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İşletmelerdeki Risk Faktörlerinin Sanal Gerçeklik Tabanlı Uygulamalarla Tespiti

Year 2023, Volume: 5 Issue: 2, 139 - 150, 31.08.2023
https://doi.org/10.38009/ekimad.1334474

Abstract

Sanayi, teknoloji, iş yapış şekilleri ve iş yönetimi günümüzde hızlı bir değişim geçirmekte ve buna bağlı olarak işletmelerde tehlikeler farklılaşmakta, risklerin boyutları değişmekte tüm bu nedenlerle insan hayatı ve ekonomik açıdan kayıplara neden olan riskler giderek artmaktadır. Yapay Zekâ teknolojisinin hızla gelişmesi, işletmeler için pek çok alanda büyük fırsatlar sunmaktadır. Bu alanda en önemli konulardan biri, risk analizidir. İşletmeler, karşılaşabilecekleri potansiyel riskleri belirleyerek, stratejik kararlar almak ve rekabet avantajı elde etmek için risk analizi yapmaktadır. Yapay Zekâ tabanlı risk analizi, geleneksel yöntemlere kıyasla önemli avantajlar sunmaktadır. Yapay Zekâ, büyük veri kümelerini hızla analiz edebilme yeteneği sayesinde kapsamlı ve detaylı sonuçlar sağlar. Aynı zamanda, karmaşık veri yapılarını anlama ve önemli desenleri belirleme kabiliyeti, işletmelere risklerin kökenini ve potansiyel sonuçlarını daha iyi anlama fırsatı tanır. Yapay Zekâ tabanlı risk analizlerinin işletmelerin sürdürülebilirlikleri ve rekabet güçleri üzerinde büyük etkileri olduğu düşünülmektedir. Yapay Zekâ ’nın hassas tahminleri ve geleceğe yönelik senaryo oluşturma yeteneği, karar vericilere stratejik planlama ve kaynak yönetimi açısından değerli bir rehberlik sunar. Ayrıca, işletmelerin beklenmedik durumlar ve belirsizliklerle başa çıkma yeteneklerini arttırarak risklerle baş etme stratejilerini geliştirme konusunda da katkı sağlar. Bu nedenle, işletmelerin yapay zekâ tabanlı risk analizi yöntemlerini benimsemesi, uzun vadeli başarıları için kritik bir unsurdur. Çalışmanın amacı, gerçek yaşam temelli eğitim materyalleri geliştirerek analitik düşünme, problem çözme, yaratıcılık, girişimcilik gibi eğitim-öğretim programlarının çıktıları arasında olması gereken becerilerin bireye kazandırılmasını sağlamaktır. Çalışma ile sanal gerçeklik ve artırılmış gerçeklik tabanlı simülasyon üreterek risk analizi eğitimi ile muhatap olacak bireylere çoklu sistem ile yeni ve özgün bir öğrenme ortamı oluşturulması, bireyin öğrenme düzeyinin iyileştirilmesi ve nihai hedef olan ‘‘tam öğrenmenin’’ gerçekleştirilmesi hedeflenmektedir. Böylece işletmelerdeki risk faktörlerinin tespitinde ve yorumlanmasında alana katkı sağlanması planlanmaktadır.

References

  • Alanen, J., Linnosmaa, J., Malm, T., Papakonstantinou, N., Ahonen, T., Heikkilä, E., & Tiusanen, R. (2022). Hybrid ontology for safety, security, and dependability risk assessments and Security Threat Analysis (STA) method for industrial control systems. Reliability Engineering & System Safety, 220, 108270.
  • Bellalouna, F. (2019, October). Virtual-reality-based approach for cognitive design-review and fmea in the industrial and manufacturing engineering. In 2019 10th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) (pp. 41-46). IEEE.
  • Cha, M., Han, S., Lee, J., & Choi, B. (2012). A virtual reality based fire training simulator integrated with fire dynamics data. Fire safety journal, 50, 12-24.
  • Craig, A. B., Sherman, W. R., & Will, J. D. (2009). Developing virtual reality applications: Foundations of effective design. Morgan Kaufmann.
  • Elford, M. D. (2013). Using tele-coaching to increase behavior-specific praise delivered by secondary teachers in an augmented reality learning environment (Doctoral dissertation, University of Kansas).
  • Isleyen, E., & Duzgun, H. S. (2019). Use of virtual reality in underground roof fall hazard assessment and risk mitigation. International Journal of Mining Science and Technology, 29(4), 603-607.
  • Gazete, R. (2012). İş sağlığı ve güvenliği risk değerlendirmesi yönetmeliği. Resmi gazete tarihi, 28512.
  • Khalil, M., Abdou, M. A., Mansour, M. S., Farag, H. A., & Ossman, M. E. (2012). A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry. Journal of Loss Prevention in the Process Industries, 25(6), 877-882.
  • Klempous, R., Kluwak, K., Idzikowski, R., Nowobilski, T., & Zamojski, T. (2017, September). Possibility analysis of danger factors visualization in the construction environment based on Virtual Reality Model. In 2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) (pp. 000363-000368). IEEE.
  • Manca, D., Brambilla, S., & Colombo, S. (2013). Bridging between virtual reality and accident simulation for training of process-industry operators. Advances in Engineering Software, 55, 1-9.
  • Mekhilef, S., Saidur, R., & Kamalisarvestani, M. (2012). Effect of dust, humidity and air velocity on efficiency of photovoltaic cells. Renewable and sustainable energy reviews, 16(5), 2920-2925
  • Mili, A., Bassetto, S., Siadat, A., & Tollenaere, M. (2009). Dynamic risk management unveil productivity improvements. Journal of Loss Prevention in the Process Industries, 22(1), 25-34.
  • Olsson, T., & Salo, M. (2011, October). Online user survey on current mobile augmented reality applications. In 2011 10th IEEE International Symposium on Mixed and Augmented Reality (pp. 75-84). IEEE.
  • Ren, A., Chen, C., & Luo, Y. (2008). Simulation of emergency evacuation in virtual reality. Tsinghua Science and Technology, 13(5), 674-680.
  • Rüppel, U., & Schatz, K. (2011). Designing a BIM-based serious game for fire safety evacuation simulations. Advanced engineering informatics, 25(4), 600-611.
  • Santos, M. E. C., Chen, A., Taketomi, T., Yamamoto, G., Miyazaki, J., & Kato, H. (2013). Augmented reality learning experiences: Survey of prototype design and evaluation. IEEE Transactions on learning technologies, 7(1), 38-56.
  • Shelton, B. E., & Hedley, N. R. (2002, September). Using augmented reality for teaching earth-sun relationships to undergraduate geography students. In The First IEEE International Workshop Agumented Reality Toolkit, (pp. 8-pp). IEEE.
  • Specht, M., Ternier, S., & Greller, W. (2011). Dimensions of mobile augmented reality for learning: a first inventory. Journal of the Research for Educational Technology (RCET), 7(1), 117-127.
  • Xu, Z., Lu, X. Z., Guan, H., Chen, C., & Ren, A. Z. (2014). A virtual reality based fire training simulator with smoke hazard assessment capacity. Advances in engineering software, 68, 1-8.
  • Yan, F., & Xu, K. (2019). Methodology and case study of quantitative preliminary hazard analysis based on cloud model. Journal of Loss Prevention in the Process Industries, 60, 116-124.
  • Van Krevelen, D. W. F., & Poelman, R. (2010). A survey of augmented reality technologies, applications and limitations. International journal of virtual reality, 9(2), 1-20.
  • Zio, E. (2018). The future of risk assessment. Reliability Engineering & System Safety, 177, 176-190.

Detection of Risk Factors in Businesses Through Virtual Reality-Based Applications

Year 2023, Volume: 5 Issue: 2, 139 - 150, 31.08.2023
https://doi.org/10.38009/ekimad.1334474

Abstract

Industry, technology, business practices, and management approaches are undergoing rapid changes in today's world. Consequently, the hazards in businesses are diversifying, and the dimensions of risks are changing. For all these reasons, risks causing losses in terms of human life and economy are increasing. The rapid development of Artificial Intelligence (AI) technology presents significant opportunities for businesses. One of the most crucial aspects in this field is risk analysis. Businesses perform risk analysis to identify potential risks they may encounter, make strategic decisions, and gain a competitive advantage. AI-based risk analysis offers substantial advantages compared to traditional methods. AI's ability to analyze large datasets rapidly provides comprehensive and detailed results. Additionally, its capability to understand complex data structures and identify significant patterns offers businesses an opportunity to better comprehend the origins and potential consequences of risks. It is believed that AI-based risk analysis has a considerable impact on the sustainability and competitive strength of businesses. AI's precise predictions and ability to create future scenarios provide decision-makers with valuable guidance for strategic planning and resource management. Moreover, it contributes to enhancing businesses' ability to cope with unexpected situations and uncertainties, thereby developing strategies to deal with risks effectively. Therefore, the adoption of AI-based risk analysis methods by businesses is a critical element for their long-term success. The aim of this paper is to develop real-life-based educational materials that enable individuals to acquire skills such as analytical thinking, problem-solving, creativity, and entrepreneurship, which are among the outcomes of education and training programs. The paper aims to create a new and unique learning environment with multi-systems for individuals who will be exposed to risk analysis education through virtual reality and augmented reality-based simulations. This will improve the individual's level of learning and achieve the ultimate goal of "complete learning." Thus, the study is planned to contribute to the field by aiding in the detection and interpretation of risk factors in businesses.

References

  • Alanen, J., Linnosmaa, J., Malm, T., Papakonstantinou, N., Ahonen, T., Heikkilä, E., & Tiusanen, R. (2022). Hybrid ontology for safety, security, and dependability risk assessments and Security Threat Analysis (STA) method for industrial control systems. Reliability Engineering & System Safety, 220, 108270.
  • Bellalouna, F. (2019, October). Virtual-reality-based approach for cognitive design-review and fmea in the industrial and manufacturing engineering. In 2019 10th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) (pp. 41-46). IEEE.
  • Cha, M., Han, S., Lee, J., & Choi, B. (2012). A virtual reality based fire training simulator integrated with fire dynamics data. Fire safety journal, 50, 12-24.
  • Craig, A. B., Sherman, W. R., & Will, J. D. (2009). Developing virtual reality applications: Foundations of effective design. Morgan Kaufmann.
  • Elford, M. D. (2013). Using tele-coaching to increase behavior-specific praise delivered by secondary teachers in an augmented reality learning environment (Doctoral dissertation, University of Kansas).
  • Isleyen, E., & Duzgun, H. S. (2019). Use of virtual reality in underground roof fall hazard assessment and risk mitigation. International Journal of Mining Science and Technology, 29(4), 603-607.
  • Gazete, R. (2012). İş sağlığı ve güvenliği risk değerlendirmesi yönetmeliği. Resmi gazete tarihi, 28512.
  • Khalil, M., Abdou, M. A., Mansour, M. S., Farag, H. A., & Ossman, M. E. (2012). A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry. Journal of Loss Prevention in the Process Industries, 25(6), 877-882.
  • Klempous, R., Kluwak, K., Idzikowski, R., Nowobilski, T., & Zamojski, T. (2017, September). Possibility analysis of danger factors visualization in the construction environment based on Virtual Reality Model. In 2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) (pp. 000363-000368). IEEE.
  • Manca, D., Brambilla, S., & Colombo, S. (2013). Bridging between virtual reality and accident simulation for training of process-industry operators. Advances in Engineering Software, 55, 1-9.
  • Mekhilef, S., Saidur, R., & Kamalisarvestani, M. (2012). Effect of dust, humidity and air velocity on efficiency of photovoltaic cells. Renewable and sustainable energy reviews, 16(5), 2920-2925
  • Mili, A., Bassetto, S., Siadat, A., & Tollenaere, M. (2009). Dynamic risk management unveil productivity improvements. Journal of Loss Prevention in the Process Industries, 22(1), 25-34.
  • Olsson, T., & Salo, M. (2011, October). Online user survey on current mobile augmented reality applications. In 2011 10th IEEE International Symposium on Mixed and Augmented Reality (pp. 75-84). IEEE.
  • Ren, A., Chen, C., & Luo, Y. (2008). Simulation of emergency evacuation in virtual reality. Tsinghua Science and Technology, 13(5), 674-680.
  • Rüppel, U., & Schatz, K. (2011). Designing a BIM-based serious game for fire safety evacuation simulations. Advanced engineering informatics, 25(4), 600-611.
  • Santos, M. E. C., Chen, A., Taketomi, T., Yamamoto, G., Miyazaki, J., & Kato, H. (2013). Augmented reality learning experiences: Survey of prototype design and evaluation. IEEE Transactions on learning technologies, 7(1), 38-56.
  • Shelton, B. E., & Hedley, N. R. (2002, September). Using augmented reality for teaching earth-sun relationships to undergraduate geography students. In The First IEEE International Workshop Agumented Reality Toolkit, (pp. 8-pp). IEEE.
  • Specht, M., Ternier, S., & Greller, W. (2011). Dimensions of mobile augmented reality for learning: a first inventory. Journal of the Research for Educational Technology (RCET), 7(1), 117-127.
  • Xu, Z., Lu, X. Z., Guan, H., Chen, C., & Ren, A. Z. (2014). A virtual reality based fire training simulator with smoke hazard assessment capacity. Advances in engineering software, 68, 1-8.
  • Yan, F., & Xu, K. (2019). Methodology and case study of quantitative preliminary hazard analysis based on cloud model. Journal of Loss Prevention in the Process Industries, 60, 116-124.
  • Van Krevelen, D. W. F., & Poelman, R. (2010). A survey of augmented reality technologies, applications and limitations. International journal of virtual reality, 9(2), 1-20.
  • Zio, E. (2018). The future of risk assessment. Reliability Engineering & System Safety, 177, 176-190.
There are 22 citations in total.

Details

Primary Language Turkish
Subjects Occupational Health and Safety
Journal Section Articles
Authors

Öznur Demir 0009-0003-0255-3354

Serap Tepe 0000-0002-9723-6049

Bülent Mertoğlu 0000-0001-6827-3791

Publication Date August 31, 2023
Submission Date July 29, 2023
Published in Issue Year 2023 Volume: 5 Issue: 2

Cite

APA Demir, Ö., Tepe, S., & Mertoğlu, B. (2023). İşletmelerdeki Risk Faktörlerinin Sanal Gerçeklik Tabanlı Uygulamalarla Tespiti. Ekonomi İşletme Ve Maliye Araştırmaları Dergisi, 5(2), 139-150. https://doi.org/10.38009/ekimad.1334474