Total Resource Management (TRM) in industry 3.5 relates to the evaluation and improvement of performance through the use of intelligent tools or methods in enhancing efficiency and effectiveness of operations. This paper illustrates a study of TRM in the rubberwood processing industry to prepare it towards a sustainable transition to industry 4.0. The rubberwood processing industry operates using massive production data. Such big data emerge from production using multi-processes because the various products come in different sizes and quality levels (grades). The rubberwood processing company in this study faces significant problems of inaccurate and delayed data. These problems introduce mistakes in inventory management and wage payment. The company also faces an economic issue due to confirmation which is labour-intensive. This study applied the Genetic Algorithm (GA) technique to verify accepted material or woodpiece and use data analytics to improve the efficiency of the verification system. Furthermore, a Web-Based Application (WBA) is developed for production data management. The results show a significant drop in the percentage of data inaccuracy when the GA confirmation method is applied and also a decrease in the percentage of production data discrepancy among processes. This successful sustainable transition is attributed to TRM because the achieved performance improvement enriches effectiveness in production, material, labour and service resources.

行业3.5中的总体资源管理（TRM）与通过使用智能工具或方法提高运营效率和有效性来评估和改进绩效有关。本文说明了对橡胶木加工业中TRM的研究，以使其朝着工业4.0的可持续过渡做好准备。橡胶木加工业使用大量的生产数据进行操作。如此大的数据来自使用多过程的生产，因为各种产品的尺寸和质量等级（等级）不同。这项研究中的橡胶木加工公司面临着数据不准确和延迟的重大问题。这些问题在库存管理和工资支付中引入了错误。由于确认工作量大，该公司还面临着经济问题。这项研究应用了遗传算法（GA）技术来验证可接受的材料或木材，并使用数据分析来提高验证系统的效率。此外，还开发了用于生产数据管理的基于Web的应用程序（WBA）。结果表明，使用GA确认方法时，数据不正确的百分比显着下降，并且各个过程之间的生产数据差异百分比也降低了。这种成功的可持续过渡归功于TRM，因为获得的绩效改进丰富了生产，材料，劳动力和服务资源的有效性。开发了用于生产数据管理的基于Web的应用程序（WBA）。结果表明，使用GA确认方法时，数据不正确的百分比显着下降，并且各个过程之间的生产数据差异百分比也降低了。这种成功的可持续过渡归功于TRM，因为获得的绩效改进丰富了生产，材料，劳动力和服务资源的有效性。开发了用于生产数据管理的基于Web的应用程序（WBA）。结果表明，使用GA确认方法时，数据不正确的百分比显着下降，并且各个过程之间的生产数据差异百分比也降低了。这种成功的可持续过渡归功于TRM，因为获得的绩效改进丰富了生产，材料，劳动力和服务资源的有效性。