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The demand for cement has significantly increased, growing by 8% in the year 2022 and by a further 12% in 2023. It is highly anticipated that this trend will continue, and it will result in significant growth by 2030. However, cement production is highly energy-intensive, with 70 to 80% of the total energy consumed during the clinker formation, which is the main cement production process. Minimising energy losses requires a radical approach that includes optimising the performance of the kilns and significantly improving their energy efficiency. One of the most efficient approaches to optimise the performance of the kilns and reduce energy losses is by integrating process re-engineering models, which leverage process data analytics, machine learning, and computational methods. This study employed a model-based integration approach to improve energy efficiency during clinker formation. Energy consumption data were collected from two semi-automated cement production plants. The data were analysed using a regression model in Minitab (Minitab 21.1.0) statistical software. The analysis resulted in a linear energy consumption equation that links energy consumption to both production and energy loss. Dynamic simulations and modelling using Simulink in MATLAB were performed based on a proportional–integral–derivative (PID)-controlled system. The dynamic behaviour of the model was evaluated using data from Plant A and validated with data from Plant B. The energy efficiency equation was established as a mathematical model that explains energy improvements based on incorporating parameters for the cement kiln system and disturbances from the environment. [ABSTRACT FROM AUTHOR]

One of the most important sectors of the world economy is the mining and metals sector. Although, many operational and commercial procedures continue to be ineffective and out-of-date, which results in crucial data omissions, security flaws, and sometimes corruption. Given that the mining industry wants to increase the emphasis on ethical and open mining practices, the industry has been looking for ways to incorporate these practices. It is envisioned that such practices will contribute to the modernisation of supply chains in addition to helping to reduce risks related to sustainability and reputation. The application of blockchain technology in the minerals industry capable of tracking natural resources has been discussed in this study, giving a much-needed layer of transparency of this technology. However, there are a lot of difficulties and problems that come up when thinking about blockchain technology; if it is to advance as an industry standard, stakeholders will need to evaluate the usefulness and scalability of the technology. While blockchain technology can be applied to a wide range of areas in the minerals industry, this study shines more light on the application of this technology to conflict minerals tracking, mineral resources reporting cheating scandals, rock mechanics designs and monitoring strategy, blasting designs and operation, mine ventilation designs and applications, mining machinery maintenance and management, and mining surveying. The study reveals that blockchain technology is starting to be seriously evaluated and used by a variety of stakeholders, even though broad acceptance has not yet been attained. [ABSTRACT FROM AUTHOR]