Left of Test: How Manufacturing Variability Affects Material Properties

For manufacturers, materials property data plays a significant role in strengthening product design, manufacturing process, after market performance and profitability. This is mainly because knowing property data gives manufacturers the ability to determine engineering property matrix. Uncontrollable and unscalable variation of material property can result in lack of prediction, thus governance on the material behavior and performance of the end product. Material researchers and engineers point out the following as the key reasons for poor product design and market performance:

1. Improper implementation of governance to perform “Left of Test”
2. Inaccurate study of manufacturing variability that affects material properties
3. Lack of experimental-analytical correlation/comparison of material properties

Left of Test (LOT) is a pre-test (processing) stage of a simple collection capture of manufacturing process characterization and uncertainty quantification of material behavior, which can result in significant variation of properties. With new manufacturing systems such as 3D printing, the number of parameters has increased. Additionally, the number of process variations of thermal or cure cycles, raw material stock variation and shelf-life need to be examined and accounted for very well. As material behavior changes, significant unplanned effects on outcome occur. Some of the key steps in left of test include test environments, boundary conditions, profile/schedule and nondestructive evaluation. These steps contribute to determining mechanical properties, physical properties and uncertainty in modeling.

A material data and process management system stores data, automates the traceability and acts as a backbone, addressing the lifecycle for all aspects of materials management. It provides linkages between items, attributes about information items as well as the information items themselves for left of test, actual test cycle and right of test.  It covers the full scope of the materials lifecycle, thus, it captures manufacturing, process and raw material characteristics in order to determine meaningful engineering property matrix. All the effects can be accounted and used to predict material behavior and performance.