Digital Product Twin
Continually optimizing services and products through digitalization
Surging digital development is spurring industrial and manufacturing companies on in their pursuit of digital transformation, its cost savings and optimization potentials. Their success hinges on guaranteeing competitiveness and setting themselves apart from the competition.
To do this, businesses are commonly providing customer service around a product – as opposed to the products themselves, which often have too similar a range of features to one another or are simply interchangeable. Managing these services isn’t proving straightforward though. It is proving difficult for businesses to keep atop of the rapid changes taking place while still ensuring their investments are worthwhile.
On the one hand, customers expect better, constantly evolving products that are perfectly aligned with their needs. They expect them now, but businesses are still playing catch-up with product emergence and time to market.
On the other, customers are considering whether, in the future, they should buy products at all, or simply invest in their service and performance via new subscription or usage-based payment models.
There’s more. Implementing new tech and processes is a complex task but going further there are even greater hurdles: understanding everything that helps form and hone a product – such as machines, tools, usage patterns and product feedback – then being able to optimize and build new services around them.
Millions of potential data points need to be traced, harmonized and presented in an accessible, centralized way. Additionally, the mindset must change towards customer centricity and intimacy to establish new customer touchpoints that better understand their needs – a difficult prospect for even small businesses.
Only once these challenges are overcome can businesses unlock the significant benefits of Industry 4.0 and beyond, but thankfully there is an encompassing solution. Developed to meet the needs of industry and manufacturing, Digital Product Twins are revolutionizing product development, manufacturing, maintenance and customer service, bringing businesses to a level at which they can successfully differentiate and compete.
A Digital Twin is a digital replica of a living or non-living physical entity such as a product, machine, piece of production equipment or simply an individual digitized component. They bridge the digital and physical worlds, allowing the seamless bi-directional exchange of real-time data so that digital replicas exist simultaneously with their physical entities.
Each digital representation provides the elements and dynamics of how smart products operate throughout their lifecycles. This means digital twins pass through the same stages of the product lifecycle as real, physical products would (design, manufacturing, delivery and customer operation, to after-sales and service), allowing a step-by-step approach to digitization to be formed.
Depending on the manufacturer and the kind of products they produce, there might be thousands – if not millions – of physical products in the field, all sending a real-time stream of precise data back to manufacturers, easily accessed through sensors attached to the product and IoT-enabled connections such as service platforms. This Industrial Internet of Things (IIoT) approach allows transparent, quick and effective analysis of the usage phases of an asset’s lifecycle.
Within the service platform, artificial intelligence models can also be incorporated, allowing equipment and product issues to be quickly identified, but also predicted. These bespoke AI service models enable smart, optimized maintenance; cost reductions; and the establishment of future-oriented, data-driven and customer-oriented service models.
With such a wealth of product usage, condition and environmental data, digital twins can be adapted without impacting the physical entity they represent. Quality and usage data can be incorporated and used to ensure optimizations are valuable, before then, finally, changes are made in the physical world. This approach reduces the risk of innovation impacting engineering, accelerates the continuous improvement process, shortens time-to-market and cuts product emergence process costs.
Service, maintenance and product emergence processes, spare parts, service ordering, order fulfillment: whatever the operation, if issues occur, Digital Product Twin can track them, providing significant benefits for the entire business.
Digital Product Twin affords predictive and prescriptive maintenance, predictive quality control, condition monitoring, horizontal alignment, horizontal and vertical integration, and the combination of different tools along the entire product lifecycle (design to dismantle or turnaround) and real-time data to monitor assets and contextualize failures.
In doing so, it tackles issues such as unexpected breakdowns, interruptions, premature wear of components, scheduled mandatory servicing and maintenance, and the identification of quality issues under specific use conditions. This reduces costs, ensures the most efficient planning and use of resources and guarantees satisfied customers and perfect product performance.
Additionally, by aligning service and spare parts processes, the risk of planning-dependent process disruptions and the occurrence of unscheduled service dates are also both reduced, all while asset and product efficiencies are improved by orders of magnitude. This results in operational and service planning requiring less human input, drastically improving productivity.
Although Digital Product Twins have only recently begun to be implemented, BearingPoint has used them (or parts of them) to transform several leading businesses.
A global wheelmaker wished to reduce its levels of unplanned downtime and the associated increase to production costs, delivery delays and the impact on its competitiveness. Our experts implemented edge computing and cloud infrastructure to collect machine data – accessible via a condition monitoring dashboard and used to create a predictive maintenance AI model. The cost-efficient approach led to a marked decline in downtime and improved the efficiency of the business’ maintenance services.
Our approach also helped a robotics and automation company break down barriers to digitalization. Together we implemented a wide range of solutions that harmonized the business’ customer and vendor maintenance processes, end to end.
This mass standardization enabled efficiency and cost savings, internal and external stakeholders could better collaborate with new tools, and both up and downstream ERP provided the basis for better-integrated engineering processes. These steps, plus a new digital governance model, provided a robust foundation for the next step of the client’s digital journey.
The optimization of processes is another key benefit of the Digital Product Twin. For a global elevator and escalator manufacturer, we developed sensor kit hardware that was rolled out across over 300,000 of the company’s elevators located around the world. Connected with a remote monitoring and predictive maintenance platform via the cloud, the IoT solution was able to provide maintenance alerts and information on equipment health.
Following this, BearingPoint created a global service excellence platform for the client that brought together product, supplier, ERP, field management, call center and customer data into a single, connected digital ecosystem. Accessible via mobile apps and dashboards designed to meet the specific needs of customers, call center workers and field technicians, the solution allowed the manufacturer to provide a fast, seamless customer journey, as well as win several digitalization awards.
These applications show just how integral Digital Product Twins are to business’ digitalization efforts, laying the groundwork that allows businesses to take advantage of new developments such as autonomous production. For any future-focused company, it’s imperative they’re quickly adopted.