Repurposing legacy metallurgical data Part I: A move toward dry laboratories and data bank
Autor
Ghorbani, Yousef
Nwaila, Glen T.
Zhang, Steven E.
Hay, Martyn P.
Bam, Lunga C.
Istiadi Guntoro, Pratama
Institución
Resumen
Advancements in modern mineral processing has been driven by technology and fuelled by market economics of
supply and demand. Over the last three decades, the demand for various minerals has steadily increased, while
the mineral processing industry has seen an unavoidable increase in the treatment of complex ores, continuous
decline in plant feed grade and poor plant performance partly due to blending of ores with dissimilar properties.
Despite these challenges, production plant data that are routinely generated are usually underutilised. In this
contribution and aligned with the direction of the 4th industrial revolution, we highlight the value of legacy
metallurgical plant data and the concept of a dry laboratory approach. This study is presented in two parts. In the
current paper (Part I), a comprehensive review of the potential for the combination of modern analytical
technology with data analytics to generate a new competence for process optimisation are provided. To
demonstrate the value of data within the extractive metallurgy discipline, we employ data analytics and simulation to examine gold plant performance and the flotation process in two separate case studies in the second
paper (Part II). This was done with the aim of showcasing relevant plant data insights, and extract parameters
that should be targeted for plant design and performance optimisation. We identify several promising technologies that integrate well with existing mineral processing plants and testing laboratories to exploit the concept of
a dry laboratory, in order to enhance pre-existing mineral processing chains. It also sets the passage in terms of
the value of innovative analysis of existing and simulation data as part of the new world of data analytics. Using
data- and technology-driven initiatives, we propose the establishment of dry laboratories and data banks to
ultimately leverage integrated data, analytics and process simulation for effective plant design and improved
performance.