Sep 13 2011

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The Key to Interlocking Traceability

A few weeks ago I summarized what I learned from an Apriso customer that implemented what I’ll call “basic traceability.” Offering much more than just an insurance policy, this customer tracked and traced component part, lot and serial numbers as part of their manufacturing process to enable real-time visibility to material flows. Benefits include better forecast accuracy, greater inventory control, improved predictive maintenance and tighter supply chain coordination.

These benefits can be enhanced by simply collecting more data. Manufacturing and supply chain processes, resource usage and other variables can also be tracked and traced – giving you what I’ll call “interlocking” traceability. A correctly implemented, next generation manufacturing operations management solution can deliver these extended levels of traceability, giving you the key to unlocking hidden data to further improve quality, delivery and cost.

This is in contrast to more traditional approaches to traceability that I have seen. Many are implemented on paper. Data is entered into systems after-the-fact. In one plant, I saw supervisors lined up in a queue after each shift, just to get data into the system. Not only does this approach lead to increased data entry burdens, but it is also prone to human error. In other cases, barcode scanning or automation are used to simplify data entry to standalone traceability systems. Although a slight improvement from a paper-based system, data can be trapped in information “silos,” thereby preventing real-time visibility that could support operational improvement activities.

These are five key success factors that can make the difference in your implementing an interlocking traceability system, and getting it done right:

  1. Implement your solution as part of an integrated platform instead of as a “silo” or point product. This will allow you to extract and extend the traceability of data to multiple functions, such as inventory, maintenance, quality and continuous process improvement.
  2. Pick a solution with sufficient flexibility to configure user-friendly screens with proper validation, allowing data capture to fit within your existing processes, avoiding additional burden of further data entry. This approach will not only reduce data entry errors, but will also be value-added to operators for the purpose of poka-yoke or error-proofing.
  3. Ensure your solution can be readily extended to integrate with the automation layer, including machines, PLC and RFID to automate data capture whenever possible; this falls back to some of what was said in #2 … the more you can automate, the greater the accuracy of your data and the higher value you can extract from your investment.
  4. Just as it is critical to have strong integration “down” to the shop floor, integration “up” to synchronize tracking with enterprise systems such as ERP, CRM or PLM is equally important. As an extension to these enterprise systems, information can be readily tracked and shared across your enterprise, resulting in greater visibility to improve operational performance. Not only will your data be more accurate, but you will actually save time and money by eliminating duplicate data entry requirements.
  5. The final step is selecting a system that is readily extensible to collaborate with external supply chain partners within a secure infrastructure; data must be able to readily travel between each of your partner’s systems and back into your own in a secure manner so intelligent business decisions can be made.

If you have implemented or are planning to implement a traceability solution without considering improvement of operational performance, then I would urge you to reconsider your implementation strategy. Even if your initial traceability scope is narrow, the key to unlocking expanded benefits by following the above five success factors can be far beyond what you might have expected.

Permanent link to this article: http://www.apriso.com/blog/2011/09/the-key-to-interlocking-traceability/

1 comment

  1. predictive maintenance

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