El impacto de la innovación y las finanzas en la competitividad de las PYMEs manufactureras

Los estudios sobre competitividad en Pymes destacan algunos factores principales que la afecta. Dada la frecuencia de aparición de la innovación y las finanzas entre estos factores, se han considerado para la realización de este estudio. Por su parte, la industria manufacturera, históricamente ha sido uno de los sectores económicos de mayor importancia en el Estado de Aguascalientes. Debido a ello, este trabajo de investigación trata sobre el impacto de la innovación y las finanzas en la competitividad de las Pymes manufactureras de esta entidad federativa. Para lo anterior, se aplicaron 206 encuestas dirigidas a los responsables de la administración de este tipo de organizaciones empresariales. Con los datos obtenidos se llevaron a cabo análisis de fiabilidad y validez de las escalas de los distintos bloques de reactivos utilizados, así como un análisis de regresión múltiple con la finalidad de evaluar la correlación entre las variables utilizadas. Los resultados obtenidos brindan evidencia empírica de que la innovación y las finanzas son factores que afectan significativamente en la competitividad de las empresas sujetas a estudio

Capacidades innovadoras como estrategia de crecimiento en PYMES familiares.

Actualmente las capacidades innovadoras de las empresas familiares son un factor determinante para  sobrevivir y obtener éxito, pues se convierten en una estrategia cuyo desarrollo y fortalecimiento depende de la gestión de la actividad innovadora realizada desde el interior de las organizaciones. Este estudio analiza el tipo de capacidades innovadoras presentes en mipymes familiares con el objeto de conocer el grado de contribución que brindan al crecimiento organizacional. Mediante un análisis exploratorio y descriptivo en pymes familiares productoras de flor en Villa Guerrero Estado de México, se encontró que las capacidades innovadoras incrementales impulsan en mayor grado el crecimiento organizacional de este tipo de empresas debido a su propia naturaleza

Capital humano, relacional y estructural en la actividad innovadora de las pequeñas y medianas empresas

Este estudio empírico busca medir la influencia que ejercen el capital humano, relacional y estructural en la actividad innovadora de estas empresas del Estado de Aguascalientes, México. El capital humano, relacional y estructural, como componentes del capital intelectual, han sido considerados como factores elementales para el desempeño innovador de las PYMES. Aunado a esto, al establecer a la innovación como una acción constante en su desempeño, las sitúa en destacados niveles de competitividad. De esta forma, el presente artículo procura demostrar la influencia del capital humano, relacional y estructural en la actividad innovadora de las PYMES de Aguascalientes

Statistical approximation of plantar temperature distribution on diabetic subjects based on beta mixture model

A change in plantar temperature distribution can be an indicator of tissue damage, inflammation, or peripheral vascular abnormalities associated with diabetic foot. Despite the efforts to detect these abnormalities through infrared thermography, there are still several problems to be addressed, especially to detect abnormalities on each foot separately. In this paper, a characterization of the plantar temperature distribution based on a probabilistic approach is proposed. The objective is to detect temperature variations on each foot eluding contralateral comparison. A beta mixture model with four components approximates the plantar temperature distributions of diabetic and non-diabetic subjects. Each component represents an area of the plantar region: toes; metatarsal heads; arch; and heel. The approximation was applied to 60 temperature distributions of non-diabetic subjects and 220 of diabetic subjects. The results suggest that it is possible to characterize distribution in terms of the mean of its beta components

FPGA-Based Smart Sensor for Online Displacement Measurements Using a Heterodyne Interferometer

The measurement of small displacements on the nanometric scale demands metrological systems of high accuracy and precision. In this context, interferometer-based displacement measurements have become the main tools used for traceable dimensional metrology. The different industrial applications in which small displacement measurements are employed requires the use of online measurements, high speed processes, open architecture control systems, as well as good adaptability to specific process conditions. The main contribution of this work is the development of a smart sensor for large displacement measurement based on phase measurement which achieves high accuracy and resolution, designed to be used with a commercial heterodyne interferometer. The system is based on a low-cost Field Programmable Gate Array (FPGA) allowing the integration of several functions in a single portable device. This system is optimal for high speed applications where online measurement is needed and the reconfigurability feature allows the addition of different modules for error compensation, as might be required by a specific application

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node

FPGA-Based Fused Smart-Sensor for Tool-Wear Area Quantitative Estimation in CNC Machine Inserts

Manufacturing processes are of great relevance nowadays, when there is a constant claim for better productivity with high quality at low cost. The contribution of this work is the development of a fused smart-sensor, based on FPGA to improve the online quantitative estimation of flank-wear area in CNC machine inserts from the information provided by two primary sensors: the monitoring current output of a servoamplifier, and a 3-axis accelerometer. Results from experimentation show that the fusion of both parameters makes it possible to obtain three times better accuracy when compared with the accuracy obtained from current and vibration signals, individually used

FPGA-Based Fused Smart Sensor for Dynamic and Vibration Parameter Extraction in Industrial Robot Links

Intelligent robotics demands the integration of smart sensors that allow the controller to efficiently measure physical quantities. Industrial manipulator robots require a constant monitoring of several parameters such as motion dynamics, inclination, and vibration. This work presents a novel smart sensor to estimate motion dynamics, inclination, and vibration parameters on industrial manipulator robot links based on two primary sensors: an encoder and a triaxial accelerometer. The proposed smart sensor implements a new methodology based on an oversampling technique, averaging decimation filters, FIR filters, finite differences and linear interpolation to estimate the interest parameters, which are computed online utilizing digital hardware signal processing based on field programmable gate arrays (FPGA)

FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation

Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities

Fused Smart Sensor Network for Multi-Axis Forward Kinematics Estimation in Industrial Robots

Flexible manipulator robots have a wide industrial application. Robot performance requires sensing its position and orientation adequately, known as forward kinematics. Commercially available, motion controllers use high-resolution optical encoders to sense the position of each joint which cannot detect some mechanical deformations that decrease the accuracy of the robot position and orientation. To overcome those problems, several sensor fusion methods have been proposed but at expenses of high-computational load, which avoids the online measurement of the joint’s angular position and the online forward kinematics estimation. The contribution of this work is to propose a fused smart sensor network to estimate the forward kinematics of an industrial robot. The developed smart processor uses Kalman filters to filter and to fuse the information of the sensor network. Two primary sensors are used: an optical encoder, and a 3-axis accelerometer. In order to obtain the position and orientation of each joint online a field-programmable gate array (FPGA) is used in the hardware implementation taking advantage of the parallel computation capabilities and reconfigurability of this device. With the aim of evaluating the smart sensor network performance, three real-operation-oriented paths are executed and monitored in a 6-degree of freedom robot