–Mitsubishi Electric Automation, Inc. has released the latest in a series of white papers to support packaging industry professionals. The paper titled, Innovative Predictive Maintenance Capabilities for Packaging Operations, provides insights on data analysis and machine learning technologies that provide in-time communication to operators and managers regarding the quality of production and the availability and effectiveness of machines. The purpose of the paper is to provide readers with innovative solutions for lowering total cost of ownership and reduce unplanned maintenance of packaging machines.
While the paper is tailored to the packaging industry, OEMs and end users in all manufacturing sectors, including food and beverage, material handling, printing and converting will glean useful information regarding the convergence of IT technologies with automation systems to leverage data and analytics that predict the need for maintenance service before a machine goes down.
The paper takes a deep dive into such topics as:
–Enabling predictive operating environments
–How the cloud drives predictive capabilities
–Advancing robotic maintenance with artificial intelligence
–New OEM business model
“Our OEM customers will especially benefit from this paper as it provides them with information they can use to lower their total cost to deploy and service their fleets, and ultimately, to provide better service to their customers,” said Elaine Wang, senior product marketing engineer, Mitsubishi Electric Automation, Inc. “It also offers end users in packaging, food and beverage, material handling, printing and converting insights into lowering total cost of ownership and maintenance of their machines.”
Wang explained that beyond reducing total cost of ownership, smart machine solutions from Mitsubishi Electric Automation provide the means to improve manufacturing, reduce waste, and increase uptime. “The failure prediction capabilities of our solution provides analytics to be aware of probable machine maintenance needs allowing the ability to schedule service and avoid unplanned downtime,” she said.
Mitsubishi Electric Automation
Filed Under: AI • machine learning, Robotics • robotic grippers • end effectors