Madencilik Sektöründe İş Sağlığı ve Güvenliği Yönetimi için Veri Entegrasyonu Uygulaması

Madencilik endüstrisi, iş sağlığı ve güvenliği açısından değerlendirildiğinde, farklı mühendislik alanlarını ve bunlara bağlı riskleri kapsamaktadır. Günümüzde, teknoloji alanında yaşanan gelişmeler, madencilik endüstrisini mevcut donanım ve yazılımlar aracılığıyla, üretim, ekipmanların bakım/onarım durumu, maliyet, çevresel koşullar ve en önemlisi iş sağlığı ve güvenliği konusunda, veri toplayabilecek duruma getirmiştir. Bu çalışmada, iş sağlığı ve güvenliği ile ilgili farklı kaynaklardan elde edilen verilerin entegre edildiği bir uygulama sunulmaktadır. Veri entegrasyonu uygulamasında kullanılan, vaka çalışması sonucunda ekipman sağlığı ile ilgili güvensiz durum kayıtlarının, farklı ekipler ve taşıma işlemleri için incelenebileceği ortaya konmuştur. Özellikle vardiya başlangıçlarının, iş sağlığı ve güvenliği ile ilgili olayların yaşanabileceği bir zaman aralığı olduğu belirlenmiştir. Veri görselleştirmesi, analiz kabiliyeti açısından sınırlı olup, günümüzde kullanılan bilgi görselleri ve modern görselleştirme araçlarına rağmen, veri içerisindeki yapılar karmaşık hale gelebilmektedir. Belirli olayların sebepleri incelenirken, veri madenciliği gibi daha sistematik yöntemlerin kullanılması önerilmektedir.

Anahtar Kelimeler:

Açık ocak madenciliği, Veri ambarı, Veri entegrasyonu, İş sağlığı ve güvenliği

A Data Integration Application for Occupational Health and Safety Management in the Mining Industry

Mining is an industry that covers various engineering disciplines and the related risks to them in terms of occupational health and safety. Recent technological improvements in available hardware and software solutions led the mining industry to be able to collect data related to productivity, machine maintenance, costs, environmental conditions, and most importantly, occupational health and safety. This study introduces a data integration application for analyzing safety related records by using multiple data sources. The case study presented in the study revealed that the unsafe events related to machine health could be analyzed for different operator crews based on haulage type. It is observed that the beginning of a shift is a potential duration where occupational health and safety related events occur. Patterns within data by visual interpretation have limited analytics capability and can become overwhelmingly complex, even with info-graphics and modern graphic tools. It is suggested to follow a systematic methodology such as data mining to find patterns for the causes of specific events.

Keywords:

Surface mining, Data warehouse, Data integration, Occupational health and safety,

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