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Generative Production Systems are generative design computation that is linked to optimal physical production. They can improve the design and production of products which have unique geometries. The purpose of this paper is to introduce a preliminary methodology for Generative Production Systems.

The paper takes the form of a literature review investigating the structures and formats of successful methodologies. The literature review also investigates Generative Production Systems' theoretical foundations, development and implementations.

The potential of Generative Production Systems is restricted because enabling information is fragmented and difficult to access. In other fields, such barriers have been overcome through the introduction of methodologies that provide guiding principles, rules and strategies (P‐R‐S). The P‐R‐S type of methodology structure is suitable for Generative Production Systems.

The use of Generative Production Systems requires more upfront investment than the use of CAD/CAM software packages. However, they require little, or no, human input after they are set‐up. The preliminary methodology provides structured guidance about how to set up a Generative Production System. Further, the explanatory text enables wider understanding of Generative Production Systems, and how they can improve design and production.

An analysis is provided for the structure and format of successful methodologies in general. A preliminary methodology for Generative Production Systems is introduced. Further, the paper provides an overview of the disadvantages and advantages of Generative Production Systems compared to typical CAD/CAM software packages.

Mass customization has yet to fulfill its original purpose as established by marketing researchers to become an alternative to mass production, largely due to its inability to achieve mass market levels of efficiency. The purpose of this study is to survey consumer's perceptions, willingness and capabilities of participating in a mass customization system, and understand the implications of its findings related to an alternative production system, generative customization.

After an extensive literature review of mass customization, consumer behavior, complex adaptive systems and generative design, a survey was conducted across US and Swedish consumers relative to their willingness and perceptions regarding mass customization, with hypotheses based upon extant research standards.

The survey results found that consumers are ambivalent toward mass customization in mass markets, and a conceptual alternative (generative customization) appears to achieve, at least conceptually, the necessary objectives relative to product design conceptualization and fulfillment that mass customization cannot achieve.

A lack of significant findings from extant research regarding consumer perceptions and tolerances regarding mass customization in mass markets is a limitation to this study. The discussion of a new concept (generative customization) as a viable alternative to mass customization as a result of the survey findings needs to be validated empirically in future research.

The paper empirically validates a definition of mass customization as a complementary rather than an alternative to mass production. It also introduces and develops the concept of generative customization as viable alternative to mass production, albeit one that must be empirically validated in future research.

Urban typogenetics investigates the use of machine intelligence for the evaluation of performance measures as a decision support system (DSS) with a focus on urban aesthetics evaluation. This framework allows designers to address performance measures, urban measures and aesthetic criteria in an adaptive, interactive generative design approach. The purpose of this paper is to provide an understanding of the structure and the nature of the framework and the application of human-in-the-loop design systems to urban design.

Significant literature reviewed lead to the identification of an application potential in the decision-making process. This potential is situated around the use of AI for the evaluation of subjective performance criteria in a DSS. Recognising that the key decisions about urban aesthetics are based on the individual evaluation of the designer, an HITL approach for computational design software to support creative decisions is presented in this paper.

Urban typogenetics for interactive generative urban design allows the exploration of complex design spaces by using a human-in-the-loop design system in the context of urban aesthetics. Hybrid aesthetic evaluation allows the designer to analyse morphological features and urban aesthetics during exploratory search and reveal hidden aspects of the urban context by visualisation of the results of the aesthetic evaluation. Integrating performance measures and urban aesthetics in urban typogenetics addresses major criteria of urban design at the beginning of the creative process.

The use of a broad interactive approach to typogenetic design in an application to urban scenarios is a novel conceptual approach to the design of urban configurations. The suggested adaptive mechanism would allow the user of a typogenetic tool to subjectively evaluate solutions by sight and reason about aesthetic, social and cultural implication of the reviewed design solutions.

It is important to provide building performance feedback to the designer as early as possible in the design process. However, many aspects of building performance are significantly affected by the design of the building’s technical systems (e.g., heating, airconditioning), which are typically configured in detail only in the later stages of design. The challenge is thus to find a method to use detailed simulation tools even during the early stages of design when values for many of the variables for the building’s technical systems are not yet available. In this paper, we demonstrate how this problem can be partially solved by use of differential representation for building and technical system, homology‐based automatic mapping of relevant information from the building to the technical system representation, and generative design agents which, with a minimal user‐input, can design and model the technical system. We conclude the paper with illustrative examples of detailed performance analysis of complex buildings and their heating, ventilation, and air‐conditioning systems, performed in early stages of design.

The integration and automation of the whole design and implementation process have become a pivotal factor in construction projects. Problems of process integration, particularly at the conceptual design stage, often manifest through a number of significant areas, from design representation, cognition and translation to process fragmentation and loss of design integrity. Whilst building information modelling (BIM) applications can be used to support design automation, particularly through the modelling, amendment and management stages, they do not explicitly provide whole design integration. This is a significant challenge. However, advances in generative design now offer significant potential for enhancing the design experience to mitigate this challenge.

The approach outlined in this paper specifically addresses BIM deficiencies at the conceptual design stage, where the core drivers and indicators of BIM and generative design are identified and mapped into a generative BIM (G-BIM) framework and subsequently embedded into a G-BIM prototype. This actively engages generative design methods into a single dynamic BIM environment to support the early conceptual design process. The developed prototype followed the CIFE “horseshoe” methodology of aligning theoretical research with scientific methods to procure architecture, construction and engineering (AEC)-based solutions. This G-BIM prototype was also tested and validated through a focus group workshop engaging five AEC domain experts.

The G-BIM prototype presents a valuable set of rubrics to support the conceptual design stage using generative design. It benefits from the advanced features of BIM tools in relation to illustration and collaboration (coupled with BIM's parametric change management features).

This prototype has been evaluated through multiple projects and scenarios. However, additional test data is needed to further improve system veracity using conventional and non-standard real-life design settings (and contexts). This will be reported in later works.

Originality and value rest with addressing the shortcomings of previous research on automation during the design process. It also addresses novel computational issues relating to the implementation of generative design systems, where, for example, instead of engaging static and formal description of the domain concepts, G-BIM actively enhances the applicability of BIM during the early design stages to generate optimised (and more purposeful) design solutions.

Gives a broad understanding of multi‐agent systems and relates it to the generative paradigm of studying complex systems. Demonstrates the functioning of the multi‐agent paradigm in some approaches in artificial intelligence and in some closely related fields. After sketching a specific approach to formalization of multi‐agent systems using tools and techniques of the theory of formal grammars and languages, gives a preview of the main developmental lines of the theory of grammar systems.

The development of capacities for sustainability thinking by large-scale social systems requires of the skilled practitioner complex abstract logics. There is an intricate complexity of relationships to consider in the observation of the landscape of thought. This paper aims to introduce a matrix as an orientating heuristic to guide this form of praxis and provides reflections on its use in the enactment of social learning.

The signifiers for four different orientations to learning and four abstractions in levels of learning are described. The configurations that result from their conjunction generate a matrix of 16 alternatives. These are combined into a heuristic to guide and inform reflexive praxis.

The conjunction of these two dimensions enables observations of the cybernetic interactions between levels of learning and orientations to learning. This depiction prompts considerations of the ethics and aesthetics of large-scale collaborative learning. In reflecting on the use of the heuristic device in practice, four primary observations are offered as possible considerations to inform ethical practice.

The value of this research is in enabling awareness of the relationship between levels of learning and orientations to learning. The originality is the application of apithology principles to the multi-dimensional learning landscapes found in complex thought-ecologies.

This paper aims to propose a generative design method combined with meta-heuristic algorithm for automating and optimizing the floor layout of modular buildings using typical standardized module units, which are the room module, the corridor module and the stair module.

The integrated framework involves the generative design method and optimization for modular construction. The generative rules are provided by geometric relationships and functionalities of the module units. An evaluation function of the generated floor plans is also presented by the combination of project cost and cost penalties for the geometric features. The multi-population genetic algorithm (MPGA) method is provided for the optimization of the combination of costs.

The proposed MPGA method is demonstrated fast and efficient at discovering the globally optimal solution. The results indicate that when the unit price of modules is high, the transportation distance is long, or the land cost is high, the layout cost, which related to the symmetry, the compactness and the energy is tend to be lower, making the optimal layout economical.

This paper presented an integrated framework of generative floor layout and optimization for modular construction by using typical module units. It fulfills the need for automated layout generation with repetitive units and corresponding assessment during the early design stage.

During recent decades, the emergence of artificial intelligence (AI) from computer science, psychology and linguistics has created a great impact on the design and implementation of process planning systems. This article provides a review of the state‐of‐the‐art AI‐based automated process planning systems. A generalised framework for expert process planning systems is proposed and prospective research issues are discussed.

This study assessed the key construction technology trends and tracked the impact of these developments on labor influencing factors in an effort to alleviate the limitations posed by skilled labor scarcity in offsite construction (OSC).

The study followed systematic literature review to acquisition initial data sets. The data retrieved form identified databases was then subjected to scientometric analysis. In next stage, disruptive factors were identified to produce a conceptual framework followed by its practical application for an OSC firm.

This study identified seven construction technologies with a potential to disrupt OSC in future. The study also developed a conceptual framework as a benchmark to help establish further frameworks for policy interns in OSC.

The review conducted only takes into account the literature from 2009 to March 2021. Any prior to the date and unpublished studies were not included in study.

A proper utilization of conceptual framework can contribute to technological adoption significantly lowering the need of labor in OSC industry. Moreover, the established discussion on understanding the purpose of deploying latest technology may reduce additional costs, management, time and allocation of labor resources.

This study provides a mechanism to intern OSC policymakers to impartially incorporate the latest technology in OSC.

This study fulfilled an identified need to study latest technological trends in OSC by utilizing bibliometric tools with SLR. The disruptive categories and factors highlighted by the study were not identified in a systematic manner in previous studies, which could further enhance the implementation of latest construction technology in OSC.