This article presents a domain-specific language for writing highly structured multilevel system specifications. The language effectively bridges the gap between requirements engineering and systems architecting by enabling the direct derivation of a dependency graph from the system specifications. The dependency graph allows for the easy manipulation, visualization and analysis of the system architecture, ensuring the consistency among written system specifications and visual system architecture models. The system architecture models provide direct feedback on the completeness of the system specifications. The language and associated tooling has been made publicly available and has been applied in several industrial case studies. In this article, the fundamental concepts and way of working of the language are explained using an illustrative example.

The use of design methods across multiple design phases of the product development process often leads to inconsistency, the loss of transparency, and the rejection of design methods by practitioners. The authors of this work intend to develop a central modelling approach that supports consistency, based on the integrated function modelling (IFM) framework. Therefore, various design methods from the literature were examined for their techniques and content to identify indicators for supporting consistency. The results led to an enhancement of the IFM framework.

Claims about what justice “requires” and the “requirements” of justice are pervasive in political philosophy. However, there is a highly significant ambiguity in such claims that appears to have gone unnoticed. Such claims may pick out either one of two categorically distinct and noncoextensive kinds of requirement that we call 1) requirements-as-necessary-conditions for justice and 2) requirements-as-demands of justice. This is an especially compelling instance of an ambiguity that John Broome has famously observed in the context of claims about other requirements (notably the requirements of rationality and morality). But it appears to have been overlooked by political philosophers in the case of claims about the requirements of justice. The ambiguity is highly significant inasmuch as failing to notice it is liable to distort our normative thinking about politics and make us vulnerable to certain kinds of normatively consequential errors: both mistakenly drawing inferences about what justice demands of us from claims that certain states or societies are not just; and mistakenly drawing inferences about what states or societies are or would be just from claims that justice does not demand of states or societies that they do certain things. Paying greater attention to the distinction between these two different kinds of requirements and the ways in which they come apart is helpful, not merely in avoiding these distortions and errors, but also in resolving, or at least clarifying, a number of other notoriously murky meta-normative debates, especially various important debates about realism and idealism in political philosophy.

The objective was to evaluate energy partitioning and predict the relationship between metabolizable energy (ME) and digestible energy (DE) in hair sheep fed tropical diets at three feeding levels (maintenance, intermediate and high). To evaluate the energy partition, a database with 114 records (54 non-castrated males and 60 females) from comparative slaughter studies was used. To estimate the ratio ME:DE, 207 observations (74 non-castrated males and 133 females) were used from six studies in a multi-study approach, two indirect calorimetry studies (n = 93) and four comparative slaughter (n = 114), using a mixed model and study as random effect. A simple linear regression equation of the ME against DE was fitted to predict the efficiency of DE to ME conversion. Gas losses were greatest (P < 0.05) for animals fed at maintenance level (7.92% of gross energy intake). The variations of energy losses in the urine were 2.64, 2.06 and 2.08%; faecal losses were 34.37, 37.80 and 36.91% for maintenance, intermediary and high level of feeding, respectively. The regression analysis suggested a strong linear relationship between ME and DE, generating the model ME (MJ/day) = −0.1559 (±0.07525) + 0.8503 (±0.005864) × DE (MJ/day). This study highlights the importance of the relationship ME:DE. Equation/factor 0.85 presented herein is alternative that could be used for the calculation of ME from DE in feedlot diets tropical. In conclusion, we suggest that for hair sheep fed tropical diets the conversion factor 0.85 is more adequate to predict ME from DE.

Intimate partner violence against women (IPVAW) is a public health problem that affects women worldwide. Consequently, victims frequently go to healthcare centers, usually with a cover reason. To address this problem, national and autonomic protocols to respond to IPVAW in health systems have been developed in Spain. In this regard, the role of primary care physicians (PCPs) will be essential for addressing IPVAW, but they could encounter obstacles in doing so. The purpose of this study was to explore how IPVAW is addressed in healthcare centers in Spain. This study synthesized the information available in the protocols to address IPVAW among health care workers in Spain and analyzed it according to World Health Organization (WHO) guidelines. Additionally, PCPs’ perspectives on these protocols and the nature of IPVAW attention from healthcare centers were explored through a focus group. The findings displayed that, although the protocols mostly conform to WHO guidelines, they are insufficient to address IPVAW. Generally, PCPs were unaware of the existence of the protocols and referred to the lack of training in IPVAW and protocol use as one of the main obstacles to intervening, along with a lack of time and feelings as well as cultural, educational, and political factors. The adoption of measures to ensure that PCPs apply these protocols correctly and to approach PCPs’ obstacles for addressing IPVAW in consultations will be crucial for the care of victims.

Digital media are a means to deliver products and services, but also a channel to interact with consumers and a source of information on users’ preferences. Data shared by customers on the web, the User-Generated Content (UGC), can give entrepreneurs a detailed perspective of the market. This work examines an application of Natural Language Processing techniques on UGC to discover insights on users' opinions. We collected more than 13.000 reviews of software from digital stores and review website to gather information on the customers’ perspective and their response to a given marketing strategy in two case studies on digital product's launch. The objective is to give support to two Italian companies in the process of business model development through data-driven evidence. We aim to discover who are the users and which are their needs using a lexicon-based approach to mine unstructured text. The results provide qualitative and quantitative descriptions of the market segments. We propose a method to examine UGC and to explore customers’ behavior on social media. The findings helped managers for the development of their business model, enhancing an informed decision-making process.

Our society is built on engineered systems. Engineers are becoming increasingly concerned with the sustainability of systems, particularly their ability to adapt to a changing world. Recently, there has been increased interest in exploring how design margins provide opportunities for a system change. There have been great developments in determining how design margins can absorb change at a system level, but it is still not clear how design margins might provide change opportunities at a decision variable level. In this paper, we show how system-level margins could be deconstructed to explore what change opportunities they may provide at a decision variable level. We also investigate how the coupling of functional requirements limits how system-level margins can be operationalized. Our analysis suggests that design margins can provide meaningful change opportunities at the decision variable level, but the mechanisms that produce these opportunities are complex. These insights lay the groundwork for future research on mapping and representing design margins in the context of system adaptability.

Currently, engineers need to manually analyse requirement specifications for determining parameters to create geometries in generative engineering. This analysis is time-consuming, error-prone and causes high costs. Generative engineering tools (e.g. Synera) cannot interpret natural language requirements directly. The requirements need to be formalised in a machine-readable format. AI algorithms have the potential to automatically transform natural language requirements into such a formal, machine-readable representation. In this work, a method for formalising requirements for generative engineering is developed and implemented as a prototype in Python. The method is validated in a case example using three products of an automotive engineering service provider. Requirements to be formalised are identified in the specifications of these three products, which are used as a test set to evaluate the performance of the method. The results show that requirements for generative engineering are formalised with high performance (F1 of 86.55 %). By applying the method, efforts and therefore costs for manually analysing requirements regarding parameters for generative engineering are reduced.

Additive manufacturing (AM) processes are now integrated in industry. Therefore, new methods to design AM parts taken into consideration capabilities and limitations are necessary. It is very difficult for teachers to effectively guide students with ideas emerging from generative design tools. AM requires significant preparation and compromises. Topological optimization is also used depending on requirements. A significant impact on the final part quality is related to the part orientation and geometric dimensions. Therefore, this white paper focuses on detailed design steps to prepare future technicians and engineers to design for additive manufacturing. Active teaching pedagogy guideline is proposed. Students have to think in 3D and use analysis tools to create and validate the optimised design. They use immersive tools to review constraints and model diagnostic algorithm to generate data. Present approaches with design guidelines and tools enable to create AM rules based on it. Questionnaire shows that students need explicit knowledge information. Features recognition and geometry diagnostic are mandatory for complex model. Immersive tool helps to evaluate post-processing. They can now relate AM product-process relationship.

Many designs are “driven” by requirements that describe maximum or minimum values of high- variability variables that must be considered. In ergonomics, minima and maxima of anthropometric variables like body height shape the design of a product. Similarly, in structural design, the highest environmental loads that can be expected during the lifetime of a product drive the design. Consequently, a wide range of methods that help designers deal with extreme requirement values has been developed. In this paper, we review these methods and propose a model for the process of dealing with extreme requirement values. The model comprises two broad stages. In the first stage, requirement values are statistically defined and in the second stage, a design is synthesized and evaluated against the requirement values. Throughout the paper, we use two examples: the design of an ergonomic chair and of an offshore wind turbine. We focus on how requirement values are defined for these two products and how they are used throughout the design process. Although these products are vastly different, both are designed by statistically deriving requirement values and then systematically designing against these values.

The transmission of information between requirements modelling and function modelling in the product development process often appears challenging because of multiple used models and different terminology of specific disciplines. The integrated function modelling (IFM) framework is used for functional analysis of technical moderate complex systems and supports cross-disciplinary modelling and communication in the design team. To improve the applicability of this method and its supporting purpose in the modelling process, the authors combined requirements as an additional entity with the existing entities of this method. Furthermore, the extended framework has been used to visualise the procedure with this approach as an example. The outlook provides the potential for further development of the method.

Nowadays, companies operate in increasingly competitive and dynamic markets with fast-changing customer needs. Simultaneously, major advances are being made in information and communication technologies, and the digitization of products is progressing. Based on these economic and technological trends, smart product-service systems (PSS) are emerging as a new form of business model. Recent studies show that the transition to developing smart PSS is a major challenge for companies and that they require methodological support, as their internal structures are undergoing significant changes.

In order to provide a sound basis for support, we have undertaken a comprehensive study to identify requirements for a smart PSS development framework. 24 interviews and 5 workshops with companies that have recently focused on the development of smart PSS provide a rich set of empirical data to explore the challenges faced by companies today. We systematically analyzed the data and evaluated the results with our respondents. To increase the robustness and generalizability of our findings, we performed a contextual literature review and analyzed additional cases. This led us to a set of 17 requirements for a smart PSS development framework.

The production preparation process (3P) enables collaboration between design and production engineers during product development but its efficiency is limited by the abundance of documentation of manufacturing constraints and capabilities. Empirical studies showed that use of production requirements can increase the efficiency of 3P, however, the support for production engineers to capture and share production requirements is scarce. A method to support production engineers in identifying, defining, structuring and sharing production requirements and collaborating with design engineers is presented. The method has three major parts - focus areas and requirement categories, a worksheet for production requirements capturing and prioritization, and a workflow for using the worksheet. The method was developed in collaboration with practitioners and contributes to the existing knowledge by providing production engineers with a structured way of working with production requirements. Evaluation of the method in the case company showed its usability when developing product variants and that additional work is needed to support the development of new product families and assembly lines.

This paper explores the value of the visual features of assistive products for a positive psychological impact on users. The research focuses on upper limb prosthetic devices and their aesthetic impact on the user. Within the presented study, these products are identified not only as assistive products but also as fashion accessories. A case study is presented that applies an understanding of human behaviour, motivation, and perception of semantic cues within the cultural context of a given society to deliver a more socially acceptable child's upper limb prosthetic.

Optimization-driven design offers advantages over traditional experience-based mechanical design. As an example, topology optimization can be a powerful tool to generate body shapes for Additive Manufacturing (AM). This is helpful, when (1) load paths are non-intuitive due to complex design domains or boundary conditions, or (2) the design process is to be automated to minimize effort associated with experience-based design. However, practically relevant boundary conditions are often difficult to put into a formal mathematical language to, for example, either feed it into a topology optimization algorithm, or provide precise quantitative criteria for CAE-supported manual design. This paper presents a survey of three industry use cases and identifies three types of requirements: the first can be directly cast into parts of an optimization problem statement (∼ 40%), the second is considered indirectly by adapting the optimization problem without explicit reference to the requirement (∼ 20%), and the third is only assessed after the design is finalized (∼ 40%). For categories 2 and 3 we propose directions of improvement to support formulating complex design tasks as unambiguous design problems.

ABSTRACT

Solution spaces are sets of designs that meet all quantitative requirements of a given design problem, aiding requirement management. In previous works, ways of calculating subsets of the complete solution space as hyper-boxes, corresponding to a collection of permissible intervals for design variables, were developed. These intervals can be used to formulate independent component requirements with built-in tolerance. However, these works did not take physical feasibility into account, which has two disadvantages: first, solution spaces may be useless, when the included designs cannot be realized. Second, bad designs that are not physically feasible unnecessarily restrict the design space that can be used for requirement formulation.

In this paper, we present the new concept of a requirement space that is defined as the largest set of designs that (1) allows for decomposition (e.g., into intervals when it is box-shaped), (2) maximizes the useful design space (good and physically feasible), and (3) excludes the non-acceptable design space (bad and physically feasible). A small example from robot design illustrates that requirement spaces can be significantly larger than solution spaces and thus improve requirement decomposition.

Product development is facing new challenges due to increasingly complex and individualized products in small batch sizes and short time to markets at high quality standards. Integrated product data management along with systematic requirements engineering and early stakeholder involvement are known to be key enablers for the success of future product development. In software development, established platforms such as GitHub exist, which have been shown to improve stakeholder communication, requirements elicitation, and software design decisions. In product development, similar platforms exist with impressive functionality, but which have some drawbacks such as closed source licenses, vendor-specific data formats, and expert-level user interfaces. To overcome the current situation, we study how the ideas of GitHub can be translated to an open source solution for product development and which concepts can be reused or must be changed. Core deliverables of our work are (1) an integrated data model of requirements (or design tasks), project schedules, and revisions of computer-aided design (CAD) models as well as (2) an interface model.

Smart manufacturing enterprises rely on adapting to rapid engineering changes while minimizing the generated risk. Making informed decisions related to engineering changes and managing risks against unexpected costs requires more information to be extracted from limited data. However, limited information in early-stage design can come in many forms, namely text and images. The development of innovative design tools and processes to link multisource data together is essential to assist designers in building model-based engineering (MBE) systems. However, the formal computational linking of multisource data is yet to be realized in MBE. We propose a framework to implement transfer learning and integrate domain specific knowledge to bridge this information gap. A synthetic dataset is created using web scraping techniques based on keywords extracted from the requirements. Requirement-image pairs are used to fine tune a contrastive language-image pretraining model to acquire domain knowledge. The results demonstrate how the content of images can be used to indicate all affected requirements for tracing engineering changes in a complex system.