Affiliation:
1. Delhi Technical Campus, Greater Noida, India
2. IMS-Ghaziabad University Courses Campus, India
Abstract
The machine learning component has significantly influenced the manufacturing business, according to the Industry 4.0 standard. The Industry 4.0 paradigm encourages the use of smart sensors, tools, and gadgets to enable smart factories that continuously collect data on production. Actionable intelligence can be formed by means of ML techniques by dealing with the collected data to increase production output without materially changing the required resources. Additionally, it is now possible to recognize complex production designs owing to machine learning techniques' ability to provide analytical visions, including intelligent and continuous inspection, predictive maintenance, quality improvement, process optimization, supply chain management, and task scheduling. This research presents analysis of internet of things-enabled manufacturing, tools other than machine learning structures used in conventional in addition to unconventional machining processes, and their strengths and weaknesses in an Industry 4.0 context, as well as a perspective on the manufacturing paradigm.
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