MANUFACTURING MANAGEMENT SYSTEM: HUMAN RESOURCES 2(RECRUITMENT AND APPLICANT TRACKING, PERFORMANCE MANAGEMENT, LEARNING AND DEVELOPMENT, SUCCESSION PLANNING ) WITH PREDICTIVE PROMOTION MODELING USING TENSORFLOW

Abstract

In the dynamic environment of the manufacturing sector, effective human resource management is essential for maintaining productivity, workforce quality, and leadership continuity. Traditional HR practices such as recruitment, performance evaluation, training, and promotion, often rely on manual processes and subjective judgment, resulting in inefficiencies and limited development opportunities. This study introduces a Human Resource module of the Manufacturing Management System (MMS-HR), specifically developed for JJM Soap and Detergents Manufacturing. The system aims to enhance human capital operations by integrating AI-powered automation and machine learning for predictive promotion modeling. It focuses on four core components: Recruitment and Applicant Tracking, Performance Management, Learning and Development, and Succession Planning. The MMS-HR system was developed using the Agile Development Framework, enabling iterative progress, stakeholder feedback, and incremental refinement. It was implemented as a web-based platform using modern technologies for both front-end and back-end development. Each HR module was designed based on the operational workflows and specific needs of the client organization. TensorFlow was integrated to support predictive promotion modeling, allowing the system to evaluate employee performance data and identify high-potential candidates for career advancement. The system successfully automated several HR functions, including applicant tracking, performance evaluations, training module delivery, and promotion assessments. These automations significantly reduced manual workloads and improved process efficiency. The predictive modeling component supported data-driven promotion decisions by identifying performance trends and aligning them with organizational needs. As a result, JJM Soap and Detergents Manufacturing experienced enhanced HR decision-making and reduced administrative overhead. The integration of key HR processes into a centralized MMS-HR platform marks a transformative step in human resource management for manufacturing firms. By unifying recruitment, performance evaluation, employee development, and succession planning under one intelligent system, the platform streamlines the employee lifecycle from entry to promotion. The inclusion of predictive analytics through TensorFlow further supports strategic workforce planning by enabling proactive talent identification and development. Future enhancements may include real-time analytics and expanded AI-driven personalization to further improve human capital outcomes.