Innovation issues

Q: Design for Six Sigma involves the discovery, development and understanding of critical-to-quality (CTQ) areas, and it also fosters innovation. But studies have shown that using focus groups and interviews based only on current users reveals ideas relative to incremental innovation because the only knowledge most customers have is of current products.

We know the greatest potential for return is in radical innovation. My question is: What useful tools are there for determining CTQ areas of radically innovative products or new products that customers have little to no knowledge of?

From ASQ’s "Ask the Experts" blog

A: These are great questions that are not easy to answer as posed. One of the dilemmas I’ve seen with organizations building toward radical innovation without enough knowledge to identify the important quality aspects is that it’s often under intense pressure to get the product to market. In some cases, the innovation presents clear aspects that need to be controlled to create an acceptable product. In other cases, the issues are unknown.

I don’t agree that the work within a group only reflects the knowledge already present. One of the best tools in these situations is carefully crafted questions posed to those most familiar with the new technology. Given my personal bias, I would ask: What will fail, and why? Then ask about material, process and feature performance variation. Focusing on failure mechanisms and variation will lead the team to uncover aspects of the product that require well-crafted specifications and monitoring.

So you don’t need a fancy tool, just a question or two. Yet, the focus is on what will cause the innovation not to meet the customer’s expectations. What could go wrong? Make it visible, talked about and examined. Creating a safe atmosphere—with no blame or personal attacks—to explore failure permits those most invested in making the product work examine the boundaries and paths that lead to failure.

After the process of safely examining failures begins, a range of tools are available that can assist with refinement and prioritization. Failure mode and effects analysis (FMEA) and highly accelerated life testing (HALT) are two examples that provide the means to further discover areas that explore the paths to failure.

The reason I mention the need to create a safe environment first is because using FMEA and HALT when someone’s reputation or status is threatened generally leads to these tools being very ineffective.

One more thought on a safe environment for failure exploration: Focus on the process, materials and interaction with customers and their environment. The correct question to ask is, "How can we make this better, more resilient and more robust?" Don’t ask, "Why did you design it this way?" Don’t say, "This appears to be a design mistake."

Everyone involved has the same goal: to create a quality product or service. But there may be a lot of unknowns related to conditions that lead to product failure. An open and honest exploration to discover the margins and product weaknesses is most effective in a safe environment for those concerned. This also includes vendors, contractors, suppliers and everyone involved with the supply chain, development and manufacturing processes.

Fred Schenkelberg
Reliability engineering
and management consultant
FMS Reliability
Los Gatos, CA


Q: Recently, I was asked about specific statistical process control (SPC) techniques that are not statistical quality control (SQC) techniques. Other than design of experiments (DoE) and failure mode and effects analysis (FMEA), I think all other techniques also can be used in SQC, although it depends on the purpose for which it is used. It would be great if you could provide some clarity on this.

Prabir Kumar
Ribandar, India

A: SQC and SPC have some differences, as well as some similarities. SQC is used to ensure product quality while taking into account risks to the consumer and producer. With SQC, process outputs and product disposition is ultimately based on sampling and lot acceptance, so its use does not depend on whether the process used to make the product is in control.

In contrast, SPC is most proactively applied to process parameters or inputs, allowing a continuous evaluation of process performance and information for continual improvement.

Despite their differences, SQC and SPC use many of the same tools. Both are capable of using any of Kaoru Ishikawa’s seven quality control tools: cause-and-effect analysis, check/tally sheets, control charts, graphs, histograms, Pareto analysis and scatter analysis.

These tools may be used simultaneously or sequenced as necessary. For example, control charts are often employed late in an improvement project after other tools are used to identify key processes and process parameters.

When using FMEA, process variables may be listed as causes of critical failure modes and therefore are candidates to be controlled through SPC. Then, on the SQC side, those same process parameters can be related to product failures, which may be documented as effects in the FMEA.

SPC has a strong connection to DoE in that DoE can determine the most important variables to monitor—the inputs that have the greatest impact on the critical process outputs. While the process outputs also may be controlled with SQC, DoE is not necessarily used to select those outputs. Outputs are more commonly based on customer or statutory requirements.

An example of the relationship between SPC and SQC can be demonstrated in the following sequence of statistical control chart implementation:

  1. Implement SQC to protect the customer and prevent complaints. No control charts should be used at this point, just compilation of data, and inspection is based on risk to the producer and consumer.
  2. Determine the scrap rates related to product capability and statistical stability at the product characteristic level.
  3. If acceptable, implement SPC on the key product characteristics (the process outputs).
  4. If unacceptable, choose from the following options: improve the process, change the specifications, make a business decision to accept the low yield or stop producing the product.
  5. Identify the key process inputs that affect the key product characteristics.
  6. If the process inputs are stable and capable, implement SPC.

Ultimately, cost of poor quality is minimized by ensuring process control as early as possible in the product realization chain. The goal is to understand the manufacturing processes well enough to know with certainty that if the process is in control, the product will meet all customer needs and requirements.

Scott A. Laman
Senior manager, quality engineering
and risk management
Teleflex Inc.
Reading, PA

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