We are living in a world of connectivity. With the advancement of Industrial IOT, manufacturing industries productivity is going very high by 30% – 40%. But at the same time the unplanned downtime of machinaries supresses the growth of the industry by pulling it down. So here is the question, what we can do to prevent the downtime of machines? The solution to the question lies in BigData analytics. Industries already adopted BigData analytics systems to improve data driven decision making which in turn reduces the cost of production. IOT with Anaytics plays a great role in transforming todays businesses by bringing operational efficiency. BigData analytics has grown up from advanced analytics to descriptive analytics then predictive analytics & finally prescriptive analysis. We have described about descriptive analytics, predictive analytics & prescriptive analytics in our previous blog. Machines perform better if maintained properly, & if we can predict when the machine will fail before breakdown then only we can prevent the loss during machinery downtime. Traditional way of maintenance is scheduling maintainance periodically to reduce wear & tear. But now we are in an era where devices can talk to each other & being in such an age, periodic maintainance sounds more old fashioned. Periodic maintenance is a preventive maintenance that does not consider the real time condition of equipments rather it is based on estimated life expectancy. We need to deploy technology like predictive analysis, so that it can be predicted early when to run the next maintenance by knowing the actual condition of the equipment & that terminology is predictive maintenance.
Deploying predictive maintenance into maintenance practice, equipment’s lifetime increases which in turn reduces cost of production. Predictive maintenance is more cost saving than periodic maintenance in terms that, it is not wise to spend money on an machine’s maintenance when it is not required. But predictive maintenance does not have a stand alone existance, it is the mixture IOT & predictive analytics(capturing data like thermal, oil, sound level etc & running analytics on it) because the ultimate goal of this technology is to schedule a maintenance when maintenance activity is the most cost effective. Not only this reduces machine maintenance cost but also it reduces downtime overheads. The benefits like early fault detection, time to failure detection, resource optimisation, cost effective assets maintenance help to achieve Just-in-time (JIT) manufacturing.