Optimizing Production Line Operations Using Cloud-Based LSTM Forecasting Techniques

A new method for optimizing and monitoring production line performance in real-time utilizing cloud-based Long Short-Term Memory (LSTM) time-series forecasting is presented in this paper. Conventional approaches to managing production lines cannot always keep up with the rapid pace of change or reliably predict customer needs. To provide a cloud-based LSTM forecasting model that can accurately and precisely estimate the outputs of manufacturing lines. The model allows for proactive allocation of resources and decision-making to improve production processes by using LSTM's capabilities, which are excellent at identifying long-term relationships and patterns in time-series data. The system finds possible inefficiencies and bottlenecks in production and gives ongoing insights into them by combining cloud computing with real-time observing sensors. It increases overall productivity, decreases downtime, and improves production line efficiency.