(untitled) (INTERNATIONAL JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING, 2025)
The study focused on optimization of production schedule system an 11 litres product in a plastic manufacturing industry, a case of Millennium Industries Ltd, Awka. Optimization of plastic manufacturing scheduling is crucial in reducing cycle time, increasing efficiency, and minimizing operational costs. In this study, Response Surface Methodology (RSM) is applied to identify optimal process parameters for an injection molding line producing 11-liter plastic containers. Experimental design and multi-variable analysis are applied to identify the optimal configuration of input factors in achieving an optimized cycle time while not compromising product quality. The input parameters that are included are Fill Time, Refill Time, Injection Unit Forward (IU FWD) Time, Gate Recycling (GAT RCY) Time, Front Close (FRT CLS) Time, Mold Parting (MLD PRT) Time, Tonnage Time, Breakaway Time, and First Open (FST OPN) Time. Experimental optimization and modeling revealed that the optimum combination of these parameters is: Fill Time is 8.072 s, Refill Time is 5.847 s, IU FWD Time is 0.245 s, GAT RCY Time is 6.457 s, FRT CLS Time is 0.790 s, MLD PRT Time is 0.551 s, Tonnage Time is 0.949 s, Breakaway Time is 0.134 s, and FST OPN Time is 1.875 s. These parameters together lowered the production cycle time to 21.721 seconds per 11-liter product an improvement of over baseline performance. The RSM model achieved strong predictive validity (R² > 0.95), thus confirming the non-linear interactions between factors. The sensitivity analysis revealed that the most critical factors affecting cycle time were Fill Time, GAT RCY Time, and Breakaway Time, followed by MLD PRT Time and FRT CLS Time as critical to avoid defects. The optimized schedule confirms that there is 22.8% reduction in cycle time from pre-optimization baselines. Resource efficiency confirms that energy consumption will reduce by −18.7% and material waste will also reduce. The present paper presents a fact-based method for plastic manufacturers to achieve leaner manufacturing, increased throughput, and improved sustainability. Future installations will add real-time IoT sensors to support dynamic schedule rearrangement in Industry 4.0 environments.