جستجوی مقالات مرتبط با کلیدواژه « productivity » در نشریات گروه « برق »

So far, numerous studies have been developed to evaluate the performance of decision-making units through DEA technique in different places, but most of these studies have measured the performance of decision-making units by efficiency criteria. The productivity is considered as a key factor in the success and development of decision-making units and its evaluation is more comprehensive than efficiency evaluation. Recently, the productivity has been considered in DEA technique. The productivity in these studies is often evaluated through the productivity indexes. These indexes require at least two time periods and also the two important elements of efficiency and effectiveness in these studies are not significantly evident. There are few studies that measure productivity through efficiency and effectiveness. This few researches also measure the efficiency and effectiveness in two stages separately. So, the purpose of this study is to develop a new approach in the DEA technique in order to measure productivity of decision-making units through efficiency and effectiveness simultaneously, in one stage and interdependently. One case study demonstrates application of the proposed approach in the branches of a Bank. Using proposed approach revealed that efficient branches are not necessarily productive, but productive branches are also efficient.

The current study investigates the optimization of solar stills (SSs) productivity under different levels of solar radiation intensity, film cooling flow rate and water depth. Taguchi method is applied to perform a minimum number of experiments and to find the optimal water depth and cooling rate that maximize the productivity of the SS. An orthogonal array, signal-to-noise ratio and analysis of variance (ANOVA) are used to investigate the influence of the operating parameters on the solar still productivity. Taguchi method and ANOVA result several that water depth is the most influencing parameter. Furthermore, the results show that increasing the solar radiation and water film cooling improve the productivity. However, increasing the flow rate more than 4 kg/hr has a slight effect on the productivity. On the other hand, decreasing the water depth leads to a great enhancement in the productivity due to the faster evaporation and condensation rates. The levels of the operating parameters under-investigation are selected as follows: solar radiation intensity (5587,5673 and 5741 W/m2/day), film cooling flow rate (2, 4 and 6 kg/hr) and water depth (0.5, 1 and 1.5 cm). The improvement in the productivity with film cooling was about 6.05% at the water depth (0.5 cm)

Behavioral economic has received much attention recently. Learning and fatigue are two typical behavioral phenomena in industrial production operation processes. The existence of learning and fatigue result in a dynamic change in productivity. In this paper, a classical economic production quantity model is extended to consider the behavioral economic value of learning and fatigue. Based on a real case study, each production cycle is divided into five phases, i.e, the learning phase, stable phase, fatigue phase, fatigue recovery (rest) phase, and the relearning phase. The new production inventory decision model is incorporated with dynamic productivity and learning-stable-fatigue-recovery effect. Numerical simulation and sensitivity analysis show that appropriate rest alleviates employees fatigue and increases productivity, resulting in a lower average production cost. On the other hand, when the rest time is too high, exceeding a certain value, it leads to the decline of the actual labor productivity, resulting in an increase in the average cost of the system.

Labor productivity is one of the most significant factors in the evaluation of construction projects performance. Improvement of labor productivity is believed to have direct impact on outperformance of the project.
This research argues about a hybrid SD-DES approach to model labor productivity considering the effects of both the context and operational level factors. The complex inter-related structure of different context factors affecting the labor productivity is modeled using system dynamics (SD) approach. Discrete event simulation (DES) is implemented to model the operational variables and their effects on labor productivity. Using the proposed hybrid SD-DES model, the labor productivity can be determined more precisely since the effects of both context and operational variables are taken into account. The proposed hybrid model is implemented in a real world case and the value of labor productivity is simulated considering the effects of both context and operational variables.