Artificial Intelligence Modeling-Based Optimization of an Industrial-Scale Steam Turbine for Moving toward Net-Zero in the Energy Sector

Augmentation of energy efficiency in the power generation systems can aid in decarbonizing the energy sector, which is also recognized by the International Energy Agency (IEA) as a solution to attain net-zero from the energy sector. With this reference, this article presents a framework incorporating artificial intelligence (AI) for improving the isentropic efficiency of a high-pressure (HP) steam turbine installed at a supercritical power plant. The data of the operating parameters taken from a supercritical 660 MW coal-fired power plant is well-distributed in the input and output spaces of the operating parameters. Based on hyperparameter tuning, two advanced AI modeling algorithms, i.e., artificial neural network (ANN) and support vector machine (SVM), are trained and, subsequently, validated. ANN, as turned out to be a better-performing model, is utilized to conduct the Monte Carlo technique-based sensitivity analysis toward the high-pressure (HP) turbine efficiency. Subsequently, the ANN model is deployed for evaluating the impact of individual or combination of operating parameters on the HP turbine efficiency under three real-power generation capacities of the power plant. The parametric study and nonlinear programming-based optimization techniques are applied to optimize the HP turbine efficiency. It is estimated that the HP turbine efficiency can be improved by 1.43, 5.09, and 3.40% as compared to that of the average values of input parameters for half-load, mid-load, and full-load power generation modes, respectively. The annual reduction in CO2 measuring 58.3, 123.5, and 70.8 kilo ton/year (kt/y) corresponds to half-load, mid-load, and full load, respectively, and noticeable mitigation of SO2, CH4, N2O, and Hg emissions is estimated for the three power generation modes of the power plant. The AI-based modeling and optimization analysis is conducted to enhance the operation excellence of the industrial-scale steam turbine that promotes higher-energy efficiency and contributes to the net-zero target from the energy sector

Impact of Stakeholders on Lean Six Sigma Project Costs and Outcomes during Implementation in an Air-Conditioner Manufacturing Industry

Modern manufacturing operations always aim toward sustainable production through sustainable operations. Lean Six Sigma manufacturing is one of the leading models to increase operational efficiency and productivity and reduce product manufacturing costs. The lean Six Sigma problem-solving methodology DMAIC has been one of the several techniques organizations use to improve their productivity and the quality of their product and services. This paper aims to apply Lean Six Sigma and DMAIC to enhance production capacity and reduce per-unit cost. Furthermore, this research work has been carried out to analyze the impact of stakeholders on Lean Six Sigma projects. The research follows the DMAIC methodology to investigate and analyze the root cause of the problems and give possible solutions for eliminating or reducing the issues. Particularly, fishbone and 5-Whys techniques were used to determine whether the two key processes, AC Outdoor unit testing with the help of reusable power cords and the un-efficient use of expanding machine, had an impact on low productivity and high per-unit cost. The analysis indicated the importance of stakeholders in lean Six Sigma projects. It has been found that key stakeholders can affect the result of lean Six Sigma projects, e.g., in the power cord modification project, a total of USD 7738 has been lost, while in expanding machine modification project total of USD 1339 has been lost due to ignorance of key stakeholders in both projects. This paper provides practical guidance to lean Six Sigma project team leaders to develop and define the key stakeholders at the beginning of the project and clearly identify the stakeholders’ responsibilities. Furthermore, the project leader must analyze and identify internal and external stakeholders b/c stakeholders may be internal or external. This paper provides theoretical guidance to lean Six Sigma project team leaders since ignoring stakeholders could give a misleading picture in terms of project cost, savings, and duration of the project. The project leader must consider key stakeholders’ costs and future strategies before starting the project. Although some project managers and experts have conducted analyses of stakeholders’ impact on projects, lean Six Sigma literature lacks solid examples of stakeholders’ impact on LSS project results. This study tries to address this research gap by analyzing the impact of key stakeholders on LSS projects

Construction of operational data-driven power curve of a generator by industry 4.0 data analytics

10.3390/en14051227Energies145122