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MAKİNELERİN ÖĞRENENDEN KARAR VERİCİYE DÖNÜŞÜMLERİ: ENDÜSTRİ 4.0 VE BÜYÜK VERİ

Yıl 2018, Cilt: 4 Sayı: 2, 219 - 223, 19.12.2018

Şebnem Özdemir Alptekin Erkollar Birgit Oberer

https://doi.org/10.22531/muglajsci.463474

Öz

Endüstrileşmenin
tarihsel yolculuğuna bakıldığında, her teknolojik değişim ve yenilik nedeniyle
paradigma kayması yaşandığı görülmektedir. Endüstriyel devrim olarak
adlandırılan bu paradigma kaymaları, merkezi; mekanikten elektrik enerjisine,
elektrik enerjisinden elektronik ve otomasyona değiştirmiştir. Günümüz
ekonomisi, toplumsal, ekonomik, teknolojik ve politik değişiklikler tarafından
tetiklenen dördüncü endüstriyel devrim ile yüzleşmek üzeredir. Endüstri 4.0
olarak bilinen bu devrimin temelinde, akıllı üretim, üretimde siber fiziksel
sistemlerin uygulanması (CPS) nesnelerin interneti, bulut bilişim, büyük veri
bulunmaktadır. Kavram sayesinde üretim süreçlerindeki farklılığa ek olarak,
kişiselleştirilmiş ürün ve hizmetlerin ortaya çıkarılması planlanmaktadır. Tüm
bunların yerine getirilebilmesi ortamın, inovasyon ve öğrenme bakımından
süreklilik kazanmasına bağlıdır. Bu süreklilik ise ancak üretim sürecine
giren-çıkan, üretim sürecini dolaylı ya da doğrudan etkileyebilecek her verinin
analiz edilebilmesi ile sağlanacaktır. Klasik fabrikalar için rekabet avantajı
sağlayan verinin analizi; söz konusu akıllı fabrika olduğunda büyük veri
analitiklerine evrilecek ve rekabet avantajının ötesinde zorunluluk haline
dönüşecektir. Bu açıdan değerlendirildiğinde büyük verinin Endüstri 4.0 kavramı
içindeki yeri ve üretim süreçlerinden nitelikli insan kaynağına kadar her
paydaş üzerindeki etkisi dikkatli bir biçimde incelenmelidir. Bu çalışmada
Endüstri 4.0 kavramı altında büyük verinin rolü ve etkinliği, endüstriyel
örnekler ve siber-fiziksel sistem mimarisi bakımından sunulmaktadır.

Anahtar Kelimeler

Endüstri 4.0 Akıllı Fabrikalar Büyük Veri Analitikleri

Kaynakça

  • [1] Drath, R., & Horch, A., "Industrie 4.0: Hit or Hype?", IEEE Industrial Electronics Magazine 8(2), 56-59, 2014.
  • [2] Höller, J., Tsiatsis, V., Mulligan, C., Karnouskos, S., Avesand, S., & Boyle, D. "Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence", Elsevier Publishing, e-ISBN: 9780080994017 , 1-352, 2014.
  • [3]Buhr, D., "Social Innovation Policy for Industry 4.0", Friedrich Ebert Stiftung, 3-16, 2015.
  • [4] Bauer, W., “Industry 4.0- An Economy Based on The Internet of Things”, 23rd International Conference for Production Research, Manila, Philippines, 2015.http://www.piie.org/icpr23/downloads/04%20Bauer.pdf
  • [5] Zug, S., Wilske, S., Steup, C., & Lüder, A., "Online Evaluation Of Manipulation Tasks For Mobile Robots İn Industry 4.0 Scenarios", IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), Luxembourg: IEEE, 1-7, 2015.
  • [6] Zhou, K., Liu, T., & Zhou, L., "Industry 4.0: Towards Future Industrial Opportunities And Challenges", 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Zhangjiajie: IEEE, 2147-2152, 2015.
  • [7] Niesen, T., Houy, C., Fettke, P., & Loos, P., "Towards An Integrative Big Data Analysis Framework For Data-Driven Risk Management In Industry 4.0", 49th Hawaii International Conference on System Sciences (HICSS), Koloa: IEEE, 5065-5074, 2016.
  • [8] Papakostas, N., O'Connor, J., & Byrne, G., "Internet Of Things Technologies In Manufacturing: Application Areas, Challenges And Outlook, International Conference on Information Society (i-Society), IEEE, 126-131, 2016.
  • [9] Caputo, A.; Marzi G.; M. M. Pellegrini, M.M., "The Internet Of Things in Manufacturing Innovation Processes. Development And Application Of A Conceptual Framework", Business Process Management Journal, 22(2), 383-402, 2016.
  • [10] World Economic Forum,“The Future of Jobs”, World Economic Forum, 1-167, 2016.
  • [11] Lee, J.; Kao, H. A.; Yang, S., "Service Innovation And Smart Analytics For Industry 4.0 And Big Data Environment", Procedia CIRP, 16,3–8, 2014.
  • [12] Kovar, J., Mouralova, K., Ksica, F., Kroupa, J., Andrs, O., & Hadas, Z., "Virtual Reality In Context Of Industry 4.0 Proposed Projects At Brno University Of Technology", 17th International Conference on Mechatronics-Mechatronika (ME), IEEE, 1-7, 2016.
  • [13] McKinsey Clobal Institute, “The Age Of Analytics: Competing in A Data-Driven World”, McKinsey Analytics, Mckinsey&Company, 2016.
  • [14] Burning Glass Technologies, “The Quant Crunch- How The Demand For Data Science Skills İs Disrupting The Job Market”. https://bigdata.ieee.org/images/files/pdf/The-Quant-Crunch_Final.pdf , 2017.
  • [15] GTAI, "Big Data", https://www.gtai.de/GTAI/Navigation/EN/Invest/Industries/Industrie-4-0/Internet-of-things/industrie-4-0-internet-of-things-big-data.html?view=renderPdf, 1-2, 2017.
  • [16] T-Systems International GmbH., "Big Data". T-Systems: https://www.t-systems.com/en/perspectives/big-data/iot-trends/big-data-analysis-440752 , 2017.
  • [17] ITRI, "Big Data Analytics for Industry 4.0 Predictive Manufacturing", ITRI- Industrial Technology Research Institute, 2017.https://www.itri.org.tw/eng/content/msgpic01/contents.aspx?&SiteID=1&MmmID=620651706136357202&CatID=620653256103620163&MSID=711022154112316330
  • [18] Lee, J., Bagheri, B., & Kao, H. A., "A Cyber-Physical Systems Architecture For Industry 4.0-Based Manufacturing Systems", Manufacturing Letters, 18-23, 2015.
  • [19] Wang, S., Wan, J., Zhang, D., Di, L., & Zhang, C., "Towards Smart Factory For Industry 4.0: A Self-Organized Multi-Agent System With Big Data Based Feedback And Coordination", Computer Networks, 158-168, 2016.
  • [20] Tan, C., Hu, J., Chung, H., Barton, K., Piya, C., Ramani, K., & Banu, M., "Product Personalization Enabled By Assembly Architecture And Cyber Physical Systems", CIRP Annals - Manufacturing Technology, 33-36, 2017.
  • [21] Liu, X. F., Shahriar, M. R., Sunny, S. L., & Hu, L., "Cyber-Physical Manufacturing Cloud: Architecture, Virtualization, Communication, And Testbed", Journal of Manufacturing Systems, 352-364, 2017.
  • [22] Kusiak, A., "Smart Manufacturing Must Embrace Big Data", Nature, 23-25, 2017.
  • [23] Özdemir, Ş., Erkollar, A., " Next Generation’s Industry 4.0 Journey: the Case of Management Information Systems", International Symposium for Production Research, 535-545, 2017.

TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA

Yıl 2018, Cilt: 4 Sayı: 2, 219 - 223, 19.12.2018

Şebnem Özdemir Alptekin Erkollar Birgit Oberer

https://doi.org/10.22531/muglajsci.463474

Öz

When the historical
journey of industrialization was reviewed, a particular paradigm shift can be
observed because of every technological change and innovation. These paradigm
shifts, called industrial revolutions, have changed the core from mechanics to
electrical energy, from electrical energy to electronics and automation.
Today's economy is about to face the fourth industrial revolution triggered by
social, economic, technological and political changes. That revolution, known
as Industry 4.0, is based on smart manufacturing, the implementation of
cyber-physical systems in production (CPS), Internet of Things (IoT), cloud
computing, and big data. In addition to the difference in production processes,
the concept is planned to reveal personalized products and services. The
fulfillment of all this depends on the continuity of the environment regarding
innovation and learning. This continuity will be ensured by analyzing every
data that may directly or indirectly affect the production process. Establishing
such a data processing policy for today's classic factory structures is an
essential competitive advantage. However, when it comes to smart factories,
this policy will evolve into the big data analytics-driven one, and become a
necessity beyond the competitive advantage. From this point of view, the role
of big data in the Industry 4.0 concept and its impact on each stakeholder,
which has different and variety contribution from production processes to
qualified human resources, should be carefully examined. In this study, it is
aimed to show the role and effectiveness of big data by presenting industrial
applications and cyber-physical system architecture under the concept of
Industry 4.0.







Anahtar Kelimeler

Industry 4.0 Smart Factory

Kaynakça

  • [1] Drath, R., & Horch, A., "Industrie 4.0: Hit or Hype?", IEEE Industrial Electronics Magazine 8(2), 56-59, 2014.
  • [2] Höller, J., Tsiatsis, V., Mulligan, C., Karnouskos, S., Avesand, S., & Boyle, D. "Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence", Elsevier Publishing, e-ISBN: 9780080994017 , 1-352, 2014.
  • [3]Buhr, D., "Social Innovation Policy for Industry 4.0", Friedrich Ebert Stiftung, 3-16, 2015.
  • [4] Bauer, W., “Industry 4.0- An Economy Based on The Internet of Things”, 23rd International Conference for Production Research, Manila, Philippines, 2015.http://www.piie.org/icpr23/downloads/04%20Bauer.pdf
  • [5] Zug, S., Wilske, S., Steup, C., & Lüder, A., "Online Evaluation Of Manipulation Tasks For Mobile Robots İn Industry 4.0 Scenarios", IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA), Luxembourg: IEEE, 1-7, 2015.
  • [6] Zhou, K., Liu, T., & Zhou, L., "Industry 4.0: Towards Future Industrial Opportunities And Challenges", 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Zhangjiajie: IEEE, 2147-2152, 2015.
  • [7] Niesen, T., Houy, C., Fettke, P., & Loos, P., "Towards An Integrative Big Data Analysis Framework For Data-Driven Risk Management In Industry 4.0", 49th Hawaii International Conference on System Sciences (HICSS), Koloa: IEEE, 5065-5074, 2016.
  • [8] Papakostas, N., O'Connor, J., & Byrne, G., "Internet Of Things Technologies In Manufacturing: Application Areas, Challenges And Outlook, International Conference on Information Society (i-Society), IEEE, 126-131, 2016.
  • [9] Caputo, A.; Marzi G.; M. M. Pellegrini, M.M., "The Internet Of Things in Manufacturing Innovation Processes. Development And Application Of A Conceptual Framework", Business Process Management Journal, 22(2), 383-402, 2016.
  • [10] World Economic Forum,“The Future of Jobs”, World Economic Forum, 1-167, 2016.
  • [11] Lee, J.; Kao, H. A.; Yang, S., "Service Innovation And Smart Analytics For Industry 4.0 And Big Data Environment", Procedia CIRP, 16,3–8, 2014.
  • [12] Kovar, J., Mouralova, K., Ksica, F., Kroupa, J., Andrs, O., & Hadas, Z., "Virtual Reality In Context Of Industry 4.0 Proposed Projects At Brno University Of Technology", 17th International Conference on Mechatronics-Mechatronika (ME), IEEE, 1-7, 2016.
  • [13] McKinsey Clobal Institute, “The Age Of Analytics: Competing in A Data-Driven World”, McKinsey Analytics, Mckinsey&Company, 2016.
  • [14] Burning Glass Technologies, “The Quant Crunch- How The Demand For Data Science Skills İs Disrupting The Job Market”. https://bigdata.ieee.org/images/files/pdf/The-Quant-Crunch_Final.pdf , 2017.
  • [15] GTAI, "Big Data", https://www.gtai.de/GTAI/Navigation/EN/Invest/Industries/Industrie-4-0/Internet-of-things/industrie-4-0-internet-of-things-big-data.html?view=renderPdf, 1-2, 2017.
  • [16] T-Systems International GmbH., "Big Data". T-Systems: https://www.t-systems.com/en/perspectives/big-data/iot-trends/big-data-analysis-440752 , 2017.
  • [17] ITRI, "Big Data Analytics for Industry 4.0 Predictive Manufacturing", ITRI- Industrial Technology Research Institute, 2017.https://www.itri.org.tw/eng/content/msgpic01/contents.aspx?&SiteID=1&MmmID=620651706136357202&CatID=620653256103620163&MSID=711022154112316330
  • [18] Lee, J., Bagheri, B., & Kao, H. A., "A Cyber-Physical Systems Architecture For Industry 4.0-Based Manufacturing Systems", Manufacturing Letters, 18-23, 2015.
  • [19] Wang, S., Wan, J., Zhang, D., Di, L., & Zhang, C., "Towards Smart Factory For Industry 4.0: A Self-Organized Multi-Agent System With Big Data Based Feedback And Coordination", Computer Networks, 158-168, 2016.
  • [20] Tan, C., Hu, J., Chung, H., Barton, K., Piya, C., Ramani, K., & Banu, M., "Product Personalization Enabled By Assembly Architecture And Cyber Physical Systems", CIRP Annals - Manufacturing Technology, 33-36, 2017.
  • [21] Liu, X. F., Shahriar, M. R., Sunny, S. L., & Hu, L., "Cyber-Physical Manufacturing Cloud: Architecture, Virtualization, Communication, And Testbed", Journal of Manufacturing Systems, 352-364, 2017.
  • [22] Kusiak, A., "Smart Manufacturing Must Embrace Big Data", Nature, 23-25, 2017.
  • [23] Özdemir, Ş., Erkollar, A., " Next Generation’s Industry 4.0 Journey: the Case of Management Information Systems", International Symposium for Production Research, 535-545, 2017.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Şebnem Özdemir 0000-0001-7231-7902

Alptekin Erkollar 0000-0003-3670-5283

Birgit Oberer Bu kişi benim 0000-0001-7231-7902

Yayımlanma Tarihi 19 Aralık 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 4 Sayı: 2

Kaynak Göster

APA Özdemir, Ş., Erkollar, A., & Oberer, B. (2018). TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA. Mugla Journal of Science and Technology, 4(2), 219-223. https://doi.org/10.22531/muglajsci.463474
AMA Özdemir Ş, Erkollar A, Oberer B. TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA. Mugla Journal of Science and Technology. Aralık 2018;4(2):219-223. doi:10.22531/muglajsci.463474
Chicago Özdemir, Şebnem, Alptekin Erkollar, ve Birgit Oberer. “TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA”. Mugla Journal of Science and Technology 4, sy. 2 (Aralık 2018): 219-23. https://doi.org/10.22531/muglajsci.463474.
EndNote Özdemir Ş, Erkollar A, Oberer B (01 Aralık 2018) TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA. Mugla Journal of Science and Technology 4 2 219–223.
IEEE Ş. Özdemir, A. Erkollar, ve B. Oberer, “TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA”, Mugla Journal of Science and Technology, c. 4, sy. 2, ss. 219–223, 2018, doi: 10.22531/muglajsci.463474.
ISNAD Özdemir, Şebnem vd. “TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA”. Mugla Journal of Science and Technology 4/2 (Aralık 2018), 219-223. https://doi.org/10.22531/muglajsci.463474.
JAMA Özdemir Ş, Erkollar A, Oberer B. TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA. Mugla Journal of Science and Technology. 2018;4:219–223.
MLA Özdemir, Şebnem vd. “TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA”. Mugla Journal of Science and Technology, c. 4, sy. 2, 2018, ss. 219-23, doi:10.22531/muglajsci.463474.
Vancouver Özdemir Ş, Erkollar A, Oberer B. TRANSFORMATION OF THE MACHINES FROM LEARNER TO DECISION MAKER: INDUSTRY 4.0 AND BIG DATA. Mugla Journal of Science and Technology. 2018;4(2):219-23.

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