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Quality

Make Informed Design Decisions; Avoid Costly Design Mistakes

By | Design Reuse, Manufacturing, Quality | No Comments

Webinar:  Chrysler, Jabil Circuits, Toshiba and  Whirlpool, avoid costly design mistakes by using a systematic approach to validating and improving product design

One of the topics I continue to research and advise manufacturing companies on is how to make informed design decisions early in the product lifecycle to improve product manufacturability and quality. In an upcoming webinar, I will disuses how numerous manufacturers, including Chrysler, Jabil Circuits, Toshiba and Whirlpool, use a systematic approach to validating and improving designs in order to reduce design iterations and accelerate time to market.

I covered the outcome of poor design decisions as reflected by the excessive number of avoidable engineering change orders (ECOs), depicted in the figure below, in a number of blog posts. The direct costs of suboptimal design are well documented:

  • Excessive design  iterations
  • Multiple tooling iterations and tool breakage
  • Longer manufacturing and assembly ramp up time
  • Unnecessary scrap, energy consumption, and other waste

Furthermore, if released to production, a poorly designed product will continue to plague the brand owner with excessive manufacturing costs, high service and warranty expenses, and tarnished brand image.

Market research shows that mature manufacturing companies use four key techniques to improve manufacturability and reduce the number of design errors and frivolous ECOs:

Improving Manufacturability

Improving Manufacturability

  • Frontload design decisions
  • Formalize and apply design and manufacturing process knowledge uniformly and consistently
  • Drive up reuse
  • Automate design checks and validation

In the webinar I will discuss the experience and the measured benefits at Chrysler, Jabil Circuits, Motorola SolutionsToshiba and Whirlpool and other manufacturers that use a formal design for manufacturing (DFM) process. I will discuss design for manufacturing excellence at Airbus, and propose a structured framework to help companies approach DFM systematically.

Ford Leads in Design for Repair

By | Automotive, Manufacturing, Quality, Reliability, Service, Service Lifecycle Management (SLM) | One Comment

New F-150 Truck Demonstrates Value of Design for Repair

Design for repair is a rare practice among most product companies. Design for Repair refers to the practice of architecting a product and incorporating certain features that make field and depot repair faster and cheaper.

Several years ago, a well-known manufacturer of laptop computers experienced a wave of units that were returned for replacement of a failed disk drive. Following the repair, many of these units developed problems with their keyboards, increasing the time and cost of the disk replacement, generating subsequent warranty repair claims, and furthering customer dissatisfaction. Once the correlation between the disk replacement and keyboard failures was discovered, analysis showed that the physical design of this laptop and the work instructions for disk replacement could put too much stress on the keyboard that could cause it to fail, sometimes several weeks later.

Auto OEMs are not that different. In the past, automakers used to perform detailed time motion studies to assess repairability and establish the criteria for flat rate repair cost. Analytic tools are available for repair process and ergonomic assessment (e.g. Siemens PLM’s Human Simulation) and for authoring effective work instructions, but are vastly underutilized today because of shrinking engineering budgets and resource shortage.

But Ford Motor Co. is taking the repairability of the new aluminum body F-150 truck seriously. Engineers made a number of design and construction changes to make sure dealers can affect faster repairs at lower cost. For instance, in the traditional design of the F-150, the apron tubes wrap around the A-pillars and are welded to the body behind the instrument panel. If a tube is damaged, the technician has to remove the instrument cluster to access the tubes. In the redesigned truck, the tubes are riveted to the bottom of the A-pillars and can be removed by pulling the rivets. A similar approach was taken in the design of the floor pan, which is constructed from individually removable sections rather than a single piece. Such approach to modular design will simplify repair work and save repair technicians many hours.

Although some of the design changes have to do with the introduction of the F-150’s aluminum body and reassuring dealers (and customers), the principles of design for repair have broader applicability. Designers of complex equipment that require intricate field repair work should employ Design for Serviceability (DFS) practices, which include design for repairability, to harmonize product and repair costs – often the increased product and manufacturing costs will be recouped through lower cost repairs, higher equipment availability, and enhanced customer satisfaction. We hope that the strategy employed by Ford with the F-150 and possibly future vehicles will help demonstrate the business value.

(Image: Automotive News)

Design For Excellence: How Manufacturers Reduce Costly Design Mistakes

By | Design Reuse, Manufacturing, PLM, Quality, Reliability, Strategy | 4 Comments

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.

 

Is Dassault Systèmes’ Target Zero Defect a Realistic Goal?

By | Aerospace, Automotive, Design Reuse, Manufacturing, PLM, Quality, Reliability | No Comments

Dassault Systèmes announced the launch of “Target Zero Defect,” an industry solution for the automotive industry the company argues will “enable zero defects across the entire product development process”, although it offers no details as of how this “industry solution” actually works.  While a noble ambition, it is an impractical goal.
It’s not that the auto industry is incapable of building much higher quality products. The problem stems from the fact that 70% or so of a car value is delivered by multitude of large and small suppliers, and the automotive supply chain is complex and fragmented. Couple these with the pressure to get new cars to market faster and at low cost, and you realize that “zero defects” is an unattainable goal.
Said differently, “zero defects” does not necessarily represent a sound business strategy. Improving product quality is critical to maintain brand leadership and contain warranty and repair costs, but, at the same time, overdoing it will lead to longer time to market and escalating engineering and manufacturing costs.
Lofty aspirations aside, Dassault does get it right when highlighting the critical need to provide digital continuity and collaborative environment from concept through final assembly and into aftermarket service. This digital thread is the foundation that automakers should use to improve two major weaknesses in today’s product development practice.

Design Reuse. The automotive industry is an overzealous innovator. While innovation for product differentiation, cost reduction or safety enhancement is important, there are dozens of parts and systems that can be carried over from one design to the next, resulting in considerable saving. (See a related blog entry.)

Process Agility. Instead of the absolute “zero defect” campaign, automakers should improve their ability to detect and react quickly to design problems. They need to apply more effective simulation and test strategies to control reliability problems, use analytics to detect issues sooner and more precisely, enable context for root cause analysis, and contain the volume of impact vehicle.

In many ways, Dassault is highlighting a critical industry need, one that can be improved by implementing an effective PLM strategy that spans multiple engineering disciplines and product lifecycle phases. The challenge Dassault will face that this approach requires automakers to make some fundamental changes in the way the manage product development, which they are unlikely to be too enthusiastic about.