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1
objeto de conferencia
The main objective of this research was to show the predictive model implementation effects adjusted to grinding process on the economic profitability of a rice milling company. In first instance, quality and production area database was used to model a multiple regression equation, using the “Step by Step” technique in Minitab 19, resulting in: Actual Performance = 0.001 + 0.9317Hest Analysis - 0.000339 Processed Sacks; Predictive R2 = 95.81% and PRESS = 47.5168; concluding that the model fits the process, it is significant and has good predictive capacity. The regression equation was then simulated with Monte Carlo by analyzing probabilities and ranges in MS-Excel, earning operational revenue amounting to S/. 3,263,787.74 corresponding to an improvement of 3.94% compared to 2019, thus improving the company's economic profitability to 9.34% in Net Profit Margin and 15.92% in the ROA...
2
objeto de conferencia
This work was prepared to develop an improvement proposal for Bermanlab logistics area through the application of engineering tools to reduce operational costs. In the first place, the existing problems in the area were identified, an Ishikawa diagram was used for the diagnosis where the causes of these problems are exposed. It was proposed to use the Kardex tools, 5S and the EOQ model for the solution. Which can reduce operating costs by S /. 9,368.16. Finally, an economic evaluation was carried out, which would have a VAN of S /. 11,987.15, an TIR of 92.95% and a B / C of S /. 2.45, concluding that the proposal would be profitable.
3
tesis de grado
This study was performed in an agro-industrial milling company with the aim of reducing operative costs over the production and manteinance areas. The company's data was obtained through an interview and documentary analysis. Initial diagnosis was made using the following methods: SWOT analysis, Porter's five forces, PESTLE analysis, IFE and EFE Matrix, Ishikawa diagram and Pareto chart. An improvement plan was designed including tools related to Production Management and Manteinance Management: Demand Forecasting, MRP, Preventing Manteinance Plan, Transport network optimization, SRM and Process Standarizing. The improvement plan was simulated in ProModel 2016 software, using projected production data from the development of the proposed tools. Results obtained were: removal of rate of unscheduled plant shutdown, 14% decreased of the production rate not achieved by the machine "Table Pad...