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      <title>NETVIBES</title>
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      <title>
      <![CDATA[ Fueling the Future of Energy ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/fueling-the-future-of-energy/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/274041</guid>
      <pubDate>Thu, 28 Nov 2024 08:47:03 GMT</pubDate>
      <description>
      <![CDATA[ Discover how a leading company in the energy sector is powering a carbon-neutral future through electricity with NETVIBES data science solutions on the 3DEXPERIENCE© platform.
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      <![CDATA[ 
CHALLENGE



A multinational leader in the energy sector found that data silos were making it difficult to manage costs, make accurate, timely decisions and avoid project delays. The company needed a 360-degree view of its assets, along with analytics and monitoring dashboards to help strengthen plant performance. In addition, it wanted a single source of truth that would help it optimize its engineering projects and boost overall competitiveness.



SOLUTION



The company chose NETVIBES data science solutions on the 3DEXPERIENCE platform to help it manage its capital projects with precision. Asset Information Intelligence solutions provide it with a single source of truth, powerful data analysis and real-time insights, along with enhanced collaboration capabilities.



BENEFITS



Users are able to make better decisions, backed by the insights that come from connected data analytics. Real-time visibility on program data, coupled with a dashboard view that contextualizes knowledge, documents and resources, has enabled the company to drive more efficient project management, accelerate project delivery and reduce construction and operating costs.







Paving the Way for Sustainable Power



A carbon-neutral energy future through electricity – that is the mission of one multinational leader in the energy sector. To help achieve it, the company is building and operating several energy plants.



In capital projects like these, even the smallest problem can cause long delays and cost overruns – all of which deter customers and governments, whose backing is crucial. However, it was difficult for the organization to avoid these issues because project data was spread across many different systems and directories. This caused a lack of visibility over millions of complex data items for equipment to be manufactured, installed and tested. It made it difficult for engineers to identify issues and next steps, or to see the impact their decisions would have in other areas like purchasing, subcontracted studies or on site. As a result, previous projects had encountered delays and extra costs.



Breaking down those data silos was essential to optimize the company’s control of engineering process. As well as bringing its data together, it wanted to be able to analyze it and visualize it in a way that would help project managers:




understand how to deliver each project on time, on budget and on specification,



draw on past experience to continuously improve planning and minimize errors,



identify potential risks ahead of time and take effective measures to reduce them.




The company had previously implemented NETVIBES data science solutions to provide change management dashboards and 360-degree views of assets. Next, it chose NETVIBES Asset Information Intelligence solutions on the 3DEXPERIENCE platform, to create a virtual twin of its program management that would incorporate key performance indicators (KPIs) and support precise dashboards to show project progress.



A Single Source of Truth



At the heart of the solution, NETVIBES integrates data from the company’s main IT systems and delivers a complete, dashboard view of assets and construction progress. It orchestrates all the information around an object, asset or process – including 3D and 1D drawings, metadata and documents – and makes it available in the context the user needs.



NETVIBES collaborated closely with the organization to develop a proof-of-value application that combined on-premise data in the 3DEXPERIENCE platform with data science capabilities in the cloud. This allowed the company to see how the solution would work, and how it could meet both their current and future project visibility needs.



In particular, the solution stood out from competing offers because it allows the company to connect natively to all its data and gain real-time insights from it. Collaboration would be easier, since the 3DEXPERIENCE platform was designed to help disparate teams work together.



Mastering Requirements Management



Making the data intuitive has made all the difference, and that is where the solution’s semantic graph index (SGI) cloud comes in. It makes it possible to manage and cross-examine data from different sources and present the information in a way that makes sense to individual users and their job role. Having instant access to the right knowledge, processes and documentation has helped the company to enhance its capital project management in several ways.



One priority in the client roadmap is to be able to project KPIs onto the virtual twin, in effect building them into the project from the start. Users will be able to analyze the maturity of requirements and explore how they relate to objects in the system, in alignment with business rules. This would enable the organization to improve its management of requirements monitoring, carry out basic and detailed design reviews and validate the different construction phases of its energy power plant projects.



Historical analysis of requirements could also help users to respond more efficiently to any volatility in requirements. By factoring in the way requirements have evolved during past projects, the solution allows them to draw on the organization’s experience and anticipate future developments.



Intelligent Equipment Assignment



Assigning equipment is one area of project management that should be simple. In reality, it often involves project managers wading through details to identify the appropriate equipment and request it for their project – only to find that the piece they wanted is already in use elsewhere.



NETVIBES simplifies this process by bringing together all the data surrounding the equipment – its 3D representation in the 3DEXPERIENCE platform and the metadata that resides elsewhere. Each piece is cross-analyzed by family, metadata and zoning so that it’s easy to identify the most suitable components and apply them to the project.



With this information provided in a single, dashboard view, the project manager can filter out any equipment that is already assigned before they start their search. Then they can explore the available pieces to find the ones that are suitable for their current project. Once that’s done, they simply select the equipment they need and assign it by dragging and dropping it into the relevant task on the dashboard.



Optimizing Project Control



Having a single source of truth has empowered the company to improve its control of capital projects. For example, threads such as construction, engineering and sourcing all happen on different timelines throughout a project, but they are all critical when it comes to meeting deadlines and budget commitments. NETVIBES puts all these threads into context so that managers can anticipate and control project delays.



Predicted delays for ongoing projects are explained using similar past cases and recurrent behaviors that have been identified. By visualizing recurrent behaviors through time, the solution also indicates whether they are still relevant or have already been addressed – a crucial distinction for project managers who are deciding on their next steps.



As a result, the organization can create project plans much faster and optimize them in terms of objectives such as time, risk and resources, while aligning with established best practices and standards. Risks are minimized because the solution uses previous capital projects to identify them early on, so project managers can generate a timely mitigation plan.



Powering a Carbon-neutral Future



By using NETVIBES to break down silos and integrate data on the 3DEXPERIENCE platform, the company has created a single source of truth that helps it to keep capital projects on track. The real-time insights and enhanced collaboration that the solution provides are driving more efficient management and tighter control, enabling faster delivery of projects and reduced construction and operating costs. As the organization looks ahead, these capabilities are helping it to build the foundation for more sustainable power provision.



“It is critical for managers to have access to all information generated by an energy power plant project, including pumps and all data for a given asset,” said Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES. “As a single source of truth for all data in the platform, NETVIBES empowers the company to make better project decisions. In addition, other stakeholders can see project status at a glance, without having to dive deep into the platform.”




It is critical for managers to have access to all information generated by an energy power plant project. As a single source of truth for all data in the platform, NETVIBES empowers the company to make better project decisions.
Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES



Learn More Here



Download the eBook&nbsp;to discover more NETVIBES data science solutions in action!




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      <title>
      <![CDATA[ Accelerating Innovation and Sustainability in Packaging Design ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/accelerating-innovation-and-sustainability-in-packaging-design/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/272306</guid>
      <pubDate>Tue, 12 Nov 2024 15:03:25 GMT</pubDate>
      <description>
      <![CDATA[ Discover how a leading company in the food and beverage industry optimizes packaging development with NETVIBES data science solutions on the 3DEXPERIENCE© platform.
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      <![CDATA[ 
CHALLENGE



Companies in the food and beverage industry must strike a delicate balance. They need to provide sustainable packaging, ensure regulatory compliance and meet ever-changing consumer demands – while making sure they can deliver projects on time and on budget. To achieve that, it is critical to ensure real-time insights into the data and contextual knowledge required to make decisions during the packaging development process.



SOLUTION



To enable those insights, a leading global company needed to unify structured and unstructured data that existed across separate systems. This would create a single set of actionable data perspectives that were tightly integrated into its development platform. It chose NETVIBES data science solutions on the Dassault Systèmes 3DEXPERIENCE platform to bring that vision to life.



BENEFITS



Innovation is accelerated as packaging developers can search for projects with similar attributes and reuse successful elements, including pallet design and certification. Guidance on next steps, with associated data and documents to hand, helps to optimize project efficiency. This has improved “first time right” packaging decisions and reduced the need for costly re-engineering efforts, delivering a potential 30% increase in packaging development efficiency.







Pioneering Packaging



In the fast-moving, highly competitive food and beverage industry, market leadership is as much about bottles, cans and boxes as the products inside them. Designs are refreshed increasingly often as companies strive to delight consumers – and as well as looking good, they must also be fit for purpose.



For one global leader in this industry, innovative bottle design goes hand in hand with exceptional quality and sustainability. As well as being visually appealing and pleasant to hold, each bottle must also be sustainable, made from recycled and recyclable materials. The lighter the bottle is, the more it will help to reduce carbon emissions, but it also needs to be strong enough to withstand shocks. The way the bottles will fit onto a pallet for transportation is also a critical factor. A competitive edge comes from combining all these elements in a way that is cost-effective and can be produced fast enough to beat competitors to market.



The company knew that it had volumes of data from previous package designs that could provide a rich source of information for new ones. If packaging designers could reuse that information, they would be able to innovate faster, replicate past successes and make sure failures weren’t repeated – while reducing the amount of physical testing needed to get the design to market. However, these valuable resources were scattered across different systems and network drives. Developers would struggle to find the knowledge they needed – if they knew it was there at all.



Digitalizing its development processes held the key for the company to overcome these obstacles. It wanted to bring all its data together in one place and make it easy for packaging engineers to search, access and understand.



“To become even faster, stronger and better, we are constantly looking for ways to improve how we design packaging, and digitization will be a key element of how we achieve this,” said a beverage packaging lead at the food and beverage provider. “My vision is an integrated packaging development system – a digital workflow which automatically guides all packaging developers through the right steps in the process, provides them with the right digital tools and simulations to be able to quickly assess and evaluate packaging, and enables them to mine the huge data history we’ve accumulated over the years.”



The company chose NETVIBES data science solutions, on the 3DEXPERIENCE platform from Dassault Systèmes, to make that vision a reality.




My vision is [&#8230;] a digital workflow which automatically guides all packaging developers through the right steps in the process, provides them with the right digital tools and simulations to be able to quickly assess and evaluate packaging, and enables them to mine the huge data history we’ve accumulated over the years.
Beverage Packaging Lead 







Shifting from Physical to Digital



Packaging design involves a lot of prototyping and testing. Carrying out this work with physical objects takes a lot of time and materials, as well as generating significant waste. By shifting the emphasis away from physical processes towards digital ones, the organization would be able to accelerate innovation and improve its sustainability performance.



To digitalize its packaging development, the company needed to harmonize data across the value chain. This would allow different teams to work on the same virtual model, using past and present design data to develop, simulate and test new bottles. It chose the 3DEXPERIENCE platform to support that shift after a proof-of-value project showed it could deliver a 30% increase in packaging development efficiency.



As well as uniting virtual and real-world digital data, the platform allows the company to create a virtual twin for each packaging design and integrate upstream and downstream tools and systems. This means that users across the value chain can access the virtual model of each design and see how their decisions fit into the bigger picture. Engineers can use it to run predictive simulations early in the design process, so they make the right decisions and reduce the need for line tests.



“It’s important to have a single entry-point to access all the simulation software tools and models,” said the company’s director of data science and analytics. “The 3DEXPERIENCE platform does that and enables businesses to collaborate, connect and scale.”




The 3DEXPERIENCE platform [&#8230;] enables businesses to collaborate, connect and scale.
Director of Data Science and Analytics



A Head-Start on New Designs



Data is only useful if it is searchable, understandable and actionable in the context each user needs. NETVIBES data science solutions make that possible by visualizing data from systems across the organization in the platform. This helps to optimize innovation in several ways.



At the start of a new design project, the solution provides intelligent search capabilities so designers can search using structured data or unstructured data. By viewing the information in context, they are better able to make decisions that will improve product quality while saving time and money.



For example, 3D geometric search allows the packaging design engineer to match their new design with similar shaped bottles that already exist across the company’s brands. They can then select the closest matches and compare specific attributes, to see where close similarities could allow them to reuse existing data – such as the materials used, pallet pattern and certification.



All this knowledge is accessed in one place so designers can review it, understand how successful the measures were and decide whether to reuse them for the new bottle. If the answer is yes, then they can quickly create a project using all the relevant content from previous projects, including component materials, engineering bill of materials, suppliers and reference documents. Then they can simply modify these elements as part of their new design. This cuts out a lot of research, trial and error early in the design process, helping to get the foundations right and prevent problems later.



Intelligent Project Execution



Innovation may start with a new idea, but its success depends on how efficiently the project can be brought to market. That efficiency gets a significant boost when all the relevant data is available at engineers’ fingertips.



For instance, running deliverables reports on past projects allows users to quickly find and reuse associated data linked to specific tasks. This helps them understand exactly what happened and when, including any issues, risks and budget involved, so they can reuse the successful parts and avoid any pitfalls.



Essentially, the company now has a system that can enhance the project’s efficiency by coaching its users team every step of the way. Everything they need, including deliverables, status and associated documentation, can be accessed from a single dashboard. They can drag and drop tasks from their to-do list to “in process” or “completed” fields. And instead of hunting among directories for the information they need – or assuming it doesn&#8217;t exist – they can instantly access the relevant templates to complete tasks like ship-and-stack tests, quickly and accurately.



Powering the Future of Packaging



For the food and beverage company, NETVIBES has already delivered significant value. It provides a unified view of data from different systems that allows development teams to search, understand and reuse information embedded across the value chain in an intuitive way. Stronger, more informed decisions have resulted, as lessons learned from past designs and physical tests are seamlessly woven into new projects.



With a fully digital, integrated packaging development system to work with, packaging engineers can now focus their time on true innovation work. This is enabling them to bring exciting, customer-centric packaging ideas to market faster, while hitting quality targets and optimizing cost. In fact, the company is looking at design efficiency gains of 30%.



This is also a solution that will power the packaging innovations of the future. By digitally accelerating innovation, the company believes that it will also allow research and development teams to work on larger projects around processing and packaging. Ultimately, it believes the technology has the flexibility, scalability and interoperability to provide an end-to-end platform that connects its R&amp;D to the supply chain.



“We are delighted to have helped our customer achieve its vision of an intuitive and optimized bottle development process, which was not possible with its existing technology,” said Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES. “The company challenged us to be forward thinking, to understand its packaging engineers’ decision-making processes and to prove the value of our solution every step of the way. In response, we provided relevant use cases that accelerated the timeline for solution adoption and delivered immediate value.”




We are delighted to have helped our customer achieve its vision of an intuitive and optimized bottle development process, which was not possible with its existing technology. We provided relevant use cases that accelerated the timeline for solution adoption and delivered immediate value.
Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES



Learn More Here



Download the eBook&nbsp;to discover more NETVIBES data science solutions in action!




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      <title>
      <![CDATA[ AI-driven customer analytics in banking ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/ai-driven-customer-analytics-in-banking/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/270256</guid>
      <pubDate>Tue, 08 Oct 2024 13:29:15 GMT</pubDate>
      <description>
      <![CDATA[ Banks are increasingly tapping into the power of artificial intelligence to extract even more value from their most critical asset: data. New capabilities help them to reveal previously unknown insights and understand what their customers truly want.
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      <![CDATA[ 
Just as the internet caused a paradigm shift in the way that consumers access banking – 58% of consumers globally now prefer to bank online or via a mobile app – another fast emerging technology breakthrough promises a similarly profound shake up across the financial services market. Artificial intelligence (AI) is expected to add up to US$4.4 trillion in value to the global economy – per year.&nbsp;And of all the industries set to benefit, banking has one of the greatest opportunities. Through AI, banks are gaining the capabilities to digitalize and automate workflows, opening up exciting ways to improve both their own employee experience by making space for more fulfilling roles, and creating more meaningful and seamless customer experiences. This is a win-win for both businesses and consumers.



As the capabilities and applications of AI grow, banking leaders are waking up to its potential and beginning to explore how they can harness the technology to tackle one of their biggest challenges: delivering timely and personalized support to their customers. While banks widely perceive customer experience as a key differentiator and source of competitive advantage, over half say they are trying to offer a more bespoke service yet their efforts end up appearing generic.



One of the key branches of AI making a real difference in this area is natural language processing (NLP) and machine learning (ML). Thanks to this technology, banks gain the capability to extract information from all manner of different sources, including social media posts, web reviews, emails, and customer satisfaction surveys, to better understand their customers and wider market trends. Tapping into this vast data pool and applying AI and NLP empowers banks to listen to their customers, anticipate their evolving needs, and constantly raising expectations, and move quickly to address pain points. Banks that successfully transform unstructured data into clear information can use it to create successful personalized customer journeys, gain trust, and foster long-term loyalty.




The huge drive towards digitalization opens up exciting opportunities for banks to capture what their customers are saying, and use that information to deliver even better services.



Taherah Kuhl, Vice President of Business Services at Dassault Systèmes




Source: Capturing the full value of generative AI in banking, McKinsey &amp; Company







Applications of NLP, ML, and semantic analysis technology



Here are three ways banks are applying NLP, ML, and semantic analysis technology to get more from their data:



1️⃣ Customer sentiment analysis



Today, consumers expect a personalized banking experience that is tailored to their specific needs and recognizes their current situation. Through NLP and ML solutions like Proxem Studio from Dassault Systèmes, financial institutions can deliver on this by analyzing all manner of data sources to understand customer sentiment in their native language (+30 languages can be analyzed with this tool). From here, they can offer personal advice and services, targeted product recommendations and promptly address queries and issues.




Before, it would have been impossible for banks to manually read and analyze the vast amount of customer feedback they receive, whether that’s from satisfaction surveys or reviews on social media. It’s meant that they’ve never really had a true understanding of customer sentiment at scale. AI changes that, providing a 360-degree view of all those sources in different languages, which they can use to identify trends and determine how well they’re meeting customer satisfaction key performance indicators.



 François-Régis Chaumartin, Vice President of Semantic Data Science at NETVIBES, Dassault Systèmes




Source: Possibilities and limitations, of unstructured data, Research World







2️⃣ Automating tasks



AI is increasingly being used to automate routine tasks and free up customer service representatives and account managers so they can spend their time tackling more complex issues and responding faster to customer requests.




Account managers can spend up to half of their time replying to incoming queries, whether that may be product advice, information requests or complaints. In more than 70 % of these cases, the response is relatively straightforward – such as stating the balance on a bank account or giving information about a new product. AI can automatically understand incoming requests, extract key information and help to compose a suitable response, saving up to one hour per day.



François-Régis Chaumartin, Vice President of Semantic Data Science at NETVIBES, Dassault Systèmes








3️⃣ Anticipating and identifying unseen risks



Financial crime and fraud remain one of the biggest challenges for banks and financial institutions. According to one report, by 2027 fraud will cost the global industry US$40.62 billion. It’s important, then, that companies take steps to proactively detect and prevent fraud and remain compliant with the fast-evolving regulations landscape. Using AI, they can do this by tracking data threats, identifying potential security breaches and disruptions before they occur, and monitoring regulatory compliance needs.




One of the key regulations impacting the financial services sector more recently is around operational resilience – meaning the ability to absorb and adapt to shocks and disruptions in the market. As part of this, regulators expect banks to have a holistic view of their enterprise and understand all possible interdependencies across the value chain that might affect their services and products. If there’s a failure that might affect the market or customers suddenly face an issue accessing their account, it’s fundamental for banks to be aware of what’s happening to minimize disruption.



Taherah Kuhl, Vice President of Business Services at Dassault Systèmes








AI and intelligent customer analytics in action



AI and NLP tools aren’t new to the financial services industry. Banks have used them for many years to get more from their data. However, Proxem Studio offers an entirely new proposition by providing users with a completely personalized and responsive semantic analyzer tool that includes:




Integrated deep learning and machine learning features



The ability to quickly set up and virtually model banking and insurance operational systems



The option to deep dive into any given subject within context, making accurate connections and relationships between concepts, market news etc.




Harnessing these combined capabilities within a single tool helps banks reveal surprising results and insights, and come up with solutions to issues they might not otherwise detect:



Ramping up customer confidentiality measures: Through Proxem Studio’s NLP insights, one bank detected an issue unique to its branches in Paris. Here, the population is high and branches tend to be small, so it was easy for customers to overhear confidential information when queuing. Being able to understand exactly what was happening allowed the bank to put in place more stringent client confidentiality measures.



Catering to local preferences: Belgium has three official languages: French, Dutch, and German. Proxem Studio revealed that high net-worth individuals in Brussels, which expect a high quality of service, wanted to be able to speak to advisors in their native language.




Over the last decade, we’ve been capturing the voice of customers to help companies automatically analyze tens of millions of customer feedbacks and extract the information they need to improve their offering and gain a competitive advantage. For over a year now, we have been investing heavily in LLMs (large language models), the foundation of generative AI. These models enable us to go even further in terms of in-depth natural language understanding, and intelligent text generation: it&#8217;s never been so easy to dialogue with the machine!



François-Régis Chaumartin, Vice President of Semantic Data Science at NETVIBES, Dassault Systèmes




Want to find out more about how you can transform your customer experience? ?







DON&#8217;T MISS RELATED BLOG POSTS




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Virtual Twins: Pioneering Operational Resilience for Future-Ready Financial Services



Cloud sovereignty and investment compliance












Taherah KUHL, Vice President Business Services Industry, Dassault Systèmes



Taherah has worked at Dassault Systèmes for the past 7 years. Focused on the Financial Services &amp; Logistics industries globally, Taherah is responsible for driving the industry strategy and vision.&nbsp;LinkedIn profile



François-Régis CHAUMARTIN, Vice President of Semantic Data Science at NETVIBES, Dassault Systèmes



François-Régis is the founder of Proxem, a start-up specialized in semantic analysis, acquired by Dassault Systèmes in 2020. He is the author of Le Traitement Automatique des Langues (published by Dunod). LinkedIn profile




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      <![CDATA[ What is NLP? (Natural Language Processing) ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/what-is-nlp-natural-language-processing/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/269333</guid>
      <pubDate>Thu, 19 Sep 2024 05:15:00 GMT</pubDate>
      <description>
      <![CDATA[ Explore the benefits and challenges of NLP and how it is revolutionizing industry. 
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      <![CDATA[ 
Ever feel like a chatbot just gets you? It’s not magic. It’s … science.



Natural language processing is a powerhouse transforming relationships between humans and technology. It helps bots understand our questions, sifts through massive amounts of unstructured data and performs advanced communicative tasks. NLP is trained on advanced algorithms to understand, manipulate and generate the human language.



Is NLP a new concept?



In recent years we have become more accustomed to AI and the pairing of language and technology with the influx of large language models like ChatGPT, yet the science and process behind them, including NLP, has been around for decades.



NLP uses algorithms to analyze textual relationships through language analysis and comprehension, while LLMs use deep learning to mimic human language and generate text. While tools like ChatGPT are relatively new, NLP has been around since the mid-20th century. It initially focused on rule-based systems in the 1950s and evolved into statistical models in the 1990s.



Natural Language Processing, defined



Natural language processing is a subfield of computer science machine learning. It enables computers to understand and communicate with human language. NLP evolved from computational linguistics which utilizes computer science to understand the very principles of language. NLP works with computers and other devices to recognize, understand and generate text &amp; speech by combining computer-based modeling of human language with statistical modeling, machine learning, and deep learning.



The advancement of NLP is enabling its integration into diverse fields such as healthcare, finance manufacturing and customer service, enhancing human-computer interactions and shaping the future of AI-driven communication technology.



“It’s a little bit like a human. It goes through documents highlighting the words and forms of expression that are important as defined by the classification plan, allowing us to quantify the various concepts,” said Kelly Stone, an NLP expert for Dassault Systèmes’ Information Intelligence brand, NETVIBES.  



Categories of NLP



NLP can be divided into three main categories regarding its various tasks and applications. When deciding what NLP works best for your business consider what task you aim to achieve. Below are three main subcategories of NLP:




Rules Based NLP: Rules-based NLP were the earliest NLP applications that answered simple if-then decision trees requiring pre-programmed rules. They were only able to provide answers in response to specific prompts.



Statistical NLP: Statistical NLP extracts, classifies, and labels elements of text and voice data and then assign a statistical likelihood to each possible meaning of those elements. This form of NLP introduced the technique of mapping language elements such as words and grammatical rules.



Deep-learning NLP: Deep-learning NLP is the dominant mode of NLP most users interact with which uses huge volumes of raw unstructured data to become more accurate. Deep-learning NLP is a further evolution of this statistical NLP.




How does NLP work?



NLP works like a digital linguist, deciphering the intricate patterns and meanings embedded in human language. It starts by breaking down sentences into smaller components, like words and phrases, and then dives deeper to understand grammar, semantics, and context.



Through machine learning algorithms and vast datasets, NLP learns to recognize pattern usage, enabling it to perform tasks such as sentiment analysis, language translation, and speech recognition. By constantly evolving and learning from new data, NLP works to adapt to nuances and changes in language over time.



NETVIBES is currently using NLP to help companies across industries overcome a number of unstructured data issues. For example, to review customer satisfaction surveys regarding a hotel for a client which involve massive amounts of unstructured data. Categories are created such as cleanliness, safety, and comfort. The model can then identify concepts in the customer reviews ranking them as positive, negative or neutral within many subcategories. The ranking of each category is then produced as a percentage of negative and positive reviews and an overall customer satisfaction percentage is derived from these subcategories.



How is NLP transforming business?



NLP has become a part of most of our everyday lives, working to power search engine results such as Google, providing customer service chatbots, and driving with voice-operated GPS systems. NLP has had a growing role in enterprise solutions, streamlining and automating business operations, increasing employee productivity, and critical business processes.



NLP is continuously being applied to diverse fields like retailing for customer service, chatbots and medicine, interpreting and summarizing electronic health records. Conversational agents such as Amazon’s Alexa also utilize NLP to listen to users and find answers.



In the healthcare field, NLP accelerates the process of reviewing and extracting relevant data from research papers, aiding in the discovery of new treatments and understanding of diseases. Chatbots and virtual assistants powered by NLP provide patients with information, schedule appointments, and offer preliminary health advice, enhancing patient engagement and accessibility.



With NLP baked into its solutions, NETVIBES is helping companies analyze large amounts of data and discover insights, monitor employee and customer experiences, and streamline business processes for previously tedious tasks.



“About 90% of a company’s data is unstructured, making it very difficult to create value from,” said Stone. “NLP can analyze any unstructured data, ranging from customer experience data such as surveys, email complaints, and help companies to quantify what is driving satisfaction and make action plans to improve the customer experience. It can analyze change requests and quality reports to help companies optimize their internal processes and improve quality”.



How can your business use NLP?



NLP makes tedious tasks easier by taking massive amounts of unstructured data and make sense of it. But NLP does not stop there, here are additional values the technology holds according to insights from DeepLearning.AI.




Linguistic tasks: This involves identifying if and when two words refer to the same entity.



Part of speech tagging: NLP determines which part of speech a word or piece of text is based on its use and context.



Word sense disambiguation: This selects a word meaning for a word with many possible meanings.



Named entity recognition: NLP identifies words or phrases as useful entities when scanning large datasets.



Spam detection: Large email services like Gmail use prevalent binary classifications to determine whether emails are spam or not. This allows for a better user experience removing unwanted emails from our inboxes.



Online grammar checkers: Grammar checkers like Grammarly use such systems to provide better writing experiences offering insights for grammatical corrections for writers to incorporate. These platforms also have helped teachers grade students&#8217; essays in the classroom.




Five major benefits of NLP



Once properly trained, NLP models can work rapidly and effectively and take on tasks for workers focusing their attention on other areas.




Faster business discovery: NLP uncovers hidden relationships between different pieces of content. Through text data retrieval, deeper insights and analysis enable better informed business decisions.



Cheaper data processing: NLP automates data gathering and processes information with less manual effort, decreasing human labor costs. When businesses have a massive volume of unstructured text data to sift through, this information can be easily categorized and understood.



Automation of tasks: NLP automates routine tasks such as customer support queries, content generation, and data extraction. This increases efficiency in business and production streamlining previously tedious tasks.



Language translation: This technology bridges communication gaps across languages facilitating global interactions and commerce. NLP is breaking down the barriers in understanding across businesses.



Improved accessibility: NLP enables accessibility features like speech-to-text and text-to-speech for people with disabilities. It further improves users experience through customization of user preference based on language and behaviors, enhancing engagement.








Why is NLP difficult?



NLP models remain imperfect and likely will never reach any level of perfection, similar to how humans continue to learn language their entire lives.




Biased training: If exposed to bias data in training, NLP similar to other AI functions will result in skewed answers. One way to overcome this is to train NLP functions on more diverse datasets. However, training datasets that are often scraped from the web are prone to bias.



Misinterpretation: In AI there is also a risk of misinterpretation due to the lack of clear quality input involving mumbles, slang, or other mispronunciations. The input to the tool is critical to ensure misinterpretations are few and far between.



New vocabulary: With new words being invented or imported NLP can only make its best guess or admit it is unsure. These datasets need to constantly be updated and trained to ensure that new conventions and ways of speaking are incorporated into the NLP tool.



Ambiguity in language: When words and phrases have multiple meanings depending on the text, this ambiguity can make it challenging for NLP systems to accurately interpret and generate human-like responses.




The main difficulty isn’t necessarily with technology, but rather the complexity of human language, explains Stone. “We don’t always realize how complex language is until we’re trying to learn a second language or misinterpreting the meaning of a text due to missing context,” she said. “



Addressing these challenges of NLP requires advancements in machine learning, natural language understanding, and the integration of broader contextual information to enhance the capabilities of NLP systems.



What is the future of NLP?



NLP is paving the way for smarter and more personalized interactions, from healthcare to customer service to entertainment. This is a new era of seamless communication and collaboration in the digital age.



Here at Dassault Systèmes, NLP understands human language at a deeper level unlocking data previously hidden in unstructured text. NLP first gained traction here through the 2020 acquisition of Proxem, a France-based specialist in AI-powered semantic processing software. NLP has since expanded into the 3DEXPERIENCE platform working alongside NETVIBES Information Intelligence applications. This platform delivers a combination of rule-based natural language understanding, natural language processing, and machine learning technologies to see and understand the bigger picture.



NETVIBES uses NLP every day to support clients in making meaning from large amounts of data. They have also introduced their version of ChatGPT that will work internally trained on their specific datasets providing more accurate information to clients and businesses. Indeed, thanks to this kind of technology Dassault Systèmes will be able to offer conversational assistants for augmented employee based on a Retrieval-Augmented Generation (RAG) that takes into account all the knowledge and instanced information from the different application of the 3DEXPERIENCE platform.



The future of NLP holds immense promise, driven by advancements in machine learning and AI. We can expect increasingly sophisticated models that understand and generate human-like text and comprehend context, tone, and nuance with greater precision. As NLP continues to evolve, ethical considerations around data privacy, bias, and the responsible use of AI will become increasingly important, shaping how these technologies are integrated into society and our business.
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      <title>
      <![CDATA[ Reaching New Heights in Productivity and Quality Assurance ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/reaching-new-heights-in-productivity-and-quality-assurance/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/268839</guid>
      <pubDate>Wed, 11 Sep 2024 10:50:45 GMT</pubDate>
      <description>
      <![CDATA[ Discover how an aerospace equipment manufacturer enhances productivity and achieves quality excellence with NETVIBES data science solutions.
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      <![CDATA[ 
CHALLENGE



A world-leading equipment manufacturer in the aerospace and defense industry found that increasing activity and production ramp-up were intensifying the pressure on its quality management processes. The company needed a way to monitor critical resources and process-plan maturity, so it could measure and manage performance and continue to ensure the high quality its customers expect.



SOLUTION



The company chose NETVIBES data science solutions to help tackle these productivity and quality challenges. Manufacturing Engineering Intelligence was selected to enhance factory performance and operations planning. In addition, BOM Intelligence made accurate data accessible across previously siloed departments and processes.



BENEFITS



NETVIBES has enabled an intelligent and accurate bill of materials (BOM) across various enterprise disciplines, helping the company to achieve its quality excellence targets in less time. Meanwhile, harmonized manufacturing and enterprise resource planning (ERP) data has helped to enhance factory productivity through better resource management and operations planning. End-to-end traceability makes it easy to monitor projects, validate milestones and produce reports that meet quality and certification requirements.







Meeting Quantity with Quality



For over 100 years, a world-leading manufacturer has been creating and marketing equipment for civil and military aircraft, on its own and in partnership with others. Demand has continued to grow, causing the company to ramp up its industrial resources and production lines. But as activity increased, so did the pressure on vital quality management processes.



To expand manufacturing productivity while ensuring the highest quality, the company needed a holistic view of its critical resources and process-plan maturity. Any gap in the process plan – such as a missing step or work instruction, or disparity between the parts in the engineering and manufacturing BOMs – would impact quality and delay the product’s readiness for manufacture. But with different departments and processes using separate systems and data, it was difficult to see the complete picture.



Process planners and engineers needed all the relevant data at their fingertips so they could quickly identify and address any issues and optimization opportunities. This would also support them in measuring and managing performance against pertinent key performance indicators (KPIs).



The company chose the NETVIBES portfolio of data science solutions from Dassault Systèmes to help it achieve those goals.



An Intelligent BOM



Efficient, high-quality manufacture is built on an accurate BOM. But this wasn’t possible with the silos and lack of standardized data that existed between the company’s departments and suppliers. Data management was complex and difficult, bringing the risk of inaccuracies and costly delays. Crucially, the lack of visibility across this misaligned data could also cause shortages of the components needed to deliver an order, while unused parts were needlessly held in stock.



To prevent these problems, the company needed a detailed understanding of how each product’s engineering BOM (eBOM), manufacturing BOM (mBOM) and bill of process (BOP) align with each other. &nbsp;That meant dissolving silos and harmonizing data across design, engineering and manufacturing departments to create a coherent view of how the relevant parts and processes fit together – and how to resolve any issues if they don’t.



NETVIBES BOM Intelligence solution was chosen to achieve that goal. The solution uses advanced data consolidation, semantic analysis and data visualization to make BOM data visible to every stakeholder who needs it, in a way that is relevant to their role. Manufacturing engineers can create report tables that provide a clear picture of BOM reconciliation progress, including 3D views to show which parts are aligned between the eBOM and mBOM and reveal in detail any parts that have not been implemented. When the engineer makes a change, the BOM reconciliation is recalculated automatically to make sure it’s always up to date.



Stakeholders across the organization can access relevant BOM data, from engineering to manufacturing, with a clear view of key metrics. This has enabled the company to guarantee more accurate BOM consumption and validation, helping it reach its target of quality excellence with better-performing BOMs and fewer development hours.




This solution strengthens the digital thread between engineering and manufacturing departments. It ensures that vital resources like manufacturing process plans and service parts lists are always in synch with the product definition and each other.
Head of Shopfloor Digital Method



Optimized Process Planning



Another goal for the company was to optimize the processes it used to manufacture its products – and that meant improving the way engineers planned those processes. If engineers could detect and address any planning issues early on, they would reduce the risk of issues like disrupted production schedules and missed capacity targets later. A full view of any relevant engineering data was the key to achieving that.



Enter Manufacturing Process Engineering Intelligence (MPEI), a solution that combines NETVIBES’ data management, analytics, visualization and search capabilities with DELMIA’s process and operational planning resources and ERP data.



MPEI draws together data from multiple applications and makes it easy to navigate, so users can quickly assess the cost, quality and maturity of each plan against KPIs. Manufacturing engineering and planning managers can quickly identify any gaps in the proposed process and the actions needed to fill them, as well as spotting opportunities to optimize the plan. For instance, if an item in the mBOM doesn’t have a process step or work instruction assigned, it is easy to collaborate on completing these elements so the project can move forward.



Addressing issues like these early in the planning process is much more efficient because it is easier and less costly to make changes at this stage. This enables the company to release complete, timely and high-quality process plans to the factory floor, smoothing the path to successful production.



Reliable Resources Management



Efficient planning and management of resources – the tools, machines and people involved in making the company’s products – is the other side of the quality and productivity coin. Smooth manufacturing can only be achieved if the right resources are made available every step of the way. A complete view of ERP data is essential to get it right.



The company is now able to combine and analyze manufacturing and ERP data for various processes. This empowers plant managers to review the maturity of areas like procurement, inventory and process planning through the lens of resources. By reviewing process maturity alongside areas like site capacity and skills ramp-up, managers can make sure they meet the finalized production plan with the right resources to carry it out.



Confident Certification



Better planning, resources and BOM management all contribute to ensuring the product’s quality, but one more key ingredient is needed: end-to-end accountability. This is especially important in a highly regulated industry like aerospace, where each product must satisfy a growing number of regulatory and certification requirements before it reaches the market.



Harmonizing data from different systems has allowed the company to create a digital thread that runs through its entire manufacturing engineering process. NETVIBES data analytics capabilities provide insights that support accurate decision-making, to help planning and manufacturing engineers get it right first time. This is enhanced by search capabilities that make it easy to find technical documentation and to identify the information needed for certification.



As a result, the company can ensure that all the characteristics and requirements for quality and certification are factored into the planning and manufacturing process. Real-time project monitoring, based on production part approval process standards, is used to validate milestones. It’s also easy to generate reports containing all the relevant information and transmit them to certification authorities.




In the aerospace and defense industry, quality and accountability are paramount. This company faced growing demand for its products, so it needed a way to optimize productivity while continuing to deliver the quality its customers expect. [&#8230;] This helped create a solution that will support its continuing growth.
Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES



A Data-Driven Future



By harmonizing its data and making it available with NETVIBES real-time analytics and visualization capabilities, the company has empowered itself to meet growing demand with greater productivity and the highest quality standards. Crucially, these capabilities are available to experts and non-experts alike, putting relevant information, analysis and actions in the hands of every decision-maker across the planning and manufacturing process.



At the heart of this achievement is the reduction of silos across the organization. Data management is much simpler, as disparate sources are connected and knowledge graphs provide a clear picture of data relationships. This has enabled the company to ensure the quality and consistency of the data that its product design and manufacturing processes are built on.



Better data is the basis for all the improvements the company has made – from enhancing the quality of its manufacturing ranges to rationalizing its production tools and equipment, reducing the time it takes to find technical documentation, and supporting excellent decision-making. And it will continue to support better productivity and quality assurance, whatever the future brings.



“In the aerospace and defense industry, quality and accountability are paramount,” said Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES. “This company faced growing demand for its products, so it needed a way to optimize productivity while continuing to deliver the quality its customers expect. The organization’s people have a deep knowledge of its data and a desire to optimize the value it delivers, and this helped create a solution that will support its continuing growth.”



Learn More Here



Download the eBook&nbsp;to discover more NETVIBES data science solutions in action!
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      <title>
      <![CDATA[ Virtual Twin Experience Powered by Data Science for the Aerospace &amp; Defense Industry ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/virtual-twin-experience-powered-by-data-science-for-the-aerospace-defense-industry/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/266969</guid>
      <pubDate>Mon, 19 Aug 2024 09:00:00 GMT</pubDate>
      <description>
      <![CDATA[ Read (or watch) the conversation between Morgan Zimmermann, CEO of NETVIBES, and David Ziegler, Vice President Aerospace & Defense Industry at Dassault Systèmes, about industry challenges and solutions proposed by virtual twin experiences on the 3DEXPERIENCE platform.
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      <![CDATA[ 
Get ready to dive deep into the world of the Aerospace &amp; Defense (A&amp;D) industry with this extract of an insightful discussion between Morgan Zimmermann, CEO of NETVIBES, and David Ziegler, Vice President Aerospace &amp; Defense industry at Dassault Systèmes. The focus of their conversation? This industry&#8217;s multifaceted challenges and how virtual twin experiences on the 3DEXPERIENCE platform, powered by NETVIBES data science solutions, are paving the way for a transformative future.







Data science to tackle aerospace &#038; defense industry challenges



These two experts provide a comprehensive overview of the industry’s current state, explaining the critical transformation drivers for companies operating within this sector. These include the need for accelerated development cycles, increased production capacities, and enhanced cost efficiency, while maintaining product quality standards and actively working towards the ambitious decarbonization goal.



The objective is not merely to introduce cutting-edge technology, but to fundamentally reimagine organizational structures, workflows, and operational strategies to better manage often conflicting objectives. The challenges may appear daunting, but this is where the 3DEXPERIENCE platform shines. From the A&amp;D industry expert perspective, it is a critical vehicle for transformation.



The data is not only aggregated&nbsp;into a “data lake”, it is strategically managed, organized and interpreted using ontologies and semantics to match the virtual model, a process known as “data science experience” at Dassault Systèmes. Virtual twin experiences, therefore, act as a crucial bridge, connecting the real and virtual worlds. Using this bridge, raw data – including non-conformances, sensor and operational data &#8211; is elevated to actionable knowledge and know-how within the virtual model. This integration provides valuable insights from various data points, like flight operations, maintenance costs, and even predictive analytics based on historical performance and real-time data feeds.



Customer use cases



Practical examples of this transformative process are already being observed within leading A&amp; D companies such as Dassault Aviation. Here, flight operations data from the aircraft are meticulously gathered, organized, and interpreted, leading to significant cost reductions and maximized fleet availability.



Moreover, the benefits of the 3DEXPERIENCE platform and virtual twin experiences extend beyond flight operations. On factory floors, real-world data from both OEM employees and supply chains is leveraged to update the virtual model of the final assembly line of an aircraft. This results in higher product quality, a more efficient supply chain, and predictive maintenance schedules that drastically reduce downtime.



Speaking of supply chains, our experts engage in a critical conversation on supply chain volatility — one of the most significant concerns in the industry. To counteract this, NETVIBES provides industry process experiences, initially developed for the automotive industry, to digitize and analyze the impact of market trends on products. This includes tracking the volatility of raw material costs, energy costs, and component shortages, empowering a leading global company to adjust product prices, budget accordingly, and strengthen negotiations with suppliers. Thus, by leveraging these industry process experiences from the automotive industry, aerospace companies gain a shortcut to accelerated value and transformation.



Conclusion



With the insights and solutions presented, it is evident that the future of the A&amp;D industry is heading towards a data-driven, digitally integrated horizon. The discussions between Morgan and David reveal a promising future where innovation and efficiency are seamlessly integrated to tackle the industry&#8217;s most pressing challenges.



The virtual twin experience is not just a technological advancement but a strategic approach towards a smarter, more efficient, and sustainable future for industry. This approach enables companies to make better informed decisions based on comprehensive data analysis, leading to optimized processes, reduced costs, and the ability to swiftly adapt to ever-changing industry dynamics.



The future, as envisioned by Dassault Systèmes, is one where the virtual and real worlds seamlessly converge to create unparalleled opportunities for innovation and growth.











You can also listen to this discussion in the &#8220;Disruptors Unleashed&#8221; podcast series.



Want to learn more about how to leverage virtual twin experience powered by NETVIBES solutions to tackle other business challenges? Watch the other videos focusing on Industrial Equipment, Transportation &amp; Mobility, Infrastructure, Energy &amp; Materials, Education and Sustainability.



Download the eBook&nbsp;to discover more NETVIBES data science solutions in action!
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      <title>
      <![CDATA[ Digital Transformation of an Automotive Manufacturer with the 3DEXPERIENCE Platform ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/digital-transformation-of-an-automotive-manufacturer-with-the-3dexperience-platform/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/266131</guid>
      <pubDate>Mon, 22 Jul 2024 06:38:37 GMT</pubDate>
      <description>
      <![CDATA[ Are you curious about how one of the world’s leading car manufacturers is using technology to stay ahead? Check out this abstract from Mag IT article.
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      <![CDATA[ 
Are you curious about how one of the world&#8217;s leading car manufacturers is using technology to stay ahead? Check out this abstract from Le Mag IT article (in French: &#8220;CAO-PLM : Renault tire un premier bilan de sa transition vers le SaaS&#8221; / in English: &#8220;CAO-PLM: Renault&#8217;s Preliminary Assessment of its Transition to SaaS&#8221;), featuring an in-depth review of Renault Group&#8217;s shift to the 3DEXPERIENCE platform, from Dassault Systèmes.







Dassault Systèmes &#038; Renault partnership: the heart of &#8220;Renaulution&#8221; plan



Renault, the renowned French automaker, has been forging ahead with its digital transformation journey following a strategic partnership with Dassault Systèmes in 2021. This collaboration marked a significant milestone in its ambitious &#8220;Renaulution&#8221; plan, which aims to revolutionize every aspect of the company&#8217;s operations, redefining the future of automotive technology and sustainability.



While the company has been migrating towards the 3DEXPERIENCE platform, this digital transformation is already showing promising results. In 2023, Renault reported a remarkable 13.1% yearly increase in sales, resulting in revenues of €52.3 billion, with an operational margin of 8%. By early 2024, the company had sold 550,099 vehicles, representing a 2.6% increase compared to the same period in the previous year. Renault partly attributes this success to the &#8220;Renaulution&#8221; transformation program, which has streamlined operations and improved efficiency across the board.



The power of the 3DEXPERIENCE platform with virtual twin experience



The 3DEXPERIENCE platform delivered by Dassault Systèmes, houses the Renault Virtual Twin (RVT), a highly detailed virtual replication of the group&#8217;s vehicles that provides an innovative approach to both design and manufacturing processes. The platform now hosts over 1,800 vehicle variants and more than 500,000 components.



The RVT enables real-time simulations and optimizations, allowing engineers and designers to test various scenarios and make improvements before physical prototypes are created. This leads to better product quality, enhanced performance, and a reduced time-to-market. With currently over 5,500 users, the platform supports collaboration across different teams and departments across key regions, fostering a more integrated and efficient workflow.



Furthermore, Renault has successfully integrated dedicated solutions as part of its RVT into the 3DEXPERIENCE platform, such as Part360 or Part Optimizer (NETVIBES Material Cost Intelligence solutions). These solutions enable the visualization and comparison of the parts&#8217; 3D models and characteristics integrated on Renault&#8217;s vehicles and competitors models. At the end, these solutions support the company for cost reduction opportunities, material procurement optimization and development time reduction.



Renault&#8217;s transition to a SaaS model also aligns with its sustainability goals. By optimizing design and manufacturing processes, the company aims to reduce waste and improve the overall lifecycle management of its vehicles. This transformation is not just about staying competitive but also about leading the way in creating a more sustainable and efficient automotive industry.




Once departments have access to the 3DEXPERIENCE platform, they establish trust in this single source of truth, promising substantial time and cost savings.
Gilles Le Borgne, Chief Technology Officer at Renault Group



In conclusion, Renault&#8217;s strategic shift towards the 3DEXPERIENCE platform and virtual twin experience has ushered in substantial benefits. This journey marks a significant digital transformation with promising future potential. With continued investment in advanced technologies and a commitment to innovation, Renault is poised to lead the automotive industry into a new era of efficiency and excellence.







Read the full article&nbsp;here to discover more about this transformation and its impact on Renault&#8217;s operations and future outlook



Also want to uncover the trends revolutionizing the automotive industry? Listen to this podcast and learn how virtual twin experiences, powered by NETVIBES on the 3DEXPERIENCE platform, are a lever of transformation and innovation.



Download the eBook&nbsp;to discover more NETVIBES data science solutions in action!
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      <![CDATA[ Using the power of data science to drive automotive profitability ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/using-the-power-of-data-science-to-drive-automotive-profitability/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/261437</guid>
      <pubDate>Fri, 03 May 2024 09:30:56 GMT</pubDate>
      <description>
      <![CDATA[ Dassault Systèmes, through its 3DEXPERIENCE platform and NETVIBES solution, spearheads the industrial renaissance by seamlessly integrating data science, AI, and virtual twin experiences to revolutionize collaboration, decision-making, and profitability in the automotive industry.
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      <![CDATA[ 
By Fedja Sehic, Director of NETVIBES, Asia, Dassault Systèmes



The world we live in is full of new industrial constraints. Regulations around sustainability, carbon emissions, energy transition, and quality are all rapidly evolving with the new industrial age. We all are aware of supply chain disruptions, fast and dramatic changes in customer expectations, demands for mass personalization and the evolution of radically new business models.



The challenge faced by the modern industries like the automotive industry is that on one hand there are vast fluctuations in raw material costs. On the other hand, the industry which so far used to work with traditional tools, and restrictive methods and processes, is forced to change its ways of working to attract a new and upcoming workforce – generation Z and millennials – from whom the future generation of business leaders will emerge.



Humanity is at an inflection point of knowledge, data, and knowhow equal only to the renaissance in Europe. Today, the surfeit of information and data that people, organizations and enterprises can access and use to model knowledge and transform knowhow into new experiences has unleashed an ‘industrial renaissance’. It is critical during this industry renaissance that companies have a robust data science strategy that can create new experiences to carry the organization into the future.



The key question for organizational leaders is how do they transform data into information by building, deepening and enriching the context around it, modeling knowledge and then driving new experiences through know-how.&nbsp; Ultimately leaders need to understand how they are revealing ‘information intelligence.’



How Dassault Systèmes is at the center of the ‘industrial renaissance’



The technology vectors that are driving the industrial renaissance &#8212; elastic cloud computing, big data, artificial intelligence, machine learning, and internet of things – are precisely what Dassault Systèmes virtual twin experiences powered by data science are using to model knowledge and transform know-how for far better ways of running industrial processes and operations than was possible before.



Key to the new experiences is the virtual twin technology, which is far more dynamic and ‘realistic’ than digital twin technology. Virtual twin experiences are about combining three levers.



The first lever is the most advanced representation of the product, factory, or company. &nbsp;That can be 3D representations, systems, models, or ontologies. The second lever is all of the real-world data that organizations are capturing from any system and then projecting on to the virtual twin. The third lever is the people and the process for collaboration.&nbsp;







How does this actually apply in the industrial world? Consider the context of an advanced product like an aircraft. &nbsp;There is a lot of data around the system – stress data, simulation data, weight and balance data, raw-materials data, and suppliers data, coming from different sources.&nbsp; As soon as this data is projected onto the virtual twin it becomes contextualized by nature. This is the power of the knowledge model and deeply contextualized data.



Dassault Systèmes makes this model the foundation of knowledge. This means as an industrial virtual twin solution – Dassault Systèmes NETVIBES – can take any data from any data source and project it onto the model of the virtual twin to create realistic 3D experiences. How does this transform the manufacturing of cost sensitive and complex products like automobiles and aircraft?



3DEXPERIENCE platform dramatically transforms collaboration



First of all the Dassault Systèmes solution based on the 3DEXPERIENCE platform dramatically enhances collaboration. When people in manufacturing organizations think of collaboration they think of emails or messaging tools. These are in fact barriers to seamless collaboration. If for finding new ideas, risks, opportunities and threats the first thing executives are doing is sending an email then traceability and efficiency are ruled out.




The virtual twin brings people, processes, data, and the most advanced representation of the data in one place to make collaboration seamless and increase the possibility of innovation.




In the case of automotive companies, the 3DEXPERIENCE platform provides real life applicable solutions for key challenges such as price volatility of raw materials that can immensely affect profitability. The platform ingests and integrates the entire set of physical data of product lines &#8212; the configurations, variants, effectiveness, and the simulations as well as metadata associated with product lifecycle management (PLM) – which is all the physics that define the product.



On top of it is the collaboration engine which includes the change management, issue management, risk management, workflows, and visualization.



In the middle is where data science and AI combine to create the 3D experience. This is where external data from any source and data indexed at a part level is integrated on to the 3DEXPERIENCE platform’s ‘semantic lake’ that provides ontologies, intelligence and context on the data.



The decision-making process with the 3DEXPERIENCE platform brings stakeholders from costing, engineering, vehicle integration, simulation, and program management among others working on a unified workflow with real world data from the ERP systems and virtual data from PLM which is context rich. The data perspectives that they now have and the ‘inferred new data created’ helps the AI in the middle to provide instant real-world insights that then become actionable without sending a single email, or sharing a spreadsheet, or presentation file between the stakeholders.



How the 3DEXPERIENCE platform helps manage price volatility




By consolidating the data from the disparate and disconnected data sources the 3DEXPERIENCE platform can compute for any car configuration the composition of raw materials and accurately forecast how each car program would be impacted by varying price levels or fluctuations in the coming years.




At any time stakeholders can simulate and visualize all of the data and the impact of the various sensitivities in the virtual twin of the car using simple drag and drop features.







The procurement team has access to a dashboard that helps them visualize everything that has been purchased. They can understand the distribution of suppliers along with the sustainability index for all factory locations as well as supplier ratings.&nbsp; The procurement team can narrow down their options to the suppliers that provide the parts at the best cost and quality. With another drag and drop the procurement team can see all the similar parts that can be used as an alternative. Thereafter, an engineer can simulate and validate the new part on the 3DEXPERIENCE platform. As the challenge is tied to procurement savings, the simulation engineer can simulate, analyze and review it and share the simulation with all stakeholders.



Meanwhile in the middle layer, data science and AI improve data quality. A dashboard helps a data engineer manage the lifecycle of the data – assess the source and quality of this data.



As far as incomplete data such as parts not having the gross weight is concerned – data scientists can identify parts with similar gross weight and construct a model which helps infer a gross weight for those parts that do not have all the information around them. This is an example of how material cost intelligence improves data quality thanks to the embedded AI.



A bigger challenge is harmonizing all the data from all the data sources with a common business language.&nbsp; This data can be coming from procurement database, compliance database, PLM or ERP, other databases or even spreadsheets. The ontologies editor – which enables the creation of specific industry ontologies of a specific business model – resolves this challenge. For example, the raw material ontology builds the necessary consistency and relationships between the data sources for all of the stakeholders in this scenario.



NETVIBES delivers transformational outcomes across five domains



NETVIBES with the data science model and the 3DEXPERIENCE platform delivers transformational outcomes across five domains: planning, virtual product development, value network, customer experience, collaboration and intelligence. 



In planning, business stakeholders can deliver programs and projects faster, on schedule, with enhanced quality and reduced risks to increase profitability. 



As far as virtual product development is concerned, the platform helps engineering and manufacturing teams to optimize crucial factors such as cost and weight.



With regard to the value network, it provides AI for sourcing and standardization which in turn enables automotive teams to find the best components at the best price with the best suppliers. 



When it comes to customer experience, the augmented AI provides unique data perspectives and value propositions on the product in the real world to drive enhanced availability and customer retention.



Finally with regard to collaboration and intelligence, the flexible AI foundation deeply contextualizes the output of data professionals, democratizes and universalizes the output through experiences that all stakeholders can contribute to and benefit from, using a single workflow. This ultimately sets the stage for faster innovation, assured cost savings and efficiency to drive profitability and sustainability amid price volatility.
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      <![CDATA[ Streamlining Standardization and Reuse of Product Parts ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/netvibes/streamlining-standardization-and-reuse-of-product-parts/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/256213</guid>
      <pubDate>Tue, 05 Mar 2024 14:07:40 GMT</pubDate>
      <description>
      <![CDATA[ A global manufacturer of spacecraft, components and instruments enhances data capture, parts reuse and visibility on project status with NETVIBES solutions on the 3DEXPERIENCE© platform.
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      <![CDATA[ 
CHALLENGE



An American manufacturer of spacecraft, components and instruments wanted to improve visibility and efficiency across its engineering programs. Its product parts data was siloed across multiple systems. This reduced visibility into overall program execution and caused employees to waste more than 20% of their time searching for existing data.



SOLUTION



The company chose the Program Excellence industry solution on the Dassault Systèmes 3DEXPERIENCE platform to unify its data. It started by using NETVIBES Sourcing &amp; Standardization Intelligence to identify standard parts and avoid migrating costly duplicates to the new system. The next steps would be to expand the content sources and provide advanced search capabilities for product lifecycle management (PLM) metadata and documentation, as well as feedback on how employees were using the solutions.



BENEFITS



NETVIBES enabled a data-centric approach to the company’s pre-migration process, accelerating implementation of the 3DEXPERIENCE platform. OnePart Reduce and Reuse helped to define and standardize parts. This supported efficient migration planning and allowed the organization to reduce its parts catalog by 80%. Along with other NETVIBES solutions, OnePart has brought impressive improvements in data capture, parts reuse and visibility on project status.







Keeping Aerospace Projects in Flight



An American manufacturer of spacecraft, components and instruments for the national defense, civil and commercial space sectors, the company provides the industry with aerospace technologies and associated products including lubricants, optical systems, star trackers and antennas.



Streamlined operations are essential to deliver these complex products and services efficiently and on schedule. However, that becomes a challenge when data is scattered across siloed systems. The company’s three separate systems held parts content. As well as reducing visibility into overall program execution, these data silos caused employees to waste more than 20% of their time searching for existing data.



The company wanted to create a single user experience and promote digital continuity across its defense and space products and services. It chose the 3DEXPERIENCE platform to unify its data and move away from its siloed systems. Part of the artificial intelligence-driven Sourcing &amp; Standardization Intelligence portfolio, NETVIBES OnePart was selected to streamline data migration and accelerate adoption of the new system. In addition, NETVIBES Data-Driven Business Performance would then be deployed as part of the Program Excellence industry solution. This would create the ideal environment for collaboration across design, engineering, manufacturing and maintenance disciplines.




Digital engineering is critical to supporting the evolution of the aerospace and defense industry – ultimately expediting the time from customer concept to program delivery. Incorporating a digital platform enforces our commitment to customers’ needs and aligns our capabilities for future missions.
&#8211; Vice President, Engineering



Clearing the Runway for Data Migration



To achieve its ambitions, the company needed to make sure the data it migrated to the 3DEXPERIENCE platform would be accurate, relevant and up-to-date. It started by verifying its parts content using spreadsheets of attributes, but the process took over an hour for each part. With hundreds of parts to review, the company needed to find a better way.



OnePart Reduce and Reuse provided the answer. By using OnePart to analyze records from multiple sources, classify parts by family type and select standard components, the firm was able to weed out costly duplicates. This helped it to plan its content migration, making sure that only preferred parts and alternatives would be migrated to the new platform.



The benefits were immediate. OnePart Reuse delivers a single source for users to search for OTS parts across the organization’s old and new platforms. In just one click, users can compare metadata from both systems side-by-side, with any differences highlighted. Verifying a part now takes one or two minutes instead of the hours previously spent using spreadsheets. It’s a huge time savings and has also reduced errors and ensured a strong business foundation to build on.



“Our customer leveraged NETVIBES early and took a targeted, data-centric approach to the pre-migration process,” said Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES. “This made it possible to accelerate its data migration to the 3DEXPERIENCE platform as it embarked on its digital transformation journey.”



More Reuse, Fewer Parts



As well as saving time and effort in adopting the new system, the company’s ability to identify and migrate standard parts dramatically simplified its catalog. Instead of the 250,000 parts listed in the original siloed system, just 50,000 were migrated to the 3DEXPERIENCE platform – a reduction of some 80%.



It’s now faster and easier for engineers to search the system and find the parts they need, which is borne out in the number of people using the system. Since deploying OnePart Reuse, the company has seen a significant year-over-year increase in the number of engineers using the search capability to reuse existing parts – and in the number of searches that each user is performing.



Minimizing the proliferation of new parts is an ongoing quest for the company’s component engineers. They must direct users towards preferred parts, or users will simply request new ones and the components library will expand again. OnePart Reduce has saved the engineers huge amounts of time by allowing them to designate preferred parts and bulk-update their status across old and new systems.



Greater reuse of standard parts has already resulted in fewer new parts being introduced. In just one year, the number of master parts has dropped by 34%. Requests for designating master parts have fallen even lower, with a 43% decrease during the same period.



Better internal parts management will also help to optimize the supply chain. By using greater quantities of fewer unique parts, the company will be able to consolidate its purchasing and inventory management practices. This will create opportunities to expand to long-term agreements with preferred suppliers. The result: lower purchasing costs and improved part availability, which in turn means fewer schedule delays.



Data-Driven Insights



Alongside OnePart, the company is using NETVIBES Data-Driven Business Performance – part of the Program Excellence industry solution – to generate insights that will help it enhance the business and empower users. It provides various cockpits that are oriented towards key operational areas: project operations, issues mitigation and change management.



Each cockpit is home to a rich source of analytics that help users answer specific questions. A project manager might dashboard the evolution and live status of a project to optimize execution, resource allocation and delivery timelines, for instance. Engineers focusing on issues management can evaluate past and current problems to identify risks, support decision making and avoid future obstacles. And for those focused on change resolution, live 360-degree analysis of the process can reveal vital information about the trends at play, the modifications needed and the impact they will have.




Dassault Systèmes…allows us to capture knowledge and make it accessible to anyone who needs it while monitoring our development activity against key performance indicators. Through collaboration, standardization and maximized reuse of data and parts across our engineering operations, we can help our customers to take their businesses above and beyond.
Vice President, Engineering



Future Focused



Unifying its data has provided the company with a platform for continuous improvement in processes and efficiency. As the organization looks ahead, it is expanding the content sources analyzed by OnePart. It is also adding advanced search capabilities for its PLM metadata, and a usability monitor application to see how employees are using the solution and which additional sources should be included. As well as improving visibility into program execution status and allowing the company to capture more data for reuse, the solution will help to ensure that content security rights are accurately mapped between the original systems and the 3DEXPERIENCE platform.



With significantly improved visibility into program execution status and expanded data mining and analysis capabilities, the company continues to increase productivity and collaboration across the enterprise.



“Our organization is powered by endlessly curious people with an unwavering focus on pioneering discoveries that enable our customers to perform beyond expectations and protect what matters most,” said the vice president of engineering. “Dassault Systèmes is helping us to support that mission. It allows us to capture knowledge and make it accessible to anyone who needs it while monitoring our development activity against key performance indicators. Through collaboration, standardization and maximized reuse of data and parts across our engineering operations, we can help our customers to take their businesses above and beyond.”



Learn More Here



Download the eBook to discover more NETVIBES data science solutions in action!
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      <![CDATA[ Boosting Internal and External Customer Satisfaction with NETVIBES ]]>
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      <pubDate>Tue, 13 Feb 2024 10:46:57 GMT</pubDate>
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      <![CDATA[ Learn how NETVIBES data science solutions are helping a leading aircraft manufacturer deliver and repair planes faster, driving happier customers.
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CHALLENGE



Providers of business aircraft must be able to respond quickly to customer requests. Because the company had accumulated diverse data silos over decades, it sometimes took hours to provide support information to customers. And introducing tens of thousands of new product parts per year led to unnecessary duplicates and costs. In order to provide the service level customers expect, the company wanted to be able to leverage the power of its data. With increased volatility and challenges to the global supply chain, it needed to prioritize 1) reducing the cost of goods sold, 2) increasing efficiencies, 3) accelerating time-to-market, and 4) optimizing overall maintenance, repair and overhaul (MRO).



SOLUTION



The company chose NETVIBES data science solutions to optimize its supply chain and improve customer satisfaction. They allow it to aggregate and access data from a single internal application that combines the data from all the systems used daily, such as ERPs, PLMs, CRMs, and all the documents with supporting content linked to clients and products in order to gain information intelligence. Each of the nearly two million parts that make up an aircraft is indexed, as are certifications and all their paper archives in digital format.



BENEFITS



This visibility has allowed the company to increase agility and accuracy while empowering users, resulting in improved efficiency and customer service. Engineering time has decreased, thus the time required to deliver an aircraft to the customer. New part introduction has also decreased by 1% to 3%, leading to a potential annual savings of $2M to $5M. Analytics enable technicians to answer questions in minutes instead of hours, driving faster repairs and happier customers. Providing the right teams access to the right data in only seconds has contributed to business transformation throughout the enterprise.



Data Overload



Aircraft production, usage and maintenance generate exponential amounts of data spread across different systems, such as the ERPs, PLMs, CRMs, and documents. Employees were required to navigate between three to ten systems to research part information during the course of their day. This unorganized data management resulted in frustration and lost time, as people were spending between 30 minutes and two hours daily looking for the right information in a business where speed and accuracy are critical, especially when repairing an aircraft. The company needed to reorganize how it worked to optimize its data management.



Customer Satisfaction Mindset



The company’s clients have expectations typical of high-end luxury business consumers, whether individuals, corporations or governments. “Our customer’s time is money, our customer’s perception is truth and our customer’s satisfaction means our survival,” said the company’s PLM director.Decentralized data management was adversely affecting customer satisfaction. Prior to personalization, a standard aircraft contains nearly two million parts. The company could spend “an embarrassing amount of time to find the part number” for a repair, the PLM director explained. That required long delays during the maintenance process. It was very challenging to prioritize issues and determine what the problem was, where it was located and how to procure the parts to solve it in a timely manner. “Timely access to data is everything…. Customers want accurate information, fast,” declared the PLM director.








Timely access to data is everything…. Customers want accurate information, fast.
&#8211; PLM Director



Connecting the Disconnected



In order to overcome its significant data management challenges, the company chose NETVIBES data science solutions. NETVIBES helps customers reveal information intelligence in order to gain insights based on data to make better informed decisions.Whereas previously employees did not necessarily know what they were looking for, whether it existed or how to find it amongst the many data silos, today they are able to easily access internal and external multisource information. Data is aggregated and streamlined in an internal application, making it available on user-friendly, targeted dashboards to the thousands of users who need it company-wide.



Seamless Part Reuse



The application improves customer satisfaction by helping deliver planes faster. The ability to search for, find and reuse parts is critical. The company had been introducing tens of thousands of new product parts per year, which led to unnecessary duplicates and costs. With queries returned in less than two seconds, NETVIBES artificial intelligence-driven Sourcing &amp; Standardization Intelligence enables designers and engineers to search for parts by 3D geometry, find them quickly and compare them using attributes, such as weight, material, shape, and more, to integrate the right one into their design for improved quality. They’re able to retrieve all data related to parts to track and ensure their certification globally. Thanks to NETVIBES optimized sourcing, new part introduction has decreased by 1% to 3%, leading to a potential annual saving of $2M to $5M.




We&#8217;ve addressed a lot of our supply chain issues.
&#8211; PLM Director



Happier Customers



The NETVIBES business intelligence layer also helps the company perform seamless MRO. Searching for replacement parts could take hours. The application provides visibility into the ecosystem in seconds, speeding turnaround time on quotes and repair. It allows users to check whether parts are in-stock around the world. The ability to procure them quickly and get them to where they need to be is essential for efficient repair. As a result, the Aircraft on Ground resolution time has decreased 36%, boosting customer satisfaction. The company estimates it has achieved 400% ROI for $20M savings. “We’ve addressed a lot of our supply chain issues,” said the PLM director. Analytics enable technicians to answer questions in minutes instead of hours, driving faster repairs and happier customers.



Unlocking the Vault



In addition, the company’s records, including paper and CAD files, were stored in an “engineering vault” stationed in the company’s main manufacturing facility, and maintained by a team of engineering archivists and data analysts. “You would never know it was here, but it is probably one of the more important rooms in our entire manufacturing facility,” said the PLM director. They explain that this room was considered an “aircraft time capsule filled with tubes stacked from floor to ceiling holding seven decades of critical engineering documents, including hand-drawn blueprints of parts, cabin designs, and aircraft drawings. There are hundreds of thousands of documents, including many of the original drawings from the very early days of the company.” If anyone needed information from the archives, they had to search through sometimes fragile paper documents hidden in the basement. Digitizing all of these documents in the application has improved the classification and conservation of the archives, making them instantly accessible.



Knowledge Transfer



NETVIBES data science solutions have added an agility layer above the company’s siloed systems. Employees are empowered to find the information they need when they need it, no matter where it resides. They know that the information is accurate and up-to-date. Instead of searching for data, users are able to spend more time innovating, designing, producing and servicing aircraft more seamlessly. In addition, the application ensures that knowledge is transferred. The company reached its goals of not only improving on-time delivery, but also reducing the cost of goods sold, increasing efficiencies, decreasing development time and accelerating time-to-market. It will continue to work closely with NETVIBES to help meet and exceed its short- and long-term goals of reducing production and operating costs in manufacturing, quality and procurement.



Learn More Here



Download the eBook to discover more NETVIBES data science solutions in action!
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