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Estimation of the Number of Occupational Accidents and Deadly Occupational Accidents Encountered in Manufacturing Sector of Fabrication Metal Products, Except Machinery and Equipment Sector in Turkey

Yıl 2017, Cilt: 1 Sayı: 1, 9 - 15, 29.12.2017
https://doi.org/10.33720/kisgd.322546

Öz



Manufacture of Fabricated Metal Products except Machinery and Equipment is the sector in which the occupational accidents  are  most experienced, in Turkey. In this study, the number of occupational accidents in the manufacturing sector of Fabricated Metal Products excluding Machinery and Equipment are examined from the Social Security Institution’s data. It is aimed to estimate the numbers of occupational accidents and fatal occupational accidents belonging to the year 2016 which have not yet been announced by using data belonging to the years 2008-2015 in the Manufacture of Fabricated Metal Products except Machinery and Equipment sector. Fuzzy Time Series and Least Squares methods are used as estimation methods. As a result of the forecast, it will be revealed which method is healthier with the accident data which will be announced about the year 2016.





Kaynakça

  • Bourne, D., Corney, J.&Gupta, S.K. (2011). Recent Advances and Future Challenges in Automated Manufacturing Planning, ASME Journal of Computer Information Science Engineering, 11(2).
  • Chen, X., Schonfeld, D.&Khokhar, A. (2007). Localization and Trajectory Estimation of Mobile Objects with a Single Sensor, Statistical Signal Processing, IEEE/SP, SSP’07, 363-367.
  • Eustice, R., Pizarro, O.&Singh, H. (2004). Visually Augmented Navigation in an Unstructered Environment Using a Delayed State History, Proceedings of the 2004 International Conference on Robotics&Automation, IEEE.
  • Facco, P., Doplicher, F., Bezzo, F.&Barolo, M. (2009). Moving Average PLS Soft Sensor for Online Product Quality Estimation in an Industrial Batch Polymerization Process, Journal of Process Control, 19(3), 520-529.
  • Fatullayev, A.G. 18.06.2017. http://www.kocaelimakine.com/wp-content/uploads/2013/04/en-kucuk-kareler-yontemi-afet-golayoglu.pdf.
  • Hu, W., Xiao, X., Xie, D., Tan, T.&Maybank, S. (2004). Traffic Accident Prediction Using 3-D Model-based Vehicle Tracking, IEEE Transactions on Vehicular Technology, 53(3), 677-694.
  • Huang, Y-L., Horng, S-J., Kao, T-W., Kuo, I-H.&Takao, T. (2012). A hybrid forecasting model based on adaptive fuzzy time series and particle swarm optimization, International Symposium on Biometrics and Security Technologies, 66-70.
  • Hwang, J., Chen, S. M.&Lee, C. H. (1998). Handling Forecasting Problems Using Fuzzy Time Series. Fuzzy Sets and Systems, 100, 217-228.
  • Kosut, O., Turovsky, A., Sun, J., Ezovski, M., Tong, L.&Whipps, G. (2007). Integrated Mobile and Static Sensing for Target Tracking, In Military Communications Conference, MILCOM 2007, IEEE, 1-7.
  • Marques, P.&Dias, J. (2007). Moving Target Trajectory Estimation in SAR Spatial Domain Using a Single Sensor, IEEE Transaction on Aerospace and Electronic Systems, 43(3), 864-874.
  • Lee, H-S.&Chou, M-T. (2004). Fuzzy Forecasting Based on Fuzzy Time Series. International Journal of Mathematics, 81, 781-789.
  • Ohno, K., Takafumi, N.&Satoshi, T. (2006). Real-time Robot Trajectory Estimation and 3d Map Construction using 3d Camera, Intelligent Robots and Systems, International Conference on IEEE/RSJ.
  • Pantazopoulos, S.N.&Pappis, C.P. (1996). A new adaptive method for extrapolative forecasting algorithms, European Journal of Operational Research, 94, 106-111.
  • Piepmeier, J.A., McMurray, G.V.&Lipkin, H. (1998). Tracking a Moving Target with Model Independent Visual Servoing: a Predictive Estimation Approach, Proceedings of the 1998 IEEE, International Conference on Robotics & Automation, 2652-2657.
  • Piepmeier, J.A., McMurray, G.V.&Lipkin H. (2004). Uncalibrated Dynamic Visual Servoing, IEEE Transactions on Robotics and Automation, 20(1).
  • Prėvost, C.G., Desbiens, A.,&Gagnon, E. (2007). Extended Kalman Filter for State Estimation and Trajectory Prediction of a Moving Object Detected by an Unmanned Aerial Vehicle, Proceedings of the 2007 American Control Conference, USA, 1805-1810.
  • Ryan, E., Pizarro, O.&Singh, H. (2004). Visually Augmented Navigation in an Unstructured Environment Using a Delayed State History, Proceedings of the 2004 IEEE, International Conference on Robotics & Automation, 25-32.
  • SGK. (2017). SGK İstatistik Yıllıkları. Erişim Tarihi: 8.05.2017, http://www.sgk.gov.tr/wps/portal/sgk/tr/kurumsal/istatistik/sgk_istatistik_yilliklari
  • Shen, G., Kong, X.&Chen, X. (2011). A Short-term Traffic Flow Intelligent Hybrid Forecasting Model and Its Application, Control Engineering and Applied Informatics, 13(3), 65-73.
  • Mevzuatı Geliştirme ve Yayın Genel Müdürlüğü, 5510 Sayılı Sosyal Sigortalar ve Genel Sağlık Sigortası Kanunu. Erişim Tarihi: 4.05.2017, http://www.mevzuat.gov.tr/MevzuatMetin/1.5.5510.pdf
  • Tang, Y., Huang, P. (2006). Boost-Phase Ballistik Missile Trajectory Estimation with Ground Based Radar, Journal of Systems Engineering and Electronics, 17(4), 705-708.
  • Tekaüt, İ.&Demir, H. (2015). AISI H13 ve AISI D2 Çeliklerinin Delinmesi Esnasında Kesme Bölgesinde Oluşan Sıcaklığa Kesici Takım Kaplamasının ve İşleme Parametrelerinin Etkisi, Journal of the Faculty of Engineering and Architecture of Gazi University, 30(2), 289-296.
  • Tozan, H.&Vayvay, Ö. (2008). Fuzzy Forecasting Applications on Supply Chains. WSEAS Transactions on Systems, 7, 600-609.
  • Vallery, H., van Asseldonk, E.H., Buss, M.&van der Kooij, H. (2009). Reference Trajectory Generation for Rehabilitation Robots: Complementary Limb Motion Estimation, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 17(1), 23-30.
  • Yagimli, M., Varol, H.S., (2008). Low Cost Target Recognising and Tracking Sensory System Mobile Robot, Journal of Naval Science and Engineering, 4(1), 17-26.
  • Yang, Y., Polycarpou, M.M., Minai, A.A., (2007). Multi-UAV Cooperative Search Using an Opportunistic Learning Method, ASME Journal of Dynamic System Measurement and Control, 129 (5), 716-728.
  • Zadeh, L. (1965). Fuzzy Sets, Information and Controls, 3-9.
  • Zhou, S., Yong, C.&Jianjun, S. (2004). Statistical Estimation and Testing for Variation Root-cause Identification of Multistage Manufacturing Processes, IEEE Transactions on Automation Science and Engineering, 1(1), 73-83.

Türkiye’de Makine ve Teçhizatı Hariç Fabrikasyon Metal Ürünleri İmalatı Sektöründe Yaşanan İş Kazaları ve Ölümlü İş Kazası Sayılarının Tahmini

Yıl 2017, Cilt: 1 Sayı: 1, 9 - 15, 29.12.2017
https://doi.org/10.33720/kisgd.322546

Öz

Makine ve
Teçhizatı Hariç Fabrikasyon Metal Ürünleri İmalatı en çok iş kazasının
yaşandığı sektördür. Bu çalışmada Sosyal Güvenlik Kurumu’ndan alınan verilerle
ülkemizde Makine ve Teçhizatı Hariç Fabrikasyon Metal Ürünleri İmalatı sektöründe
yaşanan iş kazası sayıları incelenmiştir. Makine ve Teçhizatı Hariç Fabrikasyon
Metal Ürünleri İmalatı sektöründe 2008-2015 yıllarına ait veriler kullanılarak
henüz verileri açıklanmamış olan 2016 yılına ait iş kazası ve ölümlü iş kazası
sayılarının tahmin edilmesi amaçlanmıştır. Tahmin yöntemi olarak Uyarlanabilir Bulanık
Zaman Serisi ve En Küçük Kareler yöntemleri kullanılmıştır. Yapılan tahmin
neticesinde 2016 yılına dair açıklanacak kaza verileriyle hangi yöntemin daha
sağlıklı tahminde bulunduğu ortaya çıkacaktır. 

Kaynakça

  • Bourne, D., Corney, J.&Gupta, S.K. (2011). Recent Advances and Future Challenges in Automated Manufacturing Planning, ASME Journal of Computer Information Science Engineering, 11(2).
  • Chen, X., Schonfeld, D.&Khokhar, A. (2007). Localization and Trajectory Estimation of Mobile Objects with a Single Sensor, Statistical Signal Processing, IEEE/SP, SSP’07, 363-367.
  • Eustice, R., Pizarro, O.&Singh, H. (2004). Visually Augmented Navigation in an Unstructered Environment Using a Delayed State History, Proceedings of the 2004 International Conference on Robotics&Automation, IEEE.
  • Facco, P., Doplicher, F., Bezzo, F.&Barolo, M. (2009). Moving Average PLS Soft Sensor for Online Product Quality Estimation in an Industrial Batch Polymerization Process, Journal of Process Control, 19(3), 520-529.
  • Fatullayev, A.G. 18.06.2017. http://www.kocaelimakine.com/wp-content/uploads/2013/04/en-kucuk-kareler-yontemi-afet-golayoglu.pdf.
  • Hu, W., Xiao, X., Xie, D., Tan, T.&Maybank, S. (2004). Traffic Accident Prediction Using 3-D Model-based Vehicle Tracking, IEEE Transactions on Vehicular Technology, 53(3), 677-694.
  • Huang, Y-L., Horng, S-J., Kao, T-W., Kuo, I-H.&Takao, T. (2012). A hybrid forecasting model based on adaptive fuzzy time series and particle swarm optimization, International Symposium on Biometrics and Security Technologies, 66-70.
  • Hwang, J., Chen, S. M.&Lee, C. H. (1998). Handling Forecasting Problems Using Fuzzy Time Series. Fuzzy Sets and Systems, 100, 217-228.
  • Kosut, O., Turovsky, A., Sun, J., Ezovski, M., Tong, L.&Whipps, G. (2007). Integrated Mobile and Static Sensing for Target Tracking, In Military Communications Conference, MILCOM 2007, IEEE, 1-7.
  • Marques, P.&Dias, J. (2007). Moving Target Trajectory Estimation in SAR Spatial Domain Using a Single Sensor, IEEE Transaction on Aerospace and Electronic Systems, 43(3), 864-874.
  • Lee, H-S.&Chou, M-T. (2004). Fuzzy Forecasting Based on Fuzzy Time Series. International Journal of Mathematics, 81, 781-789.
  • Ohno, K., Takafumi, N.&Satoshi, T. (2006). Real-time Robot Trajectory Estimation and 3d Map Construction using 3d Camera, Intelligent Robots and Systems, International Conference on IEEE/RSJ.
  • Pantazopoulos, S.N.&Pappis, C.P. (1996). A new adaptive method for extrapolative forecasting algorithms, European Journal of Operational Research, 94, 106-111.
  • Piepmeier, J.A., McMurray, G.V.&Lipkin, H. (1998). Tracking a Moving Target with Model Independent Visual Servoing: a Predictive Estimation Approach, Proceedings of the 1998 IEEE, International Conference on Robotics & Automation, 2652-2657.
  • Piepmeier, J.A., McMurray, G.V.&Lipkin H. (2004). Uncalibrated Dynamic Visual Servoing, IEEE Transactions on Robotics and Automation, 20(1).
  • Prėvost, C.G., Desbiens, A.,&Gagnon, E. (2007). Extended Kalman Filter for State Estimation and Trajectory Prediction of a Moving Object Detected by an Unmanned Aerial Vehicle, Proceedings of the 2007 American Control Conference, USA, 1805-1810.
  • Ryan, E., Pizarro, O.&Singh, H. (2004). Visually Augmented Navigation in an Unstructured Environment Using a Delayed State History, Proceedings of the 2004 IEEE, International Conference on Robotics & Automation, 25-32.
  • SGK. (2017). SGK İstatistik Yıllıkları. Erişim Tarihi: 8.05.2017, http://www.sgk.gov.tr/wps/portal/sgk/tr/kurumsal/istatistik/sgk_istatistik_yilliklari
  • Shen, G., Kong, X.&Chen, X. (2011). A Short-term Traffic Flow Intelligent Hybrid Forecasting Model and Its Application, Control Engineering and Applied Informatics, 13(3), 65-73.
  • Mevzuatı Geliştirme ve Yayın Genel Müdürlüğü, 5510 Sayılı Sosyal Sigortalar ve Genel Sağlık Sigortası Kanunu. Erişim Tarihi: 4.05.2017, http://www.mevzuat.gov.tr/MevzuatMetin/1.5.5510.pdf
  • Tang, Y., Huang, P. (2006). Boost-Phase Ballistik Missile Trajectory Estimation with Ground Based Radar, Journal of Systems Engineering and Electronics, 17(4), 705-708.
  • Tekaüt, İ.&Demir, H. (2015). AISI H13 ve AISI D2 Çeliklerinin Delinmesi Esnasında Kesme Bölgesinde Oluşan Sıcaklığa Kesici Takım Kaplamasının ve İşleme Parametrelerinin Etkisi, Journal of the Faculty of Engineering and Architecture of Gazi University, 30(2), 289-296.
  • Tozan, H.&Vayvay, Ö. (2008). Fuzzy Forecasting Applications on Supply Chains. WSEAS Transactions on Systems, 7, 600-609.
  • Vallery, H., van Asseldonk, E.H., Buss, M.&van der Kooij, H. (2009). Reference Trajectory Generation for Rehabilitation Robots: Complementary Limb Motion Estimation, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 17(1), 23-30.
  • Yagimli, M., Varol, H.S., (2008). Low Cost Target Recognising and Tracking Sensory System Mobile Robot, Journal of Naval Science and Engineering, 4(1), 17-26.
  • Yang, Y., Polycarpou, M.M., Minai, A.A., (2007). Multi-UAV Cooperative Search Using an Opportunistic Learning Method, ASME Journal of Dynamic System Measurement and Control, 129 (5), 716-728.
  • Zadeh, L. (1965). Fuzzy Sets, Information and Controls, 3-9.
  • Zhou, S., Yong, C.&Jianjun, S. (2004). Statistical Estimation and Testing for Variation Root-cause Identification of Multistage Manufacturing Processes, IEEE Transactions on Automation Science and Engineering, 1(1), 73-83.
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Bölüm İş Sağlığı ve Güvenliği
Yazarlar

Mustafa Yağımlı

Fatih İzci

Yayımlanma Tarihi 29 Aralık 2017
Gönderilme Tarihi 20 Haziran 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 1 Sayı: 1

Kaynak Göster

IEEE M. Yağımlı ve F. İzci, “Estimation of the Number of Occupational Accidents and Deadly Occupational Accidents Encountered in Manufacturing Sector of Fabrication Metal Products, Except Machinery and Equipment Sector in Turkey”, kisgd, c. 1, sy. 1, ss. 9–15, 2017, doi: 10.33720/kisgd.322546.