Daniel René Tasé Velázquez

Hybrid additive–subtractive manufacturing enables complex, precise production but creates major process-planning and integration challenges. This study identifies gaps in hybrid process planning, particularly for laser metal deposition and machining, using the Hybrid Manufacturing Process Planning Model (HPPM) as a conceptual reference. A PRISMA-guided systematic mapping review of Scopus and Web of Science yielded 1056 documents classified across four dimensions: holistic planning, simulation–planning integration, predictive capabilities, and multi-parameter management. Corpus-level rule-based semantic mapping was validated against consensus from seven experts using a stratified 100-document sample and complemented by a structured engineering appraisal of a targeted 100-document full-text verification set. Only 0.95% of documents showed partial planning integration, with none meeting the holistic framework criteria. Simulation–planning connections occurred in 1.42%, but only 1.23% reached functional or framework-level integration. Predictive capabilities appeared in 91.76%, although only 17.42% were planning-linked, while multi-parameter evidence occurred in 28.31%. The engineering appraisal identified persistent bottlenecks in geometry/data interoperability, thermal-to-geometric transfer, coordinate consistency, kinematics, machinability, and feedback. The principal gap is therefore the coordinated integration of physical, computational, and decision interfaces required for executable hybrid process planning.

Demand variability complicates workforce capacity planning in knowledge-intensive services, particularly when only short historical records are available. This study evaluates parsimonious benchmark models for forecasting translation-service demand and translating the resulting forecasts into staffing requirements. The empirical analysis used 122 daily observations collected over six months from a translation team providing services in English and Spanish. Demand was measured as the number of words requested per working day, while nominal individual capacity was operationalized as 2000 translated words per day. Three benchmark forecasting methods—Naive, Mean, and Drift—were compared through expanding-window rolling-origin evaluation using ME, MAE, RMSE, MASE, and sMAPE. At the one-working-day horizon, the Mean benchmark achieved the lowest MAE (3221.66 words), RMSE (4424.81 words), MASE (0.845), and sMAPE (58.14%), and it maintained the lowest values for these measures at five- and twenty-working-day horizons. Re-estimated using all 122 observations, the Mean benchmark generated a point forecast of 5472.12 words per working day, equivalent to 2.74 translator-equivalents and a baseline requirement of three translators under the nominal productivity assumption. However, observed demand exceeded three-translator capacity on 34.43% of working days, indicating the need for flexible contingency capacity. The study provides a transparent framework connecting benchmark forecast evaluation with workforce-capacity decisions under limited temporal coverage.

This paper aims to review the state-of-the-art in Cyber-Physical Systems (CPS) as a key element to Industry 4.0 and to provide engineering managers with adequate and sufficient knowledge about CPS, highlighting their characteristics, technologies, capabilities, and applications. A three-stage research method was applied to provide an extensive search and systematic literature review (SLR). We identified, selected, and reviewed 218 publications. The convergences in specific areas in which studies are still needed were detailed. We identified 5 characteristics, 7 capabilities, 17 related technologies, and 11 areas of application. Four application areas remain as an opportunity to be explored in future research, such as environmental sustainability; smart and precision agriculture; smart construction, and social sciences. This article is the first to present a wide-ranging review of CPS and bringing together a significant number of publications. Its originality is focused on detailing and analyzing CPS characteristics, technologies, and multidisciplinary applications allowing engineering professionals and managers to identify which technologies a manufacturing equipment should integrate, as well as the level of development of each of them to achieve its full operation in Industry 4.0 environment. The main limitation of this work is the fact that new features, applications, and technologies will certainly appear soon.

The hybrid manufacturing has attracted industrial community interest due to its ability to produce functional parts with varied geometries, using different types of materials in the most varied applications. As with most manufacturing processes, before executing the hybrid process for the manufacture of a certain geometry, it is important to make a proper process planning that allows having an integral and proactive view of the operation. This work aims to synthesize through a systematic literature review (SLR) the state of the art on hybrid manufacturing process planning (HMPP) models with predictive approach. Three SLRs were developed to extract the articles of interest (2012-2022) from Science Direct, Springer Link, and Web of Science databases. PRISMA method was used to gather the papers and oriented the qualitative and quantitative analysis. Snowballing technique was used to gather articles of interest out of the period defined. Literature review showed that there is still no consensus between existing HMPP models, regarding all the activities necessary to ensure proper operation. In addition, the developed models have a limitation regarding the inclusion of a process simulation step. The simulation step on the existing models, does not allow to proactively check whether the experimental process conditions are adequate to ensure the manufacture of the modeled geometry before running the hybrid manufacturing process. An efficient simulation step would ensure a predictive approach to operation performance and would imply the reduction of geometric deviations without the need for excessive experimentation, reducing material consumption, manufacturing time, and resulting in a better deposition strategy. Using computational and statistical methods as support for decision-making in the process will allow the processing and analysis of data to assertively direct the structuring of a robust model for HMPP with predictive approach. A differentiated, more complete, and comprehensive process planning model is a relevant study opportunity for future research. This paper contributes to the theory development since it identifies and analyzes the existing HMPP models, highlights important gaps on the subject, and proposes insights for future development.

The purpose of this paper is to identify and evaluate which managerial style prevails in the operational area of five IT companies and their relationship with the job satisfaction of their employees. For data collection, a questionnaire was applied to 120 participants, validating 110 responses. Questions regarding the three factors of EAEG were integrated in order to identify the focus in which the leadership predominantly operates in these companies, and the five dimensions of EST were used to measure the level of employees satisfaction regarding each dimension evaluated. Descriptive statistical processing allowed to observe that the managerial style focused on the Task prevails, with an overall average score of vt = 4.11. As dispersion measures, the sample standard deviation (St = 0.39) and sample amplitude (At = 0.91) corresponding to this factor (Task) were calculated, respectively, showing that the values are very close to the average score. It indicates that there is uniformity between the scores for each item of the factor Task. It was found that 65 % of participants confirm the role of the leadership focused on the Task. The Satisfaction with the nature of work dimension reached an average score of vd = 5.09, showing employee satisfaction. The dimension Satisfaction with colleagues reached an average score of vd = 4.34 indicating indifference on the level of satisfaction, whereas the dimensions Satisfaction with salary, promotions and leadership, reached averages of vd = 3.87, vd = 3.70 and vd = 3.46, respectively, indicating levels of dissatisfaction. Finally, were highlighted some criteria as motivators for avoid turnover in organizations that contribute to the job satisfaction of these employees.

Laser Metal Deposition (LMD) process is an additive manufacturing technique that has attracted the interest of the automotive and aerospace industries due to its ability to manufacture parts with complex geometries and different types of metallic materials. However, the structure of the deposited layers and the geometrical characteristics of the manufactured parts are influenced by the interaction among the deposition process parameters. In this paper, fuzzy inference (FIS) technique was used to develop two models for predicting the geometrical characteristics and, for optimizing the LMD process parameters using AISI 316 stainless steel powder and substrate. An experimental design, based on factorial analysis, was used to correlate the influence of selected deposition process parameters, laser power (Lp), powder flow (Pf) and focal length (Fl) with the process geometrical characteristics bead height (Bh), bead width (Bw), depth of penetration (Dp), dilution (d) and wetting angle (wa). The factors Lp and Fl were used with three operating levels each: Lp = 225 W, 250 W, 275 W, and Fl = 4.8 mm, 5.0 mm, 5.2 mm. The factor Pf was used with two levels, 9.40 g/s and 13.35 g/s. Analysis of variance allowed identifying that the Pf affect the Bh, Bh/Bw ratio, d and wa. The increase in Laser power (Lp) resulted in an increase of the geometric characteristics Bw and Dp. The first FIS, for predicting the bead’s geometrical characteristics, presented high adequacy (relative error up to 8.43 %) for assessing the experimental conditions. The second FIS indicated the best possible interaction, given the studied operating conditions and the variables evaluated. The maximum Output Defuzzified Index (ODI = 0.845) was obtained with the deposition process parameters Lp = 250 W, Fl = 5 mm, and Pf = 9.40 g/s.

This work presents the adaptation of the Quality by Design (QbD) approach for application in the quality assurance of a biomedical measuring system under development. First attempts in applying QbD to biomedical technologies indicated a significantly higher number of parameters than its traditional application in the pharmaceutical industry. These preliminary studies did not fulfill the QbD stage of Design Space (DS) configuration for biomedical devices, an essential step to identifying the proper operating ranges of parameters and guaranteeing quality features. Therefore, it persisted the challenge of configuring DS for health devices, overcoming dependences in the interaction of multiple process parameters and critical attributes. The present work develops a hybrid QbD-Fuzzy approach for multiparametric DS configuration. The proposed method was applied in the development phase of a low-cost and high-sensitive magnetic measuring system for locating metallic foreign bodies in patients, employing sensors based on the Giant Magnetoimpedance effect. The results provided the acceptable operating ranges of the multiple process parameters to ensure the biomedical equipment's suitability. The proposed strategy contributes to the QbD implementation in biomedical technologies and, therefore, promotes the reliability of diagnostic and therapeutic results in the clinical environment.

A flexibilidade das tecnologias híbridas de fabricação (HMT) para integrar os processos produtivos e as atividades de manutenção contribui para o aumento do ciclo de vida de peças funcionais ou remanufaturadas, agregando-lhes valor, dado que, pelo elevado custo de fabricação, não se justifica seu descarte. O objetivo deste artigo é investigar quais são os benefícios do uso das HMT nas atividades de reparo e remanufatura de peças no contexto da manutenção. A revisão sistemática da literatura relacionada ao tema mostrou que o emprego das HMT para executar atividades de reparo e remanufatura de peças como parte dos sistemas de manutenção está em expansão. Além disso, foi identificado que as aplicações das HMT visam o aumento do ciclo de vida dos produtos, a eficiência de recursos e remanufatura de peças no fim da vida útil como parte da reconfiguração da cadeia de valor.

Integrated mathematical model based on a heuristic method for loading and routing of vehicles: application in a tobacco company