In the industrial sector, the occurrence of downtime is unavoidable. This tends to interrupt the production workflow. Hence, an effective method to reduce the downtime frequency is by using a “machine learning” approach which is better than manual predictions. Machine learning can track, analyze and predict using a complete dataset relating to the production sector accurately than manual or other available models. By using this method, we can foresee and make predictions about unknown machine failures and take steps to improve the production efficiency. That in turn provides the manufacturer ample time to make solutions to meet the turnaround time set by customers. In a nutshell machine learning is the smartest way to eliminate downtime.
The lockdown caused by coronavirus pandemic has led several companies to subtly shift to work from home policy. However, the expectation to be more productive even in remote working conditions is still a reality for many employees. The objective is to get the job done and often there is less importance given to understanding the psychological impact of the pandemic on the workforce. Undoubtedly this adds stress to the managers too, who not only need to handle their stress but also are in a position to make sure that the team feels assured at this uncertain time. While its ideal of being productive at work is important, however mental health is far more important.
