Design For Excellence: How Manufacturers Reduce Costly Design Mistakes

QualityIn the course of designing and manufacturing new products, engineers often make costly design mistakes. They do not design the correct functionality, choose components that do not meet reliability requirements, create designs that are difficult to manufacture and service, and, in effort to correct these mistakes, they often miss time and budget expectations.

Good PDP (product development process) practices dictate that design and manufacturability mistakes are to be captured during design reviews, prototyping and early manufacturing runs. Still, too many errors aren’t identified and corrected in time, before the product is shipped, as is frequently made evident by poor product quality, high rate of warranty claims and product recalls, and expensive repair services.

My work with several manufacturing companies shows that many design mistakes are completely avoidable, and as many could have been discovered and rectified before they resulted in manufacturing problems and product failures, forced massive recalls, and tarnished the brand’s image. For example, a high tech manufacturer redesigned a plastic enclosure to improve airflow. However, the design change led to reduction in the thickness of one of the enclosure’s walls, which, in turn, produced high rate of defective enclosures during manufacturing, and subpar quality of fielded units.

The important point in this story is that the theory and practice of plastic molding is well understood, and mistakes such as inadequate wall thickness or neglecting to include support ribs should happen only infrequently, or, at least, be detected and rectified early in product development, before volume manufacturing, reducing the cost of scrap and retooling, and improving overall productivity of engineers that should focus on innovation and design rather than on managing engineering changes to correct avoidable design errors.

There are many reasons why designers make such obvious errors. In an environment where demand for faster time to market under reduced budgets and lean resources dictates rapid cadence of innovation, such error are easy to miss. And we should assume that these pressures will not ease any time soon; quite the opposite. As design complexity and the use of new material and processes continue to increase in order to stay competitive, so will the strain to accelerate innovation and time to market. Moreover, the aging of the experienced workforce is resulting in gradual attrition in practical design and manufacturing knowledge that is not easily replaceable by the low supply of well-educated yet inexperienced design and manufacturing engineers.

There are, of course, many manufacturing companies that are taking active steps to reduce the occurrences of avoidable costly mistakes. Working with these companies, I have identified the 5 key areas successful companies excel in:

  • Frontload Decisions. This is an old advice that is still as relevant as it has ever been. All product lifecycle related considerations, including manufacturability (as we discussed earlier), supply chain, service and product end of life should be evaluated and optimized early in the design. PDP practices are typically implemented as a linear forward-feeding process, which can delay critical decisions concerning downstream activities, such as manufacturability and maintainability. Good product lifecycle management practices brings all requirements and constraints, which often can be in conflict – for instance, the airflow vs. manufacturability example I presented earlier – and reach an optimal solution. I often refer to this as DFX: Design for Multidisciplinary Constraints, or, if you prefer: Design for Excellence.
  • Standardize Designs and Processes; Maximize Reuse. One of the bigger challenges I encounter in many companies is the insatiable urge to innovate, to come up with new designs, to do things differently. These are all important traits. At the same time, smart companies are careful not to innovate for innovation sake. When practical, these companies make sure to standardize design elements and manufacturing processes so that they can avoid repeating mistakes of the past, and when errors do occur, they can be identified and corrected swiftly.
  • Implement Best Practices. This is an easy advice to follow, yet not many do. Engineering, Manufacturing, Quality, and practically everyone in your product team has perspective and experience that might be worth incorporating in design guidelines throughout the product lifecycle.
  • Unify Methods and Tools. The complexity and multidisciplinary nature of product design today demands the use of several design and analysis tools to help product engineers assess the design from multiple perspectives simultaneously: functionality, cost, reliability, manufacturability, serviceability and several others. These should be synthesized into a single decision-making framework to create a complete, accurate and up to date context for higher-fidelity design decisions. By implementing a formal DFX workbench and applying complex multidisciplinary design rules objectively and consistently, companies are able to make better design trade-off decisions, identify opportunities for design reuse, apply best practices, and improve engineering productivity.
  • Maximize Communication and Collaboration. The multidisciplinary nature of product design and the increasingly elongated and often fragmented design and supply chains strain product companies. Effective collaboration in product design, manufacturing and quality management are critical. Here, again, a unified framework for encapsulating best practices, both formal and informal, can help to create an effective and agile design
    and manufacturing environment.

Obviously, different companies take different approaches and use different tools to accomplish these objectives, but it appears that independent of the tools, companies implementing a structured approach to DFX realize similar benefits:

  • Reduce the time and cost required to achieve quality targets
  • Reduce the number of design and prototyping iterations
  • Achieve faster time to market
  • Reduce occurrences and impact of manufacturing line downtime
  • Reduce manual effort handling quality spills

One such manufacturing company that I studied conducted a detailed benefits analysis of its DFX implementation and reported the following results:

  • 20% reduction in cycle time
  • 50% reduction in station space
  • 92% reduction in line downtime
  • 52% reduction in scrap

On September 5 I will host a webinar in which I will discuss this topic and present several case studies. You can register to attend the webinar here: Reduce Costly Design Mistakes Through an Automated Approach to DFx.

 

  • Joe Barkai

    After reading my blog on DFX asked about the difference between DFX and concurrent engineering (CE). In principle, CE is a process structure that can enable and support DFX, but in itself, many CE practices tend to emphasize the process much more so than the outcomes. There’s usually some discussion of the need to identify and resolve problems before they are locked into the design, but it seems that those charts that show the cost to fix an error relative the product’s development phase have been around for so long that we have become numb.

    One important practice of CE involves the formation of cross-functional teams. This allows engineers and managers of different disciplines that have different goals and constraints to collaborate in order to optimize multidisciplinary decisions: design, engineering, supply chain, manufacturing and service. Companies that excel in CE and leverage concurrent engineering to optimize design and manufacturing operations:
    • Maintain cross product centers of excellence (COC)
    • Use advanced software tools for simulation, including digital manufacturing
    • Maintain a “live” knowledge base of design rules and best practices systematically
    • Promote systems and data interoperability, including master data management and common taxonomies

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