Integrating AI with Industrial Automation: A Path to Smart Manufacturing

Abstract

Background

Artificial Intelligence (AI) joined with industrial automation devises new methods for manufacturing processes to lead into smart manufacturing innovation. The deployment of artificial intelligence and its associated systems depends on developers who understand both machine operations and workforce capabilities at their core.

Objective

This research investigates how AI adoption interacts with IoT implementation as well as workforce readiness and automation efficiency to produce significant smart manufacturing performance results. The research works to reveal fundamental barriers and potential opportunities encountered in industrial automation when integrating AI technologies.

Methods

This investigation utilized quantitative techniques through administered Likert-scale questionnaires to gather data from 355 manufacturing professionals. A group of research methods including reliability examinations, normality assessments alongside factor analytical techniques, and regression procedures helped explore connections between study variables. A mediation analysis evaluated the relationship between manufacturing performance and the driving influence of automation efficiency on performance.

Results
The study results showed important connections between the implementation of AI and IoT systems together with workforce preparedness and automation performance levels. Smart manufacturing performance responds greatly to the influential variable of automation efficiency. All construct measures exhibited consistent reliability according to Cronbach's alpha criteria which exceeded 0.78. Results from factor analysis supported the validation of the constructs where 55.3% of total variance stemmed from the first three factors. Multiple variables needed non-parametric testing because results from normality tests showed clusters of both normal and non-normal distribution patterns.

Conclusions
Research demonstrates how artificial intelligence can revolutionize production facilities while showing unions should integrate both machine standards and human talents. Although AI together with IoT produces better automation coupled with improved performance organizations still face ongoing workforce preparation difficulties. Organizations need to, reskill their employees and reform their cultural mindset to maximize the potential of smart manufacturing practice. Practical implementation strategies emerge from these research results to guide organizations executing AI-driven automation alongside broader knowledge of manufacturing intelligence.