Virtual Reality Application for the Safety Improvement of Intralogistics Systems

Abstract

Immersive technologies from the spectrum of Industry 4.0, such as Virtual Reality (VR), are increasingly used in research and safety analysis in industrial and intralogistics systems, including distribution warehouses and production plants. Safety in intralogistics systems is influenced by design and management processes, human behavior, and device performance. In all these areas, VR can serve as a supportive technology for visualization, testing, and employee training. However, this requires the development of principles for integrating VR into standard procedures for the design, modernization, and analysis of intralogistics and production systems. This article discusses the use of VR to analyze the occupational and functional safety of intralogistics systems. It reviews the literature and VR implementations aimed at examining and improving safety in industrial systems. The article explores the integration of VR into the design and analysis procedures for intralogistics and production systems. The authors present a five-dimensional decision space for assessing the use of VR, including identifying subjects of safety analysis, threats and hazards specific to intralogistics, countermeasures for these threats, factors affecting safety, and mechanisms by which VR can improve safety in intralogistics systems. As a subsequent step, the authors discuss using universal simulation environments that support VR technology to study and enhance safety in intralogistics systems, providing a framework example based on the FlexSim (2023 update 2) environment. Finally, this article addresses the threats and limitations of VR technology, along with the challenges and future prospects of VR in the context of Industry 4.0. The article concludes that VR can be an essential tool for increasing safety in the future, albeit with some reservations about certain features of this technology.

1. Introduction

Modern businesses are searching for innovative solutions to increase efficiency, reduce costs, and improve work safety. Since Industry 4.0 has become a paradigm for the development of logistics systems (see [1,2]), immersive technologies like Virtual Reality (VR) are gaining importance as tools that have not yet been fully exploited for the needs of intralogistics and industrial systems [3,4]. Implementing immersive technologies to enhance the design process and increase safety is considered an element of sustainable development, not only in logistics systems [5].

The development of VR applications in intralogistics, and more broadly in supply chains, is part of a larger technological trend related to Industry 4.0. This trend aims to improve the quality of services, safety, and comfort of people’s work and increase the capacity of systems to thrive. Consequently, these factors contribute to social sustainability goals by influencing health and safety at work and improving the efficiency and reliability of logistics processes, which translates into reducing resource losses and environmental impact [6]. The use of VR for training and safety analyses, therefore, affects health and well-being, as well as education and capacity building, enabling individuals to develop the skills and knowledge necessary for personal and professional growth.

Safety can be defined as “freedom from conditions that can cause death, injury, occupational illness, damage to or loss of equipment or property, or damage to the environment” [7]. Increasing safety, therefore, requires identifying risk factors that affect the safety of people, goods, and information, establishing methods to counteract these risks and reduce their effects, and providing knowledge on this subject to employees who manage risk executively (participate in it), operationally (supervise it), or conceptually (design it). Pursuing continuous improvement of work safety while increasing efficiency and minimizing costs, especially in the specific conditions of industrial and logistics systems, requires searching for new technologies and methods, such as VR, to open new research dimensions and drive progress.

Intralogistics systems encompass all infrastructure facilities involved in internal transport, buffering material flows (stock building), and transforming material flows through production, packaging, or picking processes [8]. The most common examples of such systems are distribution or industrial warehouses and production facilities. Intralogistics systems, such as warehouses, cargo terminals, and industrial plants, often handle very intensive material flow processes that result in significant equipment and employee movement within the facility’s enclosed space. This movement needs to be optimized to reduce labor intensity and work costs [8,9]. At the same time, it must be designed and strictly controlled to ensure the safety of employees and property, as it generates various threats to human well-being, goods, and infrastructure [10].

There is still a lack of general understanding regarding the strengths and limitations of VR when applied to the specific area of intralogistics [3,11,12]. Systematic reviews on the use of VR in various human activities, including all types of training, are present in the literature (e.g., [13]). However, these reviews typically do not refer directly to intralogistics systems but rather to broader areas like industry or engineering [4]. This indicates that there is still significant development potential in this area.

VR is a promising tool for industry and logistics, particularly in the context of early-stage and operational safety design and employee training [14,15]. When applied to intralogistics, VR can support the following areas [3,16,17,18,19]:

• Testing the physical configurations of systems in terms of passive safety for employees, equipment, and products.
• Researching the possibilities of implementing new technologies to increase safety (in combination with a simulation environment—what-if analysis), such as real-time positioning systems (RTLSs), intelligent devices, adaptive traffic control in logistics facilities, etc.
• Collecting statistically significant samples for research on the impact of specific technological solutions on the safety and comfort of work in the intralogistics system.
• Training operators and other individuals engaged in the material flow process.

Therefore, this paper aims to discuss the potential for using VR technology to improve safety in intralogistics systems. It also aims to formulate general principles for incorporating VR into the design, management, testing, and operation processes, particularly for continuous safety enhancement at different operational levels. The paper identifies the opportunities VR offers for increasing work efficiency and safety in intralogistics and recognizes potential risks that may arise from VR implementation. The focus is on identifying key areas where this technology brings significant benefits and assessing its impact on safety and work efficiency.

This study addresses the following research question: How can VR technology be incorporated into the design, testing, and operation of intralogistics systems, particularly for safety improvement, and what potential benefits and risks may arise from its implementation? To answer this question, the paper provides a comprehensive review of the literature, market solutions, and VR applications in various areas. The literature on the application of VR for safety analyses and designing intralogistics systems is limited due to the specificity of this research area. However, good practices from other areas of VR application can be analyzed and used to identify methods for integrating VR into the design and analysis procedures for intralogistics and production systems. This extensive review outlines the issues and serves as the foundation for general considerations aimed at incorporating VR as a permanent element of design activities and operational processes, utilizing popular VR technologies and universal simulation environments.

Since VR uses a computer-generated simulation environment representing actual systems, constructing simulation models for VR applications is also discussed. The VR simulation model can be single-purpose or based on an active, reconfigurable, and multifunctional simulation environment with a developed graphical layer, as expected in the simulation-based Industry 4.0 paradigm (see [1,2]). Combining VR with a universal, reconfigurable simulation environment enables cost-efficient, agile, and safe training [15,20] and serves as a control tool for investigating technological concepts. This translates into a reduction in the risk of workplace accidents and incidents, which is crucial for raising safety standards [3,20].

The following research methodology is adopted in this article:

• The intralogistics area was identified as a potential beneficiary of implementing methods to improve the safety of people and equipment through Virtual Reality (VR) training and case studies.
• A review of the literature and applications of VR for increasing safety in industrial and intralogistics systems was conducted.
• Areas and measures for implementing VR to enhance the safety of intralogistics systems and monitoring the effects of VR implementation were proposed.
• A methodology for incorporating VR-based tools into the iterative loop of designing and maintaining intralogistics systems was developed.
• Principles for using a universal simulation environment (FlexSim) to construct tailored, VR-based simulation models of systems quickly were proposed.
• An experiment to study selected aspects of forklift safety in the racking area of a distribution warehouse was presented to strengthen the assumptions of points 1–5.

  6.1.

  A FlexSim simulation model with a VR layer was designed (see Section 4.4).

  6.2.

  Simulation experiments were constructed.

  6.3.

  Simulation experiments were conducted for different scenarios of forklift operators’ work.

  6.4.

  The results were discussed.

  6.5.

  Conclusions were drawn about the possibilities of using VR to study intralogistics systems’ safety.

• A discussion was performed on the advantages and limitations of incorporating simulation models with a VR layer to study safety in intralogistics systems.

Although this article primarily focuses on VR technology, it occasionally references augmented reality (AR). Despite their differences, AR shares some similar features with VR, and the implementation of AR may be informed by previous research on VR.

The remainder of this paper is organized as follows: Section 2 provides a literature review of the topic and related areas. Section 3 discusses Virtual Reality as a tool for industry and intralogistics. Section 4 examines the integration of VR into the design and analysis procedures for intralogistics and production systems. Section 5 explores the threats and limitations of VR technology in safety analysis applications within intralogistics. Section 6 presents the challenges and opportunities for VR as a component of Industry 4.0. Finally, Section 7 discusses the findings and provides concluding remarks.

2. Literature Review—Statistics

The analysis of data gathered from scientific databases indicates an increasing significance of VR (and augmented reality (AR), not discussed in this paper) as a tool supporting Industry 4.0 in intralogistics and industrial applications. According to a 2022 McKinsey report [21], significant advancements in VR are still required and are expected to be realized in 8–10 years. However, immersive reality technologies like VR will be a key factor in learning and assessment, product design and development, enhanced situational awareness, and B2C case analysis, including safety improvements. Notably, 34% of McKinsey respondents [22] focus on implementing VR as a supportive Industry 4.0 technology. VR’s impact on reducing design time by 10.3%, increasing resilience to disruptions by 14.6%, and improving efficiency while reducing costs by 17.2% is particularly evident. This observation strongly supports the need for broader literature research.

The intensity of research in the field of Virtual Reality is extensively documented in the SCOPUS and Web of Science (WoS). A simple query for “Virtual Reality designing” in SCOPUS produces 5565 references, while WoS yields 26,539 references, indicating significant scientific activity. When the time frame is limited to 2020–2024, there are 2003 references in SCOPUS and 11,809 references in WoS. This may be related to the intensification of efforts to implement Industry 4.0 solutions in supply chains and industry following the COVID-19 pandemic. The pandemic led to a renewed focus on technologies that mitigate risk and enhance the efficiency of supply chains in the face of new threats. This topic has been widely discussed in industry reports, such as those by McKinsey & Company [1,22,23,24] and The Wall Street Journal [25]. Applications of VR in intralogistics, which are key for optimizing internal processes, are less frequently recorded (16 references in SCOPUS and 6 references in WoS for 2020–2024), suggesting a potential area for further development.

Data browsing shows that VR is often used in the context of industrial training, with 12,732 references in ScienceDirect and 674 references in IEEE Xplore, confirming its value as an educational tool. Virtual Reality also finds application in safety assessment, with 13,262 references in ScienceDirect, highlighting its importance in ensuring safe working conditions.

Queries in the SCOPUS database to search for articles containing specific words in the title, keywords, or abstract yielded 1139 references for Virtual Reality in logistics and 1441 references for augmented reality.

Selected data collected from the most important databases are presented in

Table 1. Summary of the literature review query on using VR and AR to study the security of intralogistics systems.

Phrase (Subject)	Number of Appeals
	Science- Direct	IEEE Explore	Web of Science	Scopus
Virtual Reality and logistics	7564	255	486	1203
Augment reality and logistics	5491	47	264	1477
VR and AR Technologies and Safety Assessment	2618	7	20	26
Virtual Reality and Safety Assessment	19,536	176	778	1441
Augmented reality and Safety Assessment	14,367	56	209	843
Augmented reality and Intralogistics Systems	86	4	8	5
Virtual Reality and Intralogistics Systems	95	7	6	15
Virtual Reality, industrial training	13,605	766	1419	1216

.

These numbers indicate a growing interest in applying VR in the fields of Industry 4.0. VR is increasingly used in logistics and intralogistics, particularly for on-the-job training and safety evaluations, underscoring its significant impact on innovation, efficiency, and the sustainability of supply chains.

The general conclusion from the quantitative literature analysis indicates that VR applications, especially in training, are strongly represented, as well as applications in the broader industry, particularly in supporting installation design. However, narrowing the focus to intralogistics issues specific to, for example, warehouse facilities reveals a small number of direct studies. Additionally, the analysis of the operating conditions of intralogistics systems indicates significant development potential in this area.

Furthermore, the literature does not fully address the problem of universally designing simulation models, which is discussed in this article.

3. Virtual Reality as a Tool for Industry and Intralogistics

3.1. General Picture

VR is a popular term, but its practical industrial applications have not been widely recognized since the technology was first applied to entertainment. Computer gaming is one of the most widespread areas of VR, providing a good general foundation for understanding its use in industrial contexts. However, VR is also used in other areas with varying degrees of complexity. According to Klačková [16], these technologies are most often used in engineering, the military, healthcare, entertainment, education, business, and sports.

VR can be applied in many areas related to intralogistics, including employee training, work safety improvement, and investment planning. VR fits into the trend of industrial automation and digitization. Machała, Chamier-Gliszczyński, and Królikowski [26] investigated how advanced VR applications have been used in industrial engineering in recent years. Their study presents various approaches by American entrepreneurs to using these technologies. Evaluating the efficiency of Industry 4.0, companies that have implemented augmented reality in their operations allow for the observation of the company’s situation at various levels of development (Novakova, Jakab, and Michalko [27]). In recent years, the VR technology market has been continuously developing, with machines and devices being purchased by enterprises from various economic sectors, as shown in Figure 1. The consumer sector is projected to reach USD 18.9 billion, and the enterprise and public sector is expected to reach USD 16.1 billion by 2025.

3.2. VR vs. Digital Modelling—Universal Simulation Model for VR Application

Virtual Reality (VR) involves creating an interactive computer simulation that responds to user actions and provides sensory feedback, particularly for sight, hearing, and touch, giving a sense of immersion in a virtual world (Steinicke [11]). VR requires a software layer in which a simulation model is implemented to support the logic of simulated reality and interaction mechanisms between the user and hardware. A simulation model is a digital representation of a specific fragment of reality, adapted to reproduce features and processes important for the purpose of modeling.

Key elements of a VR environment include the following:

• Virtual Content: consists of three-dimensional objects and their characteristics, such as shape, weight, color, texture, and other physical properties.
• Virtual Presence: the feeling of actually being in the VR environment, achieved through an advanced real-time tracking system, which influences the user experience (Dede et al. [28]).
• Interactivity: for VR to be realistic, it must respond to user actions. This requires the use of various input devices, such as VR controllers, Flystick VR, or VR gloves, which enable interaction with virtual content (Dede et al. [28]).

VR requires digital models of internal transport systems or workstations when used to study intralogistics systems. These models can be developed in several ways:

• A digital model as a stand-alone application: this is most often a single-purpose product with very limited or no ability to change the parameters of the modeled reality or track key performance indicators. It focuses on the high attractiveness of the sensory layer and user interaction.
• A digital model built in a dedicated environment: this model allows changes in simulated reality but still focuses on high-quality user interaction experiences and has limited ability to represent specific features of intralogistics systems.
• A digital model built in a specialized simulation environment: this model is designed for modeling intralogistics systems, emphasizing high-quality user interaction for safety analysis, mapping specific features of the intralogistics systems, and tracking selected processes and interaction parameters.

The third approach seems the most labor-intensive but provides a flexible and targeted research environment, especially when human behavior is a crucial research factor. It can also be supplemented with motion capture systems to investigate the ergonomics of work or space requirements. The authors of this article use the third approach, which is discussed in Section 4.3.

3.3. VR Hardware Layer

Among VR display technologies, the most popular are large projection screens (VR Powerwall), multi-screen systems (VR CAVE), stereo monitors, and VR head-mounted displays (HMDs). In recent years, thanks to technological development, VR goggles have become more accessible and practical, contributing to the growth of VR applications, especially in the consumer industry (Begus, Mihelj, and Novak [12]; Coburn, Freeman, and Salmon [17]).

An essential aspect of implementing VR in the industry is selecting displays that suit the user’s preferences and research goals. The choice of a specific device will affect how the research is conducted, the subjects’ experiences, and, to some extent, the results achieved. For typical and widespread applications like those discussed in this paper, it is necessary to rely on market products that are widely available but meet high professional standards. Equipment selection should be based on assessing the parameters of the technology under specific test conditions and the possibility of integration with the chosen simulation environment.

Various models of VR systems are available on the market, including those primarily intended for entertainment and gaming, such as Meta (Quest 2), Sony (PlayStation VR), and Valve (Index). There are also products designed for professional use, including Varjo (e.g., XR-3, offering high resolution and image quality), HTC (e.g., Vive Pro 2, with high image quality and advanced tracking functions), HP (e.g., Reverb G2, with user-tracking functions, including heart rate), Microsoft (e.g., Hololens, mixed reality devices with tracking and sensor functions), and Pimax (e.g., Vision 8K X, with a very wide field of view and high resolution). Additionally, displays from Apple, Meta, Vuzix, and Magic Leap are also utilized.

Choosing VR displays requires evaluating the technology based on its technical parameters, including the following:

• Resolution—crucial for the realism of the modeled environment (pixels, width × height per eye).
• Color Depth—ability to render colors (number of bits representing a single pixel’s color).
• Field of View (FOV)—the extent of the observable environment seen through the VR set (degrees).
• Refresh Rate—important for smooth simulation and realistic impression, critical for user comfort (Hz).
• Latency—delay between a user’s action and the VR system’s response (ms).
• Audio Parameters—built-in or external audio system providing a sound experience, including spatial audio capabilities.
• Tracking Accuracy—precision of the VR system in tracking movements of the head, controllers, and other motion sensors.

Other crucial parameters include the following:

8.

Ergonomics—weight, method of attaching the set to the head, pressure, adaptability to different users, and hygiene.

9.

Compatibility—types of supported connections and compatibility with the simulation system.

When using models developed within a specialized simulation environment, factors such as resolution, color depth, and sound parameters may be of secondary importance due to the limitations of the simulation environment itself. However, parameters such as refresh rate and latency are vital for the quality of work with the model, particularly in relation to potential VR sickness [29]. Ergonomic parameters are critical in every case.

When discussing VR, we should also mention augmented reality (AR). AR combines the real world with virtual elements, enriching the physical environment with digital information, most often textual or graphical (Dede et al. [28]). AR differs from completely Virtual Reality (VR) in that it does not replace reality with a virtual world but complements it by overlaying virtual images onto real environments, which may include text, graphics, and interactive objects (Gartner [30], Threekit [31], Techterms [32]).

AR technology is not discussed in this article due to its specific features. On one hand, these features exclude its use in the study of non-existent systems, and on the other hand, they provide completely different possibilities compared to VR.

3.4. Investment Planning and Workplace Design

Using simulation technologies for designing industrial layouts that do not yet exist is becoming increasingly common due to the benefits of risk and cost reduction. However, the use of VR in this context is relatively new. Menck et al. [33] presented an advanced VR-based approach to improve factory planning. Their method uses VR for simultaneous visualization, analysis, and assessment of processes to optimize production operations and minimize investment risks. In addition to factory design, Bellalouna [18] details how VR can contribute to effective factory planning. His approach allows for virtual immersion in the factory environment, offering intuitive interaction with the equipment and factory layout. This enables real-time assessment of the factory layout, considering criteria such as space utilization, efficiency, material flow, ergonomics, and work safety. Simonetto, Arena, and Peron [34] focus on designing ergonomic workplaces in assembly systems as part of Industry 4.0, combining motion capture systems and VR. Their approach includes collecting input data, designing virtual workplaces, analyzing data in terms of productivity and ergonomics, and assessing employee satisfaction with the ergonomic productivity of the workplace. Strzałkowski et al. [4] outline the potential of VR technology to advance safety practices in mining and construction. They focus on the well-being of workers, reducing accidents, and minimizing the negative environmental impacts associated with workplace incidents.

3.5. Employee Training

Holuša et al. [3] broadly discuss the use of VR in the training and safety assessment of organizations in the raw materials industry. They examine the influence and impact of VR training on employees, proving it to be a promising tool for education and training. Their findings show that VR facilitates the acquisition of practical skills, helps learners retain information better, and fosters the development of soft skills such as communication, teamwork, and leadership.

Ji et al. [35] introduce a new training method, DQL-VR, which combines the assessment of the risk of Diminished Quality of Life (DQL) with VR. This method focuses on training sessions using VR to educate users on sequential operations, standard work procedures, and assessing short-term safety risks. Additionally, Lyu et al. [19] have investigated how VR can enhance design thinking skills. Their research indicates that VR can enhance the creative and design skills of operators. Hamad and Jia [13] have studied how VR has impacted our lives, focusing on its current and potential applications and limitations. Their study highlights how VR can revolutionize education by offering more engaging experiences and aiding in the understanding of complex concepts.

Sanchez-Vives and Slater [36] emphasize that VR can disrupt the deeply rooted connection between the place where our senses indicate we are and our actual location and the people we are with. “Presence” refers to behaving and feeling as if one were in a virtual world. This concept should be studied by neurobiologists, as it can support research on perception and consciousness. In the context of industrial and logistical use, understanding and utilizing the phenomenon of “presence” in virtual environments is crucial for developing training and simulation methods. The ability to “transport” workers into a virtual environment, where they can experience and react to various scenarios, allows for more effective and safe training. Moreover, research on presence can contribute to a better understanding of how the human brain processes information in complex, dynamic environments, which is important in management and logistical planning.

Yuen, Choi, and Yang [20] present a VR simulation system based on CAVE technology designed to improve the safety of warehouse forklift operations and enhance warehouse management. The system offers a virtual environment where drivers can fully immerse themselves in forklift maneuvers and pallet operations. As a result, drivers can easily review and correct their driving techniques, and more importantly, “virtual accidents” can be created and visualized to increase safety awareness without real risk. Consequently, drivers become more alert and skilled in handling difficult conditions, making warehouses and internal logistics tasks safer, more efficient, and cost-effective to manage. Additionally, ongoing research explores the application of VR to support truck drivers during vehicle maneuvers (compare Machała, Chamier-Gliszczyński and Królikowski [26] with Standfield and Gracanin [37]). For example, Ribeiro et al. [38] focused on developing the VISTA-Sim platform, which uses VR to create personalized driver assistance systems. The platform, which assists truck drivers during docking, integrates a route planner, VR simulator, and human–machine interface (HMI), thereby increasing the safety and efficiency of maneuvers.

As an extension to the VR analysis, it should be noted that augmented reality (AR) significantly enhances the work environment in production, internal logistics, and warehousing by providing key information to workers. This information contributes to increasing the speed and quality of operations, both across the entire business area and at individual workstations. Interestingly, the feasibility of implementing AR can be tested using VR. The continuously developing features of AR in visual analysis enable effective interaction and communication with the real environment, which is reflected in its applications within Industry 4.0 (see Arm et al. [39]). Software, technology, and devices related to AR have become breakthrough discoveries for many companies, adding value by supporting quality control and the management of production and warehouse space (Saihi [2]). In logistics, AR enables employees to locate specific units of material, locations, or resources, minimizing the risk of time-consuming and potentially harmful manipulation of goods.

3.6. Work Safety and Ergonomics

Work Safety and Hygiene (OHS) is a critical area where VR finds important applications. OHS training with VR offers realistic scenarios that increase employee awareness of potential hazards and prepare them for various situations. Meanwhile, AR can be used to identify and signal potential dangers at workstations, providing employees with essential real-time information.

Safety and work ergonomics are also often discussed as key areas for VR application. Evangelista et al. [40] introduced an AR tool for assessing ergonomic risks in the workplace. Using an inexpensive D-RGB camera and an AR visualization system based on Microsoft HoloLens 2, they created a tool for the real-time assessment of ergonomic risks related to employee postures at workstations. This tool enables the monitoring of employee operations and the improvement of ergonomic conditions. Ginters et al. [41] researched low-cost AR technology and Radio Frequency Identification (RFID) in logistics, focusing on visualizing logistical items and emphasizing the importance of 3D visualization in this industry. Combining AR and RFID allows for better warehouse management, control of logistical processes, and error reduction.

Wetzel et al. [14] present an interesting application of VR to improve workplace safety, particularly in preventing accidents caused by slips, trips, and missed steps. Such accidents are common in both professional and private environments, often caused by scattered objects, dirt, or faulty infrastructure, such as slippery floors or tripping hazards. This demonstrates that Virtual Reality can help increase employee awareness of dangers. The “BGHW Warehouse Simulation” project uses VR to raise employee awareness of hazards and their consequences in a professional context, motivating them to behave safely during warehouse and internal logistics operations. The educational application was developed according to a structural design approach, aiming to eliminate hazards by employees or at least have them reported to superiors. Trainers support the application through supervised discussions.

On the other hand, Runji, Lee, and Chu [42] focus on AR applications in the industrial maintenance process. In the context of developing Industry 4.0 technologies, AR is used to facilitate manual operations by overlaying virtual information on real scenes. They also describe the use of AR in production maintenance, focusing on the needs of operators. A general process is proposed, classifying maintenance operations into four successive stages and analyzing the classification results based on geographical location, type of maintenance, AR technical elements, and integrated external sensors.

These examples highlight the growing importance of VR in areas such as work safety, training, and ergonomics, contributing to improved working conditions and increased operational efficiency. Additionally, they support ongoing work, as emphasized by Runji, Lee, and Chu [42].

3.7. Applications in Other Industries

Apart from intralogistics and production, VR is also present in other areas that provide new experiences applicable to intralogistics:

• Surgery: VR is used for neurosurgeons’ training (Stengel et al. [43]).
• Education: The use of VR tools in education has increased post-COVID-19 pandemic, offering rich and interactive educational environments that enhance student engagement and understanding (Al-Ansi et al. [44], Chan et al. [45]).
• Construction: VR is used to check structural integrity and identify installation conflicts. Zhang and Pan [46] propose tower crane layout planning (TCLP) in the context of modular integrated construction (MiC) using an innovative VR tool called cMiCrane. This tool allows for the interactive generation of crane layouts, performance evaluation, and lifting simulation, integrating users into the planning process.
• Interior Design and Architecture: VR enables clients and designers to better understand and visualize spaces before their physical realization. AR allows virtual objects to be placed in real spaces, aiding decision-making regarding appearance and functionality.
• Entertainment: VR and AR are revolutionizing how people experience games, movies, and events. VR offers deeply immersive experiences, allowing users to immerse themselves in virtual worlds. AR, on the other hand, enhances how consumers experience media by offering interactive and enriched content.
• Military and Defense Training: VR and AR offer realistic simulations and training. With VR, soldiers can undergo intense combat scenarios in a safe environment. AR is used to realistically display tactical information on the battlefield.

4. Integration of VR into Design and Analysis Procedures for Intralogistics and Production Systems

4.1. Methodological Framework for Safety Analysis in Intralogistics Using VR

Safety analysis in intralogistics is one of the key challenges, requiring continuous improvement of research methods and tools. The literature reveals that, despite the availability of general risk and safety assessment methods (see Levenson [47,48]), there is a clear need for solutions dedicated to the specific conditions and requirements of intralogistics. This research gap becomes the starting point for efforts aimed at providing more targeted solutions in warehouse and internal transport safety using VR, as emphasized by Chojnacki [49], considering safety analysis methods in warehouse systems.

Risk management in intralogistics involves applying standards like ISO 31000 [50] or HAZOP (Hazard and Operability Study) to identify, analyze, and control hazards. Tools such as checklists, root cause analyses, and methods like Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) allow for understanding the causes of incidents and assessing the potential impact and probability of hazards using techniques such as FMEA or Monte Carlo simulation (Chojnacki [49]).

Levenson [48] proposes an approach to risk management through leading safety indicators. Levenson defines a leading indicator as a “warning sign that can be used in monitoring a safety-critical process to detect when a safety-related assumption is broken or dangerously weak and that action is required to prevent an accident”. In the case of intralogistics systems, formulating leading indicators requires specific knowledge and data about the process, as well as a reference point (benchmarking). Using VR as an analytical tool may allow the identification and monitoring of leading safety indicators within the system.

The methodological framework for examining the potential of VR in intralogistics safety research requires identifying a range of possible threats and measures to counteract them. Once this range of threats and hazards is outlined, the potential influence of VR implementation can be discussed. Below is the author’s definition of the scope for examining safety problems with VR in intralogistics systems. The proposed scope was developed based on practical experience as well as the issues discussed in the literature [10,14,20,47,48,51,52,53,54,55,56].

The proposed space is composed of the following dimensions:

• Subjects of safety analysis:

  S1.

  Employees;

  S2.

  Devices and equipment;

  S3.

  Products and materials;

  S4.

  Information (security);

  S5.

  Users outside the system—who may be affected by incorrectly handled materials in subsequent links in the supply chain (related to the safety of products).

• Threats and hazards specific to internal transport systems:

  T1.

  Traffic-related events, resulting from the movement of means of transport: being hit, run over, tipping over, crushing, colliding with infrastructure elements (shelves, fenders, walls, etc.), objects falling from a height;

  T2.

  Construction-related events, resulting from structure violation: rack collapsing, falling of materials from a height, colliding;

  T3.

  Injuries related to ergonomics of workstations, working conditions, and the nature of tasks;

  T4.

  Specific workplace hazards, including mechanical injury, electric shock, exposure to various hazardous substances, explosions, burns, falls, etc.;

  T5.

  General threats such as fires, floods, terrorism, etc.

• Countermeasures increasing safety in intralogistics systems:

  C1.

  Procedures minimizing risks of dangerous incidents (occupational health and safety (OHS) compliance, emergency response plans, security, waste management procedures);

  C2.

  Safety inspections of equipment, facilities, machines and processes;

  C3.

  Safe equipment (transport means, storage systems) with high safety parameters;

  C4.

  Passive and active safety systems (globally impacting and personal protective equipment);

  C5.

  Employee awareness of threats increased by training;

  C6.

  Increasing the skills of employees in using specific work tools by training (material handling safety);

  C7.

  Monitoring and anticipating threats (systematic hazard identification and risk assessment);

  C8.

  Motivational, health and wellness programs for employees aimed at increasing safety;

  C9.

  Reliable communication and signage;

  C10.

  Favorable working conditions;

  C11.

  Incident reporting and investigation.

• Factors affecting safety in intralogistics systems:

  F1.

  Local safety culture;

  F2.

  Corporate safety culture;

  F3.

  Local technical culture;

  F4.

  Corporate technical culture;

  F5.

  Typical (dominant) workloads;

  F6.

  Boredom and work routine;

  F7.

  Employee condition and fatigue;

  F8.

  Investments in safety systems and measures;

  F9.

  Legal safety conditions;

  F10.

  Pressure to achieve results;

  F11.

  Life and economic situation of employees (motivation).

• Mechanisms of VR’s impact on improving safety:

  I1.

  Behavioral/device operation training and competency;

  I2.

  Raising awareness of threats (visualization of safety threats);

  I3.

  Testing procedures/technical solutions (emergency response plans);

  I4.

  Consolidation of knowledge;

  I5.

  Hazard identification and risk assessment.

It is impossible to rank the listed factors in order of importance, except to say that human life and health are undoubtedly paramount. Safety management measures and methods should holistically approach the issue of ensuring safety, prioritizing human well-being above all else. As Hofstra et al. [10] indicate, safety in intralogistics results from a combination of safety culture and safety behavior. However, procedural and technical conditions should also be recognized as significant factors, as highlighted in the safety culture classification provided by Hofstra et al. [10].

The aforementioned subjects (S), threats (T), countermeasures (C), factors (F), and impact mechanisms (I) create a five-dimensional space of solutions in which the impact of VR application for safety improvement can be traced and evaluated.

A methodological framework for safety analysis in intralogistics also requires specific sets of data, which include the following (compare Harabas and Klimecka-Tatar [51], Dudka [52], and Pietrzak [53]):

D1.

Dangerous events log;

D2.

Accidents log;

D3.

Monitoring systems based on CCTV and sensors;

D4.

Interviews and surveys of employees and stakeholders;

D5.

Comparative studies of systems (statistics);

D6.

Simulation and VR applications.

A comprehensive safety assessment in the intralogistics system should be based on diversified sources of information combined within the methodology (see Figure 2). Safety-related data are processed to obtain distributions that describe the probability of dangerous events and their potential consequences. Parametric and descriptive methods, along with multi-criteria models, are used for this purpose. Risk analysis methods based on deductive and qualitative approaches are quite popular, focusing on studying and modeling accidents. Risk matrices have essential applications in this context, determining the level of risk by comparing the likelihood category against the consequence severity category [57]. Moreover, checklists and compilations of hazards are among the most popular tools in risk assessment, as described in works by Szymonik [54], Rut and Wołczański [55], Myrcha [56], and Białoń and Pawlik [58]. Event logs and other sources of analytical data describing potential safety threats form the basis for implementing safety measures, which are then introduced into the system. At this stage, VR allows for better matching of measures to needs, thus increasing the effectiveness of implemented measures. VR is a promising data source for multi-aspect safety analysis, significantly expanding research possibilities into various threats.

The influence of safety culture, encompassing organizational and procedural factors, on human behavior and accident reduction is also noticeable. This is particularly important for employee training and the analysis of accident events and near-misses (Hofstra et al. [10], Krupa, Patalas-Maliszewska, and Gabryelewicz [59]). VR technology can be applied here, enhancing the knowledge and information available to employees through training with these technologies. It allows for identifying potential hazards and introducing appropriate preventive measures.

In the analysis of available methods, approaches focusing on single aspects of risk management dominate. This highlights the need for developing methods that detail each step of the procedure and the associated safety assessment methods, especially in the context of the specificity of individual industries and warehouse activities.

4.2. VR in the Life Cycle of Intralogistics System

The use of VR to support safety research and analysis in intralogistics requires a VR model built within an environment that meets the specific needs of intralogistics systems. As previously indicated, creating digital models with an immersive layer using tools dedicated to mapping logistics processes and the environment is beneficial. A VR simulation model for safety analysis, built using a modeling environment adapted to the needs of intralogistics systems, can be used at various stages of the system’s life cycle (Figure 3).

A simulation model with an immersive layer based on VR, when used to analyze the safety of intralogistics systems, should achieve the following:

• Allow for mapping material and information flows in the system (possible usage of the VR model for design and control—Figure 3);
• Have a three-dimensional graphic layer that accurately reproduces reality, including 3D textures and objects;
• Allow for mapping physical properties, including momentum conservation, gravity and mass factors, object lighting, and motion principles;
• Allow for flexible changes in processes, such as integration with a digital twin or digital shadow;
• Reflect dynamic situations in the system, such as integration with the warehouse management system, warehouse control system, material flow control, manufacturing execution system, shop floor control, or other systems that process operational data in real time.

4.3. Construction of Simulation Model for VR Experiments

The construction of a simulation model suitable for implementing VR for safety investigation can be achieved according to the scheme presented in Figure 4. As indicated in Section 3.2, the construction of a simulation model for testing safety in intralogistics systems should be implemented in a simulation environment that first reflects the physical and process aspects of the system, and then takes into account the specific requirements of a particular safety problem in the VR engine. One of the essential elements of the procedure is the selection of individuals who can be subjected to VR experiments, considering the specificity of the sensations. Some individuals may experience difficulties adapting to the VR environment, which could prevent reliable results from being obtained (see Section 5).

Advanced simulation models supporting Virtual Reality (VR) can effectively implement these key components to ensure a safe work environment. VR technology, which enables interaction with virtual objects and realistic reproduction of the workplace, opens up new possibilities in safety training. As a result, employees can gain practical experience in safe conditions without risking their health and lives, learning to recognize potential hazards and respond appropriately. VR training enhances the effectiveness of the content delivered, improving employees’ understanding and retention of safety procedures. This innovative approach, combining theory with practical experience, significantly contributes to raising the level of workplace safety.

The next chapter describes the implementation of the scheme presented in Figure 4 in the FlexSim (2023 update 2) environment, which allows for the building of simulation models of intralogistics and production processes, including Virtual Reality.

4.4. FlexSim as a Universal Environment for Safety Analysis in Intralogistics

FlexSim 3D Simulation Software is an environment for modeling, simulating, and optimizing complex enterprise processes, especially in warehousing, logistics, production, and services. OpenGL technology allows for the construction of three-dimensional models and realistic visualization, potentially supplemented with VR (see Beaverstock, Greenwood, and Nordgren [60]). FlexSim offers discrete process simulation (since 2001), mapping advanced processes of material and information flows and decision-making processes. It provides a visually dynamic environment with universal industrial solutions, input/output mechanisms for external data sources (i.e., WMS, MES, MFC, etc.), and is object-based and open-coded.

Developing VR modules in FlexSim opens new possibilities in industrial process simulation. The simulation model, initially built in FlexSim as a tool supporting efficiency investigation, can serve as a base for VR analysis. Such functionality is especially valuable in systems and processes still in the design or conceptual phase. Huerta-Torruco et al. [61] studied the use of VR and discrete event simulation (DES) in Industry 4.0. Their research, based on data collected from participants using either a VR system or a laptop to interact with a production simulation model, indicates higher performance and preferences for the VR system compared to traditional methods. This signals a new stage in the evolution of DES for the industry. One key advantage of this approach is the ability to thoroughly review and analyze future production systems, logistics, or other industrial processes before their actual implementation. This enables the identification of potential problems, process optimization, and adaptation of concepts to actual working conditions, which is extremely important in the initial design stages.

FlexSim does not offer libraries for building VR models apart from the ability to connect VR devices to the visualization layer. Software for the physics of motion and interactions requires users to develop their libraries, which the authors carry out for this research. The authors’ VR module in FlexSim enables interaction with objects in the simulation and provides accurate physics for the simulated world, focusing on elements crucial for safety analysis. This feature is handy in training, allowing users to mimic real actions and operations, essential for learning machine operation, understanding production processes, or training in work safety. It also allows for the study of work ergonomics, offering the possibility to analyze and optimize working conditions for employees, which is crucial for ensuring their safety and health and increasing the efficiency of production and logistics operations.

To build a simulation model ready for VR devices in FlexSim, the following procedure must be performed:

• Develop a VR-handling library for real-world physics based on the standard FlexSim object libraries (gravity, solid penetration, ballistics, elasticity, gripping, lighting, sounds).
• Formulate the goal of the simulation model with VR to improve safety:
  • Testing technological or organizational concepts;
  • Studying human interaction with the system under specific conditions;
  • Employee training;
  • Visualization.
• Determine the technological limits of the modeled system from the perspective of VR study needs:
  • Spatial extent of the facility (area, zone, workstation, etc.);
  • A fragment of the business (logistics) process.
• Define the scope of automated activities, including repeatable tasks in the model, automatic random events, and activities performed by a person working with VR.
• Construct an intralogistics system model using FlexSim’s standard libraries for internal transport, storage technologies, and flow and operation logic.
• Develop research scenarios for phenomena affecting safety in a specific part of the process.
• Determine the intensity of phenomena in the model (flow volumes, events, interactions).
• Develop and implement specific graphic structures (3D shapes, textures) if required.
• Design a safe workstation for the VR user.
• Conduct experiments.

In the example presented in Section 5, users can assume the role of a forklift operator and perform pallet transport operations in Virtual Reality. Using FlexSim (2023 update 2) simulation with a VR layer offers another significant opportunity: integrating multiple users—in this case, employees—into a single simulation model. This feature allows for user interaction, represented by avatars, enabling the observation and experience of the effects of other participants’ actions in real time. Such interactive VR simulation is extremely valuable for understanding teamwork dynamics and the impact of human factors on systems and processes. It enables the observation of how one employee’s actions affect the work of others and the entire system. This is particularly useful in analyzing work ergonomics, collaboration efficiency, and information flow.

Thanks to the ability to interact in a safe, controlled virtual environment, experiments and tests can be conducted without the risk of actual accidents or failures. This offers a unique opportunity to test and understand the effects of different scenarios in a way that would be impossible or too risky in the real world.

Additionally, this simulation introduces the unpredictability of human behavior, which is extremely important in studying the safety of systems and processes. This allows for the assessment of how different employee behaviors and decisions affect work efficiency and safety, which is crucial for designing safer and more efficient work environments.

5. Case Study of Using a VR-Ready Simulation Model to Examine the Safety of an Internal Transport System

5.1. Designing a FlexSim Simulation Model with a VR Layer

Considerations on using VR to examine safety in intralogistics systems, particularly embedding VR in a five-dimensional space of the safety assessment problem presented in Section 4, led to the development of a practical application example. The procedure formulated in points 6.1–6.5 in the Introduction served as the basis for experiment preparation. A scalable simulation model of the warehouse’s internal transport system was developed in FlexSim (2023 update 2) according to the procedure provided in Section 4.4. In the model, pedestrian workers and forklifts interact while performing tasks in work corridors. The simulation model was developed along with customized libraries to handle physics and interactions with objects for VR display. These libraries were designed for popular VR displays, such as the Oculus series.

By default, the FlexSim environment does not support physical interactions. FlexSim uses three-dimensional trajectories of objects in space resulting from the motion of fixed resources, items, and working resources. However, the model’s three-dimensional space and discrete time control allow for the implementation of Newtonian principles of motion under gravity and the ability to control the penetration of solid surfaces and their mutual physical interactions. A VR-ready library supporting physical interactions and events was developed as a universal FlexSim module. Although it is not available to market users, the open structure of the system allowed for its introduction, and it is now being tested as a potential future software extension.

The goal of the model was to test technological and organizational solutions for the racking area in the warehouse, study the operator’s interaction with NPCs in the system under specific conditions, and train the operator to handle contact situations.

The model was limited to the racking area, covering the system of crosscutting internal transport roads and the process of pallet put-away and retrieval.

Automated activities in the model include control of other forklift and pedestrian operators and the generation of work orders. The VR users (up to six) control forklift trucks in the area.

Such a model can be used at the following stages:

• Intralogistics system design.
• Implementing organizational and technological changes.
• Staff training.

Referring to the space of threats and measures presented in Section 4.1, this particular implementation of VR can be applied to the following:

• Subjects of Safety Analysis:
  • S1. Employees;
  • S2. Devices and equipment.
• Threats and Hazards Specific to Internal Transport Systems:
  • T1. Traffic-related events;
  • T3. Injuries related to ergonomics of workstations, working conditions, and the nature of tasks;
  • T4. Specific workplace hazards.
• Countermeasures Increasing Safety in Intralogistics Systems:
  • C1. Procedures minimizing risks of dangerous situations;
  • C4. Passive and active safety systems;
  • C5. Employee awareness of threats increased by training;
  • C10. Favorable working conditions.
• Factors Affecting Safety in Intralogistics Systems:
  • F5. Typical (dominant) workloads;
  • F8. Investments in safety systems and measures;
  • F9. Legal safety conditions.
• Mechanisms of VR Impact on Improving Safety:
  • I1. Behavioral/device operation training;
  • I3. Testing procedures/technical solutions.

The primary aim of the experiment was to determine whether the hardware and software configuration used could effectively track the plausibility of dangerous situations involving roadway devices within the confined space of the racking zone. Another goal was to assess the practical aspects of the study from the respondents’ perspectives.

5.2. Constructing a FlexSim Simulation Model with a VR Layer

The rack zone of a pallet warehouse is modeled. It is possible to flexibly shape the size and layout of the zone, as well as its elements, the following in particular:

• Dimensions of the facility, internal transport routes, and rack structures (Figure 5);
• Filling of flow units and shelves, which limits the visibility of operators (Figure 6);
• Traffic speed and intensity;
• Traffic rules, including priority rules, movement restrictions, and speed limits;
• Operation patterns and behaviors of forklifts and pedestrian workers;
• Measures to counteract hazardous situations, such as warning systems for moving devices, traffic management systems, and real-time location systems;
• The appearance of the device’s cockpit;
• Multi-user interaction schemes.

Up to six different users can participate in a single model simultaneously, performing various tasks, including operating a forklift truck. Users can also carry out other operations, such as operating a logistics train, manually transporting items to buffer stations, and operating workstations. Thanks to the ability to interact with each other, participants can check the safety of designated paths and visibility, as well as evaluate the safety and ergonomics of work at the workstations.

The presented model allows for the following:

• Testing the reaction time of pedestrian workers and forklift operators to specific types of threats.
• Determining the probability of various dangerous situations occurring.
• Examining measures to counteract dangerous situations and organizational methods.
• Immediate implementation of changes.
• Training forklift operators with a focus on interaction between employees.

5.3. Experiment Scenarios for Internal Transport Operation

The software solution presented in Section 5.1 allows for the quick creation of simulation experiments and conducting analysis of work safety in the warehouse, including crisis response scenarios.

The intensity of phenomena in the model can vary according to the needs (flow volumes, events, interactions). In particular, the number and intensity of work orders, movement speeds, and the regime of following the movement trajectory by NPCs in the model can be controlled. These elements mostly affect the possibility of dangerous situations occurring.

A series of experiments were designed for a fixed configuration of the pallet rack system and internal transport routes (4 blocks of 20 racks each, with cross aisles and a forklift, as shown in Figure 5).

The experiments involved the implementation of random tasks with a forklift following a repeatable pattern over 30 min. Each task consisted of collecting a unit, transporting it according to established traffic rules and interaction protocols with other study participants, and placing the unit in the target cell.

The experiment scenarios assumed different numbers of interacting forklifts and pedestrian workers: 5, 10, and 15. The operators maintained a constant speed of 1 m/s, while the forklifts operated at variable speeds of 1 m/s, 2 m/s, and 3 m/s. Additionally, the shelf filling, which limited visibility, ranged from 30% to 90%. The numerical results of the experiments are summarized in

Table 2. Experiment results.

No of Operators/Devices	Max Speed [m/s]	Shelf Filling 30%		Shelf Filling 90%
		Dangerous Situations [Emergency Braking]	Potential Collisions	Dangerous Situations [Emergency Braking]	Potential Collisions
5	1	0	0	0	0
10	1	0	0	0	2
15	1	0	1	0	3
5	2	0	0	0	1
10	2	0	1	0	2
15	2	0	3	0	4
5	3	1	1	0	2
10	3	1	2	1	3
15	3	2	4	2	6

.

5.4. Workstation for the VR User

The VR user workstation has been designed as a seated station, reflecting the operator’s position on a forklift. This setup creates a safe zone with a radius of 1 m from the center of the user’s chest. Consequently, the risks associated with manual manipulation during work have been minimized. There are no threats related to loss of balance or collisions with elements in the actual space surrounding the user.

5.5. Experimental Results

The obtained numerical results show the variability in the number of sudden braking situations and potential collisions in relation to the model parameters. As expected, the number of potentially dangerous situations (dependent parameter) is positively correlated with the numerical values determining traffic density, speed, and shelf occupancy (independent parameters)—Table 2.

The results show a positive correlation between the model parameters, particularly speed limits, the number of simultaneously operating devices (NPCs or users), and the number of potentially hazardous situations. While this is an expected observation, it indicates the overall correctness of the approach. Increased traffic density has led to a rise in dangerous situations, such as collisions within the established transport system. Moreover, the experiment demonstrated that visibility conditions, influenced by the degree of pallet rack filling and their transparency, significantly affect the likelihood of dangerous situations. According to the literature review, this factor is not typically considered in safety research. Nonetheless, it is crucial to implement additional organizational measures (such as principles of priority and limited trust) and technical methods (including spherical mirrors and traffic management systems).

An important part of the experiment was to determine the research participants’ feelings regarding the use of VR displays. Experiments have shown that applying an adaptation period of at least 40 min in total, divided into intervals of 5 min of work and 5 min of rest, is necessary. After such training, it is possible to carry out a 30 min test with 5 min breaks every 15 min. Due to the static nature of the experiment, it can be performed in a sitting position, which facilitates orientation in space. There were no cases of VR sickness, but it should be noted that the participants had extensive practical experience with HSD.

This study did not aim to prove the validity of specific technical solutions but to assess the usefulness of VR as a tool for testing safety in the specific conditions of a typical internal transport system. This discussion is provided in Section 6.

6. Discussion on Implementing VR to Increase Safety in Intralogistics Systems

6.1. Places of Immersive Technologies in Intralogistics Area

Based on the literature review, application studies, and the results of the experiment discussed in Section 5, it can be concluded that implementing VR as a tool for enhancing safety in intralogistics systems is a forward-looking and sustainable approach. VR significantly impacts the intralogistics sector, providing tools that enhance various aspects of design, monitoring, and operations:

• Optimization of material flow processes for safety and efficiency includes establishing favorable traffic rules, testing layouts and traffic direction, testing passive and active safety solutions, and selecting safe speeds for various working conditions.
• Testing the ergonomics of workstations involves evaluating the configuration, lighting, work organization, and the presence of strenuous and tedious movements, particularly for stationary manual workstations.
• Training operators through interactive visual guides, which speed up and facilitate learning logistical tasks. VR adds an extra dimension, allowing employees to participate in realistic virtual scenarios that simulate actual working conditions, significantly improving understanding and skills.
• Creating and testing scenarios for crisis situations, including those that are unlikely but have a high potential for negative impact.

As indicated in Section 4, using VR to increase safety should be planned comprehensively. The first step is to incorporate immersive techniques into the design stage of intralogistics systems to test technological concepts, particularly the spatial configuration and organization of internal transport and interactions of pedestrian workers, as presented in the exercise in Section 5. Using a universal simulation modeling environment to build models for a relatively quick transition from technical design and 3D graphics (.dwg) to models of space and material flows is a fundamental action. This enables simulation experiments on successive versions of spatial layouts of internal transport systems to be designed and performed iteratively, also with VR support. This approach adapts the project to safety and ergonomic requirements from the users’ perspective in a cost-effective manner.

Another VR application is mentioned in Section 4.2. In this context, it is possible to examine installations from the perspective of safety issues identified based on real event logs. It is also possible to assess the impact of planned technical and organizational changes on employee work safety.

A typical application, discussed in Section 3.5, is training employees to perform specific, repetitive tasks and preparing them to respond to unforeseen situations, including extreme crises.

The active use of VR for safety analysis will impact selected KPIs that describe safety in intralogistics systems (as proposed in [62]). Using VR as an extension of the safety improvement toolkit may contribute to improvements in the Total Recordable Incident Rate (TRIR) and Lost Time Injury Frequency Rate (LTIFR), due to increased effort in safety testing with VR. The Near-Miss Frequency Rate can be reduced through continuous situational training in Virtual Reality, particularly by repeatedly training employees in identified near-miss situations. Additionally, VR, combined with a tailored training policy, will improve the Safety Training Compliance Rate and Employee Safety Perception Survey scores by providing employees with an engaging and attractive training layer.

As part of the organization’s proactive activities, VR can be used to improve the Safety Suggestion Implementation Rate—the percentage of employee safety suggestions that are implemented—and the Corrective Action Completion Rate—the percentage of identified safety issues that have been addressed and resolved—by allowing any scenarios and solutions to be tested in controlled VR conditions. VR will also contribute to increasing the Safety Audit Score by enabling repeated testing of safety protocols and regulations in virtual conditions. Furthermore, in the event of an accident, VR can be used to improve Incident Investigation Completion Time by reproducing dangerous situations in VR conditions.

The VR simulation study of a warehouse racking system with forklifts and pedestrian operators, presented in Section 5, demonstrated the potential positive impact of using VR to study the safety of such systems. The model of the reserve area of a distribution warehouse used in the study reflects the existing system configuration. The principles of organizing the movement of roadway devices, including determining safe speeds and the spatial separation of employees from devices, strongly influence the probability of hazardous situations involving collisions between a device and an employee, between devices, and between devices and rack structures. The VR model allowed for tracking the impact of visibility conditions and traffic density on the frequency of dangerous situations. A model like the one presented in Section 5 is applicable at the design stage of the intralogistics system (see Figure 3). The universal simulation environment used to construct it, in turn, allows for the refinement of such a model to represent a system operating with specific principles implemented.

6.2. Threats and Limitations of VR Technology

Virtual Reality has its downsides, technological limitations, and challenges related to human use, as observed in practice and experiments (Stoltz et al. [15], Bräuer and Mazarakis [63], Reif et al. [64]) or resulting from incorrect application to the needs.

The adverse effects of VR implementation may include the following:

• Incorrect identification of VR application areas driven by the desire to adopt new technology, potentially hindering other, more promising technologies.
• High initial costs and efforts, particularly in creating custom VR simulation models tailored to specific needs and allocating dedicated physical space.
• Physical discomfort from prolonged use of display headsets, leading to health and well-being issues such as fatigue, eyestrain, headaches, or motion sickness. Additionally, users may unknowingly interact with their physical surroundings if the area is not adequately prepared for VR usage.
• Mental discomfort due to resistance to new technology, which can limit environmental perception and necessitate unnatural behavior over a work shift.
• Required assets include the skills and knowledge to design, implement, maintain, and operate VR applications, as well as time-consuming training.
• Creating and updating a simulation environment with scenarios for testing and training requires tailoring to the needs of ongoing research and monitoring safety issues within the organization.
• VR is unsuitable for specific applications typical of intralogistics systems, such as interaction with heavy objects (handling) and manual skill training for handling small parts.
• Concerns about data security and user privacy.

When implementing VR solutions in intralogistics systems, it is essential to clearly define their scope of application. While VR technology is highly useful for specific aspects of training and simulating unusual situations, it seems too cumbersome for full-shift work. VR has particular applications, such as the remote control of container cranes or industrial drones, but these require specific working conditions and user predispositions. Implementing VR as an everyday work tool will undoubtedly necessitate changes in work organization. In such cases, employees will not need to be physically present where tasks are performed or interact with hazardous factors. However, this shift will impose new types of burdens and fatigue, especially given the still imperfect nature of the technology:

• VR tools’ batteries may not last an entire work shift, and using additional batteries can be inconvenient for operators;
• The risk of processors overheating and slowing down after extended use or during complex data processing, which can disrupt work;
• Screens that do not automatically adjust to changes in lighting, such as when entering or exiting a building;
• Delays in image display leading to headaches;
• Eye fatigue due to the need to focus vision in an unnatural way;
• Muscle fatigue from the weight of the devices, which can make them difficult to wear for extended periods.

Regarding human barriers, there are two main challenges: privacy issues and skills (Harborth and Frik [65]). Although most employees positively evaluate VR, some may be reluctant to wear VR displays or use applications on smartphones and tablets due to privacy concerns. These concerns can stem from cameras and microphones in the devices or permissions that allow access to facial recognition, contacts, location, microphone, memory, and speech recognition functions. These challenges also pertain to issues such as what data are collected, stored, and used, and who has access to them, which can affect employee acceptance of VR technology (Bhutta, Umm-e-Hani, and Tariq [66]).

Another significant barrier concerns workers’ ability to adapt to changes and innovations and the hard and soft skills employees possess in using and managing VR (Oguz [67]). On the one hand, operators do not need advanced technical and training skills, as they can observe the correct methods of performing a task during its execution and be guided by visual instructions or voice commands during logistical operations. However, digital and practical skills are required, such as using new digital interfaces, interpreting data delivered in real time, making quick decisions, solving problems, cognitive flexibility, critical thinking, communication, and teamwork.

Implementing new technologies and devices includes using specialized systems and advanced software, such as smart glasses integrated with mobile devices like tablets and smartphones. The initial stages of this process often involve high financial costs for enterprises. Additionally, the necessity of proper employee training, regardless of the complexity of their tasks, generates additional expenses (Machała, Chamier-Gliszczyński, and Królikowski [26]). The diversity of development environments and programming languages further complicates experimentation with devices, creating custom applications, and integrating with existing systems.

One of the challenges is “Virtual Reality sickness” (VR sickness), which affects some users and manifests as dizziness, nausea, or disorientation (see Woo et al. [29]). There is a concern that intensive and prolonged use of VR may impact the mental health of users, including their sense of reality and ability to establish social connections in the real world.

6.3. VR in the Context of Industry 4.0: Challenges and Future

VR is integral to Industry 4.0, offering tools for intelligent factories and automated production processes. Integrating VR with IoT systems, artificial intelligence, and data analysis enables the creation of more flexible and efficient production and logistics systems. Despite numerous benefits, implementing VR in the industry presents challenges, such as initial costs, the need for specialized knowledge within the organization, and difficulties in integrating VR with existing systems. Utilizing universal VR simulation tools like FlexSim and popular market display devices can simplify, reduce costs, and enhance the reliability of this process. Future developments in VR will likely focus on creating more accessible and user-friendly solutions integrated into existing IT/OT systems and further combining them with other digital technologies. The evolution of VR involves several challenges, including the need for continuous updates of hardware, software, and skills [26]. Additional challenges include ensuring data security and user privacy, as well as addressing ethical issues related to the immersiveness and realism of these technologies.

The VR industry stands on the threshold of significant technological innovations. Future trends indicate further miniaturization and improvements in the ergonomics of VR devices, making them more accessible and comfortable to use. The presence of 5G technology and broadband networks enhances real-time data processing and transmission capabilities, which is crucial for developing VR applications [13].

Sahoo and Lo [68] present a detailed review of current trends and challenges associated with intelligent manufacturing, which is critical to achieving Industry 4.0 objectives. The authors focus on technologies related to intelligent manufacturing systems, such as Virtual Reality, augmented reality, mixed reality, additive manufacturing, big data analytics, the Industrial Internet of Things, and artificial intelligence.

VR could transform labor markets, creating new professions and requiring new skills from workers, particularly in operating and programming these technologies. Education and vocational training must adapt to these changes to prepare future generations of workers (see [35,44]).

7. Summary

VR applications based on simulation models constructed with universal tools like FlexSim allow for safe and effective employee training, ergonomic analysis of workplaces, and testing of new concepts in controlled and cost-effective conditions. These technologies are evolving, becoming more accessible and user-friendly. The development of technologies like head-mounted displays facilitates their integration into everyday industrial operations, opening doors to new possibilities and applications. They have become an integral part of the Industry 4.0 concept, enabling the creation of intelligent production and logistics systems.

The introduction of immersive technologies significantly enhances operational efficiency, from procurement to storage and delivery. Most importantly, it improves safety by enhancing operators’ interactions with the work environment, aiding decision-making processes and reducing the risk of human error. The use of this technology by warehouse and transport workers is becoming increasingly common, and logistics managers must skillfully implement and manage VR in the work environment.

Despite its many advantages, VR faces technological and human challenges that can slow its implementation. These challenges must become the focus of research to make VR a reliable tool for safety assessment and an effective countermeasure for safety issues. The future will bring further miniaturization, improved ergonomics, and integration with other digital technologies, increasing VR’s applications and efficiency. The development of VR may change the labor market, creating new professions and requiring new skills from workers. Education and vocational training must adapt to these changes, preparing future generations to use these advanced technologies.

In light of the presented materials and discussions, we conclude that using VR to support design, safety engineering, and safety behavior training is part of the technological trend towards developing sustainable systems. This is achieved not only by improving the safety of employees in logistics facilities but also by providing a better understanding of the system and its behavior. This improved understanding allows for more effective planning, which increases efficiency while reducing costs and environmental burdens.

VR is gaining importance in scientific research on logistics, safety assessment, and industrial training. Its use as a research and educational tool opens new possibilities for Industry 4.0, especially in improving work safety and efficiency. Notably, combining VR with FlexSim simulations enables the creation of detailed spatial models that support individual and group interactions, significantly contributing to work safety research. This approach allows for the exploration and assessment of selected work safety aspects in a more advanced way than traditional methods based on expert assessment or statistical analysis. It also allows for replicating interactions between participants, introducing the unpredictability of human behavior, which is extremely important in studying the safety of systems and processes. This way, it is possible to assess how different behaviors and decisions of employees impact work efficiency and safety, which is critical to designing safer and more efficient work environments.