This study deals with forecasting economic time series that have strong trends and seasonal patterns. How to best model and forecast these patterns has been a long-standing issue of time series analysis. In this work, we propose a Holt-Winters Exponential Smoothing approach to time series forecasting in order to increase the chance of capturing different patterns in the data and thus improve forecasting performance. Therefore, the main propose of this study is to compare the accuracy of Holt-Winters models (additive and multiplicative) for forecasting and to bring new insights about the methods used via this approach. These methods are chosen because of their ability to model trend and seasonal fluctuations present in economic data. The models are fitted to time series of e-commerce retail sales in Portugal. Finally, a comparison is made and discussed.
Machine end-effector kinematic analysis is critical to optimizing transporting components where inertial forces are the main loads. While displacements may be measured with relatively high accuracy in transportation equipment motors, the inertial forces in the transported components are seldom optimized. This is especially relevant in electronic component placement systems, where the components have a wide range of configurations (i.e., geometry and mass) and the deployment dimensional/geometric tolerances are remarkably good. The optimization of these systems requires the monitoring of the real position of the accelerometers relative to the measurement point of interest with sufficient accuracy that allows the assembly position to be predicted instantaneously. This study shows a novel method to calibrate this equipment using triaxial accelerometers on a surface mount machine to measure the end-effector accelerations and velocities in its planar motion. The dynamic equations of the system and the method for integration are presented to address the uncertainty on the exact position of the accelerometer sensors relative to the measuring point of interest exist and allow the position correction to optimize response and accuracy.
Surface-mount technology is a method for producing electronic circuits in which the components are mounted or placed directly onto the surface of printed circuit boards. The purpose of this study was to analyze nozzle change in two production lines. Following a previous study, it was proposed that one type of nozzle would place resistors while another type of nozzle would place capacitors, contrary to what happened in the initial process, where the two placed both components. However, the change of nozzle was not done globally, but only applied to two specific types of capacitors that were more critical. Even so, the positive effect of this change was globally visible, both in the decreased number of component rejection and in the reduced number of component defects in the printed circuit boards. It was also possible to estimate the percentage saving and the expected growth from this new implementation. The data were validated using statistical analysis. Finally, the current cleaning periodicity of the nozzles was examined in order to verify if it was compromising their performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.