Abstract
The heat treat industry is quickly moving away from paper chart records due to changes in heat treatment standards such as AMS 2750 and CQI9. This move to digital data capture is leading to a step-change in the amount of data captured in heat treatment facilities. The amount of data collected in manufacturing can range from a few gigabytes per day to multiple terabytes per day, depending on the size and complexity of the manufacturing operation. However, manufacturers typically use only 10-30% of the data collected due to the following reasons: Lack of data integration - data is collected by different systems in different formats, making it difficult to integrate and analyze; Data quality issues - data is often incomplete, inaccurate, and outdated, making it difficult to make sensible decisions; Limited data analysis capabilities - manufacturers often need more tools and expertise to analyze the data effectively; and Data overload - the growing volume of data generated can be overwhelming and makes it challenging to extract meaningful insights. This paper aims to help explain how to maximize data value in a heat treat operation, focusing on data integration, quality, and analysis capabilities.
