Fault recognition for specific assembly operationidentify fault patterns and avoid costly testing costs
Less scrap in 10 weeks: identify process variables in packaging
Less defects in 12 weeks: identify and eliminate wrong process variables
Decrease of average inventory: capture in-process product data and embedded analytics to pinpoint manufacturing flaws
Minimize unplanned production line downtime.
Eliminate or reduce unplanned maintenance
Optimize maintenance schedules and resources
Reduce spare parts/materials inventory
Optimize spare parts/materials location
Avoid cost of expedited parts deliveries
Reduce maintenance costs
Extend asset life; avoid new asset costs
Reduce health, safety and environmental risks
accuracy within 48-hour regarding potential equipment failures exploration – identify situations that lead to equipment outages; improve production forecast
Decrease in unplanned maintenance: analyze production data; detect impending machine malfunctions; implement preventive maintenance
accuracy predicting machine failures 2+ hours in advance analyze robotic assembly line failure data
Maximize efficiency of production resources.
Meet production and budget targets
Reduce process variability
Reduce/eliminate scrap, increase yield
Avoid unplanned downtime
Streamline processes and improve OEE
Optimize resource scheduling
Don’t miss the opportunity to modernize a legacy connected factory and increase the business value of the operation
For manufacturers, the ability to expand beyond point-to-point machine communications and control diverse protocols among small device cohorts presents numerous opportunities for business value improvement.
Discover how to manage the transition from a disjointed patchwork of connected machines to a cohesive network of devices and creative analytics that can help increase productivity, reduce costs, and improve value.