ABSTRACT
In the last years, the knowledge management methodology increased the perspective and deeply analysis in the energy evaluation, with great emphasis in the training of the maintenance teams and early detection of failure modes; these inefficiencies detection is associated to patterns recognition with expert systems. Several energy brands, utilities, universities, and design companies investigated about this problem with limits in the integration between maintenance team knowledge and the degradation of the energy equipment. Therefore, our findings are a new approach of the root cause analysis (RCA) improved with the knowledge management perspective, associated to the failure mode analysis for 164 inverters in photo-voltaic solar plant by using twenty-one failures modes; by incorporate the graph theory called Erdös-Rényi graphs with a quantitative methodology and qualitative evaluation with the knowledge management method in the root cause analysis; the dataset evaluated has 120,561 signals associated to 3,014,025 patterns, during the period from 2018 to 2021 in a PV solar plant. In this new root cause analysis method, the knowledge management is analyzed as a complement for the solution for sudden failure modes and early degradation.
ABSTRACT
Knowledge management evaluation is an important and complex problem in Peruvian universities. An efficient policy in knowledge management is a critical success factor and will also advance teaching and research. Likewise, innovation is a key resource for the well-being of national economies and international competitive advantage, especially with COVID-19 9 restrictions. This research article has demonstrated that an assessment of knowledge management (KM) capability in two private universities could be used for an efficient policy, in order to obtain the best result in knowledge management maturity. Having discussed how to construct a model for KM, the final section of this paper addresses ways of the incorporation of this technology in the society. The case study has been developed in Lima, associated to two universities with 271 teachers and 5928 students; with this model could be used for KM assessment in all university in Peru. This study uses the "Intellectus Model, Mejia model organizational knowledge capability areas and Knowledge Management Capability Assessment (KMCA) model for the assessment, before and during COVID-19. Our findings have demonstrated the university performance and challenges associated to knowledge management during COVID-19, the new policy for virtual instructions and digital transformation of the educational process have improved the cost efficiencies. However, this system also has a number of serious drawbacks and challenges in innovation, researching, connections with industry and academy; this 2021 requires a new perspective in innovation with a knowledge management scheme in Peruvian universities.
ABSTRACT
At the end of February 2020, Peru started the first cases of pneumonia associated with coronavirus (COVID-19), they were reported in Lima, Peru (Rodriguez-Morales et al., 2020). Therefore, the first week on March started with 72 infected people, the government published new law for a national crisis by COVID-19 pandemic (Vizcarra et al., 2020), with a quarantine in each city of Peru. Our analysis has considered March and April 2020, for air quality measurement and infections in Lima, the data collected on 6 meteorological stations with CO (carbon monoxide), NO2 (nitrogen oxide), O3 (ozone), SO2 (sulfur dioxide), PM10 and PM2.5 (particle matter with diameter aerodynamic less than 2.5 and 10â¯m respectively). As a result, the average of these concentrations and the hospital information is recollected per hour. This analysis is executed during the quarantine an important correlation is discovered in the zone with highest infection by COVID-19, NO2 and PM10, even though in a reduction of air pollution in Lima. In this paper, we proposed a classification model by Reduced-Space Gaussian Process Regression for air pollution and infections; with technological and environmental dynamics and global change associated COVID-19. An evaluation of zones in Lima city, results have demonstrated influence of industrial influence in air pollution and infections by COVID-19 before and after quarantine during the last 28â¯days since the first infection in Peru; the problems relating to data management were validated with a successful classification and cluster analysis for future works in COVID-19 influence by environmental conditions.