holes), pues ahí quedaba flux atrapado y se generaban las bolas de soldadura.

The application of Internet of Things (IoT) technology to Digital Twin (DT) in smart manufacturing has opened significant opportunities for real-time monitoring, predictive maintenance, and closed-loop control; however, the inherent latency that exists in these architectures (the temporal gap between a physical event and its reflection in a digital model) remains one of the most significant and least systematically understood barriers to fulfill its full potential. This paper aims to propose a formal four-layer taxonomy of latency sources in IoT-based Digital Twin systems for smart manufacturing and to review the current approaches and tools that are available for their measurement. The PRISMA protocol has been used to perform a systematic literature review, where 58 primary survey studies published between 2020 and 2026 were extracted from IEEE Xplore, Elsevier Scopus, Google Scholar and arXiv, with all the studies being coded along six dimensions (architectural layer, application domain, latency metrics reported, evaluation methodology, quantitative impact, and enabling technologies). The proposed taxonomy presents 28 different types of latencies under four layers: (L1) network, (L2) compute, (L3) data, and (L4) end-to-end (E2E), whose magnitudes vary from 0.1 ms for local network propagation to tail latencies above 500 ms in production (P99). Three categories and three cross-layer interaction patterns are formalized here and are absent from prior partial taxonomies. Among the most promising results is the finding that several high-impact interventions require no infrastructure investment: a protocol migration from Modbus to WebSocket reduces telemetry latency by 32%, while Age of Information-aware synchronization and clock drift correction deliver substantial data layer gains through software updates alone, yet remain underutilized. The review identifies a systematic under-reporting of tail-latency percentiles across the corpus, the lack of a cross-protocol jitter benchmark, and a predominance of simulation-based evaluation over real-hardware measurement. The systematic review contributions of this paper (the formal four-layer taxonomy, the proportional metric audit across the 58 papers, and the formalization of three cross-layer interaction patterns) are derived from cross-corpus analysis. The investigation also identifies three open research directions (a standardized manufacturing IoT-DT benchmark, cross-layer joint optimization frameworks, and wireless TSN validation on real manufacturing testing grounds) that together form a well-organized and practical basis to advance both the science and the application of ultra-low-latency Digital Twin technology in the industrial field.

At present, the manufacturing industries require the implementation of more efficient and flexible fabrication processes to offer high-quality products. The changeover methodologies can be used to reduce the setup times, allowing the industries to be more competitive. The application of changeover methodologies is mainly influenced by the 4Ps model, which is composed of organizational and design factors, such as people, practices, product, and processes. However, this model is not useful in determining the relationship between each one of the Ps and the changeover activities. In this chapter, the authors have developed an exhaustive review of the references to establish the indicators to design an instrument composed of 79 items and divided into the five constructs of the 4P model, which was statistically validated using the Kendall W indicator and the Cronbach´s alpha indicator.