Companies lack an understanding of their products - the key to developing their true potential
Rapid digital development is driving industrial and manufacturing companies to pursue digital transformation, cost savings and optimization potential. Their success depends on their competitiveness.
In order to do this, enterprises usually provide customer service around the product - contrary to the product itself, the product itself often has a series of functions that are too similar or just interchangeable. But it turns out that managing these services is not easy. It is difficult for companies to keep pace with rapid changes while ensuring value for money investment.
On the one hand, customers expect better and developing products that fully meet their needs. They want to have it now, but companies are still trying to catch up with product realization and time to market.
On the other hand, in the future, customers will consider whether they should buy products or invest in their services and performance only through new subscriptions or usage based payment models.
Service management is not the only challenge facing the industry. Technological innovation and investment are surging, bringing a lot of solutions and improvements, enabling the integration of digital and physical products. However, selecting, implementing, and integrating new devices, business models, and it systems is a complex task, as companies deal with a variety of solutions from multiple vendors that operate in different ways. In addition, integration components must be implemented in a mix of modern and traditional it and ot.
Implementing new technologies and processes is a complex task, but there is a bigger obstacle to going further: understanding everything that helps to shape and refine a product - such as machines, tools, usage patterns, and product feedback - before you can optimize and build new services around them.
Millions of potential data points need to be tracked, coordinated, and presented in an accessible, centralized way. In addition, the mindset must shift to customer-centric, creating new customer contacts to better understand their needs - which is difficult for even small businesses.
Digital product twins: support includes new digital services and intelligent products
Only by overcoming these challenges can enterprises obtain significant benefits from industry 4.0 and beyond. Fortunately, there is a comprehensive solution. Digital product twins is developed to meet the needs of industry and manufacturing. It is revolutionizing product development, manufacturing, maintenance and customer service, enabling enterprises to differentiate and compete successfully.
Digital twins are digital copies of a living or inanimate physical entity, such as a product, machine, production equipment or just a single digital component. They connect the digital world with the physical world, allowing seamless two-way exchange of real-time data, so that digital copies coexist with their physical entities.
Each digital representation provides the basic principles and dynamics of how intelligent products operate throughout their life cycle. This means that digital twins will go through the same stages of the product life cycle, just like real physical products (design, manufacturing, delivery and customer operation, to after-sales and service), allowing for the gradual formation of digitization.
Depending on the manufacturer and the product they produce, there may be tens of thousands - or even millions - of physical products that send accurate real-time data back to the manufacturer and easily connect to service platforms such as products and IOT enabled connections via sensors. This industrial Internet of things (iiot) approach allows transparent, fast, and effective analysis of the life cycle phases of an asset.
In the service platform, artificial intelligence models can also be incorporated, allowing equipment and product problems to be quickly identified, but also predictable. These customized AI service modes make intelligent and optimized maintenance possible, reduce costs, and establish future oriented, data-driven, customer-oriented service mode.
With such a wealth of product usage, conditions and environmental data, digital twins can adjust without affecting the physical entities they represent. Quality and idiomatic data can be combined and used to ensure that optimization is valuable and, finally, changed in the real world. This method can reduce the risk of reform impact on engineering, accelerate the continuous improvement process, shorten the time to market, and reduce the cost of product realization process.
The effect of all this is to make customers get higher quality products faster; increase retention, satisfaction and intimacy.