The Role of Artificial Intelligence in Optimizing Rubber Manufacturing Processes
DOI:
https://doi.org/10.18034/apjee.v10i1.747Keywords:
Artificial Intelligence, Rubber Manufacturing, Optimization, Machine Learning, Predictive Analytics, Smart Manufacturing, Quality Control, Industrial AutomationAbstract
This review article examines how Artificial Intelligence (AI) can be used to optimize rubber production processes. The main goals are to list rubber manufacturers' difficulties, investigate AI applications, highlight significant discoveries, and discuss the policy ramifications for effective AI integration. Using a secondary data-based methodology, the study gathers information about AI applications unique to the rubber manufacturing business by reviewing a large body of literature from conferences, peer-reviewed journals, and industry reports. The results show that artificial intelligence (AI) technologies in rubber manufacturing facilitate improved process optimization, predictive maintenance, quality control, and adaptive process control. Artificial intelligence (AI)-powered technologies enhance compounded formulations, automate shaping procedures, forecast equipment breakdowns, and maximize resource efficiency. The policy consequences encompass resolving data privacy issues, allocating resources toward workforce training, instituting moral AI governance structures, and offering monetary incentives to encourage the deployment of AI. In summary, artificial intelligence has revolutionary prospects for rubber producers to improve productivity, excellence, and environmental friendliness. Rubber manufacturing processes can be made more innovative and continuously enhanced by embracing AI-driven solutions and strategic plans.
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