Mass Customization of Personalized Digital Products

With digital technologies such as artificial intelligence, mixed reality, 3D printing and more, manufacturers can respond to customer demands in real time.

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A key challenge facing automotive and industrial equipment manufacturers is keeping pace with growing demand for customized, digital products and services. Combining a range of today’s new technologies in the product engineering process can help them drive personalization and innovation in their products and services, according to Accenture Labs.

These digital technologies include artificial intelligence (AI); edge intelligence; extended reality, which includes augmented, virtual and mixed reality; analytics; embedded sensors; and 3D printing capabilities. Applying them to automotive manufacturers’ and OEMs’ product engineering phases—including conception, design, prototyping and simulation—makes possible mass customization of constantly evolving products.

For example, a smart automobile seat tailored to personalized preferences could be more efficiently created using the voice of the customer and AI learning and problem-solving capabilities at the conception stage. This would reduce cost and time-consuming research and analysis. In the design stage, a 3D holographic presence generated by extended reality technologies could enable the product to be manipulated and developed virtually, moving it more rapidly to prototype and simulation. AI and embedded sensors in the prototype and simulation stages could generate real-time intelligence to optimize the usage, flexibility and comfort of the seat. Moreover, such intelligence offers a blueprint for developing additional tailored products.

Striving to enhance the ability of industrial manufacturers to continuously accommodate demand for new, personalized experiences on a mass customization scale is part of Accenture’s Industry X.0 (IX.0) approach. IX.0 focuses on helping companies extract the full value of digital technological advances. This approach is setting the stage for a new era of manufacturing, where mass customization—enabled by intelligent, connected products that learn and adapt to their environment and changing customer preferences—will play a major role.

Engineering success

Here are some real-world examples of how industrial manufacturers today are leveraging multiple technologies throughout their product engineering phases to move closer to industrial-grade mass customization:

  • From concept: To improve its electric vehicles in real time, Tesla is already leveraging customer input and embedded sensors. The company gathers data from sensors inside customers’ vehicles to monitor driving patterns and driver reactions to road and traffic conditions. It also tests its latest autonomous software by remotely installing it on vehicles.
  • To design: Employing virtual 3D technology, Accenture Labs recently collaborated with a customer to build a complex, industrial digital breaker box. Engineers can view the breaker box as a hologram, use gestures and voice input to pull out individual components, inspect and view them from different angles, reassemble them and, once they are correctly configured, move on to simulation and prototype. All of this can be done while collaborating with colleagues remotely, simulating amps through the virtual breaker box to determine how effective the product would perform in the real world.
  • To prototype: Converging AI and 3D printing can have breakthrough benefits at the prototype phase. For instance, Nike applied generative design, an AI technique in computational design for modeling, to remove excess weight in Olympic athletic shoes. Software assimilated the goals of the project; then, feeding project data into an algorithm, the company’s engineers used 3D-printed prototypes in the simulation phase, repeatedly testing them until the optimal design was achieved.
  • To simulation: In addition to the Nike example, manufacturers in other industrial sectors are innovating in the simulation phase. For instance, in the consumer goods space, companies are experimenting with overlaying analytics and mixed-reality technologies on physical shelves to simulate product displays and optimize them for better space planning and improved customer uptake. Such concepts can be taken from the lab to the store for real-world simulation.

Taken together, connected products, whether part of the automotive, OEM or other industrial spaces, are becoming data points for automating the design of new products and services and modifying those in customer use in real time. Companies will need to take advantage of this shift, combining multiple technologies to master mass customization and capitalize on personalized product and service demand.

>>Brian Irwin, brian.irwin@accenture.com, is managing director, automotive and industrial, North America, and products Industry X.0 consulting, for Accenture.

 

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