In the fast-paced world of Industry 4.0, mobility is not just a convenience—it’s a necessity. As businesses strive for greater efficiency, flexibility, and collaboration, the ability to access critical data and tools on-the-go has become paramount. At SmartShape, we understand the evolving needs of modern industries, which is why we’re thrilled to unveil our latest innovation: the SmartShape Digital Twin platform, now optimized for mobility.
Revolutionizing Collaboration with Digital Twins
Digital Twins have emerged as a game-changer in various industries, offering a virtual representation of physical assets, processes, and systems. At SmartShape, we’ve taken this concept a step further, creating a platform that seamlessly integrates with smartphones and tablets, empowering users to access and interact with their Digital Twins anytime, anywhere.
Bringing the Digital Twin to Your Pocket
Imagine being able to review 3D models, analyze operational data, and collaborate with team members—all from the palm of your hand. With SmartShape’s mobile optimization, this vision becomes a reality. Whether you’re on the factory floor, at a client site, or working remotely, our intuitive app ensures that you stay connected and informed at all times.
The Power of Collaboration, Anywhere
One of the most significant advantages of the SmartShape platform is its ability to facilitate collaboration across diverse teams and stakeholders. From contractors and engineers to design offices and project managers, everyone can access the same up-to-date information and contribute to projects in real-time. This level of connectivity fosters greater innovation, efficiency, and agility within organizations.
Enhanced Data Accessibility and Security
By centralizing data within the SmartShape platform, organizations can streamline workflows and eliminate the inefficiencies associated with disparate systems and siloed information. Moreover, our commitment to data security ensures that sensitive information remains protected, whether it’s accessed from a desktop computer or a mobile device.
Empowering Industry 4.0 Transformation
In today’s digital age, success hinges on the ability to adapt and innovate rapidly. With SmartShape’s Digital Twin platform, businesses can embrace the principles of Industry 4.0 with confidence, knowing that they have a powerful tool at their disposal to drive efficiency, collaboration, and growth.
Experience the Future of Mobility with SmartShape
Join us on this exciting journey as we redefine what’s possible in the world of Industry 4.0. Discover how SmartShape’s Digital Twin platform is revolutionizing mobility, collaboration, and data accessibility for organizations around the globe.
At SmartShape, we’re committed to empowering businesses to thrive in the digital era. Contact us today to schedule a demo and see firsthand how SmartShape can transform your operations.
In our relentless pursuit of innovation and enhancing the capabilities of SmartShape, we are thrilled to introduce our latest feature – Snap & Go. This cutting-edge addition to our Digital Twin platform is designed to revolutionize the way you interact with and share your smart Digital Twins.
What is Snap & Go?
SmartShape, as a connected, programmable, and collaborative Digital Twin platform, has always aimed to simplify complex industrial data and enhance visual interpretation. With Snap & Go, we take a giant leap towards making your Digital Twins more accessible, shareable, and portable.
How does Snap & Go work?
Using Snap & Go is as simple as it sounds. Open the SmartShape app on your laptop, select the model, object, or annotation you want to share, and scan the QR code with your tablet or smartphone. In an instant, your smart Digital Twin becomes pocket-sized, ready to accompany you wherever you go.
Key Benefits of Snap & Go:
Efficient Maintenance Execution: Prepare maintenance tasks on your computer and execute them on-site using a mobile device. This feature streamlines the workflow, making tasks more efficient and convenient.
Seamless Collaboration: Instantly share Digital Twins with your coworkers, promoting seamless collaboration and information sharing within your team.
Real-time Adaptability: Add and update annotations in the office during surveys, enhancing the flexibility and real-time adaptability of your work.
Quick Access to Physical Components: Scan a QR code on a physical part to easily access its Digital Twin. This provides quick and direct access to relevant information about the physical component, streamlining your workflow.
How Snap & Go Enhances Your Work:
SmartShape’s Snap & Go feature opens up new possibilities for industrial applications:
On-Site Maintenance: Efficiently execute tasks on-site using mobile devices.
Collaboration: Instantly share Digital Twins, fostering seamless collaboration.
Real-time Adaptability: Update annotations in real-time during surveys for flexible workflows.
Quick Access: Easily access Digital Twins by scanning QR codes on physical components.
Snap & Go is a game-changer, extending the power of SmartShape’s Digital Twins to your pocket. It not only enhances the efficiency of maintenance tasks but also promotes seamless collaboration and real-time adaptability. As we continue to push the boundaries of industrial innovation, SmartShape remains committed to providing solutions that simplify complexity and empower industries to thrive in the digital age.
Experience the future of Digital Twins with Snap & Go – where collaboration meets portability, and data becomes truly accessible. SmartShape, shaping the future of industry 4.0.
In the ever-evolving landscape of Industry 4.0, Aerys proudly presents SmartShape, a cutting-edge, connected, programmable, and collaborative Digital Twin platform designed to transform the way industries operate. SmartShape is set to revolutionize the naval, military, energy, water treatment, and aerospace sectors, providing a unique solution to the challenges posed by the overwhelming complexity of industrial data.
The Birth of SmartShape:
Born out of the recognition that the industrial landscape was drowning in a sea of complex and fragmented data, SmartShape emerged as a visionary solution to consolidate data into a single, collaborative, and responsive space. The goal was simple yet transformative – to make data not only accessible but visually comprehensible through the creation of intelligent shapes.
The Essence of SmartShape:
SmartShape combines 2D models, 2D plans, photogrammetry, business data, code (including processes, instrumentation, data mining, machine learning, and AI), and collaboration tools in a single, intelligent form. Accessible via tablets and web streaming in 3D, SmartShape seamlessly integrates with all major CAD software, sources of data, and operates as an open API based on web standards.
Key Features of SmartShape:
Collaborative and offline modes
Integration of conversational AI
Compatibility with all CAD software
Connectivity with various data sources (PLM, PDM, MES, sensors, etc.)
Open API based on web standards
Availability on web browsers, tablets, and smartphones
Utilization of secure and sovereign hosting
Encryption of data for security
Compatibility with cloud computing
Fight against Digital Duplicates
Real-world Use Cases:
SmartShape has already demonstrated its transformative capabilities in diverse industries. From replacing 2D paper plans at the Chantier de l’Atlantique shipyard to creating a photogrammetric digital twin for Suez’s water treatment network, and assisting Bureau Veritas in transitioning from 2D PDF plans to a collaborative 4D digital twin – SmartShape has proven its versatility and impact.
Unveiling SmartShape in Action:
The recently released video encapsulates the essence of SmartShape in a dynamic and engaging presentation. Let’s delve into the highlights:
Industry 4.0 Revolution: SmartShape is positioned as the connected, programmable, and collaborative Digital Twin platform for Industry 4.0, ushering in a new era of industrial efficiency.
Field Accessibility: SmartShape facilitates defect checks, feedback provision, and assembly process reviews directly in the field using smartphones and tablets.
Single Documentation Repository: A unique repository is created for all documents and 3D models, enabling the tracking of relevant data throughout the project lifecycle.
M.E.P Engineering: SmartShape aids M.E.P engineers in monitoring asset networks, preparing maintenance operations, and planning procedures in Virtual Reality.
Collaboration Hub: SmartShape serves as a collaborative platform shared among contractors, design offices, and other stakeholders, ensuring real-time collaboration.
Single Source of Truth: Combining all data in one place, SmartShape connects 3D models to business data, creating a unified and intelligent product shape.
Multi-screen Availability: Accessible on all screens, including Virtual Reality and Augmented Reality, SmartShape fosters real-time collaboration, enhancing team agility.
SmartShape is not just a digital twin; it’s a revolutionary force that reshapes how industries perceive and utilize their data. Aerys’ commitment to the cause of advancing civilization through sustainable software solutions is embodied in SmartShape, a tool that empowers industries to thrive in the era of Industry 4.0.
Explore the transformative power of SmartShape – where innovation meets collaboration, and the digital twin evolves into an intelligent and indispensable asset for the industries of tomorrow. Visit our website and watch the video to witness SmartShape in action – a game-changer in the world of digital twins and industrial innovation.
The management of sewage networks is a vital activity for society. The operation, maintenance, and upkeep of these critical infrastructures engage about 35,000 workers in France: sewer workers, electromechanics, hydraulicians, electrotechnicians, cleaning specialists, engineering offices, surveyors, inspectors, etc. When working in sewers, these individuals are exposed to significant health risks (falls, drownings, respiratory distress, etc.).
To reduce these risks and improve the management of its sewage networks, the City of Paris has undertaken, through a public contract, to model in 3D more than 40 km of galleries (which is ⅙ of the network). As part of this tender, the company SEMERU – a subsidiary of the FAYAT group – and SmartShape have demonstrated the possibilities offered by 3D modeling and digital twin technology. We reveal the behind-the-scenes of this project in the service of the public interest.
SEMERU: Technological Innovation at the Service of Society
A subsidiary of the energy branch of the Fayat group, the company SEMERU specializes in the development and integration of digital solutions and brings its expertise in several areas:
Environment: design, integration & maintenance of systems
Facility Management Technology: management of general services
Transport: technological & sustainable vision of people mobility
Smart City: management of technologies & control of flows
Acquisition, processing, and use of 3D data from the sewage network
The public tender opened by the City of Paris was related to the acquisition, processing, and use of 3D data for the Parisian sewer network. To demonstrate the relevance of its solution, SEMERU undertook the modeling of a part of the Paris sewers. To do this, it started by sending an acquisition team comprised of individuals all holding the CATEC certification (certificate of aptitude for working in confined spaces).
On the day of the intervention, after verifying on dedicated software that there was no lockout on the network, and after securing the perimeter on the surface, the team descended into the galleries with the acquisition equipment and progressed through the network to take a large quantity of photos. This is what photogrammetry entails, a technique allowing for the 3D digital modeling of an object or place.
As it progresses, the team conducts further measurements – including planimetry and altimetry – to locate the shots in space.
Photogrammetry: A Technique for 3D Modeling
Photogrammetry is a measurement technique consisting of determining the shape, dimensions, and position of an object in space from multiple images taken from different angles.
Mimicking human stereoscopic vision, it uses parallax, which is the difference between the viewpoints of the images, to reconstruct the relief of the scene or object. With technological evolution, this method has adapted to digital images, making possible a faithful 3D modeling of reality. This accuracy is achieved through rigorous modeling of the geometry of the images and their acquisition.
Reconstruction of a 3D model of sewers and a wastewater treatment plant in SmartShape
Once the on-site intervention is completed, SEMERU processes the photos and aligns them so that they are correctly positioned and georeferenced. After verification, it is finally possible to launch the production of the high-resolution meshed 3D model with SmartShape.
In parallel, SmartShape has integrated the 3D data of a wastewater treatment plant managed by Suez and connected to the network modeled by SEMERU. The created model results from the hybridization of two modeling techniques: photogrammetry for the sewer network (over 400 km) and 3D scanning for the wastewater treatment plant.
Simplify and secure on-site interventions with SmartShape
The solution proposed by SEMERU and SmartShape greatly simplifies interventions. Indeed, the 3D model incorporating part of the sewer network as well as a wastewater treatment plant allows all stakeholders to carry out virtual tours of the structures to visualize the equipment in place and move around in the collectors.
The ability to virtually visit the sewers is enhanced by collaborative features developed by SmartShape, allowing maintenance teams to safely prepare their on-site interventions.
Collaborative virtual tour of the sewers
Before an intervention in the Parisian sewer network, operators have the ability to connect to the 3D model in SmartShape and conduct their virtual visit together. The avatar of the first operator appears on the screen of the second, and vice versa: they can see each other and follow each other in the 3D model as if they were on site. They identify potential risks and anticipate the tasks to be carried out to perform a safe and efficient intervention.
Collaborative features
“SmartShape provides operators with collaborative features to enrich the 3D model, which they can annotate during their virtual visit. Annotations appear in real time on the screen of each connected operator. Then, each annotation turns into a geo-referenced discussion within the 3D model: operators can enrich the model with their comments and ask questions.
Moreover, the annotations made by the operators are accessible for all subsequent visits. They can thus be used by the Technical Water and Sanitation Service (STEA) to establish safety instructions or to warn of a risk.
The demonstration carried out by SEMERU and SmartShape within the framework of the modeling project for the Paris city sewage network highlights the possibilities offered by the use of a 3D model within a collaborative platform. The result is unequivocal: professionals working in this network now have an effective and sustainable tool to help them accomplish their missions with limited risk.
As a global leader in certification, Bureau Veritas has chosen SmartShape to digitize its ship classification process. The multiple back-and-forths with design offices are a thing of the past; the certification body now performs ship classification based on a single 3D model.
Bureau Veritas: A Global Player in Certification
Founded in 1928, Bureau Veritas (BV) is a company specializing in testing, inspection, audit, and certification. It operates across numerous sectors such as agri-food and agriculture, infrastructure and construction, health, raw materials, energy, and shipbuilding.
With a presence in 140 countries, BV has 84,000 employees, of which 2,600 work in the Marine & Offshore activity. Their role is to ensure the compliance of ships (both under construction and in service), offshore platforms and units, as well as maritime equipment.
BV Marine & Offshore contributes to safety at sea and provides technical expertise to assess and manage risks and improve the performance of its clients.
Addressing the Challenge of Information Sharing in the Classification Process: The Case of Chantiers de l’Atlantique
BV Marine & Offshore assists the design offices of Chantiers de l’Atlantique in the classification (design verification) of its marine assets. The key outcome is the acquisition of operating licenses for these assets and the assurance of their operational efficiency and compliance with international regulations.
This phase is critical as the consequences of poor ship design can be severe: high operating costs, reduced operational lifespan, accident risks, etc. That’s why stakeholders in this type of project (builder, shipowner, insurer, etc.) trust BV’s expertise to guarantee the quality of the ships.
As part of the classification process for ships under construction, Bureau Veritas experts are tasked with analyzing plans designed by naval construction engineers. However, the complexity of these projects places the issue of information sharing at the heart of the classification process.
Optimizing the Classification Process (Design Verification)
The classification process mainly relies on the review conducted by experts during the design and shipbuilding phases. Before using SmartShape, BV operated through an iterative loop process with Chantiers de l’Atlantique:
The shipyard’s design offices produce their 3D models in CAD.
These 3D models are converted into 2D blueprints and transmitted to BV.
BV performs its analyses and calculations and then sends the updated blueprints back to the design offices.
The design offices produce new 3D models.
These new models are in turn converted into 2D blueprints and sent back to BV for analysis.
Etc.
This process is particularly lengthy since it involves producing new versions of the documents (3D models and 2D plans) at each step. Moreover, this abundance of documents requires ensuring that every project participant has access to the correct version of the document, which mechanically increases the risk of errors due to poor synchronization.
The adoption of SmartShape has enabled Bureau Veritas Marine & Offshore and the Chantiers de l’Atlantique to rethink information sharing and to radically simplify the classification process by carrying out all operations on a single 3D model.
Perform classification on a single 3D model
Bureau Veritas is the first classification society to do away with 2D plans. With SmartShape, the classification process is conducted directly on the 3D model: all experts – regardless of their discipline – work on the same model at the same time.
BV Marine Offshore performs its calculations and analyses directly on the 3D model designed by the Chantiers de l’Atlantique. The fact that there is no need to generate a blueprint significantly speeds up the process, both for the shipyard and for BV.
Furthermore, SmartShape serves as a unique, persistent repository that aggregates all project data in real-time. BV and its clients share a single source of truth, which improves product quality by avoiding the inconsistencies inherent in multiple drawing revisions.
Optimize collaborative work on the 3D model
Working on a unique 3D model facilitates collaboration between BV experts and its clients, taking into account existing tools and processes.
A universal solution and a custom configuration
SmartShape has adapted to the specificities of the IT ecosystem of Bureau Veritas, especially in terms of collaboration and document management. In this case, it was essential to link SmartShape to its Document Management System (DMS) which is not designed for 3D plan visualization.
SmartShape has configured and integrated the tool so that BV can use the 3D model and its DMS software in parallel. Experts can thus easily communicate information to clients, who view the comments directly on the 3D model.
“The use of the 3D model improves the quality of data and exchange with our clients. Thanks to this, we save time and enhance the sharing of information among the various project stakeholders. On the shipyard side, the classification process avoids the generation of 2D plans and thus reduces the workload of the shipyard and the associated costs.” According to Olivier Degrand, Naval and Offshore Structural Engineer at Bureau Veritas.
In its approach to 3D classification, Bureau Veritas introduces a new concept called “BV Classification Status,” which indicates for each element, the progress of the design review in real time. With the color code in the SmartShape viewer, designers or shipyards can easily identify whether the design complies with Bureau Veritas rules or not.
SmartShape: a solution dedicated to industry stakeholders
SmartShape enhances information sharing and collaborative work efficiency by combining 3D modeling, collaborative platform, and digital twin technologies.
SmartShape meets the specific needs of industrial enterprises:
A self-hosted solution that combines the agility of SaaS with the security of On-premise environments.
A universal and customizable solution: SmartShape supports over 50 file formats in 2D and 3D (both standard and proprietary) and integrates with all IT environments. Its open API (with over 75 endpoints) allows you to program the platform according to your needs (files, configuration, attributes, etc.). Furthermore, the SmartShape 3D engine is open source, ensuring transparency and benefiting the longevity and security of your project.
A 3D model incorporating all data produced by project participants via the SmartShape API (3D files, 2D blueprints, photogrammetry, point clouds, Excel, etc.). The assembly of this information forms the shape of your project. During the operational phase, data captured on the asset is transmitted to the model, turning it into a true digital twin.
A tool that integrates all your business processes (plan review, quality, progress, testing, etc.) to add a layer of intelligence (smart) to your model.
A real-time collaborative platform: when annotations or enhancements are made to the model, all teams have immediate access.
An offline mode for accessing sometimes very large 3D models in environments without internet access (e.g., within the metal structure of a ship or in the basements of an infrastructure).
Military-grade encryption to protect sensitive data.
Support throughout your engineering project by a team of experts.
With SmartShape, Bureau Veritas has profoundly transformed its classification process by simplifying information flows with Chantiers de l’Atlantique. The time savings and quality improvements benefit everyone, throughout the life cycle of the ships.
This leap forward made by major industry players attests to the relevance of SmartShape in meeting the challenges of information sharing in industrial projects.
Digital transformation is a path paved with difficulties, but it’s the only possible way to avoid falling behind the competition. In the industrial sector, the obstacles are proportional to the promises of Industry 4.0 and the plethora of underlying technologies: IoT, AI, virtual reality, blockchain, digital twin…
However, before being a technological issue, digital transformation is primarily based on the human factor and the diffusion of a culture of innovation, as well as on informed strategic choices.
Putting the human factor at the heart of every transformation project
Understanding and Overcoming Resistance to Change
The biggest mistake one can make in the context of a digital transformation project is to neglect the importance of the human factor in its success. Reducing a project to its technological components amounts to omitting a fundamental variable from the equation: human psychology. Because in the end, it’s the team members who will bring to life the tools, methods, and processes that you put in their hands. In other words, the success of the project as a whole largely depends on how well you’ve managed to gain everyone’s support.
The enemy of innovation in business is resistance to change. And to defeat this adversary, it is essential to identify it in all its forms and understand its mechanisms. Here is a non-exhaustive list of obstacles you must overcome to make an innovative project successful in a business setting:
Lack of consultation: The feeling of having no say in the digital transformation process can generate resistance. To avoid this, it is important to involve employees from the beginning of the process, for example during the demonstration of a digital tool. This can strengthen their sense of belonging to the company and their commitment to the solution.
Bad communication: Knowing how to get a message across to a team is an art that must be mastered to ensure successful change management. Team members need to understand the ‘why’ and the ‘how’ of a project in order to buy into it. What is the objective of this project? How will it affect their daily work? Open, honest, and regular communication can help overcome this barrier.
Fear of the unknown: It is natural to be wary of what we do not know. To counter this fear, it is essential to continuously educate team members about new tools and methods.
Mistrust towards a technology: ‘gadget,’ ‘fad,’ ‘mirage’… an innovation is not fully accepted until its added value is demonstrated. To overcome this healthy skepticism, demonstrations and trials are better than long speeches.
Lack of skills: The arrival of a new tool can create a feeling of discomfort, particularly among employees who are less receptive to digital technology. And for good reason, no one likes to feel overwhelmed. Appropriate training and ongoing support are essential to help employees acquire the necessary skills..
Lack of stability and fatigue: innovating does not mean ‘flip-flopping.’ Digital transformation requires a certain level of stability to avoid creating a fatigue of change. To limit this resistance, it is essential to introduce changes in a gradual manner.
In industry as well as in other sectors, it is essential to understand the psychological barriers that hinder individuals’ acceptance of change. At the organizational level, and from a structuring perspective, digital transformation involves establishing a culture of innovation.
Establish a culture of innovation
Adopting new technologies is not limited to acquiring tools or technical skills; it also involves changing mindsets and work habits. And this change starts with leadership: the senior executives of the company or of a multi-stakeholder project must be committed to innovation by supporting innovative initiatives, valuing new ideas, and encouraging risk-taking.
More broadly, establishing a culture of innovation requires encouraging each member of the company to consider the possibilities offered by digital technology and to contribute to their implementation. This means creating an environment where new ideas are valued, experimentation is encouraged, and failures are seen as learning opportunities rather than faults.
To do this, it is essential to raise awareness and train employees in digital innovations. Workshops, seminars, and training courses can be organized to enable employees to discover and understand new technologies, their challenges, and opportunities.
Develop a digital strategy to address the challenges of Industry 4.0
In the face of the economic challenges of digital transformation, industrial companies cannot afford to navigate blindly. Developing a digital strategy is essential for having a clear understanding of the investments to be made and the actions to put in place to make them profitable through teams.
Prioritize projects that maximize return on investment
Digital transformation is a process that can be extremely costly in terms of time and resources. In this context, making poor investment choices can prove to be detrimental. That’s why it is crucial to prioritize projects that offer the best return on investment. This strategic approach begins with an objective evaluation of the current state of the company and the identification of high-potential use cases.
In this perspective, the focus should be on technological tools that optimize the dissemination of information and collaborative work, which are two major areas for improvement in industrial projects across all sectors. Through these types of tools, the strategic objective should be to catalyze operational efficiency. Collaborative platforms, real-time information management systems, and intelligent automation technologies, for example, can reduce errors, increase response speed, and improve overall productivity.
The implementation of collaborative solutions can eliminate communication bottlenecks and improve coordination between teams. This allows aligning everyone’s efforts toward common goals and improving operational efficiency. Additionally, increased transparency and real-time access to information enable quicker and more accurate decision-making.
Similarly, the integration of AI-based automation tools allows for the identification and elimination of inefficiencies in existing processes. This type of technology can help your teams analyze performance data in real time to identify problems before they become critical, thereby reducing the risk of errors and time loss.
Supporting transformation by accompanying the teams.
In any case, for digital transformation investments to bear fruit, dedicated support for teams is essential. This first involves promoting the dissemination of the skills required for the implementation of adopted solutions. Depending on factors such as cost, time, and the complexity of the technology to be adopted, this may require the hiring of new talents or the training of existing teams in the use of these new tools.
Next, the judicious allocation of resources—whether human, material, or financial—is an essential condition for facilitating the implementation of digital transformation. This requires anticipating future needs, strategically planning expenditures, and ensuring that all resources are employed in the most efficient manner.
The digital transformation in the industry relies primarily on the human factor and the dissemination of a culture of innovation, as well as on a clear strategy. To make the most of technologies such as AI, collaborative platforms, digital twins, or virtual reality, it is essential to focus on return on investment and to overcome resistance to change by involving teams in this transformation.
98% of industrial companies launched projects based on digital technologies in 2022. At the same time, only 44% of them have seen results (a figure that has been steadily declining since 2019). This gap highlights the increasingly stringent demands of companies with regard to digital transformation and a growing pragmatism towards Industry 4.0.
Industrial digitization is a given, but in the face of numerous constraints and uncertainties in the global context, manufacturers carefully evaluate the relevance of investments in digital technologies and must ensure the profitability of a project before implementing it. Focus on the main benefits of digital technologies for industry throughout the project lifecycle.
Surmonter le mur invisible entre le concept et la réalité
The most profitable digital technologies are those that provide industrialists with solutions to the most costly problems. These include errors, delays, document synchronization issues, and the resulting inconsistencies, as well as communication difficulties among stakeholders. These problems create an invisible wall between concept and reality. The good news is that this wall is not insurmountable.
Visualize the entire project through multidimensional modeling
Traditional 2D or 3D plans have their limitations. They certainly offer a spatial perspective of industrial equipment, but often fail to capture its complexity, its interaction with the environment, and the project in which it is involved. This is where multidimensional modeling comes into play.
Today’s digital tools allow for the integration of all dimensions of an industrial project. Not only do they take into account the spatial dimensions (X, Y, Z) of the equipment, but they also include time, budget, materials, thickness, among others. With these multiple dimensions, project management and task planning become much more efficient, which results in:
Time savings,
a reduction in errors and inconsistencies
an improvement in the overall project design.
Multidimensional modeling is not limited to providing a static representation of project data. It also allows for dynamic visualization, where the user has the freedom to adapt the display according to the specific task at hand and its unique features. This is a major asset for deep understanding and agile manipulation of complex projects.
Furthermore, immersive visualization represents another major advancement made possible by augmented reality and virtual reality. This technology makes information easily accessible, particularly for on-site operators who benefit from assistance in their tasks. In this way, they can navigate and interact with project data in an intuitive manner, thereby enhancing their engagement and efficiency.
Promote the dissemination of information and collaborative work
Traditional methods of industrial project management present significant challenges in terms of information dissemination and collaborative work. Information is often fragmented, versions can become desynchronized, and redundancies and inconsistencies are common, not to mention issues of compatibility and interoperability.
In this context, digital tools offer the possibility of simplifying project management by centralizing information and fostering better communication and smooth coordination. The digital twin, in particular, represents a major innovation in information management. By unifying all data sources and providing real-time visualization of changes, it facilitates information sharing, rapid iteration, and a better understanding of the project. This helps to avoid costly mistakes and delays, thereby promoting faster project completion.
These technologies prove to be extremely cost-effective in the long term: they contribute to better productivity, cost reduction, and faster project completion, offering a significant return on investment.
Automate the production processes
The automation of production processes using digital technologies, particularly AI and digital twins, is a cost-effective investment due to its optimization potential. For example, in aeronautics, AI applied to a digital twin can model and optimize the entire manufacturing process, creating an iterative loop of improvement.
Firstly, technical information is integrated into the digital twin. Sensors installed on the production line then collect real-time data, which is incorporated into the digital twin to enrich a machine learning algorithm. This AI is capable of predicting production performance, identifying potential problems, and suggesting improvements. These recommendations are implemented, performances are evaluated, and the results are used to improve the accuracy of the AI.
This cycle of continuous improvement, enabled by automation, leads to an increase in production efficiency and a decrease in errors, offering a significant return on investment through cost reduction and improved productivity.
Facilitate the MRO of industrial equipment
Beyond design, digital tools are relevant during the construction and operation phases of industrial equipment in that they help prevent risks and enhance safety on construction sites. For example, AI can analyze real-time data to identify potential hazards and suggest preventive measures, benefiting both employees and the longevity of the industrial equipment.
Digital technology is revolutionizing the operational readiness (MCO) of industrial equipment by generalizing automated preventive maintenance. The fundamental technology of this revolution is the digital twin. A virtual replica of an industrial equipment, it continuously collects operational data from its real-life counterpart. This data can include measurements such as temperature, pressure, operating speed, and other critical variables.
Coupled with AI algorithms, the digital twin can analyze this data to detect trends or anomalies that might indicate a potential failure. For example, a sudden rise in temperature or an unusual fluctuation in pressure could be early warning signs of a breakdown. AI can then flag these issues upstream, allowing maintenance teams to intervene and resolve the problem before a failure occurs.
By anticipating problems before they become costly breakdowns, these digital tools reduce operational maintenance costs. The savings achieved through reduced downtime and repair costs make it a long-term profitable investment.
The search for profitability guides the orientations of industrialists in the field of digital transformation. In this regard, investing in Industry 4.0 digital technologies brings tangible benefits. The improvement of project visualization, collaboration, process automation, and predictive maintenance contribute to increased efficiency, cost reduction, and a better return on investment.
*Source: Industry 4.0 Barometer, Wavestone, Bpifrance, France Industrie, 2022 Edition
Digital tools offer businesses in the industrial sector opportunities for optimizing business processes, which are essential to integrate in order to increase the profitability of projects and remain competitive.
However, the organizational changes brought about by digital transformation present challenges if the specificities and constraints of the industry are not properly taken into account. That’s why it’s essential to address the organizational challenges of digital transformation to successfully combine industrial heritage with innovative solutions.
Addressing the organizational challenges of digital transformation.
The mistake made by many companies is to reduce digital transformation to a technological issue. It is primarily an organizational challenge that can be addressed by first modeling business processes.
Digital transformation: much more than just a technological issue.
Digital transformation is not just about adding new technological tools; it’s primarily about deeply evolving business processes and the organization of the company as a whole. It’s a complex process that can cause frictions if not steered in the right direction and properly implemented. In this regard, the human factor and the desire to spread a culture of innovation are at the heart of any digital transformation project.The frictions that can arise from integrating digital technology often come from the fact that traditional industrial processes have unique specificities and constraints:
Strict regulations: Safety, quality, and environmental standards can hinder the adoption of new technologies.
Precision and reliability: Technological failures can result in significant costs and safety risks, making the adoption of unproven new technologies challenging.
Data security and protection: The integration of new digital technologies increases the attack surface for companies, thus leading to potential security and data protection issues. This challenge is especially significant for companies dealing with sensitive information. Therefore, any digital technology must be carefully assessed and secured to minimize these risks.
Process complexity: Industrial processes can be extremely complex, involving many steps, machines, and employees. This complexity requires careful planning and change management.
Capital invested in existing equipment: Industrial companies have often invested significant amounts in their existing equipment and infrastructure. Therefore, the return on investment for modernizing equipment and infrastructure must be demonstrated.
Business process modeling in support of organizational changes.
In order for the integration of digital technologies to improve the profitability of your industrial company, it is essential to consider how you can transform your business processes. To do this, the first step is to have a clear vision of these processes by modeling them accurately and comprehensively. This process modeling (or workflow) allows for the representation and understanding of all tasks, stages, and resources (human, financial, and material) that make up each process.
Take the example of a maintenance process in the aerospace sector: traditionally, regular inspections, often based on predefined time intervals or flight hours, may require the aircraft to be taken out of service, resulting in downtime costs. By modeling this workflow, optimization opportunities can be identified. A digital twin (an exact virtual replica of the plane) allows for real-time monitoring of the performance of all the aircraft’s systems. If a deviation from expected performance is detected, an alert is generated, thus accurately targeting maintenance operations. By avoiding unnecessary inspections and anticipating potential failures, the use of the digital twin can improve maintenance efficiency, reduce downtime costs, and enhance profitability.
Successfully bridging industrial heritage and digital transformation.
The pursuit of profitability is the driving force behind any digital transformation project. To ensure this profitability, it is essential to target the processes to be optimized, to include transformation actions in a roadmap, and to provide the means for this transformation by forging partnerships.
Target the business processes to optimize.
To improve the profitability of a digital technology industrial project, the first step is to identify the friction points in business processes: loss of time, errors, inconsistencies, duplicates, communication difficulties, etc. Digital technology is justified as soon as it solves a clearly identified problem and this optimization is profitable. In other words, digital transformation should be driven by the desire to solve problems in business processes and by a constant search for return on investment.
The digital twin technology can be used to optimize several business processes throughout the lifecycle of an industrial product. In the aerospace sector, for example, the digital twin transforms the processes at work during the design phase, replacing tests with simulations, especially to anticipate the behavior of components and the system as a whole under various scenarios. The digital twin also optimizes processes related to manufacturing, assisting in decision-making based on the characteristics of the project (time/budget constraints, availability of stakeholders or materials, regulatory constraints, etc.). Similarly, a digital twin transforms the processes related to keeping operational (MCO) by integrating preventive maintenance. These organizational changes reduce costs and improve the profitability of the industrial project.
Create a roadmap for digitalization.
Once these application areas are identified, it is crucial to develop a roadmap to guide digital transformation. This roadmap should define the key steps of the transformation, the technologies to implement, the necessary resources, and the performance indicators to monitor in order to measure the effectiveness and impact of the digital transformation in the company.
The development of this roadmap is based on the analysis of existing industrial processes and the expected effects within the context of integrating digital technologies. For example, in the case of a nuclear power plant, the roadmap for the implementation of a digital twin would include the following points :
Initial Assessment: Identifying business processes altered by technology (monitoring reactors, maintenance of cooling systems, etc.)
Objectives: The project should target SMART (specific, measurable, achievable, relevant, time-bound) objectives. This could be a reduction in unplanned downtime or an extension of equipment lifespan.
Design of the Digital Twin: This phase depends on the specifics of the project because the deployed tool must be customized. In any case, it is essential to model the business processes to optimize and connect to all the project’s data sources.
Implementation: Integrating the digital twin into the project involves tasks such as deploying sensors, establishing data connections, or training staff on the tool’s use.
Continuous Evaluation: After implementation, monitoring of KPIs is necessary to ensure that the digital twin operates as expected and delivers the anticipated benefits.
Establish strategic partnerships to accelerate innovation
Forging partnerships with digital solution providers is a wise decision to successfully merge your industrial legacy with the digital world. Such collaborations can grant access to invaluable technical expertise, offer co-innovation opportunities, and help overcome the inherent challenges of digitalization. It’s also a way to foster a culture of innovation within the company, stimulating idea sharing and mutual learning. In this light, it’s crucial to choose partners who share your vision of innovation and have a deep understanding of digital technologies and their applications in the industrial sector.
The digital transformation of industrial processes is essential for improving the profitability of projects. Through process optimization, digitalization brings greater efficiency, better anticipation of problems, and opportunities for innovation. However, to successfully merge industrial heritage with digital innovation, one must follow a clearly defined strategy and skillfully combine business and IT expertise.
Information sharing is at the heart of the digital transformation of businesses, and this issue is particularly pressing in the industrial sector: given the avalanche of data that each industrial project generates, traditional methods designed around the concept of documents prove to be ineffective. Managing complexity requires a more agile approach.
To avoid the pitfalls of information fragmentation in industrial projects, it is necessary to rethink information sharing and move from exchanging documents (paper or digital) to collaborative work on a digital twin. Focus on a fundamental issue for the management of industrial projects.
From data silos to information fragmentation.
The volume of data produced within the framework of an industrial project is immense. Historically, this data produced for an industrial project only existed in paper form: specifications, project description, budgetary status… and of course the drawings and models, among which we find the famous blueprints.
The development of computing has transformed the management of information in industrial projects, bringing as many solutions as new problems. The generalization of 3D modeling has greatly enriched the design phase, but has led to a multiplication of file formats: OBJ, FBX, COLLADA, 3DS, IGES, STL, OCX, 3DXML… to name just a few! The reason for this is the profusion of software on the market, meeting the varied needs of all industrial sectors.
In parallel with this digital expansion, the paper document still exists. For example, during the classification phase, the 3D models created in CAD are transposed into 2D blueprints for analysis and calculations, which then lead to new 3D models, which are in turn transposed into 2D… These lengthy iterative processes between design offices and classification bodies multiply the number of versions, and therefore the design time and the risk of errors.
In short, digital transformation has resulted in the development of data silos, leading to information fragmentation. For these reasons, information sharing in industrial projects is characterized by great complexity: data of heterogeneous quality are locked away in countless file versions, which are scattered throughout the information systems of the project’s participants.
The solution to this problem lies in rationalizing information sharing. This is precisely what a collaborative digital twin allows to do.
The collaborative digital twin: the cornerstone of the “paperless” construction site
The digital transformation of industrial project management goes far beyond the issue of paper or computer support for documents. Beyond environmental issues in which the “paperless” goal is set, it’s about addressing the challenges of information sharing and facing the challenges related to the complexity of modern industrial sites.
From this perspective, the digital twin, designed as a collaborative work platform, represents a paradigm shift in information management within industrial projects.
A persistent single repository: a single source of truth.
Designed as a single workspace, the collaborative digital twin integrates all project data, regardless of their producer and format. Design offices, subcontractors, suppliers… all project stakeholders enrich the digital twin with the data they produce.
And since there is only one digital twin that is updated in real time, it serves as a persistent unique reference. All users view the same copy and constantly work on the “original”, considered as the single source of truth.
The lack of fragmentation over time ensures that the consulted data is always up to date: each party can work in parallel without creating any “interference” on the digital twin. This approach also eliminates the problem of dead data: all additions and enrichments are made directly in the unique repository.
Finally, organizing an industrial project on a collaborative digital twin allows data to be centralized and therefore protected against risks of loss, theft, or accidental or intentional destruction, thus providing guarantees of continuity and confidentiality.
Visualize all dimensions of the data.
Unlike traditional methods of information sharing, the digital twin allows for visualizing all dimensions of a project. While paper is limited to 2D and digital documents to 3D, the digital twin incorporates all project dimensions: spatial dimensions (X, Y, Z), but also time, budget, materials, thicknesses, etc. The collaborative digital twin is not just an evolving 3D model; it’s a platform integrating all project data.
This multidimensional approach to the industrial project provides dynamic visualization: the user chooses the display modalities based on the task at hand and its specifics. The collaborative digital twin also paves the way for immersive visualization, allowing non-technical operators on-site to view information they need in augmented or virtual reality.
Unlocking the potential of real-time collaborative work.
The collaborative digital twin reveals the true potential of collaborative work. By allowing direct exchanges between the different stakeholders, it breaks down traditional silos and maximizes the quality of the information exchanged. The result?
This organization encourages direct exchanges in the form of quick iterations and maximizes the quality of the information exchanged. The absence of duplicates significantly reduces repetitions, errors, and rework, leading to a notable optimization of operational efficiency.
The digital transformation of the industrial sector is not just about moving from paper to digital. It calls for a rethinking of information management. The collaborative digital twin, by offering a unique and reliable source of data, allows us to surpass the limitations of traditional methods. Its ability to integrate and visualize all dimensions of a project, combined with its potential for real-time collaborative work, make it a valuable tool to remain competitive and meet the challenges of Industry 4.0.
Succeeding in your multi-stakeholder industrial projects: the key role of information sharing.
At the heart of multi-stakeholder industrial projects lies a key challenge: information sharing. Navigating the ocean of big data is a titanic challenge, but it is necessary to meet it to avoid the unfortunate consequences of fragmented information: redundancies, inconsistencies, errors, interoperability issues… and the inevitable time losses and additional costs that result.
Fortunately, there are solutions to address these challenges and implement sound and efficient information management. In this perspective, digital solutions – with the digital twin at the forefront, offer immense potential to support industrial project managers.
The challenges of information management.
The complexity of information sharing in industrial projects
The success of a complex industrial project relies on effective information sharing among countless stakeholders. From the project manager to the subcontractor, through design offices, classification bodies, and suppliers… These actors generate multiple flows of document and information exchanges (2D and 3D plans, technical specifications, spreadsheets, test results, quality reports, etc).
Furthermore, actors in these types of projects often operate in silos, each using their own tools and data formats. From spreadsheets to 3D design tools, through specialized document management systems, each stakeholder has their preferences, adding an additional layer of complexity.
In summary, the complexity of information sharing is proportional to the number of stakeholders involved and the diversity of data produced. However, the complexity of information flows is a major problem that, if not seriously addressed, can lead to potentially serious errors.
The pitfalls of poor information management.
A poor management of information in the context of an industrial project results in a lack of fluidity in exchanges between stakeholders. We have identified the typical pitfalls encountered in this type of project:
Data silos and information fragmentation
If we reduce an industrial project to the sum of the data produced by each participant, one could say that no one fully knows the project. Each participant holds a piece of the puzzle in their information system, but the compartmentalization of data hinders the effective dissemination and use of data, so no participant has a complete view of the project.
This fragmentation of information is exacerbated by the diversity of systems and software used, as well as the variety of file formats. It gives the impression that not one, but several parallel projects are being built. In summary, although the information produced is more comprehensive and accurate than ever, its utilization proves particularly challenging.
Redundancies and inconsistencies
As the project progresses, documents, especially drawings and designs, are constantly revised. This proliferation of documents and versions can lead to a lack of synchronization, leaving stakeholders working “blindly,” unaware of the progress of other teams.
This situation is conducive to mistakes and inconsistencies. For instance, if a design change is not properly communicated, it can lead to delays and cost overruns, such as ordering unsuitable materials or the need for costly and time-consuming adjustments. Proper management of these issues of duplication, redundancy, and version synchronization thus becomes essential for the successful completion of the project.
Compatibility and interoperability issues.
Interoperability is a crucial issue in information management. However, it is challenged by the diversity of tools and data formats used. For example, an engineering team might work with specific 3D modeling tools, while another team might prefer a particular task management software. These tools can generate files in different formats, not recognized by other systems.
This lack of interoperability creates a barrier to the smooth exchange of information. If a team cannot open an important file because they don’t have the right software, it can slow down the project. Likewise, if data cannot be integrated from one system to another due to incompatibilities, it can lead to a loss of crucial information, misunderstandings, and delays in completing the project.
Improving information management through digital means.
Now that we have identified the problem and its consequences, let’s explore how digital tools, especially the digital twin, improve information management.
The benefits of optimized information management.
Digital transformation solves problems and creates new ones. The good news is that it can also provide solutions to these new problems. Here’s a brief overview of the benefits that digital technology can offer: Smooth exchanges and mutual understanding: Collaborative platforms such as Microsoft Teams are useful for allowing stakeholders to share files, chat in real time, and organize virtual meetings, thus promoting better coordination.
Visualization of the overall project progress: project management software such as Jira or Asana offer interactive dashboards and task tracking features, allowing each stakeholder to visualize the progress of the project in real time.
Anticipating problems: Data analysis tools like PowerBI or Tableau are efficient. These tools allow for extracting relevant insights from project data and generating preventive alerts to signal potential issues.
More effective decision-making: Business Intelligence tools like QlikView or SAP BI centralize information and present it in an understandable form, thereby facilitating data-based decision-making. For instance, detecting a cost increase might prompt a review of certain procedures to optimize spending.
All these tools provide concrete solutions to the problems posed by information management within an industrial project context.
However, one might be tempted to think that multiplying tools equates to feeding the problem by adding complexity. But this overlooks the digital twin technology, which allows for the unification of all tools and data sources.
The digital twin: a revolutionary tool for information management in industrial projects.
The digital twin technology represents a significant leap in information management within the industry. A digital twin is much more than a simple 3D replica. It includes the physical aspects of a product, as well as all project variables (time, budget, materials, thicknesses, etc.).
Unlike traditional methods of information sharing which can suffer from access and synchronization issues, the digital twin centralizes all project information on a single platform. When a participant adds information to the digital twin, all other stakeholders are instantly informed. This approach eliminates concerns about document versions and ensures constant updating of the model.
The collaborative potential of the digital twin goes beyond simple coordination. It facilitates exchanges between all parties involved and allows for effortless iterations. By providing a complete view of the project in all its aspects, the digital twin promotes a better understanding and more informed decision-making. At each stage, it provides stakeholders with all the necessary information to make the most judicious decisions and actively participate in the project’s progression.
Multi-stakeholder industrial projects require optimized information management to avoid fragmentation, redundancies, inconsistencies, and interoperability issues that arise from the complexity of such projects.
The adoption of the digital twin centralizes and simplifies this information sharing, promoting smooth collaboration, a better understanding of the project, and informed decision-making.
Technical progress inexorably transforms industrial professions: some emerge while others reinvent themselves or disappear. This process has been amplifying and accelerating since the end of the 20th century with the development of industrial computing. With digital transformation, we are shifting into high gear.
Among all the digital technologies being deployed in the industrial sector, digital twins and artificial intelligence (AI) hold a predominant place. Enhanced design, predictive maintenance, process automation, decision-making support… the benefits of these innovations are numerous, provided they are integrated into professions. Through this article, we provide you with some insights on how to reconcile traditional professions with technological innovations.
Technologies that redefine industrial professions.
The digital transformation and Industry 4.0 invoke a myriad of technologies: Internet of Things (IoT), robotics, 3D printing… Among them, the digital twin and AI hold a special place: these technologies cover all industrial projects and transform many professions.
The digital twin, a new tool for industrial professions.
The digital twin plays a crucial role in the evolution of industrial professions. It is a virtual representation of an object, process, or system, capable of simulating its physical counterpart in real time. The digital twin acts as a bridge between the physical and digital worlds. This technology radically transforms the management of an industrial product throughout its lifecycle, from its design to its operation, including its maintenance in operational condition.
The use of a digital twin is revolutionizing design and manufacturing by allowing numerous iterations at no additional cost. This improves the product by reducing design errors and development time.
The professions involved during these phases had already undergone significant changes with CAD/CAM (Computer-Aided Design and Computer-Aided Manufacturing). The digital twin amplifies these changes. Some examples include:
The design engineer can test and optimize a product in a virtual environment. For example, they can simulate the behavior of an aircraft under flying conditions, the energy efficiency of a moving ship, or the performance of a wind turbine facing different winds, without having to construct a costly physical prototype.
The draftsman can visualize the design in a realistic and interactive 3D environment, exploring every detail of the design.
The CAD technician can test different designs to detect potential problems before manufacturing. They can also use the digital twin to plan the manufacturing process, for example by determining the optimal order of machining operations.
The process engineer can use the digital twin to optimize production processes. For example, it is possible to simulate different production scenarios to determine the most efficient one.
The digital twin is also a valuable ally during the exploitation phase of an industrial product. It profoundly transforms professions related to maintenance, achieving a real paradigm shift: whereas maintenance was mainly reactive (repairing failures when they occur), the digital twin generalizes predictive maintenance.
Thanks to the data collected on the physical object, it is possible to predict failures before they occur. As a result, maintenance professions are increasingly focused on continuously monitoring the condition of the product and analyzing the collected data to solve problems before they lead to costly breakdowns.
Artificial intelligence, an accelerator of operational efficiency.
Artificial intelligence also promises to transform industrial professions as the promises carried by this technology are significant. AI is, above all, a relevant answer to process and analyze massive data (big data) and to extract actionable information: by helping to decipher the complexity of reality, AI assists humans in making strategic decisions (risk management, investment, business processes, etc.). As a result, AI impacts several professions across the entire value chain.
AI is also the cornerstone of automation for industrial companies and induces changes at all levels. Examples:
Production automation: AI allows the automation of complex production processes. The role of operators then shifts towards supervision, coordination, and optimization of automated systems.
Predictive maintenance: Maintenance technicians benefit from AI, which allows them to intervene before a failure occurs. This is one of the many synergies between AI and digital twin.
Supply chain automation: Managers can rely on AI to manage inventory and automate procurement. Here too, AI allows them to anticipate more.
Integrating digital innovations into industrial professions: towards a culture of innovation.
To take advantage of new digital technologies rather than being overwhelmed by them, industrial companies must identify opportunities for integration and adopt a culture of innovation to promote the internal dissemination of these innovations.
Identify the opportunities for integrating digital technologies.
To determine whether it is relevant to deploy a digital twin or AI in an industrial context, it is essential to analyze existing processes beforehand to identify integration opportunities and pinpoint the points of convergence between these technologies and traditional trades.
For example, to analyze a maintenance process, one must understand the current process (inspection, repair, maintenance…) and take into account the resources mobilized. The next step is to identify improvement areas (recurring failures, prolonged downtimes, challenges faced, etc.) and set clear objectives to enhance this process.
Then arises the question of means: would a digital twin help achieve these objectives? Would virtual reality be relevant for remote diagnostics? Ultimately, the analysis must show whether the cost and effort required to implement a digital twin would be justified by the potential improvements in the maintenance process.
Adopt a culture of innovation.
The success of a digital transformation relies primarily on the human factor. The most powerful technologies will be of no use if employees do not support the project or are not properly trained. For this reason, it is essential to encourage exploration and experimentation to spread a culture of innovation within the company.
With this in mind, it is desirable to raise awareness and train employees on new technologies, through workshops, seminars, demonstrations, etc. For instance, it is possible to set up training in digital twins and AI. The largest industrial companies have understood this well: for example, Bosch with its “Bosch Innovation Lab”, a space dedicated to experimentation and the discovery of new technologies, where employees can collaborate on innovative projects.
Digital transformation is a lever for growth and innovation for the industry. Digital twins and AI, to name just these technologies, have a clear impact on industrial professions, and this across the entire value chain and throughout the product lifecycle.
It is crucial for companies to be proactive and seize the opportunities offered by these technological advances. Reconciling historical industrial professions with digital technologies relies on adopting a culture of innovation at all levels of the company.
