# Assessing of Losses and Dilution Impact on the Cost Chain: Case Study of Gold Ore Deposits
## 1 Introduction
### Quality Control: Losses, Dilution, Average Grade of the Valuable Component
Improvements in the mill throughput were in the range of 10-15% [57; 58; 59; 60]. For example, in KCGM it was 14%, in Porgera--15%, in Highland Valley--10% and in Cadia Valley--14%. A very interesting study, made by [PERSON] and [PERSON], showed positive effects of mine-to-mill implementation in case of data warehousing and data mining [61]. They showed that each stage in the value chain of the mine process had parameters that affected product quality. Using real-time data in warehousing and data mining, we can help decision makers in the organization and improvement of mine-to-mill value chain. A new case of mine-to-mill optimization was described on the example of hard-rock mine by [PERSON] and [PERSON]. Their study shows that it is possible to use drilling performance data as a part of mine-to-mill efforts. It can be useful to determine an optimal blast energy design by determination of target fragmentation and due to controlling of the blast fragmentation [27]. Modern studies on the assessment of how ore losses and dilution affect economic efficiency of mining companies focus on definition of engineering tasks and do not give comprehensive consideration to the possibilities of cost reduction in the production chain. This research suggests an approach, which integrates cost indicators throughout the whole production cycle from ore extraction to its processing, as well as ore quality criteria. What is understood under quality is the combination of product properties that meet the standards and technical conditions (e.g., grade of valuable components and impurities, grain composition, ore processability, etc.). In this research, the input parameter is the grade of the valuable component (gold) in the ore at the stages of extraction, transportation, and processing. The grade of the valuable component is estimated basing on the parameters of mining losses and dilution [62; 63]. Product quality management is a complex of organizational, technical, and economic measures that exert a goal-oriented influence on the product quality. The process of mineral product quality management is composed of multiple stages. First the deposit is outlined; directions and procedure of mining development are selected. The possibilities of quality management are to a great extent defined by the system of mining. The quality of mineral resources is directly affected during ore extraction, transportation, production, storage, and shipment to the consumer. At the same time, control activities, which can improve the quality of mineral resources in the process of mining, are relatively limited (an increase in product concentration in the initial raw material is mostly achieved either by enrichment or by primary processing). They include reduction of dilution and losses by improving the technology and organization of mining operations and by application of new technical means of mining production. Absolute increase or decrease in the average grade of a component in the extracted material is achieved by mineral reserves management--rational engagement of richer or poorer ones [64; 65; 66]. Foreign researchers in the area of ore quality assessment [PERSON], [PERSON] et al. [67], [PERSON], [PERSON] [68], [PERSON], [PERSON] [69], [PERSON] [70], [PERSON] [71], [PERSON], [PERSON] et al. [72], and [PERSON], [PERSON], [PERSON], [PERSON] [73] focused on the calculation of cut-off grade (CG) to estimate the efficiency of resource development, which is predetermined by the necessity to optimize extraction strategy taking into account market volatility. Studies associated with the analysis of the impact that losses and dilution exert on the ore quality in publications by [PERSON], [PERSON] [74], [PERSON], [PERSON] [75], and [PERSON], [PERSON] [76] are limited to engineering estimations and do not take into account economic aspects. Mining companies in Russia and most CIS countries in their CG calculations rely on the main provisions of the Methodology [77] and have no right to set their own CG values for ore samples and mining blocks.