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Editorial 4 Software at the heart of the future: Challenges and Opportunities for the prostep IVIP Association Dear prostep ivip members, The joint advancement of product development has always been at the core of the activities of the prostep ivip association. Since our inception, we have become the world’s largest independent platform for fostering constructive dialogue between users and vendors, and for establishing standards and pre-competitive best practices. Our focus is on the optimiza- tion of methods, processes and IT solutions in product development. But as always, the product development landscape is changing, presenting us with new challenges as well as new opportunities. One of the biggest and most important challenges today is the integration of software into the development process. The traditional product devel- opment process, which was originally heavily driven by mechanics, is increasingly being replaced by an integrated system that combines mechanics, electronics, electrics and software. This development opens up the possibility of offering customers even better and more personalized services through software-based solutions. In particular, the configuration and customization of features can be implemented directly in the software, making products more flexible and efficient. The automotive industry is a prime example of this transformation. It is a leader in the development of so-called “software-defined vehicles” – vehicles whose central functions are increasingly enabled and controlled by software. These vehicles bring a new dimension of adaptability, enabling faster and more precise responses to customer preferences and market

News in brief 6 prostep ivip Product Data Journal 2024-2 Project for the collaborative use of AI picks up speed The association project ‚FAICE - Framework for AI-Enabled Collaborative Engineering‘, which was founded in the spring of 2024, is increasingly taking shape: A virtual kick-off event in May attracted around 60 participants, demonstrating the level of interest in collaboration and AI in our community. The project continued in early June with the first on-site workshop in Darm- stadt. The first specific use cases were identified, discussed and prioritized. The current focus is on analyzing two high-priority use cases with the aim of developing prototypes for them by the end of the year: One is the ‘SysML Assistant’ use case, which deals with the AI-based gene- ration of SysML models from natural language and, conversely, with the output of information from SysML models into natural language. The second is the ‘Standards Chatbot’ use case, which involves extracting relevant information from an extensive pool of standards for a specific development context and user-friendly interaction with standards using a chatbot. Both use cases are currently being worked on intensively in small groups. The prototypes for these and other use cases will provide insights for a standardized framework for data and user management in the collaborative use of AI. The development of this framework as an enabler for safe and fair collabo- ration in the context of AI in engineering is the main objective of the FAICE project. Interested parties are welcome to join the project at any time, FAICE will also be on the program of the prostep ivip symposium. Contact Rachel Bauer rachel.bauer@prostep.com

News in brief 8 prostep ivip Product Data Journal 2024-2 Self-assessments of the Code of PLM Openness are becoming more detailed The CPO (Code of PLM Openness) and its working group have been an integral part of the prostep ivip association since 2011. For CPO, the open- ness of data-holding applications in the development process is about much more than supporting individual data access technologies or exchange formats. The previous DIN SPEC 91372 e.g. focused primarily on organizational aspects of openness at system vendors. This DIN SPEC is currently being revised and will then become an international standard. The desired goal for the future is to certify software products against the seven openness criteria, but the path is in many ways complex and long. In this respect, the next step is to significantly expand the existing CPO self- assessments. In future, it will be up to the vendor to look at individual products or packages and assess the extent to which they meet the CPO openness criteria. Working with the Standardization Strategy Board (SSB) will help to harmonize the areas of application and the relevant data stan- dards. In other words, the CPO will not be out of work in the near future. Nevertheless, there is still strong interest in bringing more user companies and system vendors into the CPO. Contact: Dr. Mario Leber mario.leber@prostep.com You can find more information about the CPO on our homepage https://www.prostep.org/projekte/code-of-plm-openness

News in brief 10 prostep ivip Product Data Journal 2024-2 with software updates delivered over-the-air (OTA) becoming a standard expectation. Managing this new landscape requires fresh and innovative approaches.. Navigating the Regulatory Maze Compliance with evolving global standards was a recurring theme, parti- cularly in the automotive cybersecurity presentations. Companies like Audi and BMW discussed the difficulties in meeting stringent regulations such as UN-R155 and UN-R156, which govern cybersecurity and software updates. The automotive industry faces a complex web of regional rules, which are not always designed with practical implementation in mind. Dr. Thomas Dickopf’ s (Audi AG) presentation underscored the importance of system engineering in navigating this regulatory environment. A key take- away was the need for harmonized standards to streamline certification processes and reduce business risks associated with software-driven trans- formations. Audi’s solution is to integrate security requirements into the development lifecycle, making the process as seamless as possible. Managing Software Across the Supply Chain Another central topic of the conference was how to manage software components across diverse supply chains. Dr. Stefan-Friedrich Schimpf’s (Robert Bosch GmbH) presentation on the Software Bill of Materials (SBOM) initiative outlined the complexities of tracking and standardizing software metadata across multiple divisions and suppliers. The use of semantic data models and unique identifiers emerged as a crucial strategy for overcoming these challenges. Bosch’s SBOM initiative aims to create a unified layer of knowledge that aggregates information from all sources, improving trans- parency and traceability by using standards such as SPDX & CycloneDX. Standardized Software Update Management: BMW‘s Approach Jürgen Etzkorn’s (BMW Group) presentation offered a glimpse into how the industry giant is tackling software update management through its Software Update Management System (SUMS). SUMS serves as a one-size-fits-all solution that covers global regulatory requirements, providing a standard- ized framework for software updates across all BMW vehicles. This approach not only ensures compliance but also streamlines the update process, making it efficient and cost-effective. A highlight of BMW’s strategy is their „five-step approach“ to managing requirements, which focuses on grou- ping and simplifying regulations for easier implementation. Challenges of Long-Term Data Management The issue of long-term archiving of software development environments, or Long-Term Archiving (LTA), was brought into focus by Till Reymann (Schaeffler Technologies AG & Co. KG). The need to preserve development data for

News in brief 12 prostep ivip Product Data Journal 2024-2 Conclusion prostep ivip Software Day 2024 showcased the industry’s commitment to embracing a software-centric future. From managing complex regulatory landscapes to standardizing software processes and integrating innovative tools, especially the automotive world is undergoing a profound transfor- mation. The challenges are significant, but so are the opportunities. As the industry navigates this shift, collaboration and standardization will be key to ensuring a future where vehicles are not only more intelligent but also safer, more reliable, and more connected than ever before. The road ahead may be complex, but with events like the prostep ivip Soft- ware Day bringing together industry leaders, the journey is one of shared progress and innovation. At the next prostep ivip symposium 2025 the topic will be discussed in a planned workshop with all interested participants and software developers in more detail. Contact Nora Tazir prostep ivip nora.tazir@prostep.com Contact Dr. Marcus Krastel :em AG

Kurz notiert 14 prostep ivip Product Data Journal 2024-2 BCC BERLIN 13 —14 MAY 2025 SOFTWARE DRIVEN PRODUCTS DIGITAL TWINS VIRTUAL PRODUCT CREATION AUGMENTED & VIRTUAL REALITY SUSTAINABILITY & GREEN TECHNOLOGIES FUTURE COLLABORATION PLATFORMS ARTIFICIAL INTELLIGENCE TRACEABILITY AND MANY MORE! Revolutionizing Industries w i t h D i g i t a l T w i n s a n d A I EARLY BIRD GET YOUR EARLY BIRD TICKET UNTIL 14 FEBRUARY www.prostep-ivip-symposium.org Premium Partner

News in brief 16 prostep ivip Product Data Journal 2024-2 Bordnetze Digital 2024: The Start of a New Era in Wiring Harness Development On September 26, 2024, Bordnetze Digital launched as the successor to the VEC Day, marking the beginning of a new collaborative format between prostep ivip and ARENA2036. Held at ARENA2036 in Stuttgart, the event showcased innovations driving the digital transformation of wiring harness development. A special thanks goes to Georg Schnauffer and the ARENA2036 team for their excellent organization and for hosting the event in such an outstan- ding venue. Kicking off with Dr. Tobias Carsten Müller (Volkswagen Group) on soft- ware development methods, the day continued with key insights such as Lena Beil (Dräxlmaier) and Mario Angos (Coroplast) on digital twins, and Nico Hahn (University of Stuttgart) on flexible cable harness production. The unveiling of DIN 72036 by Georg Schnauffer and Wolf Rumpelt (ARE- NA2036) and insights into digital identities from Dr. Hans Beck (Cofinity- X) added depth to the event. The day concluded with a panel discussion reflecting on the ideas presen- ted. We eagerly anticipate Bordnetze Digital 2025 in Stuttgart, continuing this exciting journey. More information on prostep ivip: VEC Day

News in brief 18 prostep ivip Product Data Journal 2024-2 A Week of Global Collaboration: Highlights from Japan On November 27, 2024, the Tokyo Systems Engineering Summit brought together experts from Asia and Europe to foster international collaboration. This flagship event was part of a week-long journey through Japan undertaken by Dr. Henrik Weimer (Airbus), Philipp Wibbing (Unity AG), Tomohiko Adachi (Mazda Motor Corporation), and Dr. Alain Pfouga (prostep ivip). The delegation engaged in meaningful discussions during visits to Nissan, Toyota, Denso, and Mazda. A highlight was an insightful exchange with Toshiba CEO Taro Shimada, culminating in a Push2Future interview between Taro Shimada and Tomohiko Adachi. This interview underscored the importance of Systems Engineering and global digital transformation efforts. With over 130 attendees, the Tokyo Summit featured thought-provoking keynotes and technical sessions on topics like AI, Systems Engineering, and Digital Twin. Special thanks to our Premium Partners NTT Data and PTC and exhibitors Toshiba, IAV, and Zuken, whose contributions made this event a resounding success. We are especially grateful to NTT Data – including Jens Krüger and Toshiro Uno – for their exceptional support, and to Tomohiko Adachi, whose dedica- tion was instrumental in the success of this journey. This week in Japan highlighted the value of collaboration within the prostep ivip Community, bridging continents to drive industrial digital transformation forward. We look forward to future endeavors and continued partnership!

Neue Mitglieder 20 prostep ivip Product Data Journal 2024-2 ARORIAN Arorian is a global technology solution provider headquartered in Germany, with offices in the Netherlands, Poland, US, and India. We specialize in end- to-end implementations of PLM, ALM, and SLM solutions, along with seamless integrations that bridge software, hardware, and enterprise systems to create a unified Digital Thread. We help organizations optimize their systems through: n PLM & ALM Implementations: Full-cycle consulting tailored to organi- zational needs. n System Integrations: Connecting PLM, ALM, ERP, MES, and IoT for seam- less collaboration. n AI-Enabled Solutions: Enhancing lifecycle visibility, insights, and opera- tional efficiency. n Digital Thread & Traceability: Ensuring end-to-end compliance and process optimization. n Digital Product Passports (DPP): Enabling transparency and circular economy practices. Trusted by industry leaders in Automotive, MedTech, and High-Tech, inclu- ding Fortune 500 companies, Arorian empowers organizations to achieve connected systems, sustainable operations, and accelerated innovation. With global reach, proven expertise, and a passion for technological innovation, we transform businesses through connected systems and a commitment to collaboration, compliance, and sustainability. Manan Arora CEO manan.arora@arorian.com www.arorian.com Contact

Neue Mitglieder 22 prostep ivip Product Data Journal 2024-2 ARAS Aras Corporation‘s core product is the highly flexible PLM platform Aras Innovator, which offers exceptional adaptability and a customer-friendly licensing model. With market-leading digital threading solutions, an open-source model, and the ability to manage complex product lifecycles across multiple industries, Aras PLM software serves large companies in the automotive, aerospace & defense, engineering, medical, chemical, pharmaceutical, and food industries. Aras works with a broad network of partners worldwide, delivering solutions to more than 600 global companies that use Aras as the foundation for their mission-critical product lifecycle processes. The renewed partnership with prostep underlines Aras‘ commitment to industry-wide collaboration and builds on the previous intensive and successful committee work, which has set standards in recent years. The objective of the Prostep-Aras partnership is the sustainable and targeted development of the industry. Jens Rollenmüller Regional Vice President of Professional Service, EMEA jrollenmueller@aras.com Contact

Neue Mitglieder 24 prostep ivip Product Data Journal 2024-2 Hamburg Analytics Hamburg Analytics: Innovative Solutions from the Hanseatic city of Hamburg Since its foundation, Hamburg Analytics has established itself as a partner for data-driven business optimization. Particular attention is paid to portfolio optimization, which our employees have been pioneering for over a decade. Our goal: to help companies make their product portfolios more efficient, reduce unnecessary complexity and lower their costs sustainably. Using advanced analytics and AI-driven algorithms, we analyze large volumes of data to identify relevant patterns and enable informed strategic decisions. Hamburg Analytics offers customized development and consulting services that cover the entire optimization process - from analysis to the realization of cost-saving potential. We ensure that products are optimally positioned and that resources are used efficiently. This data-driven approach enables us to ensure our customer‘s long-term competitiveness and future-proof their portfolios – always based on the evidence of their own data. Florian Tichla General Manager Client Projects florian.tichla@hamburg-analytics.de Contact

26 Revolutionizing Product Development through Interdisciplinary Data Exchange: The Digital Data Package Sarah Giese, PROSTEP AG The demands on modern data formats for product development are multifaceted and continuously growing. Traditional formats often limit themselves to domain-specific data exchange and offer insuffi- cient capabilities for linking diverse data types. This presents a significant barrier to effective and innovative cross-disciplinary collaboration.

Das Digital Data Package 28 prostep ivip Product Data Journal 2024-2 in June and discussed by the members. Feedback from this session was incorporated into a revised version, which was presented again at the OMG Q3 meeting in Chicago in September. Here, further comments and sugge- stions for optimization were collected. The final submission of the CASCaDE RFP is planned for the OMG Q4 meeting in San Francisco in December. During this meeting, a vote will also be held on the official acceptance of the RFP. The project is planned to have a duration of three years to achieve the targeted goals and successfully implement the standard. The CASCaDE Digital Data Package builds on established standards like ReqIF, SysML, STEP, JT, IDX, VEC, AUTOSAR, and Cyclone-DX. These standards will be available in a standardized form as files and in Data Spaces. This digital package thereby creates the necessary infrastructure for un hindered data exchange between a wide variety of tools and platforms. It enhances efficiency and quality in product development and maximizes the potential of digital twins and AI applications.

30 Data products for ecological sustainability Engineering for Sustainability Dr. Alexander Christ, Kristina Avdejuk, Jinzhao Hu, Dr. Marcus Krastel :em engineering methods AG In many companies, sustainability is now a factor that is already firmly established as part of the product lifecycle. When it comes to complying with the multitude of regulations and the associated reporting requirements, businesses often focus exclusively on the IT tools. This results in complex in-house developments and considerable manual effort, in particular when it comes to consolidating the rele- vant sustainability data. In this context, Engineering for Sustainability provides a comprehensive approach that contributes to the implementation of the necessary processes, data and IT architecture, as well as to business capabilities within the company. By defining and modeling modular data products, the approach improves transparency, traceability and reuse and also provides a basis for the digital product passport.

Engineering for Sustainability 32 prostep ivip Product Data Journal 2024-2 Trends Digitalization Sustainability external internal Regulations/Standards Market access Penalty payments Digital Twin Ecosystem of a company Development Production Digital Twin Data product 1 Data product 2 Business partner IT Data product n Logistics Disposal / Recycling Efficiency increase Procurement … New business models Figure 1: Factors influencing data products A digital twin revolves around its data products, see Figure 1. Data products are defined datasets that are able to obtain and aggregate data from various data sources in order to describe one or more aspects of the digital twin and, in this way, create concrete value-added. They have a modular structure in order to permit the greatest possible level of reuse. Companies are able to use data products to analyze every aspect of their products, production processes and supply chain flows and identify ways of measuring and optimi- zing these. Engineering for Sustainability The creation of these data products demands a comprehensive, all-embra- cing approach – Engineering for Sustainability. This makes it possible to develop and implement technologies, IT infrastructures and systems that are both ecologically sustainable and economically viable. Development plays a crucial role here, because up to 80 % of a product’s environmental impact is determined during the development stage [4]. And the develo- pers need the relevant data to be available at the point where the decisions are taken. In addition to indications about price, weight and delivery times, this data increasingly includes information about sustainability.

Engineering for Sustainability 34 prostep ivip Product Data Journal 2024-2 Cross-company collaboration: To ensure that different companies have a shared understanding of the concepts and similar strategic objectives, it is necessary to define what sustainability is. Here, a particular focus is placed on the exchange of material data throughout the supply chain and the inte- gration of the corresponding databases. Standardized interfaces increase interoperability and may potentially contribute to the automation of infor- mation flows. Sustainability reporting: The reporting requirements facing companies are increasing in the light of the Corporate Sustainability Reporting Directive (CSRD) [6] and the Ecodesign for Sustainable Products Regulation (ESPR) [7]. One way of gaining a better understanding of the regulations is to train employees in the corresponding subject areas, while active participation in standardization committees and industrial workgroups allows companies to help shape future requirements. One important driver is the digital product passport (DPP), which will become mandatory for the first set of product groups in the EU as of 2027 [7]. The DPP requires various data to be linked throughout the supply chain. It covers both static data relating to the product type (during development and production) as well as dynamic data for the individual product instances (during use). The semantic linkage of this data offers the potential for data-driven decisions throughout the entire development process. Five steps toward greater sustainability Use case-based approximations help companies to achieve their short-and medium-term sustainability goals. Five vital steps are required if sustainability is to be successfully anchored within a company in the long-term. 1. Definition of clear sustainability objectives, including the desired capa- bilities of the future products and business-level objectives. The potential benefits must be clearly illustrated in the light of concrete areas of activity. It is vital to have a cross-domain sustainability roadmap that harmonizes with the company’s digitalization strategy and leads to unambiguous, coordinated deliverables. 2. Analysis of the current business processes and description of the future information flows for sustainability. The modeling of sustainability reference processes helps during the implementation of the use cases and ensures that the participating stakeholders share a uniform understan- ding. In addition to engineering, production and usage, sustainability covers a wide range of other domains and demands a holistic viewpoint that covers the entire lifecycle. 3. Creation of an information model for sustainability, together with the relevant information objects and their interrelations. This model contains the data products which aggregate the relevant sustainability data from the various sources and then make this available to IT applications. It enables the semantic linking of the sustainability-related information, such as geometry data, product structures and material values. This makes it possible to trace the employed resources and the associated environ- mental effects within an comprehensive semantic information model.

Engineering for Sustainability 36 prostep ivip Product Data Journal 2024-2 example, the 3D-CAD models with geometries and volumes, materials specifications such as density or recyclability, energy consumption and emissions during production, transport routes and modes from the supply chain, etc. The representation of data products in a uniform model makes it possible to implement cross-domain information flows and reuse them for other applications, e.g. when creating a digital product passport. The data products obtain static and dynamic data from various data sources. These include large strategic IT systems, such as PLM and ERP, local data- bases, data submitted via supplier portals or data from the use phase. The data is generally accessed via web services and APIs. The typically encoun- tered challenges relate to the completeness and quality of the data. It is also necessary to make sure that the data is available in the required level of granularity. In addition, raw data from a variety of sources also has to be prepared and harmonized. Currently, the efforts made by companies often combine the issues of sustainability and digitalization under the umbrella of the digital twin. Expe- rience has shown that in-house lifecycle assessment solutions are not able to meet the requirements in the long term, involve a high level of manual effort and often only meet a handful of use cases. What is required are scalable IT technologies which focus on the data products, provide ways of flexibly integrating the data sources and have the capabilities required for the semantic orchestration of the data in the IT systems. In the case of the digital twin, the Bosch Semantic Stack, for example, is a highly product- focused, data-driven software solution that allows this flexible integration and uses established standards such as the Asset Administration Shell (AAS). References [1] Deutsches Institut für Normung e.V. (2024): Circular Thinking in Standards. Wie Normung eine Circular Economy unterstützen kann. Version 3 [2] Handschuh, S.; Gerber, P.; Schweigert- Recksiek, S. (2024): Collaborative Digital Twins – Project Overview, Intermediate Results, and intended Deliverables. Prostep ivip Symposium 2024 [3] Christ, A.; Koch, P.; Krastel, M.; Schweigert- Recksiek, S.; Trauer, J. (2022): Ready or not – Der Digitale Zwilling wird kommen! Wie können sich Unternehmen darauf vorbereiten? Prostep ivip ProduktDaten Journal 2022-2, p. 12-17 [4] McAloone, T. C.; Pigosso, D. C. (2021): Ökodesign – Entwicklung von Produkten mit verbesserter Ökobilanz. In: Bender, B.; Gericke, K., Hg. Pahl/Beitz Konstruk- tionslehre. Methoden und Anwendung erfolgreicher Produktentwicklung. 9. Auflage 2021. Berlin, Heidelberg: Springer [5] Christ, A.; Langlotz, M.; Schweitzer, G. (2024): Nachhaltige Produktentwicklung – Anforderungen an Daten und IT-Ar- chitekturen. Engineering Process Day 2024 [6] European Parliament, Council of the European Union (2022): Directive (EU) 2022/2464 of the European Parliament and of the Council of 14 December 2022 amending Regulation (EU) No 537/2014, Directive 2004/109/EC, Directive 2006/43/EC and Directive 2013/34/EU, as regards corporate sustainability reporting (OJ L 322, 16.12.2022) [7] European Parliament, Council of the European Union (2024): Regulation (EU) 2024/1781 of the European Parliament and of the Council of 13 June 2024 establishing a framework for the setting of ecodesign requirements for sustaina- ble products (OJ L, 2024/1781, 28.6.2024) [8] Kotter, J. P. (2011): Leading Change. Wie Sie Ihr Unternehmen in acht Schritten erfolgreich verändern. 1. Auflage. Vahlen, München. ISBN 978-3800637898 [9] International Organization for Standardi- zation (2009): Environmental manage- ment – The ISO 14000 family of Interna- tional Standards [10] Industrial Digital Twin Asswwociation (2024): IDTA – Der Standard für den Digitalen Zwilling. https://industrialdigi- taltwin.org/ (24.10.2024)

38 Combining the advantages of AI [1], intelligent processes and human skills: Achieve success faster, more flexibly and more reliably with AI-based project management applications Companies implement projects primarily because they are intended to fulfil an economic benefit. By using AI-supported tools, applications, and solutions, they can help to manage an increasingly complex project landscape or project portfolio more effectively and achieve results more quickly. The right mix of intelligent processes, use of technology and human creativity proves to be the most successful.

AI-based project management applications 40 prostep ivip Product Data Journal 2024-2 Are we making the right decisions about projects? Project portfolio management is about weighing up several planned projects against each other to determine which project fits a particular business strategy. Are we working on the right ones? The aim is to continuously select the right projects and maximise the impact of each project – considering costs, resources, and risks. Questions that project portfolio managers want to answer include: How can we improve resource management? How do we avoid the X, Y, Z, etc. risks? And how will our projects achieve the most important strategic goals? The most powerful PPM solutions have been continuously developed by software manufacturers over the past 20 to 25 years to cover a wide range of requirements for entire industries. One example from the automotive industry Extended Enterprise in Planisware’s flagship product Planisware Enterprise. The PPM system can help coordinating project plans or parts of projects between automotive OEMs and project teams on their suppliers’ side. Suppliers might be requested to update parts of a plan, estimate risks in a workpackage outsourced to them and give feedback on estimated changes on their side in tasks that have been assigned to them.[2] In order to fulfil specific customer requirements, PPM solutions from software providers such as Planisware, for example, have been integrating future technologies such as artificial intelligence for more than 20 years. The aim was to improve forecasts and achieve learning effects. Project data as a starting point As a cross-sectional function in the value creation process, project manage- ment offers an ideal starting point for AI applications in many respects. A lot of data is generated. On the one hand, this data is generated in the projects themselves and on the other hand, it is integrated from other systems such as ERP, CRM, etc. A general advantage of PPM solutions is that PM managers can use project data to estimate resource need, time, and financial resources in their projects with increasing accuracy. As PPM solutions in companies are usually set up as a single source of truth, the data structure is standardised and comparable. This creates ideal condi- tions for AI applications. The following section will describe how AI-based systems support project managers in companies to make better decisions, plan, and control projects, manage risks, allocate resources, collaborate, and communicate.

AI-based project management applications 42 prostep ivip Product Data Journal 2024-2 Figure 2: Analysis of success drivers in the bidding process at a wind turbine manufacturer Application in practice One example is a wind turbine manufacturer that uses predictive analytics to forecast the probability of success of its future offers. Using the AI functions of its PPM tool, the manufacturer analyses the available data in a correspon- ding portfolio view and gains two key insights into the prospects of success of its bids. Firstly, the chance of winning an „onshore project“ increases with the size of the rotor diameter. Secondly, the chance of successfully comple- ting an offshore project increases as the number of turbines increases for potential offshore customers. The predictive analysis has enabled the company to reduce the forecasting speed from several weeks to a few hours and at the same time significantly improve the forecasting quality, while significantly reducing the use of resources. Interim conclusion: Predictive analysis is revolutionising project portfolio management by enabling data-driven decisions and accurate forecasts. By identifying relevant drivers and creating better forecasts, it helps to plan projects more efficiently and complete them successfully, as well as maximising the chances of bid success. Companies that integrate predictive analytics into their PPM software benefit from more objective decision-making, better risk mitigation and optimised resource utilisation. In a world where data is becoming increasingly important, it is an indispensable tool for any forward-thinking organisation.

AI-based project management applications 44 prostep ivip Product Data Journal 2024-2 Figure 4: Generate a list of project risks for activities including impact and probability of occurrence(s) The whole thing is done in just a few clicks and in dialogue. The project managers receive the required information, for example in the form of a list or a diagram. If they now approve this activity list, the activities are created with the correct time periods, links, etc. The project managers can adjust the respective results – work plans, schedules, etc. - as required after each step. Consideration of risks in work planning A risk assessment (of the activity list) can be created analogue to the above example. After selecting an activity in the work breakdown structure, several iterations follow until the result is achieved. In this case (see Figure 04), specific details are described for each risk, such as the impact and the probability of occurrence. Define OKRs, classify key results and involve external stakeholders. In addition to project planning and risk assessment, AI-supported digital assistants can also be used in strategic planning to define OKRs (Objective and Key Results). Here, the bot can design key results for any stakeholders based on objectives. Especially in terms of risk, it can be important for companies to use their own corporate LLM. It is therefore ideal if the bot can be connected to ChatGPT or even the company‘s own generative language models.

AI-based project management applications 46 prostep ivip Product Data Journal 2024-2 The advantage for companies: The simulation thus ensures much more informed decisions and more precise planning of budgets for measures. Typical areas of application include estimating deadlines or project progress, for example in construction or development projects. The results of several simulation runs can then be used to determine how likely (e.g. 80 per cent), under optimistic to pessimistic assumptions, a completion date could be in 100 days, for example. In the model, a probability is determined for each activity and duration (influencing variables). Project expenses, project costs or risk occurrence probabilities can also be modelled. Three central points where Monte Carlo analysis really comes into its own: 1. Quantitative risk analysis: Monte Carlo simulations enable a detailed quantitative analysis of uncertainties and risks. They help to calculate the probability of different outcomes instead of relying solely on individual forecasts. 2. Scenario and sensitivity analysis: By simulating numerous scenarios, project managers can understand how different risks and assumptions affect project performance. 3. Optimisation of resources and decisions: Monte Carlo analyses support decision-making by providing more realistic estimates of schedules, budgets, and resources. This allows projects to be better planned and resources to be allocated more efficiently to minimise risks.

AI-based project management applications 48 prostep ivip Product Data Journal 2024-2 Figure 6: (Motif resource management - PSO simulation, click to time shift, weighting) Optimise project selection/ timing with one click - goal: as early as possible To avoid having to calculate such questions manually, project managers can use PPM tools that can run through and optimise the utilisation of resources in a portfolio. A quick check of the resource capacity of portfolios is one of the key functions of a PPM tool. It can show portfolio managers at a glance whether the resources for current projects are overloaded or underutilised. At the strategic level of capacity planning, AI can be used to simulate resource utilisation. In this example, the tool arrives at an optimal solution for the resource capa- cities after just a few clicks. The dates of the respective projects have been shifted so that the estimated resource requirements are always below the defined threshold value of 40 (see green line).

AI-based project management applications 50 prostep ivip Product Data Journal 2024-2 Companies benefit from four advantages of the AI-driven PSO. 1. Resource Efficiency: By intelligently balancing resources, an AI-driven PSO ensures that every project is planned at the best possible time to prevent resource bottlenecks. 2. Faster Decision-Making: Thanks to its computational method, PSO signi- ficantly speeds up the optimisation process compared to conventional methods. This is particularly advantageous in time-sensitive decision- making scenarios. 3. Scalability: Whether managing a small or large portfolio, AI-driven PSO is customisable to meet specific needs, delivering consistent, reliable results at any portfolio size. 4. Transparency and Control: The AI-driven PSO works with unrivalled speed and efficiency without sacrificing transparency and control. Portfolio managers have full insight into the optimisation process, empowering them to make informed decisions with confidence. Sources / References [1] The European Parliament defines artificial intelligence (AI) as “the ability of a machine to exhibit human-like capabilities such as reasoning, learning, planning and creativity.” […] https://www.europarl.europa.eu/topics/ en/article/20200827STO85804/ what-is-artificial-intelligence-and-how- is-it-used [2] cf. (Schießl 2020) “The complexity of scheduling in vehicle development projects”, in Prostep ProductDataJournal, No. 2020-01, page 34-37 https://prostep.epaper-pro.org/ pdj_1-2020_english/#34 [3] Monte Carlo simulation [detailed description of the three basic steps: see IBM] https://www.ibm.com/topics/monte- carlo-simulation

52 Challenges and Strategies of German Automakers to Reduce Vehicle Development Times Dr.-Ing. Jens Standke, Dr.-Ing. Peyman Merat, UNITY AG The German automotive industry is on the verge of a profound transformation, driven by the technological shift towards electric mobility, autonomous driving and digitization. This poses enormous challenges, particu- larly in terms of reducing development times for new vehicles.

Challenges and Strategies of German Automakers 54 prostep ivip Product Data Journal 2024-2 Problems with the integration of hardware and software Another key problem that lengthens development times in the German automotive industry is the inadequate integration of hardware and software. Modern vehicles are increasingly software-defined products where software is critical to functionality, usability and connectivity. This presents OEMs with the challenge of closely integrating hardware and software development processes. In many German companies, hard- and software still tend to be developed separately. This separation makes it more difficult to detect errors at an early stage and to improve the maturity level of the overall system. Early and digital integration is a key factor here, both to increase the maturity of the product more quickly and to identify and eliminate development errors at an early stage. A key approach to solving this problem is the use of whole-vehicle system architectures and the implementation of systems engineering across all areas of the vehicle - in contrast to the often fragmented approach still used today (Figure 1). Figure 1: Principle, system architecture, complete vehicle

Challenges and Strategies of German Automakers 56 prostep ivip Product Data Journal 2024-2 However, virtual development is not without its challenges. While many steps can be digitized, it is not yet possible to completely eliminate physical prototypes. Nevertheless, the digital twin is an essential tool for drastically reducing development times in the future. But the digital twin is not limited to engineering. It is also needed in produc- tion and for every vehicle that is built. This has tremendous benefits for traceability of installed components, recalls, and customer complaints that can be fed back into the product development process. A continuation of the digital twin in the after-sales process makes it possible to track the current condition of the vehicle at any time, for example to monitor or certify the condition of the battery in electric vehicles. Figure 2 shows that the use of the digital twin extends beyond the product development process to the after-sales and customer-use phases of the product. This requires an IT infrastructure that can process vehicle and usage data from the field. Virtual validation as a mark of quality Because it is not yet possible to fully verify all vehicle components using digital methods, building prototypes remains essential-even if only a small percentage of them can actually be used for verification. Unlike hardware-based validation, virtual validation allows you to run tests as often as you like with modified conditions. This not only provides a higher level of protection, but also enables faster root cause identification and early remediation of any defects found. Figure 2: Utilization of the digital twin throughout the entire lifecycle

Challenges and Strategies of German Automakers 58 prostep ivip Product Data Journal 2024-2 Highly customized brownfield IT systems Today‘s automotive IT landscape is reminiscent of 1960s manufacturing plants, with little automation, few networks, and no end-to-end material flow. In contrast, today‘s modern production halls are highly automated. Parts are delivered at the right time, in the right configuration to the recipients in the main process - the same should apply to information in development processes to ensure that they run quickly and smoothly. However, today‘s development engineers often gather the data they need as if they were in a workshop. This also complicates further automation efforts. In addition, existing systems are highly customized to the requirements of each OEM, making them inflexible when it comes to modernization. The major overhaul of these IT systems deters non-IT-savvy top managers. But this modernization is essential to make vehicle development much more efficient. At the same time, most software vendors are unable to align their systems with the needs of future vehicle development. They lack an understanding of the methods that will or should be used for future development. Due to the often long development history of the software systems themselves, users no longer fully understand them, which hinders efficient use. Essentially, the IT infrastructure must support the requirements for E2E traceability and an RFLP approach combined with Model-Based Systems Engineering (MBSE) (Figure 4) in order to best ensure virtual vehicle development and validation. The RFLP approach encompasses the descrip- tion of requirements, functions (functional structure), logical structure, and physical structure in the context of product development for the complete mapping of a complex technical product. In addition to the description, it is essential to link the data to form digital impact chains, for example to be able to perform automated impact analyses in the event of changes.

Challenges and Strategies of German Automakers 60 prostep ivip Product Data Journal 2024-2 Innovation pressure as an additional challenge In addition to shortening their development times, German OEMs must also maintain their innovative strength in order to survive in the face of global competition. In the areas of electric mobility, autonomous driving and digi- tization, innovation is the key to meeting customer demands and opening up new business opportunities. A key point in this context is the development of platform strategies. Plat- forms make it possible to scale technological innovations across different vehicle models and use them more efficiently. This applies to both hardware components and software solutions. In software, in particular, a platform strategy can help shorten development cycles while increasing the pace of innovation. In addition, partnerships with technology companies are playing an increa- singly important role. Chinese OEMs, in particular, are working closely with leading technology companies to enhance their ability to innovate. German manufacturers need to catch up in this area in order to drive forward the integration of new technologies such as artificial intelligence, autonomous driving and connected mobility solutions.

62 The Role of AI in Enhancing PLM Systems Andreas Grave, Aras The ability of Artificial Intelligence (AI) to detect patterns and anomalies in vast amounts of data has made it an essential tool for Product Lifecycle Management (PLM) in industrial project and manufacturing contexts. Appli- cations range from predictive maintenance and auto- mated risk analysis to accurate cost and time forecasting. However, these opportunities require organizations to first establish a well-organized data framework to fully harness the power of AI.

The Role of AI in Enhancing PLM Systems 64 prostep ivip Product Data Journal 2024-2 Beyond IT – The Role of Change Management In addition to an open system architecture embedded in a cloud frame- work, effective organizational change management is key to a successful PLM implementation. PLM projects rarely fail because of technical hurdles; instead, they often stumble because organizations fail to lead people through the transformation. Without clear communication and buy-in, the system, no matter how advanced, runs the risk of being underutilized. As AI becomes part of PLM, it is important to address its impact on employees. Many see AI as a potential threat to their roles, especially since the technology can perform many processes more efficiently than humans. The challenge is to change this perception by showing employees that AI enables them to focus on higher-value activities, such as creative problem solving and strategic innovation. Companies must actively cultivate this mindset by investing in training and creating a workplace culture where AI is seen as a tool for empowerment, not replacement. From Design to Sustainability: AI in Action AI unfolds its full potential when it is tightly embedded in the interaction between people and PLM systems. Beyond data analysis, it acts as “collabo- rative intelligence,” assisting teams with real-time optimization suggestions and automating routine coordination tasks. Over time, it continuously learns from projects, creating an organizational knowledge base that can be applied to future efforts.

The Role of AI in Enhancing PLM Systems 66 prostep ivip Product Data Journal 2024-2 Accelerating AI Integration These developments are no longer futuristic; they are already underway. Gartner predicts that by 2025, generative AI systems will handle 70% of text- and data-intensive tasks, and by 2026, half of all PLM solutions will integrate AI. Currently, we are in the “AI-Assisted” phase, where AI assists in decision making and interactions. Soon, however, we will enter the “AI-Suggested” phase, where systems proactively suggest solutions and make actionable recommendations. Organizations that embrace AI will be better prepared for the next era of PLM, where humans remain the central decision makers, but AI greatly enhances efficiency and innovation. AI adoption is growing rapidly, especially among IT-driven companies in technology-open industries. These organizations are using AI to improve processes and embed its capabilities into their offerings. While implemen- tation is often slowed by security concerns, the EU AI Act provides regulatory clarity and acts as a catalyst. This legislation adds another layer of govern- ance, but provides a clear legal framework and greater planning certainty.

68 Bimodal augmented reality used to support assembly processes in networked production environments Erik Freydank, Fraunhofer Institute for Production Systems and Design Technology; Manuel Schiewe, Fraunhofer FOKUS

Bimodal augmented reality 70 prostep ivip Product Data Journal 2024-2 Figure 1: Complete demonstrator workflow Augmented reality as the interface during human-robot collaboration Augmented reality (AR) technology makes it possible to overlay the real world with additional virtual information. As a result, complex assembly workflows can be clearly depicted in the form of step-by-step instructions even in highly individualized production environments. The relevance of support systems of this type is underscored by a current study on the use of assistance systems during assembly. In particular, the study emphasizes the role of projections and smart glasses in future systems for human-robot col- laboration (HRC) [3]. Three main requirements were defined for the design of the AR system: It had to display the assembly steps, output real-time information from the networked assembly equipment, and permit the user-friendly and, most im- portantly, hands-free operation of the system in order to avoid interfering with the assembly tasks. It was also necessary for information to continue to be displayed in the right context and in spatially appropriate positions in order to exploit the full potential of the augmented reality application.

Bimodal augmented reality 72 prostep ivip Product Data Journal 2024-2 Figure 4: The assembly steps can also be displayed and performed using an HMD. Integration in the assembly demonstrator In the assembly demonstrator, a fuel cell is interactively assembled with the help of a cobot (collaborative robot). The robot performs most of the tasks, including the automatic verification of the components, while the human is responsible for the more delicate assembly activities (Figure 3). The assem- bly instructions are projected directly into the assembly operator’s field of vision using AR display technology, with the result that the operator can see the required work steps at all times. The system is flexible: The overall process server derives the relevant pro- cess steps from the specific fuel cell configuration and passes this informa- tion on to the AR systems. Consequently, data such as the fuel cell’s specific stack height is included in the instructions, meaning that individual work steps can be repeated with variations. In parallel to this, there is a bidirec- tional flow of information. For example, the assembly process can be inter- rupted by means of optical error detection so that a warning or error-han- dling instructions can be overlaid on the display until assembly is able to continue.

Bimodal augmented reality 74 prostep ivip Product Data Journal 2024-2 By contrast, the AR-HMD makes it possible to position interfaces freely in space and depict 3D elements. This results in an immersive visual display that allows users to anchor digital information in their physical environment. This immersive experience can speed up the assembly process, particularly in the case of complex tasks. However, the visual field of the AR display in the HMD is restricted, meaning that users have to move their heads to see all the relevant information, thereby impairing the overall view. Ergonomic considerations also play an important role when selecting the most suitable AR technology. Both systems allow the assembly personnel to keep their hands free for their manual activities, thereby ensuring a high level of efficiency. AR projection is a robust system which does not require any additional equipment such as user glasses. This makes it more comfort- able to use. However, the display is tied to a fixed location and cannot be used dynamically at different assembly stations. The HMD offers a high level of flexibility because it can be used at different assembly stations. Nevertheless, users may be exposed to physical strain due to wearing the device on their heads. This may be perceived as un- pleasant, especially during extended periods of use. Moreover, the battery life is restricted, making a solution with replaceable battery packs and/or cable-connected units necessary during longer shifts. Figure 5: Strengths/weaknesses profile of AR systems

Bimodal augmented reality 76 prostep ivip Product Data Journal 2024-2 Identifying the usage scenario The comparison makes it clear that both AR systems have their strengths and weaknesses. It is therefore necessary to consider the actual assembly use case in question before choosing the support system that is most ap- propriate for it. Due to its greater flexibility and dynamic space requirements, the HMD- based variant has shown itself to be better suited for changing environ- ments and assembly workstations that have to be frequently reorganized. It can be of benefit in production lines that regularly change between differ- ent products or processes. Nevertheless, the HMD is battery-powered and this can be a disadvantage compared with the use of projectors, because work has to be regularly interrupted to change or replace the battery, in particular during periods of extended operation. Because the device is worn, comfort also plays a role during periods of extended use. However, an HMD is a particularly good way of learning new processes quickly and for familiarizing personnel with complex assembly scenarios. This is because the assembly steps can be learned most effectively in an immersive spatial environment. The possibility of depicting the assembly steps directly in the three-dimensional working environment helps users in- tuitively understand the actions they need to perform. This not only shortens the learning curve but also reduces susceptibility to errors during the learn- ing process because users are able to receive immediate visual feedback. However, a projection solution should be preferred for permanent use at a fixed assembly workstation with lower requirements in terms of mobility and flexibility. The ability to display information stably over a large area on the working surface results in intuitive user guidance without any undue fa- miliarization times. Projection improves ergonomics because, given that there is no need to wear any additional equipment, the solution does not require any direct physical contact with the user. For repetitive tasks and in environments requiring a permanent visual display, projection is the more efficient and user-friendly long-term choice. References [1] https://de.statista.com/statistik/daten/ studie/255082/umfrage/strutur-des- bruttoinlandsprodukts-in-deutschland/ [2] https://www.plattform-i40.de/IP/ Navigation/DE/Industrie40/ WasIndustrie40/was-ist-industrie-40.html) [3] Empirische Ergebnisse zum Einsatz von Assistenzsystemen in der Montage, ZWF, 10.1515/zwf-2024-1097

78 Agile product development: Identification of architecture components in the context of manufacturing-specific use cases M. Eng. Terence Larusch, Fraunhofer Institute for Production Systems and Design Technology The digital transformation is putting growing numbers of businesses in a position to react flexibly to changing requirements and optimize their development proces- ses. One key element in this development is the creation of a digital twin which acts as a virtual replica of a physical product.

Agile product development 80 prostep ivip Product Data Journal 2024-2 The modularization process involves the top-down identification of the var- ious activities required in order to achieve the goal. This process continues to be cascaded iteratively for each sub-activity as shown in Figure 1. The result is a structure tree containing various sub-activities, all of which are identified on the basis of the overall goal. Finally, the activities at the bot- tommost level lead to the identification of functions and technical elements that can be used to extend the twin architecture and permit the implemen- tation of the corresponding use case. Figure 1: Modularized use case for identifying core activities (blue) that require certain architecture components

Agile product development 82 prostep ivip Product Data Journal 2024-2 Activity Module Filing the calculation rule Edge device: Local storage and rapid provisioning Send machine data Machine (e.g. 3D printer) Send/capture machine configuration Filing of machine data MQTT broker: Efficient, scalable communication with central database Streaming system: Continuous integration of the data, real-time monitoring Reference calculation rule Implementation of calculation DVisualization of results Dashboard: Access to and centralized real-time implementa- tion of calculations and visualization of the results Table 1: Overview of the identified core activities and assigned architecture elements When incorporated in a draft architecture, this results in an all-round picture that reflects not only the external systems (ERP, MES, PLM etc.) and services but also the link to the physical sources of value added together with the intermediate elements. Figure 2: Overall depiction of a basic architecture for a twin with modularization of the identified elements (green)

84 prostep ivip Scientific Award – for engineers focusing on virtual product creation

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