PLE and the Birth of the Digital Twin

Michael Molitch-Hou posted 2017-09-07

Necessary to the evolution and proliferation of the digital twin are the software tools that make it possible to track and manage this digital copy of the physical product. Businesses are increasingly familiar with product lifecycle management (PLM), product data management (PDM) and other related technologies. They may be less familiar with product line engineering (PLE).

While PDM aims to manage a product and all of its associated information and PLM manages

that product across its lifecycle, PLE streamlines the management of product variation across an entire product line, and across an enterprise. And, whereas PDM and PLM are needed to manage the digital side of the digital twin, PLE is, in some ways, the place where that twin is born.That’s a strange thing to say, but it’s also an interesting perspective on both the concept of the digital twin and PLE. To learn more, ENGINEERING.com spoke with Dr. Charles Krueger, CEO of BigLever, a PLE company with prominent customers that include Lockheed Martin, General Dynamics, a major automotive manufacturer, and more.

The Concept of the PLE Factory

The traditional method for designing a family of products involves a disparate set of development teams within an organization. Each team will set about working on its specific product, and each feature that product contains, and will communicate with other teams when necessary to share assets and information.

When this method is applied to, say, the work of creating a line of cars, you might imagine different product teams working on the standard model, the deluxe model and the luxury model. Although the luxury team might be installing a steering assist mechanism and Apple CarPlay, many of the vehicle’s features will be the same as those installed in the other two models.The luxury team will then have to reach out to the other product engineering team to request the assets and information associated with those features for its own design work. The deluxe and standard teams have to do the same as well. As the product line grows, the complexity of managing all the products in the product line grows, exponentially.

With PLE, all of the assets for a product line are poured into BigLever’s Gears configurator, which uses features associated with each product to create the product line portfolio. (Image courtesy of BigLever.)

Rather than deploy redundant efforts to develop different products, PLE seeks to eliminate the redundancy and reduce the chaos by taking advantage of what’s common across all members of the product family.

Gears from BigLever

BigLever’s approach to PLE involves automating the process of assigning a product family’s digital assets to the products within that family, based on features. Using the company’s Gears PLE Lifecycle Framework, users can select which features (referred to as a bill of features, or BOF) will be assigned to a given product within a family. Once selected, the digital assets associated with those features will automatically be included in that product. These include assets like requirement management, design models,bill of materials (BOM), software source code, user documents, test cases, calibration data, certification documents, and more.

In Gears, you can see the feature options for power door locks in a vehicle laid out as a feature tree. Some features can be selected, others can be made the default for a product line, and others have further options from which to choose. For instance, the digital keypad for a door lock has an integer setting that allows multiple digits to be included in the keypad. (Image courtesy of BigLever.)

Krueger explained that Gears is agnostic when it comes to the tools already in place by organizations to manage their products. “They’re not interested in us asking them to change their preferred toolset in an engineering organization,” Krueger said. “So, we don’t replace tools. We augment existing assets and tools that people already know and love.”

Here you can see various products in a family and their associated BOF. The basic model of the line only features a basic key cylinder (the little plastic tube that pops up when the car is unlocked). The premium plus model has a digital keypad. (Image courtesy of BigLever.)

In the video below, starting at about minute 40, you can see how Gears works and how it integrates with model-based engineering (MBE) software MagicDraw from No Magic. The demo illustrates how the locking features of a car can be determined for various products within a product line by going through the feature catalog and selecting such features as autolocking, after the vehicle reaches a certain speed; a plastic cylinder or LED light to indicate that the doors locked or unlocked; whether or not a standard metal key or a key fob is used to unlock the door; and so on.

Once selected and saved as a profile for a specific product in the family, say, the standard or luxury model, a simulator generates what these options would look like for an actual car. Represented by photos that animate upon mouse click, the simulator allows the user to ensure that the proper BOF was selected.

On the left, you can see that the simulator has created a visualization of the basic model, with a simple cylinder lock and metal key entry. On the right, the premium plus model has a key fob, five-digit key entry, an LED instead of a cylinder, and push-button ignition. (Images courtesy of BigLever.)

The BOF can then be opened in a tool like MagicDraw, where all of the necessary MBE data would be carried over. The same would be true for other software tools. For instance, Gears would be able to connect the necessary BOM data for PLM software, CAD data would be available for use in CAD software, and so on.

Here you can see the data associated with the BOF brought into MagicDraw. (Image courtesy of BigLever.)

You can imagine that for a given manufacturer, the feature catalog can become quite complex. BigLever works with its customers to provide strategic guidance and assistance in defining the feature catalog and establishing an operational PLE factory that is tailored to each customer’s organization, situation and needs.

PLE and the Birth of the Digital Twin

With the concept of the digital twin, we imagine a physical product out in the world that, using IoT sensors and big data, informs its digital replica maintained by the manufacturer. This digital replica contains not just CAD models and associated simulations, but all of the necessary manufacturing information that goes along with it.

Before we can even reach that stage, according to Krueger, we would need PLE. Using the automotive example again, Krueger said, “In the automotive world, you may have tens of thousands of different configurations of automobiles based on options and variants. In order to understand if a safety recall applies to a particular vehicle, we need to understand precisely what’s contained on that vehicle.”

Before the vehicle is manufactured and a digital twin is created, it is necessary to know what features make up that vehicle. To do that, one would have to return to the BOF, which was created in the PLE factory. “All of your requirements and design information and part selection—all of the digital assets relevant for a particular product—everything is being driven by this bill of features,” Krueger said.

The BOF for products are fed into the Gears Product Configurator, which makes it possible to create digital twins of each product. (Image courtesy of BigLever.)

In this way, the BOF is like the original DNA of every product and every digital twin that is subsequently made. The BOF for the standard model of a vehicle is used for every single standard car that leaves the factory and heads onto the streets. It also forms the basis for all of the data that goes into the digital twin associated with that car.

A powerful real-world example of this concept in action is illustrated by General Dynamics, a BigLever customer and number six defense contractor for the U.S. military, which leverages PLE for its live training systems product line. PLE allows General Dynamics to more easily and rapidly deploy new variations, refinements, and enhancements to its training systems, so it can address changing missions and threats with much greater efficiency.

These simulated combat and training systems are shipped to remote areas where the U.S. Army is conducting simulated warfare. To get the systems to these locations, General Dynamics ships train carloads of equipment tothe field. The worst thing in the world for these simulation scenarios would be for them to be missing a part in the middle of nowhere.

To simplify this complexity, General Dynamics organizes the entire product line with BigLever’s software, managing part deployments and tracking those deployments as a form of the digital twin. With the features of each product, such as a specific training scenario, first determined from the BOF created in Gears, it’s then possible for General Dynamics to replace parts or upgrade software within the entire product line or in individual instantiations of the product in the field.

General Dynamics’ war simulation products are managed as part of a product line, which enables better tracking of usage and quality control (Image courtesy of the U.S. Army, General Dynamics and BigLever.)

Krueger explained how PLE is particularly useful in the case of an automotive product recall. Where as it may be easy to track a mechanical part that is responsible for a product failure in many cases,as technology evolves, determining the exact cause of a failure and its resultant effects will require better management through PLE.

“Imagine an autonomous vehicle that notices you’re drifting out of your lane and nudges your steering wheel to bring you back into the lane,” Krueger said. “Those kinds of features impact sensors, actuators, radar, software and electronic steering. A feature of that type could involve hundreds of parts. If there’s a problem there, understanding vehicle defects in them, is more than just tracking your mechanical parts made by a particular manufacturer. It’ll be necessary to tie back to this single notion of a feature, as the differentiating characteristic.”

The State of PLE

BigLever was established 16 years ago, but Krueger has been in the field for over 20 years. As a prominent figure in the space, he is actively involved in not just innovating PLE technology, but also in ensuring its adoption through the establishment of best practices and standards.

As with all new concepts, PLE may be difficult to understand when an organization is initially introduced to the topic. To help the world at large make sense of it, Krueger has been involved in the development of International Organization for Standardization (ISO) standards for PLE, as part of an initiative sponsored by the International Councilon Systems Engineering (INCOSE).

With the team assembled about a year ago, the ISO group for PLE has written its first draft of the standards, which is now being reviewed by the international community. This community will, according to Krueger, “contribute and agree to a well-thought-out, concise, simple, clear, unified description of what Feature-based PLE is – the best practices for achieving PLE success.” He also sees PLE being adopted more widely, not just by an increasing number of organizations, but also across entire organizational bodies.

“Over the last two years, entire enterprises and presidents of large corporations are saying that they see the benefit with PLE on their programs and applying PLE across the entire enterprise,” Krueger said. “We’re seeing now enterprise initiatives, as opposed to just individual engineering initiatives. This comes as a very strategic, competitive advantage that executives are going after.”

When you consider the concept of PLE, a method for engineering entire product lines by considering the features they share in common, it seems logical to adopt the approach as a strategic practice within a business. Now that entire enterprises are starting to do so, we may begin to see what that looks like more and more.