Time
2 months
Location
Singapore
Sector
Industry
Description
An industrial company based in Singapore reached out to us with the objective of implementing predictive analysis to prevent machine failures. The desired outcome of the project was to develop tools that could maximize machine efficiency and reduce equipment damage.
Solution
We embarked on the project by processing time series data obtained from a multitude of sensors deployed in the production facilities. Through a comprehensive analysis of this data, we were able to identify the root causes of production facility breakdowns. Leveraging these insights, we developed a unique machine learning solution tailored to the specific needs of the client.
Results
The results of our work were highly successful. Based on the data provided, our solution enabled the customer to predict machine failures with an exceptional accuracy rate of 98.7%. This predictive system played a pivotal role in minimizing production downtime, consequently reducing costs associated with both scheduled and unscheduled maintenance. Additionally, the integrated statistical system facilitated the accumulation of crucial information regarding the reliability of the primary components and machinery, further driving down the cost of maintaining the production line. As a result, our solution significantly improved the operational efficiency of the client’s production facilities.