In today’s Industry 4.0 environment, digital solutions and data are becoming critical aspects of the product life cycle. Understanding your product, quantizing its characteristics, then iterating and improving your design approach are key to staying a step ahead of the competition and exceeding your clients’ expectations.
Digital twin technology is an emerging innovation that’s helping manufacturers to iterate and improve on their products at every stage of the product life cycle, from ideation and design to long-term maintenance. What are digital twins? They’re physically accurate digital representations of your physical products. IoT devices attached to a real product in physical space collect data across parameters to build a digital twin that performs and reacts to forces in exactly the same way as its real-life counterpart.
At 4D Systems, we offer Siemens and Dassault Systemes digital twin products. Both of these best-of-breed digital twin solutions can help you develop, build, iterate, and maintain products faster, cheaper, and more intelligently. In this article, we’ll be looking at some of the key opportunities Dassault and Siemens digital twin solutions have to offer.
Digital twins help optimize every stage of the product lifecycle, allowing you to build out new products faster and cheaper than before. The benefits of our Siemens and Dassault digital twin solutions start from the ideation and prototyping phase.
Physical prototypes are expensive to manufacture and replace, take time to make, and can’t always be subject to a full range of testing. Physical prototyping constrains the design team by making it harder to fail fast: building testing, and iterating on a failed prototype can take weeks or months, stretching development cycles, and adding to costs.
Digital twins can transform both product and process design. First, leverage a solution to build a physically accurate digital twin of your product. Then, you can test out product iterations in digital space to identify tolerances, weak points, and design flaws.
Solutions like Tecnomatix Process Simulate can help you do the same thing for specific parts of your manufacturing process. You can import models, specify parameters in your production process, validate robot actions, and more.
Digital twins enable a rapid iteration loop, with testing, development, and improvement taking place in a matter of days. Physical prototyping still has its place: key milestone builds can be physically prototyped. But digital twins allow the design team to assess the impact of tweaking minor parameters, paving the way to optimal product design.
Fewer physical prototypes and a faster turnaround time can potentially save thousands of man-hours, in terms of time and development costs. These costs can be passed onto clients, allowing you to deliver better solutions with quicker turnaround, for cheaper.
Great products don’t just deliver at the point of sale. When clients invest in your products, reliability and long-term value are key priorities. Aftersales maintenance forces clients to make a tough decision: either operate a product until component failure — which can increase downtime — or replace parts early, increase costs.
Manufacturers typically rely on the preventive maintenance paradigm to mitigate risk and manage maintenance costs. Preventive maintenance relies on the useful life estimate, a metric that describes the average lifespan of a particular component, the point at which the component has a roughly 50 percent chance of failure. The issue with preventive maintenance is that, statistically, there’s a high likelihood that any given component could last slightly longer or slightly shorter than the useful life estimate. More granular data, including data about the product’s operating environment, could help get a more accurate picture about their specific maintenance needs. This is where predictive maintenance solutions like Dassault 3DExperience comes into the picture.
According to a Deloitte study, the predictive maintenance paradigm can extend an asset’s lifetime by 20 percent and reduce costs by upwards of 12 percent. These long-term benefits extend across the entire life of a product, increasing its value manifold.
What exactly is predictive maintenance, though? Predictive maintenance involves using digital twin technology to identify long-term stressors and weak points in your products, across a range of operating environments and parameters. By modeling the effects of different stressors on digitally twinned components, you can fine-tune estimates for component life span. This can help customers optimize their maintenance cycles, saving down-time, and costs.
Enterprise sales cycles are long and clients require proofs-of-concept and capability demonstrations. Physical PoCs and capabilities demonstrations can be expensive and high risk, especially in earlier stages of the sales cycle. How can manufacturers demonstrate product excellence while managing development costs?
Digital twin solutions offer manufacturers the opportunity to develop virtual PoCs and showcase product functions and capabilities to clients right at the first or second meeting. Digital twins can be built to spec, perfectly aligned with client requirements. Once the sales conversation has started in earnest, they can be used as a blueprint to build real, physical PoCs and prototypes. By taking complexity and cost out of the equation, digital twin technology allows sales teams to spread their wings, reach a wider client base, and get more projects in the pipeline.
As leaders in the PLM space, 4D Systems helps clients optimize every stage of the product lifecycle. Our digital twin solutions help cut costs, increase flexibility, and enhance R&D capabilities. In a rapidly changing manufacturing environment, 4D Systems’ digital twin products can help you stay a step ahead, exceed your goals, and align your approach with Industry 4.0 best practices.
Reach out to us at 800-380-9165 to chat about driving transformation at your manufacturing facility.