Conquering the Challenges of Technological Growth and Success

True to my profession as an engineer, I am a total geek at heart and proud of it. Spending time in automobile museums always fascinates me. It excites me to see a prescient innovator from the past come up with an idea like headlights. The first ones were Limelight carbide models that had a nasty habit of setting the horseless carriage on fire. Within a couple of generations there were sealed beam electric headlights, safe, effective, and increasingly affordable.

[ad:30648]

We can’t imagine not utilizing these technologies as they rapidly evolved. Progress in the automotive industry was rapid and gave birth to modern mass manufacturing far beyond just cars and trucks.

Today, we are on the cusp of a new era of disruptive innovation in the automotive industry. Companies like Tesla and Google are redefining expectations for consumers with electric cars that can get the pulse racing and autonomous self-driving vehicles that have the potential to change everything we do in personal transportation. Tesla and Google are both beginning to attempt the tricky transition from pure design innovation and boutique manufacturing to becoming mass-market providers.

Scaling their operations to meet mass production demands without compromising product quality and their disruptive innovation agility will be challenging. Last year Tesla produced about 80,000 cars vs. General Motors’ nine million vehicles. Google is working on bringing manufacturing in-house and developing their supply chain. Both companies are investing heavily in testing and scaling up production capability. But they are being challenged by initiatives such as the one at General Motors, which has invested heavily in acquiring embedded technology providers, such as Cruise Automation.

General Motors is now moving from retrofitting Chevy Volt models to be a self-driving vehicle to producing the second-generation Chevy Volt designed from the ground up to be autonomous. General Motors has the deep pockets to relocate Cruise Automation to a new, larger facility in Michigan and add 1,000 additional engineers to focus on perfecting self-driving technology challenges. GM has also formalized a partnership with Lyft, the rideshare company, ensuring both market and brand visibility for its self-driving vehicles.

Tesla and Google CEOs, Elon Musk and Sundar Pichai, respectively, have acknowledged that moving into manufacturing on a mass-market scale requires a very different mindset and approach. People are eagerly awaiting Tesla’s Model 3, and the company is struggling to keep pace with the pent-up demand for the more affordable offering. Google and Tesla will need to be creative and focused, and make some concessions to embrace proven manufacturing techniques. Keeping their competitive edge in the area of innovation and agility will only be possible if they can rapidly move from concept engineering to production with minimal iterative realignments required. Production and fidelity to quality, safety, and design requirements must remain exceptional as demand drives up production targets.

One way they can support these goals is to embrace new technology in their approach to assessing and controlling risk introduced in the design and process development stages. Moving to intelligent tools that utilize tree-structure methodology for developing design, as well as process failure mode and effects analyses (FMEAs) and control plans, can provide enormous benefits and value.

Among many other positive attributes, tree-structure development of FMEA content can eliminate the need to create and maintain separate block diagrams for process FMEAs, permit easy reuse of content from one FMEA to another, and create a knowledge tool for assessing the true impact of a change request. When the FMEA and control-plan content integrate with inspection results and nonconformance data, it’s possible to provide both engineering and production with real-time feedback concerning design and quality issues. The ability to see a visual representation of a “failure net” and a “where used net” can make all the difference in addressing a problem while it is manageable rather than reacting to a warranty or recall crisis down the line.

Developing a “single source of truth” to drive managerial decisions will only be possible if these companies and others develop tools and processes that support both internal and supply chain communication and business intelligence. Siemens has invested considerable resources and capital in developing next-generation tools for “N to N design and quality solutions.” Providing integrated solutions for product and application life-cycle management; advanced product quality planning and control plan (APQP)—an automotive industry supplier requirement developed by the Big Three; FMEAs; production part approval process (PPAP); and quality control and assurance; combined with exceptional data reporting and analytics; positions companies to be both agile and innovative while maintaining rock-solid quality and brand reputation.

Siemens recently held an informative webinar with Quality Digest that offered a closer look at how these tools can work together to support growth and ensure competitive design and quality benchmarks for any organization. You can watch a recording of the webinar “Advantages of a Tree Structure FMEA: Agility, Scalability and Accelerated Quality Feedback” here. We will be watching Google and Tesla and rooting for their success as they grow and transform the marketplace.

About The Author