Araştırma Makalesi
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Enhancing Operational Efficiency in Crushers Through the Use of an Industry 4.0 Based Crusher Control System

Yıl 2024, Cilt: 22 Sayı: 2, 84 - 92, 29.11.2024
https://doi.org/10.56193/matim.1551615

Öz

In the aggregate and mining industry, an excessive flow rate of raw material from the feeder, caused by irregularities in the raw material being processed by crushers, can lead to blockages or excessive strain on the crusher. Conversely, a low flow rate of raw material can result in high energy consumption by the crusher, despite operating at a low capacity. The issues encountered in the first group result in excessive energy usage in the secondary and tertiary groups. The study focuses on a system that utilizes artificial intelligence and is based on industry 4.0 principles. The system aims to maintain production in the crusher within a specific range by controlling the flow rates of the feeders using an algorithm. This control is done automatically without the need for user intervention. The system optimizes energy consumption while maximizing production capacity and ensures uninterrupted operation.

The system was developed during the installation phase at an aggregate pilot plant in the Kahramanmaraş Evri region. It assesses the material capacity data using a belt scale on the crusher, feeder, and output conveyor. This data is then compared to the limit values stored in the database, and the system generates an information signal to initiate the required control actions. Based on this matching result, it sends information to the inverter, coordinates the production cycle, manages and documents the process stages using a structured learning system and artificial intelligence logic.The installation procedure was conducted using two distinct density gradation inputs. As a consequence of the reporting, the records in the report were compared during both the active and inactive states of the system. The project achieved an efficiency of 22% in terms of energy consumption per unit capacity. Based on the whole yearly energy usage, a total of 368609.7 kg of carbon emissions were averted. The facility's aggregate crushing capacity was increased by 40%.

Proje Numarası

Bu makale UMTİK 2024 'te sunulmuş ve başvuruda MATIM'de yayınlanması için değerlendirme talebinde bulunulmuştur.

Kaynakça

  • 1. Aso, K., Wakiyama, I., and Kita, Y., "Concrete dam construction using computerized aggregate plant (CAP). ; Automatic production control using image processing. Jidoka kotsuzai plant (CAP) ni yoru concrete dam seko. ; Gazo shori wo chushinnishita seisanryo no jido seigyo." , Kensetsu No Kikaika , Japan, 512 (1992), 47-51
  • 2. Hulthen, E., Evertsson, C., M.,’’ Real-time algorithm for cone crusher control with two variables’’Minerals Engineering, Department of Product and Production Development, Chalmers University of Technology, SE 41296 Göteborg, Sweden, 24 (2011), 987-994
  • 3. Arman, Y. Kırma-Eleme ve Taşıma Makinaları Seminer Notları, (2014), Ankara
  • 4. D. Legendre, R. Zevenhoven,‘’Assessing the Energy Efficiency of a Jaw Crusher’’, Elsevier, 30 (2014), 1-12,
  • 5. Salhaoui M., Gonzalez A.G., Arioua M., Ortiz F.J., Oualkadi A.E., Torregrosa C,L. ,‘’ Smart Industrial IoT Monitoring and Control System Based on UAV and Cloud Computing Applied to a Concrete Plant’’Sensors,19 (2019),3316
  • 6. Bhadani K., Asbjörnsson G., Hofling K., Hulthén E., Evertsson M., ‘’Application of design of experiments (DoE) in evaluating crushing-screening performance for aggregates production’’(2024)
  • 7. Bag, S.ve Pretorius, J.H.C. (2020). “Relationships Between Industry 4.0, Sustainable Manufacturing and Circular Economy: Proposal of A Research Framework”, International Journal of Organizational Analysis, 30(4), 864-898.
  • 8. Yavuz, O. (2021). “Döngüsel Ekonomi ve Endüstri 4.0”, Sonçağ Yayıncılık, Ankara
  • 9. Latan, H., Izeppi, C.W., Fiorini, C.P., Jugend, D., Jabbour, S.L.B.A., Seuring, S. ve Jabbour, C.J.C. (2020). “Stakeholders, Innovative Business Models for The Circular Economy and Sustainable Performance of Firms in An Emerging Economy Facing İnstitutional Voids”, Journal of Environmental Management, 264,1-12
  • 10. Alonso-Martinez, D., Marchi, V. ve Maria, E. (2021). “The Sustainability Performances of Sustainable Business Models”, Journal of Cleaner Production, 323, 1-11.
  • 11. Gupta ve diğerleri (2021) Gupta, H., Kumar, A. ve Wasan, P. (2021). “Industry 4.0, Cleaner Production and Circular Economy: An İntegrative Framework for Evaluating Ethical and Sustainable Business Performance of Manufacturing Organizations”, Journal of Cleaner Production, 295, 1-18.
  • 12. Hadi, S. ve Baskaran, S. (2021). “Examining Sustainable Business Performance Determinants İn Malaysia Upstream Petroleum İndustry”, Journal of Cleaner Production, 294, 1-12.
  • 13. Fernando, Y., Jabbour, C.J.C. ve Wah, W. (2019). “Pursuing Green Growth in Technology Firms through the Connections between Environmental İnnovation and Sustainable Business Performance: Does Service Capability Matter?”, Resources, Conservation & Recycling, 141, 8-20.14. Agrawal, R.W.V.A., Kumar, A., Upadhay, A. ve Garza-Reyes, J.A. (2021). “Nexus of Circular Economy and Sustainable Business Performance in the Era of Digitalization”, International Journal of Productivity and Performance Management, 71(3), 748-774
  • 14. Agrawal, R.W.V.A., Kumar, A., Upadhay, A. ve Garza-Reyes, J.A. (2021). “Nexus of Circular Economy and Sustainable Business Performance in the Era of Digitalization”, International Journal of Productivity and Performance Management, 71(3), 748-774.
  • 15. Dayong N., Junjun L., Lıang Y., (2022). Jaw crusher based on image recognition automatic control. China, CN115445694A
  • 16. Bıchao C., (2019). Efficient and intelligent jaw type crusher. China, CN110193396A
  • 17. Qıhuı C., Jıngjıng L., Jiebin L., Siming P., (2019). Automatic control system for preventing overload shutdown of jaw crusher. China, CN209866306U
  • 18. Katsuhiro I., Kamoshida Y., (2004). Crushing system. Japan, EP 1433531A1
  • 19. Keun P. S. (2023). System and operational methods for manufacturing execution based on artificial intelligence and bigdata. Korea, KR20230017556A
  • 20. Tao, F., Mın F., Xueyong F., Xıngsen Q., Sıfang Z., Rongdu S., (2021). Jaw crusher self-adaptive control method. China, CN112264178A
  • 21. Tao, F., Mın F., Xueyong F., Xıngsen Q., Rengdu S., Jichao Z., (2021). Constant-power control device and method for cone crusher through self-adaptive feeding. China, CN112973841A
  • 22. Serdaroglu R. E., (2021). A Crusher Supported by Artificial Intelligence. Turkey, 2021/014961
  • 23. Serdaroglu R. E., (2022). A system and method supported by artificial intelligence algorithms for use in mineral and aggregate crushing plants. Turkey, 2022/019220
  • 24. Serdaroglu R. E., (2023). An Algorithm Designed for the Total Optimization for Power Saving, Production Quantity and Quality by Modelling Operational Parameters in Aggregate Production Systems. Turkey, 2023/19650

Konkasör Tesislerde Endüstri 4.0 Tabanlı Kırıcı Kontrol Sistemi ile Verimliliğin Arttırılması

Yıl 2024, Cilt: 22 Sayı: 2, 84 - 92, 29.11.2024
https://doi.org/10.56193/matim.1551615

Öz

Agrega ve madencilik sektöründe, konkasör (kırma-eleme) tesislerde primer grupta çalışan makinalardan kırıcılarda, hammadde düzensizliği nedeniyle besleyiciden gelen yüksek debideki hammadde kırıcıda tıkanıklığa veya zorlanmalara sebep olurken düşük hammadde debisi kırıcının az kapasitede yüksek enerji tüketimine neden olur. Primer grupta yaşanan bu problemler akabinde sekonder ve tersiyer gruplarda da gereksiz enerji sarfiyatını beraberinde getirir. Gerçekleştirilen çalışma besleyicilerin debilerini önerilen bir algoritma içinde kullanıcı müdahalesi olmaksızın kontrol ederek kırıcıdaki üretimi önceden tanımlanan bir üst limit değer aralığı içinde tutmayı hedefleyen, maksimum üretim kapasitesinde enerji tüketimini optimize eden, kesintisiz çalışma sağlayan öğrenici, endüstri 4.0 tabanlı yapay zeka destekli bir sistem ile ilgilidir.
Kahramanmaraş Evri bölgesindeki bir agrega pilot tesiste gerçekleştirilen devreye alma çalışmalarında oluşturulan sistem; kırıcı, besleyici ve çıkış bandı üzerindeki bant kantarı ile malzeme kapasitesinin bilgilerini veri tabanındaki limit değer aralığı ile eşleme yöntemiyle değerlendirip gereken kontrolü, direkt ve bilgi sinyali üreterek gerçekleştirir. Bu eşleme sonucuna göre frekans konvertere bilgi iletir, üretim döngüsü düzenler, yapılan işlem adımlarını öğrenici bir sistem yapısıyla ve yapay zeka mantığıyla kontrol eder ve raporlar.
Devreye alma süreci iki farklı yoğunluklu gradasyon girdisi ile gerçekleştirilmiştir. Raporlama sonucunda sistemin devrede olduğu ve olmadığı zamanlarda rapor kayıtları karşılaştırılmıştır. Yapılan proje ile birim kapasitede harcanan enerji miktarında %22 verimlilik sağlanmıştır. Yıllık toplam enerji tüketime göre 368609,7 kg salınımı engellenmiştir. Tesis agrega kırma kapasitesinde %40 artış sağlanmıştır.

Etik Beyan

N/A

Destekleyen Kurum

Burçelik A.Ş. öz kaynakları ile gerçekleştirilmiştir.

Proje Numarası

Bu makale UMTİK 2024 'te sunulmuş ve başvuruda MATIM'de yayınlanması için değerlendirme talebinde bulunulmuştur.

Teşekkür

Yok

Kaynakça

  • 1. Aso, K., Wakiyama, I., and Kita, Y., "Concrete dam construction using computerized aggregate plant (CAP). ; Automatic production control using image processing. Jidoka kotsuzai plant (CAP) ni yoru concrete dam seko. ; Gazo shori wo chushinnishita seisanryo no jido seigyo." , Kensetsu No Kikaika , Japan, 512 (1992), 47-51
  • 2. Hulthen, E., Evertsson, C., M.,’’ Real-time algorithm for cone crusher control with two variables’’Minerals Engineering, Department of Product and Production Development, Chalmers University of Technology, SE 41296 Göteborg, Sweden, 24 (2011), 987-994
  • 3. Arman, Y. Kırma-Eleme ve Taşıma Makinaları Seminer Notları, (2014), Ankara
  • 4. D. Legendre, R. Zevenhoven,‘’Assessing the Energy Efficiency of a Jaw Crusher’’, Elsevier, 30 (2014), 1-12,
  • 5. Salhaoui M., Gonzalez A.G., Arioua M., Ortiz F.J., Oualkadi A.E., Torregrosa C,L. ,‘’ Smart Industrial IoT Monitoring and Control System Based on UAV and Cloud Computing Applied to a Concrete Plant’’Sensors,19 (2019),3316
  • 6. Bhadani K., Asbjörnsson G., Hofling K., Hulthén E., Evertsson M., ‘’Application of design of experiments (DoE) in evaluating crushing-screening performance for aggregates production’’(2024)
  • 7. Bag, S.ve Pretorius, J.H.C. (2020). “Relationships Between Industry 4.0, Sustainable Manufacturing and Circular Economy: Proposal of A Research Framework”, International Journal of Organizational Analysis, 30(4), 864-898.
  • 8. Yavuz, O. (2021). “Döngüsel Ekonomi ve Endüstri 4.0”, Sonçağ Yayıncılık, Ankara
  • 9. Latan, H., Izeppi, C.W., Fiorini, C.P., Jugend, D., Jabbour, S.L.B.A., Seuring, S. ve Jabbour, C.J.C. (2020). “Stakeholders, Innovative Business Models for The Circular Economy and Sustainable Performance of Firms in An Emerging Economy Facing İnstitutional Voids”, Journal of Environmental Management, 264,1-12
  • 10. Alonso-Martinez, D., Marchi, V. ve Maria, E. (2021). “The Sustainability Performances of Sustainable Business Models”, Journal of Cleaner Production, 323, 1-11.
  • 11. Gupta ve diğerleri (2021) Gupta, H., Kumar, A. ve Wasan, P. (2021). “Industry 4.0, Cleaner Production and Circular Economy: An İntegrative Framework for Evaluating Ethical and Sustainable Business Performance of Manufacturing Organizations”, Journal of Cleaner Production, 295, 1-18.
  • 12. Hadi, S. ve Baskaran, S. (2021). “Examining Sustainable Business Performance Determinants İn Malaysia Upstream Petroleum İndustry”, Journal of Cleaner Production, 294, 1-12.
  • 13. Fernando, Y., Jabbour, C.J.C. ve Wah, W. (2019). “Pursuing Green Growth in Technology Firms through the Connections between Environmental İnnovation and Sustainable Business Performance: Does Service Capability Matter?”, Resources, Conservation & Recycling, 141, 8-20.14. Agrawal, R.W.V.A., Kumar, A., Upadhay, A. ve Garza-Reyes, J.A. (2021). “Nexus of Circular Economy and Sustainable Business Performance in the Era of Digitalization”, International Journal of Productivity and Performance Management, 71(3), 748-774
  • 14. Agrawal, R.W.V.A., Kumar, A., Upadhay, A. ve Garza-Reyes, J.A. (2021). “Nexus of Circular Economy and Sustainable Business Performance in the Era of Digitalization”, International Journal of Productivity and Performance Management, 71(3), 748-774.
  • 15. Dayong N., Junjun L., Lıang Y., (2022). Jaw crusher based on image recognition automatic control. China, CN115445694A
  • 16. Bıchao C., (2019). Efficient and intelligent jaw type crusher. China, CN110193396A
  • 17. Qıhuı C., Jıngjıng L., Jiebin L., Siming P., (2019). Automatic control system for preventing overload shutdown of jaw crusher. China, CN209866306U
  • 18. Katsuhiro I., Kamoshida Y., (2004). Crushing system. Japan, EP 1433531A1
  • 19. Keun P. S. (2023). System and operational methods for manufacturing execution based on artificial intelligence and bigdata. Korea, KR20230017556A
  • 20. Tao, F., Mın F., Xueyong F., Xıngsen Q., Sıfang Z., Rongdu S., (2021). Jaw crusher self-adaptive control method. China, CN112264178A
  • 21. Tao, F., Mın F., Xueyong F., Xıngsen Q., Rengdu S., Jichao Z., (2021). Constant-power control device and method for cone crusher through self-adaptive feeding. China, CN112973841A
  • 22. Serdaroglu R. E., (2021). A Crusher Supported by Artificial Intelligence. Turkey, 2021/014961
  • 23. Serdaroglu R. E., (2022). A system and method supported by artificial intelligence algorithms for use in mineral and aggregate crushing plants. Turkey, 2022/019220
  • 24. Serdaroglu R. E., (2023). An Algorithm Designed for the Total Optimization for Power Saving, Production Quantity and Quality by Modelling Operational Parameters in Aggregate Production Systems. Turkey, 2023/19650
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Mühendisliğinde Optimizasyon Teknikleri, Makine Mühendisliği (Diğer)
Bölüm Araştırma, Geliştirme ve Uygulama Makaleleri
Yazarlar

Özge Güler 0000-0003-4076-1624

Mustafa Cemal Çakır 0000-0003-0816-4029

Proje Numarası Bu makale UMTİK 2024 'te sunulmuş ve başvuruda MATIM'de yayınlanması için değerlendirme talebinde bulunulmuştur.
Yayımlanma Tarihi 29 Kasım 2024
Gönderilme Tarihi 17 Eylül 2024
Kabul Tarihi 13 Kasım 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 22 Sayı: 2

Kaynak Göster

Vancouver Güler Ö, Çakır MC. Enhancing Operational Efficiency in Crushers Through the Use of an Industry 4.0 Based Crusher Control System. MATİM. 2024;22(2):84-92.