The Knowledge Base: The Era of Advanced Packaging
Standard of Excellence: Finding and Developing Future Leaders in Manufacturing
Global Sourcing Spotlight: Navigating the Variables of Holiday Schedules in Global Sourcing
The Challenge of Traceability Data: A Call for Action
August 7, 2023 | Dr. Eyal Weiss, CybordEstimated reading time: 1 minute
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.
The Challenge
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.
To read this entire article, which appeared in the August 2023 issue of SMT007 Magazine, click here.
Share on:
Suggested Items
Foxconn Announces Strategic Partnership With Zettabyte to Transform AI Data Centers
12/25/2024 | FoxconnZettabyte, a global leader in AI data center software and infrastructure solutions, is proud to announce a strategic partnership with Hon Hai Technology Group (Foxconn), the world's largest electronics manufacturer.
n-hop technologies Limited, OneAsia Network Limited Partner to Revolutionize Data Transfer and Networking Solutions
12/20/2024 | ACN Newswiren-hop technologies Limited, a leader in telecommunications and computer networking innovations, and OneAsia Network Limited (OneAsia), the AI factory enabler with data centres across APAC, have signed a Memorandum of Understanding (MOU) to collaborate on pioneering large data transfer solutions and AI Data Centre networking technologies.
Avnet Insights: Engineers Outline Opportunity for AI
12/19/2024 | AvnetFor the fourth consecutive year, Avnet, Inc. (Nasdaq: AVT) will release its Avnet Insights survey, which has been keeping a pulse on how engineers are responding to the market since 2021. This year’s survey examines technology’s new frontier: Artificial Intelligence, and the promise – and challenges – it presents for product design.
Flex Factory Recognized for Manufacturing Excellence and Continuous Improvement by the Association for Manufacturing Excellence
12/19/2024 | FlexFlex announced that its Zhuhai, China site, specializing in advanced assembly, tool design and manufacturing, and metal and plastics capabilities for Lifestyle and Data Center customers, received an Excellence Award from the Association for Manufacturing Excellence (AME) for demonstrating world-class continuous improvement and results. This is the third consecutive year a Flex facility received an AME Excellence Award.
Statistically Testing Inner Layer Yield Improvement Projects
12/18/2024 | Dr. Patrick Valentine, UyemuraCan we trust our measurement system to give us reliable data? Is it accurate, repeatable, and reproducible? Measurement is the foundation of quality. We measure for two primary reasons: to make decisions on product quality and to provide data that will inform continuous improvement projects. We can engage in continuous improvement projects if we are confident in our measurement systems.