IoT Factory - Official Gates

Factory is a smart production line monitoring solution powered by AI and IoT technologies, which empowers you to monitor everything on the shop floor from a centralized, live dashboard. The solution involves highly trained machine learning algorithms that are able to predict machine failures and brings higher operational intelligence that your legacy system was not able to perform.

Our Industry 4.0 solution enables manufacturers to connect multiple production lines and machines, acquire data at different stages of production from several disparate sources, and develop capabilities like remote monitoring, edge analytics, and predictive maintenance, and digital twin.

Benefits

Legacy industrial control systems that are prone to cyber threats
Product development and innovation
Lack of real-time data and disparate data systems
Implementing procedures that allow faster time to market
Keeping abreast of regulations and managing compliance
Environmental concerns and considerations

Essential for Industries Including

Factory managers can generate and analyze reports of the current work environment. They can also get alerts in case of critical environment conditions.

OEE

Availability

Performance

Quality

Behind Time

Downtime

Features

Power-packed with ML and AI capabilities

Demand forecasting and capacity planning.
Detect unexpected equipment failures symptoms.
Suggest supply chain bottlenecks.
Predictive maintenance with advanced algorithms.
Digital twin to regulate production.
Real-time demand visibility.

Factory performance monitoring and predictive analytics

Live, interactive dashboard with KPI graph for each factory.
Monitor performance of each production lines.
Collect data and improve operations with machine learning.
Data stream processing for predictive maintenance analysis.
Predict machine failure & efficiency degradation.
Predictive modeling for effective maintenance scheduling.
NLP to derive requested reports quickly.

Ticketing Systems for Issue Tracking

Smart organization, prioritization, and routing of tickets.
Predictive insights for service management requests.
Machine failure prediction and auto assignment of tickets to a technician for maintenance.
Accurate classification model based on the historical information of tickets.
Auto update ticket status when the status of machinery changes.
ML algorithms to predict estimation for task completion.

Anomaly diagnosis and precisions

ML algorithms modeled for making the most accurate predictions of failures.
Detect the misuses of a system or suspicious events.
Instant notifications on mobile devices to immediately act and resolve the issues.
Self-learning algorithms that continually improve production line efficiency.