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

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%.

Anahtar Kelimeler

• Aggregate Production
• Process Monitoring
• Process Control
• Artificial Intelligent
• Industry 4.0

Konkasör Tesislerde Endüstri 4.0 Tabanlı Kırıcı Kontrol Sistemi ile Verimliliğin Arttırılması

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.

Anahtar Kelimeler

• Agrega Üretimi
• Proses Görüntüleme
• Proses Kontrol
• Yapay Zeka
• Endüstri 4.0

Kaynakça

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