Manufacturing Industries generate a massive amount of data and according to a research these companies will spend approx $ 65.2 billion per year on technology by 2021. Predictive maintenance can assist in making machines more stable and anticipated by monitoring their execution allowing us to see when problems are being started and make improvements and replacements before actual failures occur or cause other more costly problems. By using machine learning we can enhance the efficiency and reduce costs in the manufacturing units. Devices create the meta-learning data model and are up to 250 percent extra accurate and 40 percent quicker than humans.

Data analytics can be effective in the Manufacturing Industry in various forms, some of the important applications include :-

  • Fault prediction and preventive maintenance.
  • Machine failure prediction.
  • Manufacturing Overhead and Labour cost tracking.
  • Managing Supply Chain Risk
  • Increasing the accuracy, quality, and yield of production.
    Greater visibility into supplier quality levels, and greater accuracy in predicting supplier performance over time.
  • Selling only the most profitable customized or build-to-order configurations of products that impact production the least.
  • Quantify how daily production impacts financial performance with visibility to the machine level.