The ongoing development of technology and AI facilitates the emergence of service robots in various application fields. Hence, the development of robot-infrastructure product-service systems (PSS) will become increasingly important. Based on the existing literature we propose a new methodological approach for a joint development of robot and infrastructure in the context of a socio-technical system with various stakeholders. We suggest digital models and physical prototypes to synchronize service and product development. The applicability is demonstrated for autonomous waste management robots.

The paper presents a hybrid user-centred/simulation approach to populate the design specification. It presents an application in the field of exoskeleton design, with the final goal to support workers to carry out their professional tasks. More than 100 professionals (mostly health workers) participated in the survey. The qualitative requirements were extracted are then tested in simulation environments. The approach proved to generate meaningful results for product concept generation. Beyond the expectations, the simulation also showed more adequate product architectures.

This paper presents a novel method for automatic contradiction detection in requirements engineering using a hybrid approach combining formal logic with Large Language Models (LLMs), specifically GPT-3. Our three-phase process detects contradictions by identifying conditionals and pseudo-grammatical elements, and employing LLMs for nuanced contradiction detection. Tested extensively, including on a real-world electric bus project, our method achieved 99% accuracy and 60% recall. This approach significantly reduces manual effort, enhances quality, and is scalable for future advancements.

Transferring natural language requirements to use case diagrams helps to avoid inherent ambiguities. However, this is usually a manual, time-consuming task that can be accelerated by utilizing Artificial Intelligence in terms of Natural Language Processing. Thus, this contribution proposes a conceptual framework for automatically grouping interrelated functional requirements and deriving use case diagrams by combining formerly isolated approaches. Moreover, the latter are evaluated by a qualitative potential analysis to support their future industrial application.

Anticipating all technical requirements that a product must meet throughout its lifespan has become difficult due to a rise in market, regulatory, and technological uncertainty. As a result, the attribute values of these requirements may be highly uncertain at the start of product development. We propose a mathematical model that captures and quantifies this uncertainty in a clear and comprehensive manner. We evaluate the approach by encoding uncertain requirements for an automotive project. Misconceptions regarding probabilities are alleviated and the requirements are unambiguously defined.

Product development is multidisciplinary with high uncertainties necessitating coordinated decision-making between design and production. This paper presents a method to work with production requirements to support production preparation during product development aligned with different product and production maturities. The work was conducted in collaboration with two global manufacturing firms. The method supports identification, definition, and structuring of production requirements and the collaboration between design and production engineers for requirement prioritization and follow-up.

Manufacturing process selection presents numerous challenges to designers, including product complexity, consideration of production volumes and part tolerances. This paper introduces a design support tool based on the axiomatic design model to systematically transform requirements into functions and technological capabilities. The results from an evaluation of the implemented prototype tool in the field of medical device design demonstrates its usefulness in selecting the most suitable candidate manufacturing process for a given artifact, while taking into account multiple user requirements.

Requirements changes are a leading cause for project failures. Due to propagation effects, change management requires dependency analysis. Existing approaches have shortcomings regarding ability to process large requirement sets, availability of required data, differentiation of propagation behavior and consideration of higher order dependencies. This paper introduces a new method for advanced requirement dependency analysis based on machine learning. Evaluation proves applicability and high performance by means of a case example, 4 development projects and 3 workshops with industry experts.

As an outcome of the multi-criteria evaluation of different alternatives, product developers receive information on whether the evaluation alternatives meet the demanded property profile. If not, product characteristic and property changes are required, which can have desired and undesired effects. This contribution presents an MBSE-based approach, which extends the relational requirement model by value functions and product properties. Its novelty can be found in the integration of multi-criteria decision models, which are used to improve alternatives based on property change impact analyses.

Adaptive façades (AF), unlike conventional façades, respond to their environment to reduce energy consumption while increasing comfort. The planning of AF presents architects and engineers with a variety of challenges. One central challenge is the specification of the right planning goals in the early phases. This paper identifies in a systematic literature review the main characteristics which were crucial in previous realizations of AF. Due to the comprehensive approach it provides a reference for the goal definition of subsequent projects and the development of further methodical support.

This paper presents approaches to compare criteria and help designers make decisions based on trade-offs between criteria. The impetus for the paper is to identify possible directions to improve/innovate a product and propose a value shell model displaying various criteria or their combination to represent the effort needed to improve the criteria. The focus is on automotive market and approaches in industry and government are differentiated. Since the effort (manpower, cost and time) needed to improve a product is not public knowledge, the paper leaves the evaluation of the approach to users.

The design process aims to maximize the value in the end solution. For traditional manufacturing firms pursuing a servitization strategy, non-functional requirements become more important compared to before. Therefore, this paper investigates issues in capturing and utilizing non-functional requirements for value creation in a servitizing firm. A single case study was conducted, which resulted in six issues across the design process. It was evident from the research that the firm requires new support to enable a better inclusion of non-functional requirements in the design process.

Finding redundant requirements or semantically similar ones in previous projects is a very time-consuming task in engineering design, especially with multilingual data. Due to modern NLP it is possible to automate such tasks. In this paper we compared different multilingual embeddings models to see which of them is the most suitable to find similar requirements in English and German. The comparison was done for both in-domain data (requirements pairs) and out-of-domain data (general sentence pairs). The most suitable model were sentence embeddings learnt with knowledge distillation.

Requirements act as a limitation of the solution space, which represents the stakeholders’ needs and guides the whole product development process. Therefore, forgotten requirements can lead to wrong decisions when using them as a basis for decision-making. This contribution introduces a novel approach to link the requirement and evaluation criteria models to address this problem. For setting up those criteria consistently, the requirements are classified using natural language processing and derived by a ruleset based on a developed mapping between requirement classes and criteria types.

Future transport will change drastically with the introduction of automated vehicles. Here, Autonomous Mobility on Demand (AMoD) will play a major role, requiring a radical change of vehicle design, with many different conceivable concepts. This technology shift holds high potentials and high risks. Uncertainties about future usage profiles, operator and customer requirements have to be dealt with. An approach to elicit initial requirements for future vehicle concepts considering the entire ecosystem is introduced. The applicability is shown for a specific urban mobility scenario.

A reference process should consider to the needs and behaviours of the process users, as well as all relevant restrictions and boundary conditions within the company and its environment. Therefore, this contribution provides a method to synthesize relevant requirements on reference processes and supports the consideration of these requirements during the design of a new, company-specific reference process based on meta-models. The developed method was used to design a reference process for automotive predevelopment projects and its applicability and usefulness was evaluated successfully.

Identification of latent or unarticulated customer and other stakeholder needs has been a significant barrier to improving the efficiency and effectiveness of the front-end phase of new product development processes. In-depth determination of stakeholder needs entails analysis of their intentions; the overall aim of the work reported in this article is to establish a framework of intentional analysis, and its associated methods and techniques for improving traceability of design practice during the early phases of the design process. The specific aim of this article is to present a conceptual framework for design rationale systems. The framework built upon the cross-fertilization of approaches and methods drawn from systems engineering and philosophy, focussing on the notions of antecedence and consequence. It was developed in the course of tackling design problems originating in industrial contexts. The methods developed were thus evaluated, updated, and refined in real applications. Two application cases are described that have been drawn from the aerospace and power sectors, respectively. The applications showed that the framework's central antecedent/consequent scheme provides a cell from which to develop either a history of actual successive changes, or a tree of alternative possible projected designs.