Unplanned downtime holds the top position as the most concerning problem in the manufacturing industry. Downtime in manufacturing is often related to machine failure, production failure and unplanned stop. The impact of downtime in manufacturing can be serious and lead to loss in manufacturing process and production. Over the years, manufacturers had always tried to implement and figure out the best way to avoid unplanned downtime. In recent times, the evolution of industry 4.0 brings about the emergence of a predictive maintenance approach as a successor of preventive maintenance in avoiding unplanned downtime. What are the differences between predictive maintenance and preventive maintenance?
Predictive maintenance belongs in the same group of maintenance strategy as preventive maintenance. Both are a type of proactive maintenance where work on assets is done in advance to reduce the risk of unplanned downtime. Both approaches also aim to increase asset reliability and reduce the likelihood of equipment failures. The aspect that differs between the two approaches is the way they are executed.
The following explains the key differences between predictive maintenance and preventive maintenance:
- Predictive maintenance is a condition-based maintenance where the maintenance occurs when required based on the data analysis provided by the sensors and other monitoring tools on the equipment while preventive maintenance has a routine and defined schedule maintenance where the maintenance occurs on specific time every cycle.
- Predictive maintenance is more focused and more specific as it addresses the actual problem for maintenance compared to preventive maintenance where the maintenance occurs regularly to maintain the parts in good condition without taking the actual issues into account.
While both approaches focus on the same outcome, predictive maintenance has become a more popular option as the solution to prevent unplanned downtime as it offers benefits such as increase in production performance, increase in return of investment (ROI) and reduction of production cost. With that being said, it is undeniably worthy to say that predictive maintenance should be on the checklist of every organisation that is moving forward in digitalisation.
“If you have read the news, big corporation is lead the way for smart factory initiation, just like recent news shared by Sony planned to transformed over 75% of existing manufacturing to be smart factory to compete in this and next generation, heavily robotics and automation, tie to real time sales data to allow backend adjust for what to produce for optimize the demand and supply. We expect to see more companies move into the same direction. With massive of smart sensors deployed in smart factory, predictive maintenance provide a early detection with access to data, which in term as maintenance strategy, is of course more proactive, can contribute toward higher availability and uptime for the smart factory, which contribute to the bottom line, since most of the manufacturing depend on never stop running to lower the production cost.” added by Vincent Lim, subject matters expert (SME), consultant for E-SPIN Group.
E-SPIN Group in the enterprise ICT solution supply, consulting, project management, training and maintenance support for multinational and government agencies, across the region E-SPIN do business. Please feel free to contact E-SPIN for your inquiry and requirement, so we can assist you on the exact requirement in the packaged solutions that you may require for your company digital transformation (DT), industry 4.0 transition requirements. Implementing infrastructure continuous monitoring and providing proactive alerting, early warning and insight for minimizing unplanned downtime is just one of the many areas we may help.