This paper provides a systematic review of the 5S and Kaizen methodologies as documented in Science Citation Index (SCI) literature from 2013 to 2025. Once viewed strictly as manufacturing tools, these Japanese management philosophies have evolved into universal frameworks for operational excellence. The study analyses their implementation across manufacturing, healthcare, construction, and the service sector, while exploring recent integration with Industry 4.0 technologies including IoT, digital twins, and artificial intelligence. The review consolidates data from 33 primary SCI studies, revealing statistically significant performance improvements across all sectors. Quantitative findings include a 370% efficiency improvement in construction, a 43.39% performance increase in Indian tertiary hospitals, a 53% occupational risk reduction in wood processing, and an 82% reduction in information search time in the apparel industry. The digitisation of lean tools under the Lean 4.0 paradigm offers new pathways for reliability and scalability. Findings consistently indicate that the 'Sustain' (Shitsuke) phase remains the primary barrier to long-term success, and that leadership commitment is the dominant critical success factor.

Aluminium 6061-T6; Turning; Solid Lubricant; Boric Acid; Molybdenum Disulphide; Taguchi Method; ANOVA; Surface Roughness.

Cloud computing has transformed the way organizations store, process, and manage data by providing scalable, flexible, and cost-effective computing resources. Database Management System as a Service (DBMSaaS) has become an essential cloud service that enables users to access database functionalities without maintaining dedicated hardware and software infrastructure. However, existing cloud database systems still face several challenges, including resource inefficiency, latency, security vulnerabilities, and workload imbalance. This paper proposes a novel cloud-based computing system for Database Management System as a Cloud Service that integrates intelligent resource allocation, distributed computing, adaptive workload management, and enhanced security mechanisms. The proposed architecture dynamically provisions computing and storage resources based on workload patterns, ensuring improved performance and efficient utilization of cloud resources. Role-based authentication and secure isolation techniques enhance data protection while maintaining high availability. The proposed framework is expected to improve scalability, throughput, response time, and reliability compared to conventional cloud database systems. The study provides a foundation for developing intelligent cloud database platforms suitable for modern data-intensive applications.