Das Kapitel befasst sich mit der Komplexität moderner Designprobleme, die häufig kollektive Kreativität und Expertise erfordern, die auf verschiedene Teilnehmer verteilt sind. Es führt ein kollaboratives Rahmenwerk ein, das generatives Design und BPMN nutzt, um Designprozesse zu optimieren und Teilnehmern unterschiedlicher Herkunft einen effektiven Beitrag zu ermöglichen. Das Rahmenwerk digitalisiert Designabsichten und nutzt eine BPMN-Plattform, um Kommunikation und Entscheidungsfindung zu erleichtern, was zu automatisierten und effizienten Designworkflows führt. Die Erforschung von Metadesign-Prinzipien unterstreicht die Bedeutung von Flexibilität, Zusammenarbeit und Evolutionsfähigkeit bei der Schaffung von Bedingungen für erfolgreiche Designergebnisse. Das Kapitel behandelt auch den Stand der Technik bei digitalen Designwerkzeugen und betont die Rolle von Algorithmen und parametrischen Modellen bei der Verbesserung der Designflexibilität und der Verringerung der Ressourcenverschwendung. Eine detaillierte Methodik wird vorgestellt, einschließlich des Einsatzes der Camunda-Plattform für die Integration von BPMN-Workflows und die Automatisierung von Prozessen. Das Kapitel schließt mit einer Diskussion zukünftiger Entwicklungen, in der die Integration webbasierter generativer Frameworks und IoT-Paradigmen zur weiteren Verbesserung des Designprozesses vorgeschlagen wird.
KI-Generiert
Diese Zusammenfassung des Fachinhalts wurde mit Hilfe von KI generiert.
Abstract
Modern Society is facing design problems with increasing complexities and their resolution requires specific knowledge, thus cross-disciplinary collaboration has become more frequent. Collaboration entails communication, interaction and idea-sharing between the participants and it tends to be more time-consuming and does not guarantee successful results. The origin can be found in conflictual situations during the collaboration, which include different progress statuses, antagonist objectives, overlapping activities, and difficulties in reaching an agreement between the parties. Consequences of a poor design process management include contradictory file versions, bringing efforts in clash detection and synchronisation, project delay and lower design quality.
The present paper proposes the design process optimisation that deals with interdisciplinary collaborations. In particular, it investigates an infrastructure that supports the actors’ communication, their impacts on the design product and their involvement during the decision-making process. It relies on the digitalisation of design intents, expressing them as a set of relationships and parameters while a Business Process Management Notation (BPMN) platform provides the communication infrastructure. A prototype has been experimented, showing the feasibility of cross-disciplinary participation. It has proved the possibility of involving actors from different professional backgrounds, breaking down boundaries in the Design disciplines. In addition, the design process digitalisation allows its automation, bringing benefits in terms of time, conflicts, human resource reduction and therefore the overall design quality. The exploration that concerns how to create conditions for good results to emerge, rather than on a fixed design product, is known as metadesign.
1 Introduction
The development of civilisation has brought the proliferation of needs and the specialisation of scientific domains. As a result, modern designers are gradually losing absolute control of their projects, getting trained in specific but limited expertise [1]. Under this perspective, the increasing complexity of the modern design problems requires collective creativity where expertise relevant to a complex problem is distributed among participants, each of whom has different expertise and skills [2].
The collaboration entails participation and inclusion, which are specific to the context and the design stage [3]. Different groups of participants are involved during the needs definition, design development, as well as design outcomes evaluation. Each participant should be correctly placed and coordinated during the design process and to impact the final result [4].
Fig. 1.
The representation of a process/context/actor specific Design Process [3].
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The cooperation between actors and being able to deal with problems with increasing complexity has been considered a crucial feature of metadesign [5]. Under this perspective, Fischer and Giaccardi [6] have defined metadesign as “a conceptual framework defining and creating social and technical infrastructures in which new forms of collaborative design can take place”.
Compared to the traditional design approach, metadesign does not provide fixed solutions but focuses instead on creating conditions for appropriate designs to emerge and thrive [7]. It focuses on the process and the context that could bring satisfying outcomes. Metadesign embraces contingencies since it is not possible to foresee all kinds of needs or have all the proficiency to do that [8], and it differs from a traditional design from flexibility, collaboration and evolvability perspectives [9].
The present paper proposes the design process optimisation that deals with interdisciplinary collaborations. In particular, it investigates an infrastructure that supports the actors’ communication, impacts on the design product and their involvement during the decision-making process. It relies on the digitalisation of design intents, expressing them as a set of relationships and parameters while a Business Process Management Notation (BPMN) platform provides the communication infrastructure. A prototype has been experimented, showing the feasibility of cross-disciplinary participation. It has proved the possibility of involving actors from different professional backgrounds, breaking down the boundaries of Design disciplines. In addition, the Design Process digitalisation allows its automation, bringing benefits in terms of time, conflicts, human resource reduction and therefore overall design quality. The exploration that concerns how to create conditions for good results to emerge, rather than on a fixed design product, is known as Metadesign.
2 State of the Art
The introduction of digital tools in Design started with the spread of personal computers and the use of algorithms is considered as a valid support to automate the design process [10, 11]. According to the modern connotation in Computer Science, the term algorithm is "a set of precise instructions to calculate a function" [12] and "the process based on algorithmic thinking that enables the expression of parameters and rules that, together, define, encode and clarify the relationship between design intent and design response" is the definition that W. Jabi has attributed to "Parametrical Design" [13]. As a result, a parametrical model facilitates the custom adaptations of design solutions to demanding changes, providing effective solutions to enhance flexibility in the design process, reducing resource wastes (time, human, materials), together with improvements in managing and controlling the project.
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By providing adequate inputs, a parametric model is able to generate the corresponding outcome. In addition, it is also possible to explore the proper combination of parameters to achieve optimal performances with the support of an evaluation system [14]. In this vein, the use of algorithms supports the development of a performance-based generative design framework, achieving a flexible and automated desing process.
On the other hand, BPMN is defined by ISO standards (ISO/IEC 19510) to represent the Business Processes graphically. It describes complex processes and enhances its readability and inter-operation between all business stakeholders, actors, or participants [15]. BPMN elements are semantically defined, which means that the created models are executable with the support of process engines [16]. It can be mapped in an Extensible Markup Language, or XML, for instance Business Process Execution Language. The latter is a language that connects Web Services, APIs and human processes in a Service-Oriented Architecture and shares data in a business workflow. Consequently, Business Processes can be machine-readable and allows human-machine interactions.
In the literature, there are many implementations of BPMN as a valid support tool to manage and control the procedures among different stages of the AEC/FM industry. Aram et al., have explored the implementation of BPMN in a BIM database data exchanges [17]. Gardini et al. have pointed out the benefits of BPMN during the construction and supervision phase, allowing automation of the inspection management and offering traceability of the procedures for the quality certification of the product [18]. Corneli et al. have implemented BPMN Choreographies combined with Blockchain technology for the digitalisation of construction site management [19].
3 Methodology
An investigation of the available BPMN platforms has been performed. The present work uses Camunda, a free, source-available and Java-based platform to provide BPMN standard-compliant workflow integrated with a process automation engine. It can be embedded with Java-developed applications and other languages via REST protocol. These characteristics enable the creation of customised APIs for specific needs and allow the implementation of IoT technology. In addition, Camunda is integrated with tools for process automation (Zeebe), monitoring and troubleshooting processes running in Zeebe (Operate), examination and improvement of the processes (Optimise), and to orchestrate human workflows (Tasklist) [20].
There are two milestones in the proposed design framework where the interaction between the parties is explicitly required. The first is represented by the input data placement to feed the generation process (knowledge sharing), and the second is when the involved participants are invited to express their assessment regarding the outcomes (decision-making). A representation of the framework is provided in Fig. 2.
Fig. 2.
Representation of a collaborative framework based on GD strategy in BPMN.
For demonstrative purposes [21], four accounts (lanes in Fig. 1) have been created corresponding to a hypothetical collaboration between the Project Process Management Team (that can be the Design Team), Stakeholders, Engineering Team, and Manufacturing Team. The corresponding access privileges and specific activities have been assigned to users. The input data was collected through a web-based platform that each participant can access with their credentials.
After the Design Team has defined the design intentions, a Parallel Gateway generates the input data submission request to the corresponding team. The data collection is performed by Form modules, a function that creates customised interfaces with required team-specific fields where the participants can submit their values. These could be strings or numbers, selecting data in a radio button, checkbox or drop-down menu.
A digital BPMN platform allows business process automation since they are semantically defined. The integrated tool Operate has been used to manage the workflow and to monitor the process stage, accomplished tasks and the collected variables. The latter are collected in a CSV file and then used to activate the generative design process.
The outcomes generation relies on instructions that express the design intents (which can be run by a metaheuristic algorithm) and integrated with an Evaluation System (ES), composed of a set of design objectives. In a performance-based generative design process, the ES leads the exploration of the near-optimal solutions [14] and the outcomes performance score can be considered in the framework's decision-making process, where the participants are invited to express their opinion regarding the level of satisfaction (Table 1). The assessment can be: Very Satisfying, Quite Satisfying, Indifferent, Not Satisfying, corresponding to values four to zero (Table 2). The Assessment request can be formulated using the Form module again and includes the most performative outcomes identification number and performances score according to the ES.
The assessment from each team can be associated with a Fitness Function where the assessment of each team can be attributed to their different weights. The Final Decision task is a Business Rule Task based on the DMN – Decision Model and Notation. This standard was introduced by Object Management Group in 2015, completing the BPMN to express decision logic. In the present work, the decision rule is to skim out the configuration with the highest Fitness Function score.
In the hypothetical process shown in Fig. 1, the decision-making process is composed of the same teams in the data collection process. In real situations, there can be created as many Pools as the number of participants.
Table 1.
“Decision Making Request” form configuration.
General
Validation
Field Label
Key
Required
Outcome Identification
Id_Number
X
Performance 1
Score_Perf1
X
Performance 2
Score_Perf2
X
Performance 3
Score_Perf3
X
Table 2.
“Evaluate” task form configuration for each Performance assessment.
General
Values
Field Label
Key
Label
Value
Select
Select_Evaluation
Not Satisfying
0
Indifferent
1
Quite Satisfying
2
Very Satisfying
3
4 Results, Future Developments and Conclusion
The present paper has explored the metadesign of an interdisciplinary collaborative framework based on generative design strategy, exploring the BPMN standard for the design process automation. A digital tool used in business management has been implemented to create an infrastructure where participants are involved in data collection, outcomes generation, and decision-making processes. Actors who may have no design experience can systematically contribute to the design process, blurring the boundaries between the disciplines. The digitalisation of the design intents and the communication infrastructure allows the automation of the design process, bringing benefits in terms of reduction of resource waste (time and human efforts in case of changes and bottleneck situations) and increasing design quality.
Nevertheless, the present framework needs improvements under several aspects.
First, it is possible to achieve complete processes’ automation by integrating a web-based generative framework [22], instead of a set of instructions defined in a local programming compiler proposed in [21, 23]. In this vein, the design product could be reactive to the parameter changes (corresponding to its evolution during the design process) and each participant can see the impact of their own decision on the design product, becoming in turn the designer [10]. As a result, the design process can be implemented with the IoT (Internet of Things) paradigm since it will be able to detect – through human operators or sensors – and react to the context changes [24].
Secondly, according to the metadesign features of flexibility, collaboration and evolvability – where the framework is associated as an open system allowing significant modifications when the needs arise [5] – the proposed framework can be considered as a semi-open system, which means that the participants can not update its structure but only the value of some parameters. The rationale behind this is to maintain the designer's intents, emerged by the definition of the relationship between elements, and at the same time, allowing cross-disciplinary collaboration. An application scenario could be a framework that enables the design product's customisation, where a proper solution will be achieved by changing specific parameters. In this case, a metadesign project can be expressed as a set of instructions encoded with Blockchain technology and become a product per se [25].
The present research contributes to the development of metadesign studies, in particular it has explored a digital framework featured with the flexibility of the design product according to the context that allows cross-disciplinary collaboration. It is therefore noteworthy for further investigation, in particular if considering its potentiality with the integration of the IoT paradigm and Blockchain technology.
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