Quality – Word of many meanings… Root of many debates… (Part 1)

GE Automation

Quality – Word of many meanings… Root of many debates… (Part 1)

Posted in General on Wednesday, 20 January 2016
Quality – Word of many meanings… Root of many debates… (Part 1)

Trouble is, as product and process innovation increasingly underpins profitability, that approach can’t hold up, because (to list a few):

  • Product lifecycles are shortening – there are no longer years or even months of a product’s life to “shake out” product design tweaks, equipment settings and material specifications
  • Complexity of design/formulation and processes are increasing (if it wasn’t high enough value-add to justify UK wage structures, we’d off-shore it, right?).
  • The move to leaner supply chains – a minor problem with quality can ripple through to missed shipments and/or increased logistics costs like never before.

Just as a mixed bag of efficiency analysis tools has a role to play in helping identify wasted capacity, a proper quality management program will have several critical elements aimed at requirements like:

  • Recording final product characteristics and facilitating isolation of non-conforming goods (as noted when the gauntlet clanged)
  • Avoiding defects or adulteration (too often turning into “scrap or re-work the bad stuff”, rather than determining root causes)
  • Complying with regulations
  • Maximising yields
  • Ensuring consistent behaviour within a process
  • Managing specifications for materials (finished, WIP and raw)

So what’s the problem? Every firm knows how to do these, right? Yes. And that IS the problem. These individual requirements spawn isolated processes, which are typically gate-focused, rather than analysis-focused. So the tools and data sets that grow around them identify symptoms, rather than guide to improvements. And every quality incident becomes a manual exercise in taking snapshots of data, and trying to divine whether the pattern of events and interactions around today’s event is likely to repeat itself (or if today is itself a repetition).

So the question we leave as our cliff-hanger to lead into Part 2: If we’ve learned to apply value stream mapping in support of throughput analysis, what does it take to adapt that kind of thinking so it can be as useful in supporting quality requirements (with the added complication of an ever-changing production mix)?


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