A computer study of the improvement of PV panel monthly outputs when the panel azimuth is changed thrice daily

The purpose of the calculations was to estimate the most suitable slopes and azimuths for three different positions per day of a solar panel in order to obtain the most possible energy from the PV panel compared with a stationary PV panel. The calculations were made in the computer program PV F-CHART.

Improvement of Routine Test Process of High Voltage Power Capacitors

The capacitor test process at ABB Capacitors in Ludvika must be improved to meet future demands for high voltage products. To find a solution to how to improve the test process, an investigation was performed to establish which parts of the process are used and how they operate. Several parts which can improves the process were identified. One of them was selected to be improved in correlation with the subject, mechanical engineering. Four concepts were generated and decision matrixes were used to systematically select the best concept. By improving the process several benefits has been added to the process. More units are able to be tested and lead time is reduced. As the lead time is reduced the cost for each unit is reduced, workers will work less hours for the same amount of tested units, future work to further improve the process is also identified. The selected concept was concept 1, the sway stop concept. This concept is used to reduce the sway of the capacitors as they have entered the test facility, the box. By improving this part of the test process a time saving of 20 seconds per unit can be achieved, equivalent to 7% time reduction. This can be compared to an additional 1400 units each year.

A finite sample improvement of the fixed effects estimator : applied to technical infficiency

The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.

On statistical bounds of heuristic solutions to location problems

Solutions to combinatorial optimization problems, such as problems of locating facilities, frequently rely on heuristics to minimize the objective function. The optimum is sought iteratively and a criterion is needed to decide when the procedure (almost) attains it. Pre-setting the number of iterations dominates in OR applications, which implies that the quality of the solution cannot be ascertained. A small, almost dormant, branch of the literature suggests using statistical principles to estimate the minimum and its bounds as a tool to decide upon stopping and evaluating the quality of the solution. In this paper we examine the functioning of statistical bounds obtained from four different estimators by using simulated annealing on p-median test problems taken from Beasley’s OR-library. We find the Weibull estimator and the 2nd order Jackknife estimator preferable and the requirement of sample size to be about 10 being much less than the current recommendation. However, reliable statistical bounds are found to depend critically on a sample of heuristic solutions of high quality and we give a simple statistic useful for checking the quality. We end the paper with an illustration on using statistical bounds in a problem of locating some 70 distribution centers of the Swedish Post in one Swedish region.