Top Causes of Machine Failure and How IoT will Help to Resolve them
During the initial days, there were limited machine failures as machines were not too complicated. But, with the advancements in machines via program and logic controllers the scenario of fewer failures has changed. Machine failure, once a tackled part of life for manufacturers and OEMs, has encountered its match with various technology utilizing IoT devices, edge computing and the cloud.
According to a study, Wall Street Journal & Emerson discovered that industrial manufacturers have met an unplanned downtime and 42% of the time it is because of equipment failure. In order to prevent machine failure, its first key concern is to interpret what it is and why it occurs in an industrial environment.
The production line is buzzing along when a sudden failure occurs. Intermittent Failure is generally hard to recognize. Intermittent failures can usually be prevented with maintenance and can see over time as a machine’s efficacy takes a steady reduction. Few gradual failures can be prevented via regular maintenance.
The Common Causes of Machine Failure
Although some causes of machine failure can be uncertain and difficult to recognize. The following are few common causes of machine breakdown and can be utilized to monitor, prevent future instances of failures.
Accidents
A small part of machinery being handled or operated in the wrong manner can be ushered to internal parts becoming adverse and causing failure. Equipment being placed can also cause components such as gearboxes, clutches to become displaced or damaged, which would also tend to machinery to stop working properly.
Insufficient Maintenance
Maintenance that occurs too rarely can let issues go by unnoted which can then lead to a huge effect of failure, but regular maintenance, essentially, presents havoc into the system each time. Whenever a technician opens up a piece of machinery, there is always the possibility of risk and breakdown.
Physical Wear and Tear
This cause of industrial machine breakdown involves things such as a bearing failure, corrosion, metal fatigue, misalignment and surface breakdown. Corrosion of components can be problematic when the machinery is disclosed to water contamination.
Early bearing failure is most generally caused by the contamination or loss of bearing lubricant. Metal fatigue appears when you try to cut wires without the utilization of tools.
How IoT will help you to Prevent Equipment Failure?
IoT devices give unusual insight to manufacturers and OEMs with the help of the data they provide. IoT-connected machinery can run within an intelligent network that analyzes machine data to recognize bottlenecks, inform operators of imminent failures and—when connected with machine learning— even give advice for next actions depends on KPIs.
There are several strategies you can utilize to prevent equipment failure and picking up the right one depends on the cruciality of the machine, the certainty of its failures and the budget. Following are ways how IoT will help you to prevent equipment failure.
Preventative Maintenance
Preventive maintenance involves constantly inspecting machines earlier to use, initiating and staying to a maintenance schedule, continuously replacing components before their average lifecycle is over and anything that attempts to takes off the failure before it occurs. Predictive maintenance depends on the actual condition of the machine rather than the scheduled time. This enables companies to forecast equipment failure before they could appear and offers enough time to schedule future maintenance.
Real-Time Data Analysis
Machine-to-machine (M2M) is described as the technologies that enable machines to interact with each other. The IoT takes M2M to the advanced level by involving an additional element which is data. The accessibility of all machine data in one virtual network provides OEMs the capability to accumulate and monitor the data to build better predictive analytic models.
Instead of waiting for a system to fail, manufacturers are capable of precisely forecast failure because sensors begin reporting back when operating conditions move out of specification. By precisely mapping user behavior, recognizing failure patterns and rapidly realizing recurring concerns, OEMs will be capable to plan out failures, boost their product and uptime.
Exact Performance Metrics
Reliability, availability and other basic performance metrics likewise mean time between failures and mean time to repair can be estimated automatically with the help of the system and given to reporting dashboards. This eliminates the human element in recording all downtime, assuring the data is as precise as possible. Additionally, reliability metrics from distinct customer sites can be monitored to recognize best practices for execution around the world.
Predictive Maintenance
The prime reason behind applying IoT to handle your assets is predictive maintenance. Predictive maintenance utilizes past machine performance to model asset behavior. With sufficient data, algorithms can operate to forecast equipment failures depends on real-time data of machines that are IoT-connected. Anomaly detection creates predictive maintenance efficiency. It is a method that directs any different pattern of activity that could result in system failure.
Using a CMMS with an application programming interface (API) that creates a connection with IoT devices possible will be essential in assuring the actionable data can be given to the end-user in a functional way. IoT-enabled predictive maintenance provides a competitive edge to manufacturers by improving uptime, minimizing resource waste and delivering strategic insights that can grow beyond maintenance schedules into process optimization and more.
IoT-connected machinery has the capability to use the cloud for thorough, rich analysis and edge computing for quick insights, even in safer and air-gapped environments. In the near years, the IoT will be necessary for boosting productivity and efficiency everywhere.