A smart production system can be made energy-efficient using renewable energy and is considered to maintain the extended material requirement planning under a logistics system by using radio frequency identification. The tracking technology provides information about products with real-time notification. This study investigates renewable energy usage within a smart production system as renewable energy can contribute to Net Zero Emissions. The logistics framework involves an autonomation technology-based production system, optimum cash flow, logistics, and carbon emissions. Time is an essential influencer for material requirement planning. The model is solved with a Laplace integral transformation, where an associated matrix method is utilized by the input–output analysis. The theoretical concept is elaborated through an illustrative numerical example, where the energy consumption and corresponding net present values are evaluated. Numerical and graphical studies prove the effectiveness of the model for the use of renewable energy within for material planning under a reverse logistics system. The result reveals that efficient renewable energy consumption can save considerable costs and reduce the negative net present value of the system. It is found that skilled workers are worthy of a smart production system, not only in a qualitative aspect but also in an economic aspect.

中文翻译：

---

在混合动力智能生产系统中扩展物料需求计划 （MRP）


智能生产系统可以使用可再生能源实现节能，并被认为通过使用射频识别来维护物流系统下的扩展材料需求计划。跟踪技术通过实时通知提供有关产品的信息。本研究调查了智能生产系统中可再生能源的使用情况，因为可再生能源有助于实现净零排放。物流框架涉及基于自主技术的生产系统、最佳现金流、物流和碳排放。时间是物料需求计划的重要影响因素。该模型使用拉普拉斯积分变换进行求解，其中输入-输出分析使用相关的矩阵方法。理论概念通过一个说明性的数值示例进行了详细说明，其中评估了能耗和相应的净现值。数值和图形研究证明了该模型在逆向物流系统下使用可再生能源进行物料规划的有效性。结果表明，高效的可再生能源消费可以节省大量成本并降低系统的负净现值。研究发现，技术工人不仅在质量方面，而且在经济方面都值得拥有智能生产系统。