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Evolving from Detection to Prevention:  Quality Assurance and Quality Control

Aug 23, 2018

Quality Assurance Procedures

You'll often hear quality assurance (QA) used interchangeably with quality control (QC).  In practice, they are very different. 

Quality assurance is proactive.  The entire cradle to grave product life cycle is considered, and specifications are crafted for not only the customer-driven product requirements, but also specific processes that result in a quality outcome.   The outcomes are both physical and perceived experiences that are essential to the brand.    The goal of QA is to build a cost-effective, repeatable product that delights the customer. 

Quality control is  reactive.  QC is about checking parts, validating specs are met, and catching defects before they ship to the customer.

Summarized in a sentence, QA  is about preventing poor quality whereas quality control is about detecting poor quality.

Quality out of control. 

The following is an excerpt from a real story.  Company A outsources manufacturing to a supplier in China, and the relationship started out well.  Specifications were sent to the supplier, tooling was cut, samples approved, production began, containers were shipped, and upon receipt of goods - a random sample was taken to check tolerances against a spec.  The entire container is deemed scrap, and the end-customer missed a window of opportunity to drive revenue during the busiest season of the year.  Because the samples were initially good, nobody thought it necessary to check parts in production.  Behind the scenes, between sampling and production, an entire layer of mid-management had turned over.  Plans for in-process inspections were specified, subsequently mis-filed, and as a result, not executed during production.   

Introducing QA

Quality assurance starts upstream, and at its finest, involves a strong relationship with a supplier.  The process unfolds in three ways, each of which are essential for a physical and emotional customer experience upon which great brands are made. 

1. Customer Requirements

At the heart of every great product lies what the customer desires, and is willing to pay for.  It's stunning how often customer requirements take a back seat to engineering possibilities.  Products that are over-designed are a common problem, resulting in solutions that are too expensive to build in time, material, and process.  Not enough can be said about homework upfront.   A good product manager will drive out the mission critical "why" behind customer experience.  From how it looks, to how it works, to how it's packaged and shipped - customer input over the entire life cycle is essential to maintain quality and control costs.  It starts during product development, and continues in perpetuity over the useful life of the brand.  Getting it right translates to 5-star ratings, repeat sales, and referrals - on which revenue growth plans depend.  Exactly which features are non-negotiable with customers?  Why?  Which features are "must have" vs. "nice to have?"  What is unique about each feature, and how is that uniqueness measured?   How does perception change over time?  How can we measure that?   These are the raw ingredients of a robust Quality Management  System.   

2. Before Production 

Next, it's time to strategize a robust manufacturing process.  Best practice involves DFMEA (Design Failure Mode and Effect Analysis) , whereby design and manufacturing engineers collaborate and negotiate tradeoffs in the design with the realities of manufacturing a high-quality, cost-effective product.   DFMEA offers an organized way of managing risks.  

A DFMEA involves several phases.  

  • Review the design.  Each component of a  product is evaluated relative to other components on the drawing. 
  • Identify and score .  Potential failure modes are brainstormed, noting the potential effects.  
    • Severity ranking:  Each issue is assigned a severity ranking related to the outcome of the failure.  A score of 10 is the highest, indicating a major safety issue that impacts human life.   
    • Ease of detection ranking:  How easy is it to detect this issue during a manufacturing process?  A score of 10 is a failure mode that is difficult to detect. 
    • Occurrence ranking.  A score of 10 indicates a failure mode frequently occurs. 
  • Do the math.  Calculate the Severity x Occurrence x Detection (SOD)  - also can be called the Risk Priority Number (RPN)
  • Focus on improvements. 
    • Develop and execute action plans to reduce SODs. 
    • Continuously measure SODs, and continuously improve.
    • Perform mistake proofing.

Identifying issues as far upstream as possible offers he highest opportunity to mitigate risks early.   Manufacturing engineering goes into production with both eyes wide open.  DFMEA should be applied on new designs, upon significant design modifications, or when the product is applied in a totally different way.  

3. In-Process Production 

At CMD, teams do so much more than simply inspect parts.  We proactively work with clients to DFMEA a robust design, and then engage reputable manufacturers committed to making quality products.   We look for suppliers demonstrating evidence  and commitment to quality systems.  CMD works collaboratively to develop suppliers with the highest potential.  These relationships take time, and payoff in the long run, resulting in containers full of high-quality product.   

Over the years, CMD's quality engineers have executed hundreds of successful quality programs on behalf of clients, using a wide variety of proven systems used the world over by the world's leading industries.  

  • Lean Manufacturing
  • Statistical Process Control (SPC)
  • Measurement System Analysis (MSA)
  • Root Cause Analysis
  • Corrective Preventative Action Management 
  • Implementing the "Top 7" (most commonly used tools)
    • Control charts - helps see how a process evolves over time.
    • Check sheets - great tool to collect data. 
    • Pareto chart - bar graph that highlights factors of significance.
    • Scatter diagram - graphs xy pairs of data - allowing trends to be spotted. 
    • Cause and effect - (aka fishbone charts) - helps sort ideas and identify possible causes of problems. 
    • Run charts - helps sort data and see patterns 
    • Histogram - helps map out frequency of issues. 
  • And much more...

Quality systems like these can help companies strike a balance between meeting customer requirements, ease of manufacturing, and economic realities. 

Conclusion  

Is your organization just inspecting parts?  Running into constant issues?  Time to step it up to prevention - and infuse quality assurance?   CMD can help. With decades of experience collaborating with clients and developing suppliers, teams at CMD are committed to quality products and systems on which brand reputation and revenue depend.  Let's get started on defect prevention today.

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Topics: Manufacturing, Operations, quality assurance