V3I9P39

Application of Deterministic Finite Automata to Local Rice Post-Harvest Processing and Milling 

Zaid Ibrahim¹, M. T. Umar²*, S. I. Abubakar³

Abstract

Rice milling operations involve ordered sequences of activities in which incorrect execution of processing stages may affect workflow consistency. Existing descriptions of rice processing pathways are commonly presented as procedural diagrams and do not provide a formal mechanism for verifying allowable and invalid operation sequences. This study develops a deterministic finite automaton (DFA) framework for modelling and verifying a selected local rice milling sequence consisting of cleaning, pre-heating, drying, husking and polishing operations. Each processing stage is represented as a state, while each operation is represented as an input symbol. A complete DFA with a dead state is constructed to distinguish admissible sequences from incomplete and erroneous sequences. The extended transition function, accepted language, regular expression representation and state minimality are established mathematically. The resulting seven-state DFA is shown to be minimal using distinguishable right languages. A computational verification of all strings of length zero to eight confirms the theoretical classification of possible sequences. The proposed model provides a formal sequence-monitoring framework for agricultural processing systems. The DFA does not estimate physical variables such as moisture content, milling yield or grain quality; rather, it provides a mathematical representation of operation order and process compliance. The framework demonstrates the potential of finite-state modelling as a foundation for future data-driven and condition-aware agricultural process models.

Keywords:

Deterministic finite automaton; rice milling; discrete-event systems; process verification; regular language; sequence monitoring