ANALYSIS OF THE OPTIMAL ORDER OF DIAGNOSTIC ACTIVITIES USING AN IT TOOL – A CASE STUDY
Authors:   Silesian University of Technology, Gumiński Adam , Zoleński Wojciech ,   Silesian University of Technology, Gumiński Łukasz ,   Silesian University of Technology
Published: February 2025

Purpose: The article deals with the problem of supporting a decision-making process in
manufacturing enterprises. It concerns the possibilities of software algorithm determining the
optimal path of knowledge acquisition in the form of an expert system. As part of the research,
the conditions for developing the inference module and the knowledge base were determined.
In order to assess the usefulness of the analysed expert system, its validation and simulation
analysis of determining recommendations regarding decisions made by system’s user were
carried out.
Design/methodology/approach: The research include the following tasks: literature study
in the field of expert systems, analysis of existing IT solutions supporting decision-making
processes in manufacturing enterprises, analysis of applied expert systems and conditions for
their implementation, determination of design assumptions in terms of functional and non
functional requirements, preparation of expert system architecture, development
of a knowledge base in the expert system, development, programming and verification of the
expert system’s inference module, formulation of final conclusions and indication of directions
for further development of the expert system.
Findings: The study resulted in the development of the IT tool supporting a decision-making
process in a production process. The developed expert system is intended to provide the expert
with advice on the knowledge acquisition path that he should take in order to minimize the cost
of inference. In order to perform this task, the system performs simulations and conducts the
inference process on them, checking which path, with the parameters provided by the expert,
is the best. The core of the application is the inference module of the system. It is used to
perform simulations and derive the canonical form of the final hypothesis, and to determine the
nesting levels of individual statements.
Research limitations/implications: At the current stage of development, the application's
capabilities developed in the research, are limited. This is due to the fact that the database
of statements that are interrogative conditions can only consist of a few dozen statements and
the number of depths cannot exceed 10 levels, because the computational load becomes so
serious that conducting a simulation would take too long for the expertise to be useful.
In the current state, the increase in the load on the machine on which the inference process is
run grows exponentially with the addition of subsequent statements that are interrogative
conditions. Further development of the application depends on finding a metaheuristic that will provide
a solution that meets the requirements in a sufficiently short time. The solution to this problem
might be achieved with a genetic algorithm.
Originality/value: The value of the research is the identification of elements determining
a decision-making process in a production enterprise. The conducted research resulted in
developing and implementing the expert system, the task of which is to provide support in the
decision-making process based on the transferred knowledge. The application module
is responsible for interpreting the knowledge entered into the system and transferring the
processed knowledge in the form of specific advice.