Collaborative Design Framework Research Articles

LLM enabled generative collaborative design in a mixed reality environment

In the collaborative design process, diverse stakeholder backgrounds often introduce inefficiencies in collaboration, such as delays in design delivery and decreased creativity, primarily due to misunderstandings and communication barriers caused by this diversity. To respond, this study proposes an AI-augmented Multimodal Collaborative Design (AI-MCD) framework. This framework utilizes Large Language Models (LLM) to establish an iterative prompting mechanism that provides professional design prompts for Generative AI (GAI) to generate precise visual schemes. On this basis, the GAI cooperates with Mixed Reality (MR) technology to form an interactive and immersive environment for enabling full participation in the design process. By integrating these technologies, the study aims to help stakeholders form a unified cognition and optimize the traditional collaborative design process. Through a case study involving the development of heart education products for children, the effectiveness of the framework is emphasized, and the practical application and effectiveness of the proposed method innovation are demonstrated.

The Design Posture: A Collaborative Learning-By-Doing Approach

In September 2021, Codesign Toscana1 organised a pop-up school animated by a concept implicitly present in many design-related debates and around which our practices as an interdisciplinary collective have developed over the last five years: the “Design Posture” (hereafter DP). By relying on a collaborative design framework, we experimented with a cooperative learning approach using the urban context as a non-formal education platform and, following the direct experience of the pop-up school, named “Response/Ability” we discuss the possibility of new horizons in the urban context to organize educational platforms that rely on reclaimed city spaces and that generate insights for young generations.

A Model Driven Framework for Collaborative and Dynamic Design and Implementation of NoSQL-Oriented Data warehouses

Nowadays, modernizing the data warehouse ecosystem is a key challenge in decision support systems. This modernization is crucial for ensuring scalability and meeting evolving business requirements, especially with the advent of big data. A promising solution involves implementing data warehouses with contemporary data stores, such as NoSQL. In this context, we introduce in this paper a framework that leverages Model-Driven Architecture (MDA) to design and implement modern data warehouses across NoSQL data stores. Our MDA approach aims to offer a collaborative, dynamic, and reusable process for developing NoSQL-oriented data warehouses tailored to specific project requirements. It facilitates the automatic and dynamic generation of a hybrid data warehouse model from its conceptual model, which encompasses structural, domain, and access parameters. Moreover, our framework includes the generation of implementation code for the data warehouse, along with a set of files to validate, document, and illustrate the data warehouse schema on a target platform. Finally, we present a detailed case study to highlight the effectiveness of our MDA framework.

Optimal Stealthy Attacks With Energy Constraint Against Remote State Estimation.

This article investigates the problem of energy-constrained stealthy attack strategy against remote state estimation for cyber-physical systems. Taking into account the energy constraint, the malicious attacker is required to schedule the off-line generated signals to modify the transmitted data with limited times over a finite-time horizon under the stealthiness condition, which makes the design of attack strategy more complex. Different from the attack schedules which are studied on the basis of prescribed attack signals in the existing results, the attack strategy is presented under the framework of collaborative design to deteriorate the estimation performance to the largest extent, which yet leads to the coupling between the attack schedules and attack signals. To overcome the difficulty without sacrificing the optimality, the attack design problem is solved in two steps. First, analyze the problem with the given attack schedule to derive the optimal attack signals. Then, the optimal schedule is obtained by efficiently solving the nonlinear 0-1 programming problem based on the algorithm of reducing the search space which is designed to eliminate a part of the nonoptimal solutions. To demonstrate the theoretical results, a simulation example is provided.

Dual-Level Framework for OpenBIM-Enabled Design Collaboration

Design coordination and collaboration are crucial in the architecture, engineering, and construction (AEC) industries, necessitating the integration of diverse disciplines and expertise to achieve unified and functional designs. Traditionally, these disciplines operate in isolation, leading to a fragmented design process. Building Information Modeling (BIM), recognized for its collaborative capabilities, presents an opportunity to revolutionize traditional design practices. However, existing research on BIM primarily assumes an ideal environment where all major participants use BIM models, overlooking the dynamics of mixed 2D Computer-aided Design (CAD) and 3D BIM environments. Addressing this research gap, this study aims to establish a dual-level OpenBIM-enabled collaborative design framework, enhancing the design process across various disciplines. The study employs a case study approach, applying this framework to an airport project in Chengdu, China. The airport includes different corridors that are similar in scope and scale but distinct enough to allow for a comparative study. The results demonstrate a 27% faster completion rate, a 98% reduction in design errors, and improved user satisfaction with the proposed method. The paper concludes by discussing the limitations of the study and suggesting avenues for future research.

Client-engaged collaborative pre-design framework for modular housing

Although modular construction benefits from standardized and repeatable modules, clients for housing projects seek tailor-made designs, making mass customization necessary. However, challenges persist in promptly identifying and satisfying these unique client needs during the early design phase, despite previous research efforts to address this limitation. This paper introduces the Client-engaged Modular Housing Platform (CEMHP), a collaborative design framework for the early phase of modular housing projects that supports the capture of client requirements, their analysis, the creation of visual content, and the reception of feedback from clients in an integrated manner. The results indicate that CEMHP enhances client decision-making, improves collaboration, and reduces unnecessary repetition. However, further data collection from clients and the enhancement of an algorithm for recommending suitable design samples based on this data remain necessary.

Collaborative optimization for variable stiffness composite laminates using a fiber angle description method based on Archimedean spiral function

When optimizing the fiber orientation of multilayer composite laminates, with the increasing number of layers, the number of design variables increases sharply, resulting in a large amount of computational cost. To address this challenge, this paper proposes a novel discrete fiber angle optimization method based on the Archimedean spiral function and applies it to a collaborative design framework of topology and fiber orientation. The proposed method uses the normal distribution function as the angle selection function in every layer. To prevent convergence issues in optimizing the fiber angle, a new candidate angle weighting formula is proposed. Further, a discrete fiber angle parameterization method based on the Archimedean spiral function for the thickness direction of laminates is presented, which requires only one variable to represent the fiber angle of any two layers in the element. To circumvent the issue of local optima and expand the design space, a collaborative optimization strategy is employed to improve the discrete fiber angle optimization results. Finally, the numerical examples indicate that in comparison to conventional approaches, the correlation of the proposed method with initial values is significantly reduced (σ2=0.00188). Under identical initial conditions, this method can improve the structural stiffness by over 20% at maximum.

Modelling transdisciplinary pedagogy: A method for collaborative curriculum design

This article explores a transdisciplinary, collaborative, curriculum design project to promote institutional belonging as a driver of student engagement, and to equip graduates with the fluency to work across disciplines. It demonstrates a facilitated method, to construct learning outcomes that break with typical subject-based knowledge and associated hierarchies of expertise. After considering a small number of precedents, the authors use curriculum models to inform a design specification. Following the formation of a multidisciplinary design team, a development tool (Lego® Serious Play®) was selected for a design workshop. A qualitative analysis of the workshop transcript was then used to inform the learning outcomes for a common module to be taken by all first-year undergraduates. Finally, the article considers how the process provided a framework for collaborative design that has been implemented in further projects, and led to the creation of a growing community of practice. The project provides insights for others embarking on collaborative curriculum design initiatives, especially where transdisciplinary learning is an objective.

Proposal of a Conceptual Framework for Collaborative Design of Immersive Professional Training: Application to the Textile Industry

AbstractImmersive technologies have an increasing use in professional training. However, the usability of applications has limits due to a lack of consideration of end users in the design of these new supports. This paper reviews the literature and discovers that few approaches offer to include different collaborators' work, or the end user, in the design process. This study proposes a conceptual framework design for immersive professional training (IPT) and its application in the textile industry.

Collaborative optimization design framework for hierarchical filter barrier control suspension system with projection adaptive tracking hydraulic actuator

Collaborative optimization design framework for hierarchical filter barrier control suspension system with projection adaptive tracking hydraulic actuator

A wiki-based framework for collaborative learning design in teacher education

A wiki-based framework for collaborative learning design in teacher education

Use of parametric approach for user-oriented development in building design: preliminary investigations

Building design is a highly interdisciplinary research field integrating technological, architectural, structural, social and other aspects. Participatory design, or co-design, already used in other disciplines, is now facilitated by the diffusion of Building Information Modelling which offers greater control of the interdisciplinary aspects in building design. But unlike other disciplines, architecture is characterized by a high number of requirements, partly formalizable, quantifiable and optimizable and partly only intuitive. Furthermore is difficulty to employ a collaborative design framework because designer and end user work on different knowledge levels: one works on satisfying classes of requirements, and the other is unable to abstract his needs and therefore properly formalize requirements or desires. The use of simple parametric models in the pre-design phase, based on algorithms capable of generating geometries dependent on multiple modifiable variables, could overcome this problem.This paper offers a preliminary investigation on the possibility of integrating bottom-up design aspects by giving parametric models to possible end users and allowing them to explore the design space, identifying preferential outputs and overcoming some of their technical gaps. Working in parametric environments in the pre-design phase opens to the integration of tools such as evolutionary multiobjective optimization algorithms (EMOA). New fitness functions can be defined to bring design closer to the end users’ proposed outputs without neglecting performance optimization, which is typical in parametric design. The framework proposed differs from existing “product configurator”, used in industrial design, which allows the personalization of aesthetic characteristics. This paper aims at a greater understanding of the end user’s will for satisfying them better in the subsequent design phases.The technological tools currently available to make this framework possible will be analysed, identifying shortcomings and problems, along with methodological implications.

The co.LAB Generic Framework for Collaborative Design of Serious Games: Development Study.

BackgroundSerious games are increasingly used at all levels of education. However, research shows that serious games do not always fulfill all the targeted pedagogical objectives. Designing efficient and engaging serious games is a difficult and multidisciplinary process that requires a collaborative approach. Many design frameworks have been described, most of which are dedicated to the development of specific types of serious games and take the collaborative dimension into account only to a limited extent.ObjectiveOur aim was to create a generic serious game design framework that could be adapted to all kinds of serious games and implemented in a collaborative web platform.MethodsWe combined the results of a literature review with our experience in serious game design and development to determine the basic building blocks of a collaborative design framework. We then organized these building blocks into categories and determined the features that a generic design framework should include. Finally, based on the paradigm of complex systems and systemic modelling, we created the co.LAB generic design framework and specifications to allow its implementation in a collaborative web platform.ResultsBased on a total of 10 existing design methodologies or frameworks, 23 building blocks were identified and represent the foundation of the co.LAB framework. These blocks were organized into 5 categories: “context and objectives,” “game design,” “mechanics,” “learning design,” and “assessment.” The arrangement by categories provides a structure that can be visualized in multiple and complementary ways. The classical view links game and learning design while other views offer project, systemic, and process visualizations. For the implementation of the co.LAB framework in a web platform, we propose to convert the building blocks into “cards.” Each card would constitute a collaborative working space for the design of the corresponding block. To make the framework adaptive, cards could be added, adapted, or removed according to the kind of serious game intended. Enhancing the visualization of relationships between cards should support a systemic implementation of the framework.ConclusionsBy offering a structured view of the fundamental design elements required to create serious games, the co.LAB framework can facilitate the design and development of such games by virtue of a collaborative, adaptive, and systemic approach. The different visualizations of the building blocks should allow for a shared understanding and a consistent approach throughout the design and development process. The implementation of the co.LAB framework in a collaborative web platform should now be performed and its actual usability and effectiveness tested.

Joint Coding/Decoding Optimization for DC-BICM System: Collaborative Design

Differential chaotic bit-interleaved coded modulation (DC-BICM) system can achieve coding gain from channel code without loss of bandwidth in the differential chaos shift keying (DCSK) system, but the current DC-BICM system using the belief propagation decoding algorithm has high decoding complexity, which brings burdens to resource-limited applications. In this letter, a novel collaborative design framework based on joint coding and decoding optimization is proposed for the DC-BICM system over multipath Rayleigh channels. Firstly, the column-weight-based (CWB) shuffled scheduling decoding is introduced into the DC-BICM system to lower the decoding complexity, called shuffled-based DC-BICM system. Then, a CWB extrinsic information transfer (CWB-EXIT) algorithm is developed for the theoretical analysis of this system. With the CWB-EXIT algorithm, a low-storage protograph low-density parity-check (P-LDPC) code is designed for this system, and the column-weight distribution is taken as an important constraint in the collaborative design process. In this way, the storage space used for storing the scheduling order in the CWB shuffled scheduling can be saved, whose size is proportional to code length. Theoretical analysis and simulations show that the shuffled-based DC-BICM system with the low-storage P-LDPC code can achieve lower decoding complexity, less storage requirement and better performance than the existing systems.

Protocol‐based collaborative design for discrete‐time switched systems with sojourn probabilities

SummaryThis article focuses on the collaborative design of a class of discrete‐time switched systems with sojourn probabilities. For the purpose of preventing the data collision, the Try‐Once‐Discard (TOD) protocol is employed to govern the information transmission between sensors and the controller. Moreover, it is worth noting that the values of sojourn probabilities, which are not given ahead, have an effect on the system stability. As a consequence, a novel collaborative design framework is established, in which the sojourn probability and static output‐feedback controller are to be designed simultaneously. By considering the effect from the TOD protocol and using the Lyapunov function related to the mode and protocol, a sufficient condition is derived to guarantee the exponential mean square stability of the closed‐loop system with a prescribed lower bound on the decay rate. Then, the desired sojourn probabilities and controller gains dependent on the corresponding mode and protocol are obtained in terms of convex optimization method with equality constraints. Subsequently, an estimation approach is provided to estimate the decay rate and decay coefficient of the closed‐loop system. Finally, one numerical example is given to testify the effectiveness of the proposed design approach.

Multidisciplinary aircraft integration within a collaborative and distributed design framework using the AGILE paradigm

The aircraft design is a collaborative and multidisciplinary process. It involves several experts with different disciplinary competences. These disciplinary experts often belong to different departments or organizations. The EU funded H2020 AGILE project aims at developing new generation of Multidisciplinary Design Analysis and Optimization (MDAO) frameworks. In particular, the AGILE project tackles the investigation and the development of technologies able to enhance the collaboration between the disciplinary experts. The present paper deals with a MDAO framework developed in the context of the AGILE research project. The integration of some disciplinary expertise is described by means of a case study of an innovative regional aircraft. Some disciplinary design variables are investigated to verify the correctness of disciplines integration and to quantify the mutual dependences among the design disciplines. In particular, the variation of the engine By Pass Ratio and the electrification level of the On-Board Systems are investigated through the MDAO workflow developed for aircraft preliminary design. Finally, the results show a plausible interaction among the disciplines and interesting trends regarding aircraft systems electrification.

Does collaborative learning design align with enactment? An innovative method of evaluating the alignment in the CSCL context

This study reports on a novel design methodology, namely, design-centered research (DCR), developed to analyze and evaluate the alignment between an online collaborative learning design and its enactment. The approach is illustrated in a study involving 40 groups in total. Twenty different online collaborative learning activities were designed and enacted by 20 groups of three students in each of two iterations. The collaborative learning design plans from the first round were adjusted after reflecting on misalignments observed through the method during the enactment, and then enacted and tested again by another 20 groups in the second round. The proposed method involves an interaction path graph as well as three proposed indicators of group functioning. These three indicators include: (a) the range of activated knowledge, (b) the degree of knowledge building, and (c) an interactivity of the approach. This approach to quantification of alignment between a collaborative learning design and its enactment was successful in revealing areas for improvement of the design. The results of the two round study indicate that the alignment significantly improved after the optimization of the collaborative learning design based on the analysis of the first round. The findings also suggest that optimizing a collaborative learning design using this method is associated with improvements in group performance. Building on these findings, the collaborative learning design framework is discussed in detail in this article, and resulting implications for practitioners are discussed in depth.

Gamification of Crowd-Driven Environment Design

This article explores whether crowd-sourced human creativity within a gamified collaborative design framework can address the complexity of predictive environment design. This framework is predicated on gamifying crowd objectives and presenting environment design problems as puzzles. A usability study reveals that the framework is considered usable for the task. Participants were asked to configure an environment puzzle to reduce an important crowd metric, the total egress time. The design task was constructed to be straightforward and uses a simplified environment as a probe for understanding the utility of gamification and the performance of collaboration. Single-player and multiplayer designs outperformed both optimization and expert-sourced designs of the same environment and multiplayer designs further outperformed the single-player designs. Single-player and multiplayer iterations followed linear and exponential decrease trends in total egress time, respectively. Our experiments provide strong evidence toward an interesting novel approach of crowdsourcing collaborative environment design.

An integrated fuzzy QFD and grey decision-making approach for supply chain collaborative quality design of large complex products

Complex structure and high technical barriers make it difficult for manufacturers to design new products independently, hence supply chain collaborative design prevails. Supply chain collaborative design has been discussed in the literature and multiple effective methods have been proposed. Nevertheless, the systematic framework for collaboration has been scarcely addressed, and multi-objective decision-making with uncertain information and poor data is still a research difficulty. This paper proposes a novel collaborative quality design framework for large complex products supply chain by integrating the fuzzy QFD (quality function deployment) and the grey decision-making approach. The proposed method exerts QFD design deployment function to decompose design tasks to all participants in the supply chain systematically, from overall design to detailed design. The joint design team composed of supply chain participants, can effectively ensure that all design phases are aligned with the general design objective. In addition to market competitiveness and quality, multi-objective assessments are developed in the fuzzy QFD to make the design method more practical. Moreover, a weighted multi-attribute grey target decision-making method assists decision-makers to identify the optimal quality scheme with uncertain information and poor data. The proposed framework is applied to a new launch vehicle design in China to illustrate its effectiveness. Implications and suggestions for future research are discussed.

Collaborative-Design Conflicts: Costs and Solutions

Collaborative design exposes software architects to the risk of making conflicting modeling changes that either can’t be merged or, when merged, violate consistency rules, nonfunctional requirements, or other system constraints. Such design conflicts are common and incur a high cost, including having to redo and abandon work. Proactive conflict detection can alleviate this risk. This article motivates the need for design conflict detection, describes the benefits of such detection to practitioners, and identifies requirements for building detection tools. In particular, FLAME is a collaborative-design framework that efficiently and continuously detects design conflicts. This article is part of a theme issue on collaborative modeling.