Abstract

The mining industry is essential for manufacturing because it provides the basic materials for the related value-adding processes. Deep integration of the mining industry is, however, still an exception rather than a rule. This industry and its processes differ greatly from the processes of an average manufacturing company. This is because we cannot have directly comparable results in the absence of applications of standardized modeling tools for supply chains such as the SCOR model. These circumstances hinder the integration and understanding of, and exchange between, industries relying significantly on each other. The research problem of this thesis is set in the early supply chain processes of the mining industry; it focuses on the modeling of such processes with the goal of standardizing them and improving the integration as well as the performance of this industry in the supply chain. The modeling is based on the adaptation of the integrated supply chain frameworks DCOR and SCOR to the mining industry. Today, the existing solutions of supply chain models focus mostly on the manufacturing industry, instead of the whole supply chain, since they do not incorporate the processes of the mining industry. It was found that these mining processes can have a significant and varying effect on the performance of the downstream processes and hence on the entire supply chain. In the dissertation, the analysis of the unique characteristics of the mining industry and its processes helps to identify the challenges faced by this industry. Previously, it was determined that the greatest challenges facing the mining industry are in the sourcing process. Moreover, comparing the mining processes with the processes of the manufacturing industry, the sourcing process presented the largest gap. As a consequence, the sourcing process in mining differs from the “source” process of the SCOR model. From the above, the modeling efforts focus on the processes of exploration, engineering design, construction, and extraction. To develop the modeling of these processes, the integrated DCOR and SCOR models were used. Through literature review the gap between the SCOR model and the processes of construction and extraction, and the gap between the DCOR model and the processes of exploration and engineering design, were determined. Subsequently, each process was analyzed in order to adapt SCOR and DCOR models to such processes. After that, an integrated model for the sourcing process in mining could be obtained and analyzed. The research evaluation was conducted by using two case studies from distinctive mining processes (extraction and exploration) based on “real world” information about copper companies in Chile. The purpose of choosing two cases was to highlight the general applicability of the adapted SCOR and DCOR models. The evaluation confirmed that it is possible to describe the mining processes by using standard SCOR and DCOR models, which were adapted by using the mining language to guide the implementation of the developed model. This research work is a first attempt to create a basis for further research in the early part of the supply chain in the mining industry, which relies on the availability of mineral deposits. This paper demonstrates how SCOR and DCOR models may be adapted to describe the processes in the mining domain. This implies that these models allow modeling a crucial aspect of the mining industry, with no need to integrate other generic processes into the existing SCOR and DCOR models. In addition, it can be concluded that there is a potential for integration between the processes of the early part of the supply chain in the mining industry and other processes in the supply chain by using SCOR and DCOR models. Owing to the unique characteristics of the mining industry, this thesis demonstrates that the process “source” of the SCOR model is different from the sourcing process in mining. This thesis argues that adaptation of the integrated SCOR and DCOR models allows a description of this sourcing process. This is a significant research contribution, since this sourcing is the greatest current and future challenges for the mining industry. Additionally, this work highlights that the adapted SCOR and DCOR models to mining allow selection and use of key performance indicators (KPIs), and validate best practices along the supply chain. It can be safely said that the amount of information and standard KPIs derived from mining operations will increase in the near future due to these types of models. This offers opportunities as well as challenges for mining companies and manufacturing companies. Consequently, in future research, the selection of the most suitable KPIs and best practices can contribute to improvements in integration, transparency, and performance of the mining processes, and therefore, improvements in the performance of subsequent processes in the supply chain.