Businesses, to stay competitive, need to accelerate their digital transformation journeys and make the transition to industry 4.0. It would include achieving real-time convergence between physical and digital platforms and disrupting the market through innovation. There is an urgent need to shift towards an intelligent industry and create a sustainable value chain by embracing connectivity. The next phase of digital transformation is fueled by the advent of futuristic technologies. These include artificial intelligence, the cloud, the internet of things, 5G, and edge computing.
According to a survey on digital engineering conducted by the Capgemini Research Institute, 57 percent of companies in the manufacturing sector are unable to generate, capture, share, and reuse data across their value chain. However, with digital transformation being the buzzword for these companies to remain competitive, maintaining digital continuity will be critical. This posits the role of digital engineering at the core of any digital transformation initiatives.
In fact, innovations in disruptive technologies have led to the enablement of use cases that were hitherto unachievable. The examples may include connected products, autonomous vehicles, multi-physics simulations, reimagined customer experiences, remote operations, and new as-a-service models. Digital engineering helps businesses to identify new opportunities, navigate complex ecosystems, and tackle industrial challenges.
It includes breakthrough innovation and human-centric design to achieve end-to-end transformation. Digital product engineering helps businesses to foster synergies at scale between the digital and engineering realms to create intelligent products, services, and operations. With so much talk about digital engineering, let us understand what it is all about and what the game changers are for this model.
What is digital engineering?
Digital engineering is a holistic data-driven approach to designing end-to-end complex systems and the convergence of various concepts and technologies. These include digital twins (simulation of operations of a physical system), reality models, connected data environments, and reality models. It does away with the traditional document-based method of developing a system. It aims at developing systems through technological innovation, offering an authoritative source of truth, and establishing a support engineering infrastructure. This is done by streamlining and accelerating collaboration and communication across disciplines. Digital engineering allows product developers to build innovative solutions within a virtual environment. The entire model has computable data at its core and has the potential to offer vast possibilities. Further, it facilitates the real-time evaluation of design systems to enable informed decision-making.
5 game changers of digital transformation
In the competitive digitized world where products need to find market acceptance, digital engineering can drive personalized manufacturing for customers. This is done by leveraging technologies such as big data, cloud computing, the internet of things, and mobile. Besides, it involves seamless collaboration, product traceability, quality management, reduced expenses, and operability. The 5 game changes driving digital assurance services include:
1. Digital Evolution: Being the new kid on the block, the processes, supporting technologies, and storage related to digital engineering are evolving at an exponential rate. In other words, such rapid developments will always pose a disruptive threat to existing practices. Thus, the technologies or processes that are considered new today may become outdated or archaic in the not-so-distant future. These are likely to be replaced by better tools, which will transform the way projects are designed and delivered.
2. Deciphering Data: Capturing data and analyzing the same is important to develop effective and accurate virtual models to test the performance of a design. The design engineer should understand how to decipher data and use the insights to finetune the design specifications and functions. This is of utmost importance as data lies at the core of any initiative related to Industry 4.0. The data can emanate from different sources and needs to be integrated and analyzed to derive useful insights. Further, with the fusion of real-world and virtual data, designers can increase safety and quality, enable predictive maintenance, optimize the product, improve environmental performance, and many more. Any shortcomings in this field can lead to cost overruns and missed deadlines.
3. Maintaining Basic Engineering Principles: The debunking of basic engineering principles is not envisioned in digital product engineering. In fact, the principles are merely enhanced by the application of technology. This would mean enhancing the engineering curriculum so that future design engineers are able to decide when to use the appropriate digital tools. The optimum solution would involve the augmentation of human resources and machines.
4. Better Optioneering: In the traditional scheme of things, forecasting the performance of a design was predicated on the analysis of a single option. This was not only a time-consuming and challenging exercise, but the option might turn out to be unacceptable in the end. Digital engineering solutions, on the other hand, harped on harnessing cloud processing to create multiple design options. All such options are tested simultaneously in the virtual environment to arrive at an accurate result instantly.
5. Reshaping of Collaboration: Digital engineering strikes at the traditional practice of designers working in siloed departments. It deals with co-designing solutions through real-time collaboration between departments and processes. As paper-based processes are done away with, the development and delivery of products by leveraging various digital platforms is hastened. This will lead to a change in the working methodology – from silo-based processes to seamless collaboration among processes.
Conclusion
A seamless data flow through the product lifecycle is critical to driving product innovation. However, the presence of legacy systems running in silos hampers achieving digital continuity. This is because such systems mostly comprise subsystems carrying out additional tasks independently of each other. Further, the lack of data association among various units restricts the ability of the system to use the data and achieve the business objectives. Digital engineering services can visualize the data across the product lifecycle by optimizing the information system and leveraging the right toolchain.
