Artificial Intelligence Deployment Pilot Study at Manufacturing Industry Kenge Rohit1,*, PhD Student, Khan Zafar1, PhD Student 1Sandip University, Nashik, India Mahiravani, Trimbak Road, Nashik-422213, Maharashtra, India *Corresponding author e-mail: rohit.kenge@gmail.com
Abstract Smart robot and feigned reality had been seen previously in the Greek antiquity story. Aristotle’s logic building and its argument ability was a milestone in human’s prospect to know self-intelligence. Artificial intelligence is also known as AI had been present in every field from the past century with continuous development in it over the years. We studied the AI evolution from 1943 neural network, machine learning, to deep learning till 2016 in detail introduction. In 2016, Hintze, an assistant professor at Michigan State University, described four main types of AI starting with today’s task-customised intelligent computer systems and ending at responsive computer systems which do not available currently. The four main types are reactive machines, limited memory, the theory of mind and self-awareness. Further, we tried to explore AI subareas, a stepwise implementation guide for business, importance, applications and limitations in a detailed literature survey. In methodology, we executed AI pilot project deployment step by step by selecting a small pilot area a compliance high-voltage testing of the finished product before sending to the customer for improving the cycle time of the testing process at the electrical power product manufacturing company. We received a benefit of process cycle time improvement, improved traceability, higher productivity and real-time data availability with the AI application in this project. We concluded this study with the main goal of AI is to deploy software that can analyse the input and give the required output. AI provides manlike communication with software and helps in decision-making for a given task, AI is not a man replacement, but AI improves the overall productivity, trust on the process, traceability of product based on real-time captured data and lead time of total process to improve the customer satisfaction exceptionally. Top Keywords: AI, AI evolution, ML, Deep learning, Neural networks. Top |