In the rapidly evolving energy sector, the quest for optimized photovoltaic (PV) systems has taken a significant leap forward, thanks to innovative research led by Marziyeh Kashani from the Department of Industrial Engineering at Najafabad Branch, Islamic Azad University, Najafabad, Iran. Kashani’s work, published in the Majlesi Journal of Electrical Engineering, translates to the Journal of Electrical Engineering, offers a fresh approach to designing PV systems that are not only efficient but also deeply attuned to customer needs.
At the heart of Kashani’s research is a novel integration of mathematical modeling, Quality Function Deployment (QFD), and Design Structure Matrix (DSM) methods. This multi-faceted approach aims to bridge the gap between customer expectations and the technical requirements of PV systems, ensuring that the final product is both commercially viable and technically sound.
The journey begins with identifying customer needs (CNs) through a systems engineering framework. These needs are then translated into functional requirements (FRs) using the first matrix of QFD. Kashani explains, “By interpreting customer needs into functional requirements, we ensure that the design process is customer-centric from the outset.” This step is crucial as it sets the foundation for a product that meets market demands.
Next, these FRs are prioritized using the Analytical Network Process (ANP), a method that considers the interdependencies between different requirements. This prioritization is then fed into the second matrix of QFD, where it is examined alongside various component alternatives. Kashani elaborates, “The use of QFD and ANP allows us to systematically evaluate and prioritize the components that will best meet the identified functional requirements.”
The Design Structure Matrix (DSM) comes into play to evaluate the interdependencies between different components. This ensures that the selected components work harmoniously together, optimizing the overall performance of the PV system. Finally, a multi-objective mathematical model is used to select the optimal components, balancing technical performance, cost, and customer satisfaction.
The implications of this research for the energy sector are profound. By providing a structured approach to PV system design, Kashani’s work could revolutionize how solar power systems are developed. This could lead to more efficient, cost-effective, and customer-oriented PV systems, driving the adoption of renewable energy and reducing reliance on fossil fuels.
Moreover, the integration of QFD, ANP, and DSM methods offers a blueprint for other industries looking to optimize their product development processes. This research could inspire similar approaches in other sectors, leading to a wave of innovation and improved customer satisfaction across various industries.
Kashani’s work, published in the Majlesi Journal of Electrical Engineering, marks a significant milestone in the field of renewable energy. As the energy sector continues to evolve, this research provides a roadmap for developing PV systems that are not only technologically advanced but also deeply aligned with customer needs. This could shape future developments in the field, paving the way for more efficient, cost-effective, and customer-centric solar power systems.