Let us start by describing what is Predictive analytics.
Predictive analytics is a branch of advanced analytics which is used to make predictions about unknown future events. Predictive Analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about the future.

So, how does this apply into the manufacturing world? Well recent case studies done on the topic have a few information that manufacturing companies here in kenya need to HEAR.

A breakdown in critical equipment is costly to manufacturers both in terms of repairs as well as downtime and loss of productivity. According to Information Technology Intelligence Consulting, 98% of organizations say a single hour of downtime costs over $100,000. Thus, ensuring that all equipment is functioning optimally therefore remains a key priority for manufacturers, many of whom are turning to predictive maintenance technology to do so.

Widespread adoption of predictive maintenance technologies could reduce companies’ maintenance costs by 20%, reduce unplanned outages by 50% and extend machinery life by years according to management consulting firm McKinsey & Company.

Predictive maintenance programs monitor equipment using any number of performance metrics. By automating the data collection process through the use of IoT technology, manufacturers can develop a better understanding of how systems work and when they will fail. The ability to predict when maintenance should be performed saves manufacturers valuable time, money, and resources. Typically, monitoring tests can be conducted while equipment is in operation, which means there is no loss of production due to equipment shutdown.

Well, what do you think? SHARE your though and more on the topic.