# Integrating Process Re-Engineering Models in Cement Production to Improve Energy Efficiency
## 1 Introduction
The data-based approach usually involves the use of data analytics, machine learning, and other computational methods that establish process predictions and improvement scenarios for various processes involved in clinker production [19; 20; 21]. Some studies [20; 21; 22; 23; 24] have also suggested that model-based optimisation techniques offer a holistic and data-driven methodology for analysing energy consumption and improving energy efficiency in cement production [20]. Further, integrating process modelling with advanced controls, and predictive algorithms is one of the most feasible techniques to optimise energy-intensive operations, such as kiln heating, grinding, and clinker formation [21; 22]. Additionally, leveraging real-time data and sensor technologies enables the development of dynamic models that adapt to evolving production conditions and variables [23]. These models can provide insights into the energy performance of the system, identify areas of inefficiency, and suggest optimal operating conditions [24]. Recent advances in research to improve energy efficiency have focused on integrating model-based approaches with sustainable methods to strike a balance between improving plant performance regarding energy consumption and lessening environmental effects [25]. These sustainable approaches include the use of alternative fuels such as biomass to potentially lower carbon emissions [26], together with advanced technologies that involve optimising equipment performance [26; 27]. Other sustainable methods that have been studied include the use of cement blends in raw materials and feeds to reduce the carbon footprint of cement manufacturing [28]. Furthermore, the utilisation of waste materials as fuel sources, such as municipal solid waste and tire-derived gasoline, is being studied for its potential to reduce environmental impact [29]. Mathematical modelling has also played an essential role in optimising production and energy consumption for the cement industry for several decades, with regression analysis mostly used in model formulation due to its capability to identify correlationsbetween multiple variables [30]. A fundamental regression equation usually connects a dependent variable, such as energy consumption, to one or more independent variables relevant to production [31; 32]. This type of analysis has proven beneficial in predictive analytics and process optimisation, enabling producers to turn large amounts of operational data into usable information [33]. Regression models also help in understanding how numerous parameters, such as kiln temperature and raw material properties, influence energy consumption, and this allows for focused interventions to improve efficiency. The ability to predict outcomes based on current and historical data using regression modelling is one of its unique advantages that promotes successful planning and decision-making, which is imperative for improving energy efficiency [34]. The use of other modern control techniques, such as PID controllers, in cement production helps in improving energy efficiency [35]. PID controllers use feedback techniques to reduce the difference between desired and actual output values. Control signals are generated efficiently by taking into account past, present, and anticipated errors [36]. Modified PID controllers have shown great potential for optimising cement plant processes, specifically improving energy efficiency [37]. The advantages of using advanced approaches with optimised and modified PID controllers include managing the nonlinear, multi-variable dynamics and process restrictions in cement plants [37; 38]. Model simulation of dynamic systems is also one of the advanced approaches that have been used in energy control systems to minimise energy use, boost efficiency, and reduce environmental pollutants while maintaining production standards [36; 39]. Implementing an integrated systems approach to energy optimisation in cement plants can result in significant cost reductions [39; 40].