The world is evolving, and it has transformed from the industrial age to the era of connected and intelligent products in both organizations and competition. The advances in technology in the last decade have led to the introduction of a new term called Industry 4.0 or the fourth industrial revolution and that has led to the emergence of the term Quality 4.0. Quality 4.0 is the digitalization of traditional quality approaches and the focus on the use of digital tools to improve an organization’s ability to meet customers’ requirements with high quality. The purpose of this paper is to assess the environments of higher education institutions (HEIs) against the 11 axes of LNS Research Quality 4.0 framework and provide insights about their readiness for Quality 4.0 transformation. The framework helps the organizations digitalize their traditional quality practices and transform to Quality 4.0 through exploring the traditional quality—Quality 4.0 continuum of tools and/or concepts related to each axis so they can assess their transformation efforts accordingly. This paper uses these continuums to identify the quality implementation efforts conducted by HEIs through analyzing the continuums’ related practices adopted within their environments and find out what should be done to get to the full transformation to Quality 4.0 within the higher education field. The study shows the HEIs potential of adopting the Quality 4.0 tools and techniques of varies axes of the framework while revealing a limited adoption of most of them in the current times. This is due to several challenges the most impacting of which is having fragmented processes together with fragmented data systems and sources. The study is concluded with a proposed roadmap to assist HEIs to get the best out their efforts in the Quality 4.0 transformation process.
10 March 2025 in Journal of Industrial Information Integration
Hybrid renewable energy systems (HRESs) are increasingly used because they integrate diverse energy resources whose availability can complement one another over the day–night cycle. However, the high cost of system components, particularly batteries, and the dependence of energy generation on weather conditions can undermine their economic viability. Researchers, therefore, seek to optimize HRES configurations to achieve a balance between reliability and lifecycle cost by performing techno-economic studies using different techniques. One of the industries that started relying more on renewable energy is the mobile telecommunication industry, especially in the remote stations where the expansion of the grid is expensive and the renewable resources are abundant. This study introduces the scope of hybrid renewable energy system optimization and applies a study case to a remote telecommunication station where the existing energy system was installed without prior techno-economic assessment. Using mathematical models, single and multi-objective (lexicographic) optimizations are conducted using the particle swarm optimization algorithm and a deterministic exhaustive search numerical algorithm, to minimize the lifecycle cost of the system, maintain reliability for a full continuity of service, and reduce the dependency to the diesel generator to contribute to the decarbonization objective of the world. The computational results show a significant reduction in the cost of the system from USD 525,512.83 for the existing system to approximately USD 197,879.03 (reduction of 62.3% of the actual cost), and the operating hours of the diesel generator from 1401 h/year to 770 h/year. More details are presented in the Discussion section.