https://matjournals.net/engineering/index.php/JoRAP <p><strong>JoRAP</strong> is a peer reviewed Journal in the discipline of Engineering published by the MAT Journals Pvt. Ltd. The Journal provides a platform to Researchers, Academicians, Scholars, Professionals and students in the Domain of Mechanical Engineering to promulgate their Research/Review/Case studies in the field of Recent Activities in Production. The Journal aims to promote high quality empirical Research, Review articles, case studies and short communications mainly focused on Production Systems, Operation Management, Quality Techniques, Statistics Integrate Resources, Manufacturing Technology, Operation Management, Automation Manufacturing, and Tool Engineering.</p> en-US Journal of Recent Activities in Production (e-ISSN: 2581-9771) https://matjournals.net/engineering/index.php/JoRAP/article/view/3961 <p><em>Modern manufacturing plants struggle to satisfy customer requirements in high-mix production settings, where wide product variety leads to operational inefficiencies. Repeated changeovers create substantial machine downtime because of lengthy setup times, and workloads are often distributed unevenly, placing excessive strain on certain workstations. These issues cause delayed deliveries, higher operating expenses, and wasted resources. This research examined a flexible production system model for high-mix operations through discrete-event simulation. A comprehensive workflow of a flexible manufacturing system was created, featuring a process flow diagram with routing sequences for fifteen product types, such as aluminum pistons, steel parts, copper alloy components, and cylinder liners. The model proved highly accurate, showing a 0.996 correlation between simulation results and real production data. The improved layout significantly enhanced performance, raising average resource utilization from 78% to 92%. Findings suggest cellular layouts are best suited to high-mix environments. Additionally, a hybrid scheduling rule achieved the best tradeoff between shorter lead times and dependable deliveries. A cause-and-effect analysis identified frequent setups, fixed routing, and rigid layouts as key downtime drivers in the baseline system. The validated model serves as a useful decision-making aid for manufacturers aiming to boost flexibility and efficiency in high-mix production.</em></p> Akaninwor Godson Chijioke Chuku Ifeanyi Emmanuel Copyright (c) 2026 Journal of Recent Activities in Production (e-ISSN: 2581-9771) 2026-08-05 2026-08-05 1 14 https://matjournals.net/engineering/index.php/JoRAP/article/view/4022 <p><em>The rapid advancement of digital technologies has fundamentally transformed manufacturing systems, leading to the emergence of smart manufacturing under the Industry 4.0 paradigm. This review examines the role of key enabling technologies, including the Industrial Internet of Things (IIoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), Digital Twins, Big Data Analytics, Cloud Computing, and intelligent automation, in modern production environments. This study presents a comprehensive assessment of peer-reviewed studies published between 2013 and 2024 to identify technological developments, industrial applications, implementation strategies, and current research trends. The reviewed literature indicates that the adoption of Industry 4.0 technologies enhances production efficiency, product quality, operational flexibility, predictive maintenance, and real-time decision-making through data-driven manufacturing. The paper also discusses major implementation challenges, such as investment requirements, cybersecurity concerns, workforce skill gaps, and technology integration issues, particularly for small and medium-sized enterprises (SMEs). Finally, future research priorities are highlighted to support the development of scalable, secure, sustainable, and human-centric smart manufacturing systems capable of meeting the evolving demands of next-generation industries.</em></p> Azazullah Shamshad Alam Copyright (c) 2026 Journal of Recent Activities in Production (e-ISSN: 2581-9771) 2026-08-18 2026-08-18 15 32