SMT iconnect007 Part 3/3: The Challenge of Traceability Data: A Call for Action
Imagine the following scenario: You’re working in the electronics manufacturing industry as an operations manager in charge of overseeing the assembly of cutting-edge devices. One day, you receive news that one of the series of products you’ve shipped to market has experienced a major malfunction, causing an uproar among customers. You frantically try to pinpoint the root cause only to lose yourself in the labyrinth of incomplete traceability data. The frustration mounts, leaving you grappling with the consequences of an ineffective traceability system. But what if there was a way to transform this experience into a seamless operation?
Traceability is the cornerstone of ensuring product quality, compliance, and customer trust, but traceability data as it exists today is not nearly as reliable as one might hope.
Enter individual material traceability, an upgraded approach to filling in data gaps, mitigating vulnerabilities, and eliminating potentially costly consequences.
Despite diligent efforts by manufacturers to implement robust traceability systems, three gaps persist between expectations and reality.
The first is a date code mismatch. In some cases, the traced date code—the code assigned to a product indicating the year and week it was made—differs from the real date code.
The second is a production lot mismatch. These are cases in which the traced production lot—the number used to relay the batch of origin—does not reflect the real lot code. This disparity indicates the presence of multiple lots within a single traced lot, which suggests reel design variations may have been grouped and packaged together accidentally.
The third is a part number mismatch. A part number reflects an item’s particular rating, voltage, speed, and many of its other qualities, and these parts need to be assembled with compatible ones. When a mix-up occurs and the wrong components get paired, the functionality of the end product is compromised. To make matters worse, it is very hard to detect this discrepancy during onsite testing.