Manufacturing companies are utilizing machine learning to gain greater intelligence, leading to new business opportunities and process improvement. SpeedWise® Machine Learning (SML) can optimize production processes, predict maintenance for equipment, and improve efficiency while reducing machinery costs.

Use Cases

Predict Equipment Maintenance

Businesses that manually perform maintenance checks on a routine basis can benefit from an automated machine learning process. The automated process will analyze patterns in data and make recommendations on which equipment may need maintenance. For example, the algorithm may detect that the temperature rise for a machine is unusual based on the data associated with it. Forecasting maintenance ahead of time before machine failure will result in significant savings.

Forecast Production Demand

Machine learning models can analyze patterns of supply utilization to predict demand of supplies needed. Understanding the utilization of supplies can also help manufacturing firms adjust inventory stock to meet demand.

Quality Control

Typically, inspections require intensive human labor, and defects are often missed. Machine learning models can detect anomalies by deeply examining large amounts of data for thousands of products. For example, incorrect packaging labels for food products is a large cause for loss. Machine learning can use historical data to recognize unusual labels for products.

Product Development

Manufacturing companies can benefit from machine learning by optimizing their product development strategy. Historical data for products such as manpower needed, cost of material, marketing costs, legal fees, and more can help manufacturing firms while planning for product development.