The amount of information in our society and its opportunities have given rise to Big Data research. The systems supplier industry needs suitable tools and methods to ensure the harvest and utilization of Big Data in their product development. This paper used Systems Thinking to analyze the current state in the industry and suggested leverage points for further research direction. The findings suggest that the research project should emphasize the industry cases, the collaboration between the companies and academia, develop a Big Data systems architecture, and maintain a socio-technical view.

In the uncertain process of product development, the developer is decisively responsible for product success. He operates in a complex environment that directly influences his synthesis and analysis activities. The context of the socio-technical system of product development has already been extensively researched and defined by a large number of factors. However, the developer is described as part of the context and not as the centre, which means that many of these factors have no interaction with the developer. For the design of methods and tools that support the developer in his activities in the development process, a summarizing understanding of the influences on and by the developer is necessary. In order to create a unified understanding of the developer at the centre of product development, a Systematic Literature Review was conducted. In this article, the procedure and findings are presented. The aim was to identify factors from the literature that significantly influence the interaction of the developer in his environment. As a result, these were documented in a model, which represents the basis for further, human-centred research in the context of product development.

Do different sustainable design methods generate different sustainable design ideas? Do they also drive different product innovation ideas? This project empirically tested three design methods: The Natural Step, Whole System Mapping, and Biomimicry. Testing involved qualitatively categorizing 1,115 design ideas from 23 workshops for over 30 companies, including consultancies and manufacturers in consumer electronics, furniture, and apparel. The categorized ideas were then counted to determine if the different design methods caused different kinds of ideas. They did. For example, The Natural Step drove more ideas on green material choice, circular end of life, and social impacts, while Biomimicry drove more durability ideas and Whole System Mapping drove more cost reduction ideas, among other differences. Overall, The Natural Step generated the highest percentage of sustainability ideas, Biomimicry generated the most innovation ideas, and Whole System Mapping generated a balance of both. These preliminary results should help designers and engineers choose design methods suited to the types of design solutions they desire.

Risk management (RM) in new product development (NPD) is often implemented as a standardized framework and ends up being carried out as a tick the box, non-value adding activity. To avoid this problem, RM needs to be tailored to the organization and NPD project. This paper identifies a gap in both understanding and facilitating tailoring, i.e. design of RM systems in NPD. To understand how to design RM systems, we must better understand how RM adds value to NPD activities. We applied Product Development Value Stream Mapping (PDVSM) to RM and conceptualized a Risk Value Stream Mapping (RVSM) framework to support design. Through a state-of-the-art literature review, we identified typical categories of value and waste in RM as well as approaches to model the RM in NPD. We developed and tested components of the RVSM framework based on PDVSM in three case companies. In this paper, results are presented regarding waste, value and potential ways to model the value stream in RM. The framework enables a diagnosis of the current state of RM in companies and supports future design activities pertaining to RM systems. This paper is positioned at the intersection of design, lean thinking and RM

In the midst of Industry 4.0 where digitalisation is stimulated through the Internet of Things (IoT), Big Data, and machine learning technologies, an increasing volume of valuable data has been acquired from sensors and interconnected devices. This data-driven paradigm can enable organisations to create new or improved products and services, build long-term customer relationships in a value co-creation manner, adapt to continuous business reconfiguration or address societal challenges such as sustainability. Scientific research addressing Data-driven design has increased steadily in the last few years. However, despite this, there is still a need for a comprehensive understanding of data-driven design processes. Thus, through a systematic literature review, we review the data-driven design activities observed in the new product and service development and types of data utilised in New Product Development (NPD) process. This paper contributes to design research and through reviewing the current landscape of Data-driven design identifies ten data-driven design activities and four-dimensional aspects in NPD process.

Studies of supplier involvement in product development have revealed potential benefits including faster time to market, reduced cost and increased quality. However, existing literature has mainly focused on the customer's perspective on advantages, disadvantages and factors to be considered when involving suppliers in product development. This paper addresses the supplier's perspective by answering following research question: How do challenges that originate from involvement in customer's product development affect a supplier? The question is answered through a single case study at a supplier that develops and manufacture products primary used in capital goods. Thirteen challenges are identified, classified as being internal or external, and categorised into five areas: (A) Customer requirements, (B) Information exchange between customer and supplier, (C) Product variety management, (D) Design- manufacturing integration and (E) Processes and work instructions. The findings suggest that internal challenges need as much attention as external ones that originate from the customer. Also, an indication of when the challenges affect the supplier during product development is presented.

Manufacturing process (MP) selection systems require a large amount of labelled data, typically not provided as design outputs. This issue is made more severe with the continuous development of Additive Manufacturing systems, which can be increasingly used to substitute traditional manufacturing technologies. The objective of this paper is to investigate the application of image processing for classifying MPs in an unsupervised approach. To this scope, k-means and hierarchical clustering algorithms are applied to an unlabelled image dataset. The input dataset is constructed from freely accessible web databases and consists of twenty randomly selected CAD models and corresponding images of machine elements: 35% additively manufactured parts and 65% manufactured with traditional manufacturing technologies. The input images are pre-processed to have the same colour and size. The k-means and hierarchical clustering algorithms reported 65% and 60% accuracy, respectively. The algorithms show comparable performance, however, the k-means algorithm failed to predict the correct subdivisions. The research shows promising potential for MP classification and image processing applications.

The early consideration of human factors in product development hugely favours the development of products, which excel with a positive user experience. The virtual environment of product development however, still has significant gaps in the virtual assessment and simulation of human factors, especially for user-product interactions composed of human movements. This motivates us to introduce a concept for data-driven prediction and analysis of user-product interactions. Heart of the concept is a predictive component that models the interaction between the user, represented by a musculoskeletal model, and the product, represented by product characteristics. We describe the implementation of this concept based on a pilot study for a lifting task. Motion capturing was performed to build a database and compare the results of our novel approach. The resulting kinematic and dynamic quantities show similar curve profiles with a small constant offset to the measured data. This indicates that the concept enables the virtual comparison of different designs or concepts regarding human factors.

The digitalisation of the industry offers new opportunities to discuss design activities and support tools. Advancement in AI allows thinking about new Designer-AI tools interaction in the design process. The paper aims to initiate a characterisation of tools issued from researches in the application of AI in Design to rethink the division of work between Designer-AI tools. The paper is based on the literature on the concept of Levels of Automation in cognitive engineering, manufacturing and robotics, and proposes a grid of characterisation of the Level of Automation for the design process.

Understanding the viewpoint of clinicians in a healthcare setting is a vital task to comprehend the success of patients undergoing physical rehabilitation. Addressing user experience is an essential activity which designers undertake when formulating product specifications at the early stages of product design. The involvement of clinicians during the product use-phase influences the progress and achievements attained by the patients throughout their rehabilitation journey. Several clinicians (n=16) were asked to participate in a qualitative study to evaluate the performance of different personae in activities of daily living. The experiences of patients who use rehabilitation products as part of their therapy session at the clinic were evaluated. Based on this evaluation, a set of clinician requirements were formulated to reflect the overall experience when using rehabilitation products. Understanding these requirements brought about several implications to be considered during the design cycle. Through these considerations and by adopting a user-centred design approach, designers are in a better position to design innovative products targeted at providing a high-quality user experience which increases customer satisfaction.

Increasing product complexity and individual customer requirements make the design of optimal product families difficult. Numerical optimization supports optimal design but must deal with the following challenges: many design variables, non-linear or discrete dependencies, and many possibilities of assigning shared components to products. Existing approaches use simplifications to alleviate those challenges. However, for use in industrial practice, they often use irrelevant commonality metrics, do not rely on the actual design variables of the product, or are unable to treat discrete variables. We present a two-level approach: (1) a genetic algorithm (GA) to find the best commonality scheme (i.e., assignment scheme of shared components to products) and (2) a particle swarm optimization (PSO) to optimize the design variables for one specific commonality scheme. It measures total cost, comprising manufacturing costs, economies of scales and complexity costs. The approach was applied to a product family consisting of five water hose boxes, each of them being subject to individual technical requirements. The results are discussed in the context of the product family design process.

Monitoring properly the circularity performance of technical products is a point of increasing importance. Yet, evaluating the circularity potential of products during (re)design and development phases is a challenging task. In this study, several C-indicators are experienced by doctoral students and industrialists through two workshops on a real-world industrial product. The values obtained for each indicator are collected and analyzed: as all participant are working on the same technical product with the same dataset, the circularity scores calculated are compared to discuss the reliability and the uncertainty related to these indicators. These new empirical insights are put in parallel with the existing critical analyses of C-indicators from literature. As a result, future research directions on circularity indicators are advanced and discussed, including: the integration of uncertainty considerations into the assessment methodology of circularity indicators; the uptake by industry of such indicators during product design and development; the link between circularity and sustainability scores.

The use of exoskeletons promises improved ergonomics, empowerment of users and prevention of musculoskeletal disorders. However, the development process is complex and a generic development methodology that will guide and assist designers through it is missing. The goal of this paper is to describe a methodological approach that will assist the conceptual design of exoskeletons. Based on derived methodological requirements, activities 1, 2, and 3 of the VDI 2221 (Methodology for the development of technical products) are specified to adapt the generic guideline to the development process of exoskeletons. These activities include the analysis and determination of the relationship between the use case, product requirements and motions, technical functions, and design solutions. For generating a list of product requirements designers must focus on the workers’ motions and needs for a for a task-specific and personalised development. Use case specific movements are generalised by using rotational and translational basic movements that result in six degrees of freedom and from which a function structure is derived. The method is critically reviewed based on the established methodological requirements.

Adaptive buildings constitute an interdisciplinary approach for realizing the next generation of buildings in order to reduce the immense material requirements and energy demand throughout all lifecycle phases. Based on a novel cooperation between the disciplines of Architecture and Civil and Mechanical Engineering, adaptive support structures and skins are developed within the Collaborative Research Centre SFB 1244. A holistic planning process is required in order to reduce the high complexity and achieve a goal-oriented procedure during the planning of such buildings and the development of integrated systems.

Part of this research is the development of new specific and the transfer of established methods from different disciplines. The experience gained during the planning of an adaptive, high-rise demonstrator building within the research project has shown that the methods for application must be provided in the form of a method toolbox to present their purpose, application time and results within the planning team. Based on the examination of existing method toolkits, this paper focuses on the development of an approach while considering context-specific requirements.

As the benefits and potentials of agile approaches become increasingly clearer, also hardware product development seeks to apply those methods and procedures. However, mechatronic hardware products are often subject to stricter safety regulations so that a consequent risk management is essential. This paper presents a risk management method suitable for agile product development projects. The method together with an adapted agile procedure were applied and evaluated in a successful industrial case study. This lead to the extended application of agile approaches in other parts of the company.

Operational Excellence (EO) is increasingly present in scientific and managerial news. Increasing competition, increasingly uncertain events, demands customers and society increasingly pressing, the evolution of systems towards cyber physics systems, push organizations to adapt their engineering methodologies. Excellence operational (EO) is one of the answers proposed by the scientific literature to make engineering organizations more flexible, more responsive, more efficient and therefore more competitive. In this article, we share a state of the art of operational excellence (EO) in system engineering (IS) through its most modern methodologies: the Lean Six Sigma (LSS), Theory of Constraints (TOC) and Agility (A) with an operational approach including social and societal responsibility via the Quality-Cost-Delay-Security-Environment (QCDSE). We finish by sharing four assumptions that will serve as a basis, in our future contribution, to propose a synergy solution to implement an Operational Excellence approach in systems engineering organizations.

The strive for design principles, qualitative and quantitative design tools, and product development methodologies that enable and support the design of robust products, that is products which are insensitive to noise and variation, is an ongoing challenge for both practitioners and academics. This paper reviews and classifies recent research efforts dedicated to robust design originating from the design society and carves out important challenges and potentials for future research. The main novelty of the paper can be found in the structured analysis and classification of recent robust design efforts as well as in the systematic elaboration of future research challenges, which seeks to stimulate a discussion on future tasks and challenges in robust design research.

The purpose of this work is to compare the creative outcome in the educational context of students belonging to two different cultures, namely Singaporean and Portuguese and determine whether they respond differently to the same design brief. The participants from both samples equal 121 student designers and span from 18–25 years old. Students were randomly distributed within a uniform, standard of student performance, which allowed for fair comparison between groups. Expert judges were employed to judge the creativity of concept sketches generated during a Collaborative Sketching exercise. To evaluate the creative outcome, we employed the Consensual Assessment Technique based on a rubric-based system developed in our earlier works. The analysis of variance procedure revealed no statistically significant difference between the averaged total scores of the two groups on the appropriateness measure. However, the student designers from both samples showed statistically significant differences when provided with a baseline brief in the novelty measure. In consideration of the overall creativity scores, a relatively equivalent performance is observed across the two universities.

It is important to be able to compare and evaluate different solutions early in development. This paper proposes a method for structuring historical data into a data model that can support the evaluation of new design concepts. The data is contextualized by linking it to a hierarchical decomposition of existing products. Two case studies were conducted to evaluate the value of using historical data when evaluating new concepts. The cases confirm that the proposed method is useful for evaluation of new concepts.

Today, product success more than ever depends on the satisfaction of consumer needs. Besides, manufacturers need to shorten development cycles and accelerate product release in order to stay competitive. This is achieved by applying customer-oriented methods allowing for fast and reliable acting. During the early phase of product development, requirements acquisition is crucial for later success of products, since specifications are most influenceable at this point. Referring to the decisive concept generation phase, material and production definition is difficult due to the highly complex interrelations between material properties, production process capabilities, and resulting product characteristics. Especially in the context of lightweight design, concurrent material and processing technology selection must be considered due to its various possible interfaces.

Thus, this contribution outlines an integrated approach towards an enhanced material and process related, customer-oriented requirements acquisition during the early phase upstream of product detailing. Here, conventional multi-criteria decision-making and tactile recognition are employed in an agile transformation model.