Robot-Assisted Quality Control in the United States Rubber Industry: Challenges and Opportunities
DOI:
https://doi.org/10.18034/abcjar.v7i2.755Keywords:
Robotics, Quality Control, Rubber Industry, Automation, Industrial Robotics, Process Optimization, Machine Learning, InspectionAbstract
Within the US rubber business, robot-assisted quality control (QAC) offers a compelling opportunity to improve productivity and quality. This study examines the possibilities and problems of incorporating robotics into rubber manufacturing quality assurance procedures. The principal aims of this study are to assess the potential applications of robotics in material handling, injection molding, and quality inspection; to identify implementation challenges; to investigate prospects with robotic technology advancements and Industry 4.0 principles; and to provide policy recommendations for successful adoption. A review methodology based on secondary data was utilized to examine extant literature, industry reports, and case studies. Important discoveries show that robotics significantly improves productivity, accuracy, and product quality—despite the significant obstacles to cost, technological complexity, and human-robot collaboration. Policy implications emphasize that government incentives, workforce development initiatives, and well-defined regulatory frameworks are necessary to support the widespread deployment of robot-assisted quality control. In the end, adopting robotics offers a revolutionary route to competitiveness and quality-driven innovation in the changing rubber business in the United States.
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Copyright (c) 2018 Manzoor Anwar Mohammed, Rahimoddin Mohammed, Prasanna Pasam, Srinivas Addimulam
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