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Use of graphic methodologies, to analyze yearly factory data for improved identification of problems and solutions

机译：使用图形方法，分析年度工厂数据，以改善问题和解决方案的识别

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摘要

Most of the information generated daily in sugarcane factories is not adequately analyzed, because factories do not have the resources to do it or the time. Few factories analyze the information, and the analysis normally performed includes means and simple line graphs. Graphic methodologies such as box plots or histograms allow a more accurate analysis of the data and offer more practical information from which the staff can draw conclusions quickly. In this study, daily data from one Louisiana (LA) factory across four processing seasons (2015-2019) were analyzed, and three work areas were identified where improvements needed to be implemented to increase their efficiency (milling tandem, mud filtration, and boiling house). Two other areas were also highlighted for good performance due to previous changes implemented in the factory (juice liming and evaporation). In the milling tandem, the extraction of pol was 96%, leading to a pol in bagasse 2%; additionally, the imbibition remained above 200%, generating a Brix drop greater than 3 points. In the mud filtration station, an improvement in the performance of the station was observed over the years, despite the variation in the amount of mud being processed, which increased proportionally to the rainfall (R-2=77%). However, the efficiency could be enhanced by increasing the capacity of the station, which was below what references indicate (0.4 vs. 0.5-0.7 m(2)/tc/h). In the evaporation station, the use of an online measure of the heat transfer coefficients along with some other factory changes in 2019 improved the final evaporator syrup Brix, because the percentage of syrup Brix data within the target range increased from 25% and 30% between 2015 and 2018 to 53% in 2019. In the boiling house, it is necessary to increase the exhaustion in the C pans because the purity drop should be 20-point and the purity drop reached was only 12% with occasional values of 16%.
机译：每天在甘蔗工厂产生的大多数信息都没有充分分析，因为工厂没有资源做到这一点。少数工厂分析信息，通常执行的分析包括手段和简单的线条图。图形方法如盒子图或直方图，允许更准确地分析数据，并提供更实用的信息，员工可以快速得出结论。在这项研究中，分析了来自四个加工季节（2015-2019）的路易斯安那州（LA）工厂的日常资料，并确定了三个工作区域，其中需要实施以提高其效率（铣削串联，泥浆过滤和沸腾屋）。由于在工厂中实施的以前改变（果汁跛行和蒸发），另外两种区域也突出了良好的表现。在铣削串联中，搅拌的萃取是96％的，导致甘蔗渣＆ 2％;此外，吸收仍然高于200％，产生大于3分的Brix跌幅。在泥浆过滤站中，多年来观察到车站性能的改善，尽管正在处理的泥浆量的变化，这与降雨量成比例增加（R-2 = 77％）。然而，通过增加车站的容量可以提高效率，这低于参考文献的表明（0.4 vs.0.0.7m（2）/ tc / h）。在蒸发站中，2019年使用传热系数的在线测量以及其他一些工厂的变化改善了最终蒸发器糖浆Brix，因为目标范围内的糖浆Brix数据的百分比增加到25％和30％之间2015年和2018年的2019年为53％。在沸腾的房子里，有必要增加C盘中的疲惫，因为纯度下降应该是20点，并且达到的纯度下降只有12％，偶尔值为16％。

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