Rethinking quality in the digital age

Can automotive players cope with autonomous driving's quality implications?

Autonomous driving has introduced sophisticated new components and systems, which run under a heavy load of distributed embedded software and electronics. Without proper safeguards, these highly vulnerable systems could become the Achilles' heel of next-generation vehicle design.

While the auto industry has proved itself adept at managing traditional quality-related risks in the past, this time may be different. Autonomous vehicles and other innovations that rely on advanced electronics and software require new robust quality management systems and advanced tools and methods capable of preventive monitoring and control.

The new functional capabilities of autonomous vehicles will force quality departments to assume a leading role that will include:

• Taking steps to reduce extensive late-stage design changes.
• Stabilizing the supply chain, architecture and functionality performance.
• Reducing warranty problems and associated liability damages.

The launch of the precursors to autonomous vehicles and other advanced technologies has already tripled product recalls over the past five years, a clear sign of the increasing complexity of new products. What's more, traditional problem-solving does not support the root cause analyses in these cases because of the intermittent nature of failures that these complicated integrated systems exhibit.

Take the growing complexity of parking assistance systems, for example. Initially little more than simple ultrasonic sensor-based object detection units, they have evolved into highly complex systems that rely on more than 12 ultrasonic sensors and increasingly complex algorithms.

Automakers need to manage this complexity tightly, and monitor it during product development and production, adapting analytics, tools and methods to achieve standardized results.

Given the shift from a mechanical approach to one based on electronics and software, future automotive quality management must include preventive digital quality controls. Today's conventional continuous improvement and visual quality management methods can't cope with these new challenges, as illustrated by the fact that more than 30 percent of warranty cases today result from electrical and electronic components.

"Quality-to-market" is an innovative approach for assuring the reliability of highly complex electronics- and software-driven technologies. Its core philosophy is that quality ultimately drives time and cost considerations. It focuses on areas such as start-of-production delays and overspending on deliveries, engineering and manufacturing, as well as reliability issues and warranty claims.

Automakers and Tier 1 suppliers have always focused on the quality of products and systems, but time and cost issues have dominated their processes and the decisions made in executive boardrooms.

Quality organizations, on the other hand, have concentrated on single problems or the provision of methodical support. To establish a balanced link among quality, time and cost, companies need to shift to quality-to-market as a guiding management paradigm, which covers the entire extended supply chain.

Research reveals that the number and proportion of software-related recalls in the U.S. has increased steadily — unmistakable evidence that the auto industry is not ready for this rapid influx of technology. The complexity involved in embedding new technologies in existing vehicles has raised new challenges. Consequently, companies need to adjust the new processes involving digital quality controls, technical risk management and quality predictive systems.

Transitioning to this new paradigm will require a fundamental change in mindset that enables the company's central quality function to perform as a neutral authority, delivering a transparent and traceable quality control "dashboard."

One example would involve the collection of field failure data into a common structure in a "data lake" to classify failure patterns or other algorithms, enabling companies to solve technical problems faster.

A collaborative and fully transparent supplier management approach will help companies identify and resolve bottlenecks faster. Organizations will be able to map product field and production data directly to new product development cycles, enabling engineering to make better, smarter and more cost-efficient decisions.

The quality-to-market approach redefines the quality department's traditional role in the digital age. But moving to this paradigm will require significant changes in roles and responsibilities.