Real-time stock analysis for blending recipes in industrial plants

TL;DR

This paper presents a real-time stock analysis application for industrial blending processes, integrating planning algorithms to optimize ingredient usage and production quantities, replacing traditional spreadsheets.

Contribution

It introduces a centralized, user-friendly application with algorithms for real-time stock assessment and production planning in industrial blending, implemented in C#.

Findings

The application effectively identifies needed ingredients for blending.

It calculates maximum producible quantities based on current stocks.

It determines optimal production quantities for efficiency.

Abstract

Many companies use Excel spreadsheets to keep stock records and to calculate process-specific data. These spreadsheets are often hard to understand and track. And if the user does not protect them, there is a risk that the user randomly changes or erase formulas. The paper focuses on the stocks of products used in a blending process with a known recipe. Developing an application that can bring this data in a centralized form and that can assist the operator in decide is a necessity. When a programmer implements an application that uses data from plants he needs to consider one fundamental aspect as reading real-time data from the process. The real-time stock analysis application takes into account all the above elements. The application is easy to use by an operator in the command room of installation because of the planning algorithms integrated into it. The algorithms proposed and implemented in this paper have well-defined goals: identifying the ingredients needed to achieve the blending process for required quantities, determine the quantities of the finished product that can be made with the existing ingredients and determine the optimum quantities of the finished product. The application implemented in C# intensively uses these algorithms and gives the user the ability to build the result step by step.