دانلود رایگان مقاله اندازه گیری عملکرد کم آبی گیاه سیب

ABSTRACT

 Given the importance of the Chilean dried-fruit market and the characteristics of the industrial process of dehydration, it becomes imperative for companies to measure the ef- ficiency of their production processes in order to identify critical areas and take the necessary actions to improve them. Hence, the present work performs an efficiency analysis for the production of dried apples in a plant of the Maule region, Chile. The methodology used is Data Envelopment Analysis, considering both discretionary and non-discretionary variables. The results indicate that the application of the model without non-discretionary variables shows higher efficiency indices than the model with non-discretionary variables. Additionally, the efficiency analysis results, segregated by variety, origin, and fruit type, indicate that the selection of these segregations could be used to increase the production or generate higher efficiencies. Finally, the technological change in the same plant is analyzed through the Malmquist index. The findings of this research could help improve the decision-making process of managers concerned with the efficient use of resources within the company.

6. Conclusions

DEA models have been proven to be a reliable, flexible, and efficient tool in measuring the performance of the dehydration process. This work examines two input-oriented BCC-DEA models, with DVs and NDVs. Thus, the NDM provides the technical efficiency measurement in the current decision process of the company, while the DVM provides the measurement in a proposed strategic decision process. The information obtained from both models helps managers to identify the inefficient lots and helps to take the corrective actions in order to continue the improvement. Through the BCC-DEA models, it was possible to: calculate an efficiency measure for each processed lot, identify the efficient lots, and provide benchmarks for the inefficient lots according to the segregation or classification performed. This fact is highly relevant for a company, as it allows to determine the possible causes of inefficiencies and to estimate the possible improvements in the use of resources. In general, irrespective of fruit segregation (variety, origin, or type), the application of the DVM shows better results, higher efficiency indices, and lower variability coefficients than the NDM. However, regardless of fruit origin, the production process reaches similar efficiency levels with both models. This information could help solve bottlenecks in the buying process and improve the logistics process. Additionally, processing organic apples allows higher efficiency levels than processing ordinary apples. This result could be used to promote the consumption of the organic apple varieties in the dehydration process, and to increase the commercial prices of products labeled as organic. Considering the efficiency analysis for the overall segregations (as an aggregated data set), it could be observed that the relative efficiency frontier obtained by applying a DVM is higher, by approximately 13%, than the relative efficiency frontier of the current situation, which is represented by a NDM. This implies that a change in the decision process, either in the selection of the fruit or in the setting process of the machinery, could allow a cost reduction. At the same time, according to the DVM in Fig. 4, we have found potential reductions in the storage time, by approximately 35%, which results in savings and better efficiency levels.