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Computer-Aided Manufacturing systems are common means to increase the flexibility and efficiency of production planning in manufacturing companies. Digital transformation processes increase innovation cycles and product individualization [1] and, by doing so, the complexity of production planning and CAM systems use [2]. In the R&D project CAM2030 a new generation of CAM systems is developed by integrating innovative technologies (AI, cloud computing, evolutionary algorithms). The highly innovative process requires new methods. This paper presents an integrated methodological approach that enriches co-creation methods [3] by integrating visualization methods of process modeling [4]. The methodology was developed in three steps: concept development, concept realization, and concept evaluation. Concept development: Due to the Covid-19 pandemic, a remote co-creation workshop was designed based on two assumptions: (1) Co-creation at an early stage of the innovation process benefits from integrating users’ perspective and need information [5]. (2) Modeling and visualizing CAM planning processes allows to build up a shared understanding of the status quo. Human-centered work design experts compiled, modeled, and visualized the project-specific CAM planning process with the C3 modeling method [4]. Technical communication experts focused on methods and tools to gather need information (requirements for intelligent CAM systems) remotely. The workshop comprises three parts: warm-up challenge to identify no-go design features of CAM systems, discussion of the CAM planning process and model, and derivation of design requirements and automation potential. Each part uses different practices, e.g., teams working in separate breakout sessions, documenting their results in a shared document on Google Docs in real-time. Concept realization: The workshop was conducted in February 2021 via Zoom. The participants (CAM users, software developers, researchers) (n=21) were acquired within the project consortium. The workshop was audio- and video-recorded. The participants’ notes were stored in Google Docs. The transcribed audio data were enriched with additional information, e.g., participants’ notes. After the workshop, the data were used to integrate, categorize, and prioritize need information and to revise the process model. Concept evaluation: The concept was evaluated by the workshop participants and the workshop leader team guided by two research questions: Is this methodological approach suitable for innovation processes? What are the potentials and challenges of the approach? The approach proved to be highly productive. The integration of co-creation and process modeling seems to be a promising approach to involve diverse perspectives in the design of intelligent CAM systems. The process model supported the workshop participants in creating a shared understanding of the CAM planning process and identifying potentials for optimization and automation. The collaboration in heterogeneous groups yielded a structured catalog of requirements that will go into the further innovation process of CAM systems. Shortcomings concern the live adaptation of the process model as well as bringing together partial results from different groups and cluster ideas. Under pandemic conditions, the approach is practical to a limited extent. Future research will focus on how the nexus of co-creation and process modeling can be advanced to enrich the design of innovative software systems.

Climate protection and the limited availability of conventional energy sources have led to efforts to facilitate a transition to renewable sources. This trend also changes the way in which electricity is consumed and distributed: Recently, end-users have taken an increasingly active role in the electrical power system that enables a collective form of energy self-consumption and sharing - so-called ‘energy communities’ [1]. In these communities, energy is generated with solar or wind technologies and distributed between members using local grids and community battery storages.The diffusion of energy communities on a large scale could provide advantages such as increasing customers’ electricity savings, electricity suppliers' sales, and grid operators' revenues due to reduced grid tariffs for inner-community electricity transfer [2]. A barrier to a large-scale rollout is the fact that energy often remains invisible to most citizens and is merely perceived in terms of ‘energy services’ ("[…] functions performed using energy which are means to obtain or facilitate desired end services or states" [3]). This focus on energy services can give rise to a wide range of information needs but also to different attitudes in the evaluation of energy communities from the perspective of potential customers. Therefore, it is necessary to analyze whether companies address such requirements in order to establish a positive customer experience.In this study, the topic is operationalized through three research questions:Communication from the company's point of view: How are energy communities advertised by companies that support customers in implementing them? Information needs from the customer's perspective: What do potential customers want to know about energy communities?The questions are examined in a comparative analysis based on text mining methods. For this purpose, data were collected from two types of sources: Comments from social media addressing energy communities and promotional in which companies communicate energy communities to potential customers. Both data sets were analyzed with regard to the research questions.The results show a mismatch between what customers want to know about energy communities and what companies communicate about such forms of energy production and distribution. In particular, risks perceived by potential customers (such as concerns about the equitable distribution of energy) are hardly addressed. By resolving such mismatches, the diffusion of energy communities could be accelerated. The results are discussed in terms of possible measures to enhance the customer experience.References[1] Iazzolino, G./Sorrentino, N./Menniti, D./Pinnarelli, A./De Carolis, M./ Mendicino, L. (2022). Energy communities and key features emerged from business models review.Energy Policy, 165. https://doi.org/10.1016/j.enpol.2022.112929.[2] Fina, B./Monsberger, C./Auer, H. (2022). A framework to estimate the large-scale impacts of energy community roll-out. Heliyon, 8 (7). https://doi.org/10.1016/j.heliyon.2022.e09905.[3] Fell, M. J. (2017). Energy services: A conceptual review. Energy Research & Social Science, 27, 129–140. https://doi.org/10.1016/j.erss.2017.02.010

Digital transformation processes in the course of industry 4.0 affect computer-aided manufacturing (CAM) in two ways: The acceleration of production and innovation cycles shortens the time to carry out CAM-planning tasks; simultaneously, an increasing product individualization raises the complexity of CAM-planning tasks and quality requirements for the planning results. Thus, CAM users need to solve complex CAM-planning tasks in increasingly shorter time frames. Efforts to meet the quality requirements nonetheless lead to overload and frustration of the user [1], [2]. To overcome this challenge, the R&D project CAM2030 aims to develop a new generation of CAM systems that integrates innovative technologies (artificial intelligence, cloud computing, and evolutionary algorithms) to make CAM-planning processes more efficient for the CAM planner. The innovation process requires a novel methodology that involves the stakeholders’ different perspectives, esp. the users’ preferences and needs, and brings them into compliance. This paper presents a co-creation-based framework for the agile development of AI-supported system components. The framework intends to continuously support the innovation process of complex software systems in a highly interdisciplinary team working collaboratively under remote conditions. The framework was developed successively in line with the project’s progress over two years. The resulting framework describes a multi-level and partly iterative approach that covers the following stages of the innovation process: (i) the elicitation, specification, and prioritization of requirements for AI-supported CAM systems, their user interface, and CAM user training; (ii) the design of an interactive prototype for selected parts of the user interface; (iii) the prototype testing; and (iv) the iteration of (i) to (iii) as well as the refinement of their output. The approach applies and adapts co-creation methods for use in online workshops. The research activities focused on the development, implementation, and evaluation of the single workshop concepts, partly complemented by studies investigating topics such as user expectations and requirements concerning new features and the system introduction. The main characteristics of the workshops are their interdisciplinary composition of participants, their conduction under remote conditions, and the mix of methods and tools to support collaboration in each stage of the innovation process [3], [4].The framework application shows a high potential to support the development of AI-supported CAM systems in creating a shared vision of the individual stages of the innovation and the innovation process as a whole. The framework helps to: (i) understand and reflect the user’s needs and preferences, (ii) align different and partly controversial perspectives, and (iii) identify and overcome sticking points of the system development. The project shows that the innovation and development process benefits from the active involvement of end users (workers and companies), the continuity of interdisciplinary exchange, and iterative testing. Limitations arise from the restricted application scope of the framework (innovating automated CAM system components for the CAM parameter optimization by well-educated CAM planners in German SMEs). Future research should consider the reconciliation of innovation processes with day-to-day business in manufacturing companies and the framework’s transferability to other application contexts. Acknowledgments: This research and development project is funded by the German Federal Ministry of Education and Research (BMBF) within the “Innovations for Tomorrow’s Production, Services, and Work” Program (funding number: 02J19B081) and implemented by the Project Management Agency Karlsruhe (PTKA). The authors are responsible for the content of this publication.References:[1] Hehenberger, P. (2020). Computerunterstützte Produktion: Eine kompakte Einführung. Berlin: Springer.[2] Jakobs, E.-M., Digmayer, C., Vogelsang, S. and Servos, M. (2017). Not Ready for Industry 4.0: Usability of CAx Systems. In: Ahram, T. and Falcão, C., eds Advances in Usability and User Experience. AHFE 2017. Advances in Intelligent Systems and Computing, 607th ed. Cham: Springer, pp.51-62. [3] Piller, F. T., Ihl, C. and Vossen, A. (2010). A typology of customer co-creation in the innovation process. SSRN Electronic Journal, 4. [4] Rußkamp, N., Digmayer, C., Jakobs, E., Burgert, F., Schirmer, M., Niewöhner, S. (2022). New ways to design next-generation CAM systems. An integrated approach of co-creation and process modeling. In: Waldemar Karwowski and Stefan Trzcielinski (eds) Human Aspects of Advanced Manufacturing. AHFE (2022) International Conference. AHFE Open Access, vol 66. AHFE International, USA. http://doi.org/10.54941/ahfe1002682