INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 485
OCCUPATIONAL SAFETY MANAGEMENT SYSTEM IN MANUFACTURING
ENTERPRISES: A PROGRAM FOR CREATING A CONCEPTUAL MODEL FOR
RISK ASSESSMENT AND ANALYSIS
Sulaymanov Sunnatulla Sulaymanovich
Doctor of technical sciences, professor, Tashkent State Transport University
+99897775-51-79 ssulayman@mail.ru
Orcid number https://orcid.org/0000-0001-5275-5200
Saidov Doston Nuriddin ugli
PhD candidate of Tashkent State Transport University
+99890 167-96-00
Orcid number https://orcid.org/0009-0004-4803-6026
Batirova Mavluda Mirxadiyevna
Senior teacher of Tashkent State Transport University
+998 91 191 46 56
movludabotirova0@gmail.com
Orcid number https://orcid.org/0009-0006-8542-003
Abstract:
This article describes the conceptual model for creating a program for creating a
conceptual model of a labor protection management system at manufacturing enterprises and
examples of the created program. A conceptual model for assessing and analyzing risks is
proposed for developing a labor protection management system at manufacturing enterprises.
The model uses modern approaches and digital technologies aimed at minimizing production
risks based on the requirements of the ISO 45001 standard. Also, accidents are analyzed and
safety measures are determined based on the Heinrich theory, Domino theory and the human
factor model. As part of the model creation, a Python software model was developed to increase
production safety, which allows monitoring and assessing the level of worker safety. The results
indicate the need to apply innovative approaches to minimizing risks and increasing labor
productivity at enterprises.
Keywords:
Labor protection, risk assessment, ISO 45001, production safety, digital technologies,
python model
Introduction.
The effective organization of occupational safety and the establishment of
a safety culture in manufacturing enterprises are among the most crucial aspects of modern
industrial development. Various risk factors exist in production processes, and the ability to
identify, assess, and effectively manage them in advance is an integral part of occupational
safety. Ensuring safe working conditions not only protects employees' health and lives but also
plays a vital role in increasing productivity and ensuring the sustainable development of
enterprises.
The following theoretical models are utilized to ensure occupational safety in the
management of labor protection: Heinrich's Theory (which suggests that behind every major
accident, there are 29 minor incidents and 300 near-misses) [1], Domino Theory (which explains
that accidents occur as a result of a chain reaction of interrelated events) [2], and Human Factor
Theory (which states that workers' skills and behavior directly impact safety) [3].
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 486
Methodology.
ISO 45001 is an international standard for occupational health and safety
management systems, encompassing elements such as development, implementation, monitoring,
and continuous improvement [4].
To successfully implement a practical model of an occupational safety management
system, the following stages are developed: assessment phase, planning phase, implementation
phase, and analysis and monitoring phase.
The scientific and theoretical foundations of occupational safety management focus on
ensuring safety in production processes, preventing workplace accidents, and safeguarding
employees' health. To adapt this system to industrial conditions, it is necessary to develop a
comprehensive management system based on modern risk analysis methods, digital technologies,
and international standards [5].
The organization and management of occupational safety in manufacturing enterprises
consist of the following stages:
Formulating Occupational Safety Policy – The company’s management develops a
general safety and occupational health policy, ensuring compliance with international (ISO
45001) and national standards while defining commitments to protect employees' health and
safety.
Risk Identification and Assessment – Potential hazards in workplaces are identified, risk
assessment methods such as FMEA, HAZOP, and SWOT analysis are applied, and measures are
developed to reduce risks based on workplace condition assessments.
Implementation of Regulatory and Legal Documents – Internal occupational safety
regulations are established, workplace safety standards are created, and compliance with labor
codes and legal regulations is ensured.
Training and Education in Occupational Safety – Regular training sessions for employees
and managers are conducted on workplace safety, emergency response procedures, and the
correct use of personal protective equipment (PPE) [6].
Implementation of Control and Monitoring Systems – Work conditions are continuously
monitored, employee compliance with safety requirements is checked, and accident and
occupational disease statistics are maintained regularly.
Emergency Preparedness – Plans for fire, explosion, and chemical hazards are developed,
rapid response teams are formed, evacuation routes are designated, and drill exercises are
conducted.
Continuous Improvement of the Occupational Safety System – The system is regularly
updated based on employee feedback, innovative technologies, and automated management
systems. Internal and external audits are conducted to assess the effectiveness of the safety
system.
The sequential processes outlined above contribute to ensuring a safe working
environment in industrial enterprises, reducing workplace accidents, and increasing labor
productivity.
Below, we develop a conceptual model for organizing and managing occupational safety
in industrial enterprises. This model includes all key stages of occupational safety and is built on
a systematic approach.
The proposed model represents the step-by-step process of organizing and managing
occupational safety in industrial enterprises. It can be utilized to enhance industrial safety
management and establish a structured control system.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 487
A Python-based program has been developed to implement this occupational safety
management model, with a corresponding code structure prepared for automation.
from graphviz import Digraph
# Mehnat muhofazasini tashkil etish va boshqarish jarayoni modeli
dot = Digraph('Mehnat Muhofazasi Boshqaruv Modeli')
# Tugunlar (bosqichlar)
dot.node('A', '1. Mehnat muhofazasi siyosatini shakllantirish')
dot.node('B', '2. Risklarni aniqlash va baholash')
dot.node('C', '3. Mehnat muhofazasi bo'yicha normativ-huquqiy hujjatlar')
dot.node('D', '4. Mehnat muhofazasi bo'yicha trening va o'qitish')
dot.node('E', '5. Nazorat va monitoring tizimini joriy etish')
dot.node('F', '6. Favqulodda vaziyatlarga tayyorgarlik')
dot.node('G', '7. Mehnat muhofazasi tizimini takomillashtirish')
# Bog'lanishlar
dot.edge('A', 'B')
dot.edge('B', 'C')
dot.edge('C', 'D')
dot.edge('D', 'E')
dot.edge('E', 'F')
dot.edge('F', 'G')
dot.edge('G', 'B', label='Tahlil natijalariga asoslanib qayta ko'rib chiqish')
dot.render('mehnat_muhofazasi_modeli', format='png', cleanup=False)
Result.
An algorithmic model of labor protection organization and management
processes was developed using the Python program. For this, the Python program and the
Jupyter Notebook (.ipynb) platform must be installed on the computer. To launch this platform,
perform the following steps:
For Windows OS:
1. Press Win + R to open cmd (Command Prompt).
2. Enter the following command “jupyter notebook” and press Enter.
3. The Jupyter interface opens in the browser.
Figure 1. Overview of the Jupyter interface in the browser
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 488
The Python3 part of the platform is selected from the image.
Then a window will open in this form, in which the model code is placed below.
Figure 2. Model view in Jupyter window
After pasting the model code, pressing Shift+Enter will display the answer in a window like this.
This response will appear in the
window. Now, to open this file, a command is given to the code part of the Jupyter interface.
When this command is given, the
model drawing below will open in the Jupyter interface (Figure 2).
During this program, a simple small code is written that also demonstrates the "Safety
Monitoring System for Workers". This code is also written using Python and the response is
received through the Jupyter interface. The model performs the following functions: Assessing
the risk level of workers, Checking compliance with safety rules, and Generating a Report.
This code is written to assess the safety rating of workers and determine the level of risk.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 489
Figure 3. Model of the processes of organizing and managing labor protection in
manufacturing enterprises
The purpose of writing the code is:
Analyze the safety score of workers
Assign a risk level for each worker (Safe, Medium risk, High risk)
Create a table of results and save it to a CSV file
How the code works
List of workers
Each worker is given an ID, Name, and Safety score (safety_score).
For example: {"id": 1, "name": "Ali", "safety_score": 95}
assess_risk(worker) function
Evaluates the risk level based on the worker's safety score:
80 and above → "Safe"
50-79 → "Medium risk"
Below 50 → "High risk"
generate_report(workers) function
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 490
Figure 4. Code for the safety monitoring system for workers
Calculates the risk level for each worker and adds it to the table
Displays the table on the screen
Saves it to a CSV file (safety_report.csv), which can then be used for analysis or
monitoring.
Result (output report)
The table that appears on the screen:
ID Name
Security Rating Risk Level
1
Ali
95
Safe
2
Vali
80
Safe
3
Sardor
60
Moderate risk
4
Jamshid 30
High risk
This code can be used to automatically assess, monitor, and report on the safety level of workers,
identify potential hazards in advance, and take action. When the code runs, a safety_report.csv
file is created that can be opened in Excel or other programs.Each worker in the system has a
safety rating. If he or she engages in unsafe behavior, his or her rating is lowered and the system
issues a warning.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 491
The response is obtained by running the following code in Python.
Figure 5. The view of the safety monitoring system for workers in Jupyter
The report was created by pressing Shift+Enter to run the code in this window.
To use the worker safety monitoring system code, you can run the following code in Python and
get the following result. First, the code looks like this, and it is placed on the Jupyter platform.
This code is designed to
create a simple model
for a worker safety
monitoring system. Its
purpose is to do the
following:
1.
Monitor
worker
safety status – The data is created in a table format, which contains the following indicators for
each worker:
Protective clothing (X) (1 – present, 0 – absent)
Safety compliance (Y) (as a percentage)
2. Calculate safety rating (Z) – The overall safety rating of each worker is calculated based on
the following formula:
Z = X ∙ Y ∙ 100
This rating helps determine how well an employee is following safety rules.
1. Output safety results – The results are displayed on the screen so that they can be easily
reviewed.
2. Save results in CSV format – The results are saved in the safety_report.csv file for further
analysis or use in other systems.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 492
This system can be used to monitor how employees are following safety and identify
problems in advance. If an employee has a low safety rating, additional work may be needed
with them.
Figure 6. Code for
monitoring
worker
safety status
Above, a conceptual
model has been developed
for optimizing the labor
protection
management
system and assessing and
analyzing
risks
at
production
enterprises.
The
model
includes
important factors that
allow increasing labor
safety, reducing accidents,
and effectively managing
production processes.
Above, a conceptual model has been developed for optimizing the labor protection management
system and assessing and analyzing risks at production enterprises. The model includes
important factors that allow increasing labor safety, reducing accidents, and effectively
managing production processes.
This result is obtained.
During the study,
various models of labor
protection were coded and
analyzed using the Python
programming
language,
and the results were
evaluated
practically.
Algorithms
for
determining the level of
risk were developed and
their
application
in
production processes was
tested.
The
results
obtained
proved
the
effectiveness of digital
technologies in improving
labor protection.
Conclusion.
Based on the results of the analysis, innovative approaches to assessing and
managing risks in manufacturing enterprises were proposed. This model is of great importance
for increasing the efficiency of the labor protection system, monitoring the level of compliance
with safety regulations, and preventing accidents.
INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE
ISSN: 2692-5206, Impact Factor: 12,23
American Academic publishers, volume 05, issue 03,2025
Journal:
https://www.academicpublishers.org/journals/index.php/ijai
page 493
In the future, there are prospects for further improving this model, using artificial
intelligence technologies, and developing real-time risk monitoring systems.
References:
1. Власова Наталья Олеговна Генрих Шенкер и его аналитическая теория // Искусство
музыки: теория и история. 2012. №6. URL: https://cyberleninka.ru/article/n/genrih-
shenker-i-ego-analiticheskaya-teoriya (дата обращения: 01.03.2025).
2. Зобнин Алексей Владимирович Теория домино в истории зарубежной политической
мысли // Вестник ИвГУ. Серия: Гуманитарные науки. 2016. №4. URL:
https://cyberleninka.ru/article/n/teoriya-domino-v-istorii-zarubezhnoy-politicheskoy-mysli
(дата обращения: 01.03.2025).
3. Семыкина Светлана Владимировна Человеческий фактор и его социально-
экономические и институциональные формы в современной экономике // Вестник
Курской государственной сельскохозяйственной академии. 2010. №6. URL:
https://cyberleninka.ru/article/n/chelovecheskiy-faktor-i-ego-sotsialno-ekonomicheskie-i-
institutsionalnye-formy-v-sovremennoy-ekonomike (дата обращения: 01.03.2025).
4. GOST R ISO 45001-2020
5. Sulaymanovich, S. S., Nuriddin ogli, S. D., & Mirxadiyevna, B. M. (2024). Innovative
approach to improving the efficiency of the system of organizing and operational
management of labor protection at enterprises. Journal of Adaptive Learning Technologies,
1(6), 79–84. Retrieved from
https://scientificbulletin.com/index.php/JALT/article/view/282
6. Sulaymanov S.S., Batirova M.M., Saidov D.N. — Korxonalarda mehnat muhofazasini
tashkil etish va operativ boshqaruv tizimi samaradorligini oshirishga innovatsion yondashuv
2024 йил 1-сон ISSN №2181-2209 Journal of innovative research in textile and light
industry
