Akademik Veri Yönetim Sistemi
12th INTERNATIONAL CONGRESS ON OCCUPATIONAL SAFETY AND HEALTH, İstanbul, Türkiye, 20 Kasım 2025, ss.115-121, (Tam Metin Bildiri)
Today,
the rapid digital transformation of industrial activities is fundamentally
changing work practices at every stage, from production to maintenance
processes. The core components of Industry 4.0 artificial intelligence (AI),
the Internet of Things (IoT), big data analytics, and cyber physical
systemsenhance the efficiency and competitiveness of enterprises, while
simultaneously introducing new types of risks and opportunities in the field of
occupational health and safety (OHS). This transformation, through production
line automation, the widespread use of robotic systems, sensor-based monitoring
networks, and digital twin technologies, not only improves worker safety but
also exposes the limitations of traditional risk management models. Conventional
risk assessment methods such as HAZOP, FMEA, or Fine-Kinney have static
structures that make it difficult to fully represent the dynamic and
continuously changing environments of digitalized production systems. Since
these methods rely on historical data and fixed scenarios, they remain limited
in monitoring dynamic risks and sudden hazard changes. In contrast, modern
industrial systems operate through real-time data collection, continuous
monitoring, and predictive maintenance; therefore, risk management must act
with the same speed and flexibility. At this point, digital OHS systems come
into play, building a proactive safety culture through sensor-based data
monitoring, AI supported analytics, and IoT based alert mechanisms.
The
mining sector, in particular, is one of the industries where the impacts of
digitalization are most visible. Traditionally characterized by high risk
working environments, mining operations face serious accidents caused by
vehicle-human interactions, gas accumulation, rock falls, and equipment
failures. Consequently, smart sensors, proximity detection systems, gas
monitoring technologies, and data-driven control mechanisms have become
essential tools for improving safety performance within the digital
transformation process. Reports published by international organizations
especially EU-OSHA (European Agency for Safety and Health at Work), ICMM
(International Council on Mining and Metals), MSHA (Mine Safety and Health
Administration), and NIOSH (National Institute for Occupational Safety and
Health) highlight that these technologies have significantly contributed to
accident prevention, hazard awareness, and early risk detection. The advantages
of digitalization in the OHS field are not limited to risk identification. They
also foster the transformation of workplace culture, enhance employee
awareness, and promote data driven decision-making in management processes.
Through real time monitoring systems, hazardous situations can be immediately detected
and addressed, while AI based algorithms can predict potential dangers such as
equipment fatigue, gas concentration increases, or human error, preventing
possible accidents in advance. This evolution transforms the traditional reactive
OHS approach based on post incident interventions into a proactive and
preventive safety paradigm. However, these technological innovations introduced
by digital transformation also bring new areas of responsibility. Factors such
as data quality, cybersecurity, privacy, and human machine interaction are
critical for the success of digital OHS systems. Poor data quality can lead to
inaccurate risk assessments, while cybersecurity vulnerabilities may expose
production lines or safety systems to malicious interference. Moreover,
inadequate design of human machine interfaces can generate new types of risks,
such as ergonomic stress, cognitive overload, or distraction. Therefore,
ensuring the sustainable implementation of digital OHS requires a holistic
approach that integrates technical infrastructure with the human factor.
This
study examines the transformative effects of digitalization on occupational
health and safety (OHS) risk management through data and case studies obtained
from both national and international literature. The aim is to reveal how
digital technologies are integrated into occupational safety processes, in
which areas they have achieved success, and in which aspects new regulations
are needed. Within the scope of the study, and particularly through the example
of the mining sector, the contributions of digital systems in areas such as
accident prevention, data management, monitoring of employee behavior, and risk
communication are evaluated.