Skip to main content
ARS Home » Southeast Area » New Orleans, Louisiana » Southern Regional Research Center » Commodity Utilization Research » Research » Publications at this Location » Publication #414789
Research Project: Improved Conversion of Sugar Crops into Food, Biofuels, Biochemicals, and Bioproducts

Location: Commodity Utilization Research

Title: Update on the development of a secure online application (app) for visualizing manufacturing reports

Author
item Terrell, Evan
item Lima, Isabel
item MANSALIKA, ANURAG - Audubon Sugar Institute
item EGGLESTON, GILLIAN - Audubon Sugar Institute
item IMBACHI ORDONEZ, STEPHANIA - Audubon Sugar Institute

Submitted to: Meeting Abstract
Publication Type: Proceedings
Publication Acceptance Date: 4/18/2024
Publication Date: 4/18/2024
Citation: Terrell, E.C., Lima, I.M., Mansalika, A., Eggleston, G., Imbachi Ordonez, S. 2024. Update on the development of a secure online application (app) for visualizing manufacturing reports. Meeting Abstract. p.80-84.

Interpretive Summary:

Technical Abstract: Raw sugar factories in Louisiana generate tremendous amounts of daily manufacturing data which are diligently compiled and shared among the employees, supervisors, and stakeholders of the factory. These daily reports contain lots of detailed information pertaining to the material amounts and transitions, e.g., cane, juice, syrup, raw sugar, etc. A working prototype of visualizing graphically the information from multiple Louisiana raw sugar factories was built using the Shiny package in R (RStudio) (https://shiny.posit.co/). First, factory data must be read from daily manufacturing reports and compiled in a table of values (for example, in a Microsoft Excel spreadsheet). Troubleshooting the process for fully automating the data transcription process is ongoing. Once there is a centralized dataset for a given location or set of locations, then the developed R code reads these data points. The R code then presents a graphical user interface whereby variables of interest can be selected from drop-down menus and plotted against one another. The user can also generate trends over time within each grinding season, or for multiple seasons, for comparison purposes. Ideally, this could be done by factory personnel from anywhere in the factory using computers, phones, or other mobile devices. Overall, data analysis and visualization are critical to understanding process flows and operations and are the first step towards the incorporation of artificial intelligence and automation in manufacturing industries. It will also be greatly beneficial for future exploratory data analyses to compile a large volume of data in a centralized location. Developmental work on the presented app is ongoing to incorporate more desired data and features.