An Approach to Zero-Failures Maintenance Using Industry 4.0 in Network Connected Multistage Industrial Machines

The industrial manufacturing systems are increasing in complexity to market changes. One of the best challenges of this complex systems is reach the schedule production baches without unexpected failures, looking for the zero defects. The presence of Multistage Machines (MSM) at industrial manufacturing systems allow to produce big batches in very short times. Nevertheless, these types of machines normally are manufactured as an ad hoc machine and have not maintenance strategies tested for preventive or predictive actions. Also, if a component of this machine fails, the entire machine fails, causing the loss of the production batch. Recent publications have developed local preventive and predictive maintenance strategies for industrial multistage machines, as an individual machines with local work conditions in different places. Nevertheless, the accumulated knowledge of a MSM cannot be used as relevant information to improve maintenance actions in other MSM. This research develops and proposes a network system, called Master Maintenance Management (MMM) to establish a continuous connection with all MSM, working as a datalogger who collects all relevant information for all MSM and suggest maintenance warning predictive and preventive warnings for machines and use them for preventive actions in the rest of each MSM working at the same conditions. So, the capability of one machine for take a local predictive action is performed by the MMM to take a preventive action in the other machines connected to the same network. This approach has been developed with thermoforming multistage machines, who have local preventive maintenance strategy based on individual maintenance times and predictive maintenance strategy based on some distributed sensors in the machine and a behaviour algorithm, called Digital Behaviour Twin (DBT). The most relevant benefits of this approach are the limitation of unexpected failures in the connected machines by using accumulated information of other MSM, the change of the predictive actions to preventive actions, and the machine perform by design changes suggested with all the database collected.