California Gold Rush and Vehicle Platform Design Strategy

By Automotive, Manufacturing No Comments

Product companies employ platform-based design strategy to simplify design, reduce cost and accelerate time to market of new products. In the automotive industry, a platform represents a set of common design, engineering, and production systems that is used to build any number of distinct models, all based on the same underpinning but are visually entirely different.

Not a new concept, a platform based portfolio is practiced more aggressively and consistently as of late. In response to growth opportunities in global markets, automakers design and manufacture cars tailored to narrow markets and demographics while minimizing the effort and cost of designing and manufacturing parts for each market variant. Ford Motor and Volkswagen are two car manufacturers exercising this strategy most diligently. See a detailed, if incomplete, list of badged models and the platforms they are built upon.

I recently learned that design and manufacturing concepts emphasizing design commonality can be found dating back to the California Gold Rush period, long before Henry Ford introduced in 1913 standardization of parts and manufacturing process that formed the cornerstones of the assembly line.

John “Wheelbarrow Johnny” Studebaker made a small fortune making sturdy wheelbarrows for California gold miners. In 1852 he returned to his home in South Bend, Indiana, to join his brothers in the Studebaker Wagon Corporation that supplied wagons for the Union Army. According to the Seeley Stable Museum in San Diego, by 1868, the company had standardized many common wagon parts to accelerate production and keep prices down. Studebaker also created designs for regional customer needs, such as the “Concord Steel-Axle California Wagon” that was developed especially for the western trade.

By the turn of the century, the Studebaker Corporation entered the new era of ‘horseless carriages’, manufacturing gasoline powered cars and, for a short period, electric cars. Here, again, Studebaker did not follow the common approach of vertical integration and put Studebaker bodies on gasoline-powered chassis purchased from another company.

(Image source: Bar E Ranch)

Design Reuse: Reusing vs. Cloning and Owning

By Design Reuse, Manufacturing, PLM One Comment

Reusing vs. Cloning and Owning

As I am preparing for my presentation and panel discussion at the Product Innovation Congress in San Diego next week, I am speaking with colleagues and experts in all things PLM. I recently spoke with Charlie Krueger from BigLever on product line engineering (PLE) and how some organizations and individuals practice design reuse.

We often encounter instances in which the engineering team makes use of an existing design or an inventory part in a new product. They assign it a new part number and sometimes a new name, and move it to the new system’s bill of materials (BOM), and from that point onward the part start a product lifecycle of its own. Charlie terms this approach “cloning and owning.”

Obviously, that’s not what we mean when advocate design reuse.

In a recent blog on design reuse I discussed the importance of reuse not only for the more obvious and better understood reasons such as accelerating time to market and reducing inventory costs but, more significantly, for the ability to reuse design, manufacturing and service knowledge associated with these physical objects.

If commonly used and shared parts and subsystems carry separate identities, then the ability to share lifecycle information across products and with suppliers is highly diminished, especially when products are in different phases of their lifecycle. In fact, the value of knowledge sharing can be greater when it’s done out of sync with lifecycle phase. Imagine, for example, the value of knowing the manufacturing ramp up experience of a subsystem and the engineering change orders (ECOs) that have been implemented to correct them before a new design is frozen. In an organization that practices “cloning and owning”, it’s highly likely that this kind of knowledge is common knowledge and is available outside that product line.

An effective design reuse strategy must be built upon a centralized repository of reusable objects. Each object—a part, a design, a best practice—should be associated with its lifecycle experience: quality reports, ECOs, supplier incoming inspections, reliability, warranty claims, and all other representations of organizational knowledge that is conducive and critical to making better design, manufacturing and service related decisions.

  • Organizations should strive to institute a centralized product management strategy that consolidates and exploits PLM and PDM data, ERP systems, and, in all likelihood, a myriad of informal and unstructured emails and spreadsheets.
  • To maximize the value of design reuse, information must be shared across product lines independent of the lifecycle phase of each product. In particular, incorporate late-stage knowledge such as service and warranty information in design decisions of new products.
  • Effective reuse would benefit from the ability to decompose system architectures differently. In addition to structuring product information using traditional engineering and manufacturing BOMs, encapsulating and organizing information by feature families and configurations, such as in the methodology behind PLE, is highly effective, especially in complex product architectures.

Wisdom of Things

By Internet of Things (IoT) No Comments

On a recent Internet radio show I discussed the potential business value of the Internet of Things (IoT) and my views about the accelerators and, the more critical, inhibitors to the evolution of this much advertized concept.

Wisdom of Things

The potential value of the IoT is not in the ability to connect and access remote devices via the Internet. It is in the information gathered and shared by a large number of connected devices in a meaningful fashion that provides a new business value, new business models. To borrow a phrase from social networking, in Wisdom of Crowds, connectedness (in this case among people) enables new value; think of the Internet of Things as facilitating the “Wisdom of Things.”

In his book The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations, James Surowiecki argues that the aggregation of information in groups results in decisions that are often better than could have been achieved by any individual member of the group. Truth be told, I am not a big fan of the Wisdom of Crowds theory when it comes to people. But I do believe that the collective information stemming from multiple information producers: sensors, measurement devices, decision support systems and, yes, to some extent, people, can be aggregated to improve decision making and extract greater business value.

IoT narratives often talks about smart connected devices. Some devices, from factory robots to home thermostats are designed to have localized decision making capabilities, and could be considered smart. But many other devices are not much more than connected sensors, for example the Fitbit personal activity tracker or even the proverbial IoT refrigerator that notifies the homeowner to add milk and eggs to the grocery shopping list.

The true “smarts” of the IoT does not happen at the individual device level.  It is a result of aggregating data from multiple heterogeneous devices, both “smart” and “dumb”, and is therefore available and discoverable at the edge of the network.

Conduit vs. Content

The concept of “Wisdom of Things” leads to another observation about the Internet of Things. The potential impact of the IoT is much less a function of how many things are connected and how, but rather it is in exploiting the information they share. In other words, new business models need to focus not on the IoT “pipes”, or the conduits, but rather on the content that flows through them.

Therefore, I do not consider remotely accessible devices in a manner that until recently we used to refer to as machine to machine (M2M) communication as being synonymous with the IoT. M2M applications have been shown to provide tangible and meaningful value, but they tend to focus on individual devices and narrow domains and not on the aggregation of heterogeneous information to gain deeper insight into more complex decision-making domains.

If we accept the notion that IoT business models are predicated on information aggregation, then we begin to better understand and address the barriers to maturing from M2M to IoT, to realize the business impact of the IoT.

 

Stratasys Acquires GrabCAD

By Manufacturing, Mergers & Acquisitions No Comments

Stratasys Acquires GrabCAD: Analysis and Implications

3D printer company Stratasys announced today of definite plans to acquire Cambridge, Mass.-based GrabCAD. GrabCAD is known for spearheading efforts to create an “open engineering” environment that allows engineers to share 3D CAD models. Terms of the transaction were not disclosed, but the price is estimated to be about $100 million. This is the latest in a string of acquisitions by Stratasys. Previous notable additions include MakerBot last year for $403 million and Solid Concepts earlier this year for $295 million. GrabCAD co-founder and CEO Hardi Meybaum will continue to head GrabCAD within the Stratasys group operations.

Since its launch in 2010, GrabCAD has amassed a user base of 1.5 million mechanical designers and a database of 520,000 3D CAD models, ranging from novelty items and toys to guns to complex models of gearboxes and 5-axis CNC machines. However, revenues of the venture-backed company did not track this trajectory. Read More

The Emergence of Application-Specific IoT

By Internet of Things (IoT) 4 Comments

General IoT vs. Application-Specific IoT

2014 Gartner Hype Cycle Special Report

2014 Gartner Hype Cycle

Gartner recently published the 2014 Gartner Hype Cycle Special Report, which evaluates the market perception and penetration for over 2,000 technologies, services and technology trends. Of particular interest to many was the placement of the Internet of Things (IoT) at the top of the Peak of Inflated Expectations. Gartner defines the Peak of Inflated Expectations as: “Early publicity produces a number of success stories—often accompanied by scores of failures. Some companies take action; many do not.”

And, indeed, inflated market size forecast and grandiose visions of IoT reign supreme. Morgan Stanley forecasts that by that by 2020 there will be75 billion connected devices, whereas Harbor Research estimates the same market will consists of a meager 8 billion connected devices. Gartner estimates that by 2020 there will be 26 billion connected devices, IDC counters that with 30 billion connected devices, Cisco says 50 billion… you get the picture.

Do you think they really know? The typical rationale offered by industry analysts is that they use different market and technology taxonomies, hence the vast differences.

On the other hand, does it really matter that much? Read More