Autonomous Driving (Popular Mechanics)

Software Behind the Wheel: How Software is Driving the Auto Industry into the Future

By | Automotive, PLM | One Comment

It’s Not Your Father’s Oldsmobile

Automakers have been keeping a steady pace of technology innovation and manufacturing excellence for over a century. Since the big industrial breakthrough of the highly efficient assembly line, auto manufacturers continue to design and manufacture cars that are successively better, safer and cleaner. For many decades, the industry has been at the center of the US economic development, and, to many, a social icon.

But more recently, over the past decade or so, the iconic and seemingly stable industry has been in turmoil. It has been undergoing massive changes caused by the cumulative effect of rapid technology innovation, disruptive business models, new competitors, and emerging supply chain ecosystems whose full impact is not fully comprehended yet.

One of the most profound changes the auto industry is grappling with is the emerging notion of connected and autonomous cars. Most industry visionaries and practitioners portray a bold vision of a future in which cars, occupants, and cloud-based information and control systems communicate and exchange information in an omnipresent Internet of Things cloud. Cars are becoming part of the Internet, or, in today’s parlance, they are yet additional “things” in the Internet of Things (IoT). Read More

Section perpendiculaire du moulin des Verdiers (Jean-Jacque Lequeu, 1778)

PLM as an Innovation Platform

By | PLM | No Comments

The Promise of PLM

A recent discussion titled Dassault Systèmes Bets Big on a Product Innovation Platform argues that the role of a PLM platform is to bundle different data sources and enable smooth data exchange among tools, processes and users. While not incorrect, this view is potentially limiting.

File and data interoperability, single source of (electrical/mechanical/software) truth, hardware/software development synchronization, and similar notions have been the core principles of PLM for quite some time; some, in fact, for a very long time. How well PLM vendors achieve these goals is a topic for a separate conversation. Read More

Steam Shovel in front of Hollywoodland Sign (C. 1925)

Caterpillar: Smart Iron Delivers Customer Value

By | Automotive, Telematics | No Comments

From Product Promise of the Past to the Promise of the Future

In the pre-digital revolution economy, products were defined by features and technical specifications that product marketers and designers believed were important to customers. Product companies enumerate technical specification and delineated contract terms to which they promised to adhere.

In the digital era, the product promise of the past is quickly transforming into the product promise of the future, in which the competitive edge is achieved not by technical specifications but rather by the ability to help customers realize meaningful business outcomes.

The key to success in the era of the pervasive digitalization and ubiquitous connectivity the of the Industrial Internet of Things is to shift the product strategy away from tightly controlling products and supply chains, and waging price wars aimlessly and in vain, to focusing on delivering and measuring customer value. Product thinking must shift from inside the company to customer value and a dynamic, interconnected, and collaborative ecosystem that continually aligns and realigns itself around worthy innovation

In my book The Outcome Economy: How the Industrial Internet of Things is Transforming Every Business I pose a challenge to industrial manufacturing companies: “The question that remains is: will your organization be a leader in pursuing the promise of the future, or be a footnote in the annals of the past?”

One company that is at the forefront of realizing the product promise of the future is industrial equipment manufacturing giant Caterpillar. Read More

The Persistence of Memory

Teaching Self-Learning Machines to Forget

By | Internet of Things | No Comments

Many tasks in which humans excel are extremely difficult for robots and computers to perform. Especially challenging are decision-making tasks that are non-deterministic and, to use human terms, are based on experience and intuition rather than on predetermined algorithmic response. A good example of a task that is difficult to formalize and encode using procedural programming is image recognition and classification. For instance, teaching a computer to recognize that the animal in a picture is a cat is difficult to accomplish using traditional programming. Read More

Time Warp (Mike Gambino, 2011)

Autonomous Vehicles: Slow Down to Go Faster

By | Automotive | One Comment

Reprioritization of Autonomous Vehicles Development is Needed

Everyone is in the self-driving car race. Google has been developing autonomous driving capabilities since 2009 and continues to demonstrate incremental improvement in its autonomous driving technology since. By 2012, Google’s fleet has logged 300,000 self-driven miles. Tesla’s AutoPilot, another household name on the driverless car stage, has logged nearly 250 million miles of hands-free driving. Delphi’s Roadrunner completed a nearly 3,400-mile cross-country trip, 98% of it in self-driving mode.

Fearing the perception of falling behind in the race to take the checkered flag, practically all major automakers and suppliers are investing heavily in self-driving technologies and are very vocal telling their own bold vision of crash-free, stress-free traffic. And if you are a car executive who doesn’t dream big enough, you are out! Read More