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* Corresponding Author: Professor Farzad Pour Rahimian, Teesside University, UK, email:
f.rahimian@tees.ac.uk
Integrated BIM and DfMA Parametric and Algorithmic Design Based Collaboration
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Framework for Supporting Client Engagement within Offsite Construction
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Sajjad Bakhshi a (s.bakhshi@tabriziau.ac.ir), Mohammad Reza Chenaghlou b
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(mrchenaghlou@sut.ac.ir), Farzad Pour Rahimian*c (f.rahimian@tees.ac.uk), David
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Edwards d,e (drdavidedwards@aol.com), Nashwan Dawood c (n.n.dawood@tees.ac.uk)
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a: Department of Architecture, Islamic Art University of Tabriz, Tabriz, Iran
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b: Department of Civil Engineering, Sahand University of Technology, Tabriz, Iran
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c: School of Computing, Engineering & Digital Technologies, Teesside University,
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Middlesbrough, UK
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d: School of Engineering and the Built environment, Birmingham City University,
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Birmingham, UK
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e: Faculty of Engineering and the Built environment, University of Johannesburg,
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Johannesburg, South Africa
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Integrated BIM and DfMA Parametric and Algorithmic Design Based Collaboration
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Framework for Supporting Client Engagement within Offsite Construction
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Abstract
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As a proactive reaction to current ineffective collaboration strategies, this study sought to combine
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the capabilities of Building Information Modelling (BIM) in the Design for Manufacturing and
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Assembly (DfMA) method with mass customisation into a framework that enables customers to
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participate in the offsite construction configuration process. This approach engenders greater
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customer satisfaction whilst increasing production and construction efficiency. A model capable
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of facilitating the use of construction information in the proposed framework was developed to
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implement the proposed framework into practice. Combining the BIM model within the
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framework provides all project stakeholders with prerequisite information needed for a building’s
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configuration. This collaborative process utilises an algorithmic composition in which the current
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assembly information in both the BIM model and framework is used as a controlling factor in the
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configuration process. The parametric environment of Revit and the algorithmic environment of
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the Dynamo plugin were used to realise the proposed framework (as a proof of concept).
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Keywords: Offsite Construction; DfMA; BIM; Dynamo; Parametric Design; Algorithmic Design;
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Integration; Collaboration;
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1. Introduction
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In the past few decades, prefabrication has been heralded as the most effective and efficient
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construction approach by architecture, engineering, construction and operations (AECO)
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professionals [1]. Palpable advantages of this construction approach over the conventional onsite
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construction methods include efficient use of resources, environmental sustainability and higher
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construction quality control [2-6]. However, due to its complex, distinctive supply chain processes,
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this construction approach has constantly presented diverse collaboration challenges between
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different project stakeholders (e.g. designer, contractor and client) [7,8]. A notable area that has
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received scant academic attention is client collaboration with the offsite construction (OSC) design
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section. However, project organisations have traditionally kept the client away from the design
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and construction process, often ignoring their preferences and satisfaction, much to the detriment
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of future contract success [9]. In addition, compared to conventional onsite construction (OnSC)
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methods, the design phase in the OSC method is of greater significance because it is less
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customisable and requires more accurate tolerances. Therefore, high-level collaboration and
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interaction among all project parties are vital to project success [10]. Hence, an effective and
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efficient design process requires development that meets customer requirements and preserves a
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high quality of the design process output in OSC projects.
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This study was motivated by an efficient and effective collaborative design. The construction
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process facilitates information transfer, knowledge development, technical coordination and
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allocations of resources so that all project parties can function optimally while reducing
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unnecessary conflicts [11]. Hence, this design approach provides a basis to ensure effective
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interaction between the client and the design team. Moreover, the customisation strategy is
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commonly used for augmenting cooperation between two parties which not only enjoys the
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positive aspects of mass production but also fulfils client’s preferences. However, given the
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inherent complexities associated with prefabricated buildings (PBs), such a strategy lacks the
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necessary flexibility for clients to choose the components separately without considering the
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technical requirements of customised construction. This inflexible approach confuses the client
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[12] and reduces customised buildings' design, production, and assembly efficiency. In the design
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process of PBs, the design for manufacture and assembly (DfMA) method can provide a reasonable
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basis for considering the manufacturing and assembly principles during the early stages of design
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to maximise efficiency [12-14].
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Similarly, as an environment used to produce and exchange rich construction data, building
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information modelling (BIM) with its parametric structure can increase the efficiency of the
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building design process. Therefore, integrating DfMA and BIM allows designers to consider the
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design, production and assembly requirements more efficiently in the OSC design stage [15].
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However, there are no definite mechanisms to ensure client collaboration in selecting and
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designing the building elements and components, even in these advanced design approaches.
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Therefore, there is still a gap in theory and practice due to the lack of a mass customisation strategy
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to help integrate current BIM and DfMA approaches to support the better engagement of the clients
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in the decision making processes of offsite manufactured buildings.
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As such, this research aims to integrate a BIM-based DfMA approach and customisation to provide
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a strategy consisting of complementary stages for optimal customer participation in the design
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process of high-performance PBs. Specifically, the work seeks to develop a new design framework
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for meeting client preferences based on the production and construction requirements of PBs. A
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new information model for the prefabrication information model (PIM) was developed as the
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product of this research. PIM gathers all information related to the production, construction and
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customisation of all prefabricated elements to enable tailored configuration of PBs to meet client’s
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needs. The design data for a building’s elements were then developed into a BIM model. Finally,
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in the parametric environment of BIM, a new design algorithm was developed which uses both
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models to facilitate collaboration between the client and design team in building a configuration
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process. Because this algorithm considers all the functional and physical relationships defined in
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the form of PIM, along with all the assembly information produced in the BIM environment, it
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automatically limits the choices (options) of the client. Hence, this algorithm allows the client
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preferences to be met while reducing production and assembly challenges and rework in the design
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and construction stage.
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2. Related studies
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Two main areas were focused upon to introduce the proposed theoretical and methodological
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framework:
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1) Prefabrication and production, in which due emphasis is given to the inherent characteristics
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of the offsite construction method. Consequently, the three concepts of ‘supply chain
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management’, ‘product architecture and modularity’ and ‘client preferences and customisation’
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are investigated (separately). This allows prefabrication to be performed from the product-oriented
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perspective.
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2) OSC design principles, in which due emphasis is given to the efficient OSC design
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implementation through investigating the state-of-art solutions in this field. Thus, DfMA as an
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OSC design approach, BIM as an OSC design tool, and utilisation of BIM in the DfMA approach
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in the OSC design process are investigated.
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2.1. Prefabrication and production
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Generally defined, the term ‘prefabrication’ refers to planning, designing, producing and
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assembling building elements offsite to ensure a fast, efficient construction of a permanent
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structure [16]. The tangible benefits of the factory-controlled (vis-à-vis OnSC) production of
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building elements (constituting the different components of a complex product) include lower
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materials and power wastage, enhanced construction quality, higher efficiency and a
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comparatively shorter construction process [17,18]. Moreover, since the design and production
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processes utilised for PBs are product-oriented, other mass production processes (e.g. supply chain
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management [19]; product architecture and modularity [20]; and client preferences and
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customisation [21]) can be seamlessly implemented.
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2.1.1 Supply chain management
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All economic, environmental and social considerations are integrated into a coordinated supply
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chain through key inter-organisational systems [22-24]. This enables the effective and efficient
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management of materials, information and financial processes related to the production and
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distribution of products [25-27]. In so doing, the requirements of all beneficiaries are met, thus
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augmenting an organisation’s tangible competitiveness and flexibility [28]. The efficient supply
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chain management of the contemporary prefabricated construction industry as a complex product
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includes diverse activities. These facilities can provide services, products and materials for supply
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chain members (viz. suppliers, clients, manufacturers, architects/engineers, general contractors,
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consultants, subcontractors and developers) [29]. As a result, supply chain management engenders
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considerable efficiency and cost-effectiveness gains while reducing waste and shortening
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production processes [30]. However, inherent complications associated with supply chain
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management in the construction industry creates the omnipresent risk of interruption amongst
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project stakeholders - thus representing negative drawback related to this approach to construction
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[31].
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2.1.2 Product architecture and modularity
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Product architecture allows project management team members to specify the parts and
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components' specific functions, the product's physical configuration, and the way the parts or
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components are functionally interrelated after the ultimate product functionality is determined
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[32]. In modular design, most methods have predetermined modules to eliminate production
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complications of a given product - particularly in terms of the physical and functional
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interrelationships between components, while simultaneously increasing the efficiency of
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customisation, production, assembly, maintenance and disassembly processes of the product [33-
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35]. Hence, when a modular design is implemented, equal consideration must be given to the
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methods of planning, designing, production, construction, maintenance, disassembly and reuse
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[36].
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2.1.3 Client preferences and customisation
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Customisation within mass production reflects an aura of procurement modernity where
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contractors equip clients with the flexibility to adjust proposals to their individual preferences [37].
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Subsequently, clients can utilise this unique strategic chance to gain a competitive advantage and
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considerable economic value [38,39]. In short, this strategy encapsulates the benefit of mass
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production features whilst giving a greater choice to the customer. Furthermore, the customer-
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oriented decoupling point (CODP) model developed by Lampel and Mintzberg [40] defined client
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participation in the product supply chain using five different levels ranging from pure
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standardisation to pure customisation. This model allows companies to engage client participation
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based on contractors' limitations and capabilities in the product supply chain.
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Zhang et al. [41] developed a model to investigate the potential effects of the mass customisation
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approach, and product modularity on the integration quality of the product supply chain and the
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ensuing competitive quality secured. Data gathered by 317 international manufacturers on
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different standards (variables) were used to empirically test this model (viz: 1) mass customisation;
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2) product modularity; 3) supply chain quality; 4) internal quality integration; and 5) customer
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quality integration. In their study aimed at increasing production system efficiency, supply chain
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and customisation, Schoenwitz et al. [42] introduced a technique to compare client customisation
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preferences for different categories of PB elements available in its product architecture. Where
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client preferences are incompatible with the company’s priorities, a strategic framework
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implements necessary measures to align these individual preferences.
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2.2 OSC design principles
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The design phase is of paramount significance towards ensuring construction quality, economic
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efficiency and low environmental impact. Seemingly, in OSC, due attention should be paid to the
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design stage owing to important complexities commonly faced in the different stages of
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production, assembly and supply chain of such buildings [3,10,43]. In response to these
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complexities, the implementation of state-of-art developments in OSC design (DfMA as a
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sophisticated design approach [14] and BIM as a sophisticated design tool [44]) can ensure a high
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rate of quality in all stages in building construction.
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2.2.1 DfMA as a design approach
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To ensure the effective design for PBs, DfMA considers diverse factors in the design stage as a
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relatively up-to-date PB design method [45]. DfMA primarily seeks to integrate production and
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assembly principles in the product design stage so that the occurrence of potential future problems
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are minimised [12-14]. Because PBs are costly due to their inherent complexities, DfMA can be
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implemented as a highly efficient and reliable approach for the production of PBs. Moreover,
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considering the features mentioned above, it is necessary to implement a suitable strategy that
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responds to the common information requirements determined in the design stage and develops
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the exact product information for each prefabricated element obtained through DfMA
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implementation [15].
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2.2.2 BIM as a design tool
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BIM has received ubiquitous academic attention due to its potential technical and quality
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enhancement capabilities throughout a building’s whole life cycle [46,47]. In relation to OSC,
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many designers and researchers have implemented a BIM parametric structure and its data
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exchange capability to enhance design information production quality and design information
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transfer, thus improving the quality of all the design processes of PBs and their components [48-
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53]. Combining the parametric characteristic of BIM with the capabilities of Application
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Programming Interface (API), unnecessary design repetitions are avoided [54]. This can reduce
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the inherent inflexibility in the OSC design stage while meeting the need for high coordination
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necessary for the OSC design stage [55]. Moreover, the parametric modelling capability observed
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in BIM can be used as a basis to trigger an innovative workflow in planning modular and
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prefabricated construction. If the technical monitoring frameworks necessary for such workflows
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are implemented, waste in such construction projects can be minimised considerably [56]. For
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example, Ramaji and Memari [36] presented a specific product architecture information model for
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modular multi-story buildings. To increase design and production efficiency, they employed Level
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of Details (LoDs) available in BIM to address construction issues encountered in the design phase
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and align LoDs and different levels of their product architecture model.
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Other research studies focused on the maximum increase of design process efficiency through
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implementing BIM parametric design tools in developing designs based on a DfMA method;
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where all the requirements in ‘design’, ‘production’, and ‘assembly’ of PBs are achieved to prevent
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repetitive work in these three stages. For example, Yuan et al. [15] proposed an innovative
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framework for DfMA implementation using BIM parametric modelling for domestic housing.
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Once modelling was completed, the production information model of the house was optimised. If
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all the production and assembly requirements were met, the model was sent to the production unit.
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Such a framework can use the BIM family templates and API to create the needed elements and
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assembly functions not existing in BIM as BIM-redevelopment. The newly created elements are
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subsequently added to BIM standard parametric prefabricated component library. Following a lean
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construction and DfMA methodology, Gbadamosi et al. [57] proposed an effective method for
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optimising the assembly process of prefabricated elements. In their study, Revit software along
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with a Dynamo algorithmic environment was implemented to benefit from the parametric
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modelling capability of BIM and to transfer design information using Industry Foundation Classes
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(IFC) format.
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Similarly, Li et al. [58] emphasised the need for an integrated conceptual framework to understand
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present studies and signpost future research based on BIM capabilities. Moreover, it can simplify
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the process of decision making by OSC stakeholders. In their proposed framework, the parametric
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capabilities of BIM and data exchange through information format constitute a key role. This
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framework was used as a basis to develop a design for X(DFX) strategy.
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2.2.3. BIM as a collaboration tool
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The built environment has been perennially caught up in a low productivity problem for a long
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time [59]. Poor collaborative processes and lack of productive information exchanges have been
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identified as primary reasons for this [60,61]. In addition, the discontinuity between design and
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construction has been cited as a significant contributor to this problem [51,62-68]. However, it has
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taken major developments in digital technologies like the Internet, project extranets, BIM, and the
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Internet of Things (IoT) to generate the kind of optimism that the industry has never experienced
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before. The built environment is not alone in sharing the excitement around these technologies.
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These technologies have captured the imagination of just about every industrial sector. But, of
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course, no technology can result in addressing the challenges of any industry on its own. A set of
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complementary processes [61,64] needs to be developed in tandem for the technologies to enable
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change effectively. Quite encouragingly, such processes have been developed recently,
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particularly in information management and collaborative working in the built environment sector.
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These are positive developments and whose integrity and effectiveness will be tested over the next
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few years.
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Meanwhile, the wider world (including the built environment) is experiencing a paradigm shift
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due to the industry 4.0 revolution. Recent technological and other process-based advances and
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innovative technologies in the built environment mentioned above have a key role in this process.
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As widely reported in the popular and scientific media, the nine pillars supporting Industry 4.0 are
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1) The Internet of Things, 2) Big Data, 3) Augmented Reality (AR), 4) Advanced Visualisation,
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Virtual Reality (VR) and Simulation, 5) Additive Manufacturing, 6) System Integration, 7) Cloud
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Computing, 8) Autonomous Systems, and 9) Cybersecurity.
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In the built environment sector, these nine pillars can be underpinned by BIM, widely regarded as
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the tool of choice to address key issues as industry fragmentation, value-driven solutions, decision
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making, client engagement, and design/process flow to name but a few. Therefore, it could be
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argued that Construction 4.0 has ten pillars, including the nine Industry 4.0 pillars and BIM [69].
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Exemplars from other industries such as automotive, aerospace and oil and gas currently
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demonstrate the power and application of these technologies. However, the built environment has
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only just started to recognise terms such as “golden key” and “golden thread” as part of BIM
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processes and workflows. Construction 4.0 offers a portfolio of potential solutions to bridge the
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knowledge and information gaps between design, construction and operations [70,71].
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This has led to the emergence of a series of cutting edge technologies in the AEC realm, including
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but not limited to virtual reality-based collaboration technologies [63], artificial intelligence-based
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optimisation [72], data-driven decision support [73], smart data modelling [72], blockchain and
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distributed ledger technologies [74], and computer vision and graphics [75,76]. For example, these
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advancements can now assist decision-making in predicting the cost and performance of optimal
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design proposals [77].
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Advancements in cryptography and read-only data management optimisation are paving the way
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for fully-fledged distributed ledger technologies for digital twinning and asset lifecycle
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management. Previous research has demonstrated real-time centralised solutions for openBIM.
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Collectively, these developments are forcing a paradigm shift in design from asynchronous to real-
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time data exchanges. This ultimately can improve inter-organisational perceptions of social
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presence [78] and imbuing confidence in the design shift expected of openBIM standards and the
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neutral information format of IFC [79,80]. Consequently, several research studies have sought to
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increase the quality of collaboration in the design stage. For example, Rahimian et al. [63]
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enhanced the quality of client collaboration in the design section in OSC, implementing open-BIM
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standards, IFC format, along with BIM parametric characteristics (attributes) to transfer neutral
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design information to a BIM server and to connect (relate) the information to the Unity
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environment. This enabled the graphical information of buildings and their elements to be
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visualised and displayed in immersive environments such as VR and AR for the client, thus
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providing effective interaction with low latency with the design team. Apart from these technical
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characteristics for fostering collaboration between the client and design team, the PAS 1192-2
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standard [81] offers guidelines under the title of a common data environment (CDE), which
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describe how the different parts of the design team interact with one another and with the client.
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These guidelines are provided to engender systematic interactions during the various stages of
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designing buildings.
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In summary, in addition to the parametric capabilities to increase supply chain process efficiency
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in general and the design process of PBs, BIM can facilitate collaboration between project
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stakeholders [4,59,75,82-84]. Furthermore, BIM can support participatory working during design
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and decision-making processes thanks to the inherently systematic and ontological information
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representation structures.
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2.3. Summary of the literature
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Collecting, processing and integrating multi-aspect information from construction projects is vital
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for meeting sustainability metrics and cost and time related Key Performance Indicators (KPI)
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[63]. This needs to fully cover design decision drops, technical specifications, client preferences,
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building materials and assembly. Yet, as stated in Section 2.2.1, due to the complex supply chain
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issues, there is always the risk of the disrupted flow of information among the various stakeholders
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involved in PB projects.
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A review of extant literature suggests that the design stage in OSC is of paramount significance
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partly because of the unique characteristics of PBs. If undertaken properly and efficiently, it can
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prevent cost escalation and project overruns in the design stage and, consequently, all supply chain
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stages. Moreover, it was emphasised that a hybrid combination of DfMA and the capabilities of
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BIM tools in the design stage could both facilitate the design process and increase the efficiency
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of the manufacturing and assembly stages in OSC. However, although many studies are completed
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on increasing design efficiency and mass customisation in OSC, there seems to be a shortage of
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studies aimed at studying customer satisfaction during the design stage in OSC projects. Moreover,
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scant research has investigated how the client can collaborate effectively in the design stage of
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PBs and their elements. In more specific terms, despite a myriad of capabilities offered in BIM
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applications for leveraging collaboration among different stakeholders of construction projects,
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there is still a practical and theoretical gap in the body of literature for supporting clients'
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engagement within the process of customising PBs. The lack of research in these areas substantiate
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the primary motivation for the present study.
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3. Research methodology and framework
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3.1. Research methodology and design
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This study adopted a sequential mixed research methodology comprising five phases: 1)
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Identifying the client engagement issues in the OSC design stage 2) Establishing customisation
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principles 3) Developing a new design framework 4) Developing a proof of concept prototype 5)
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Evaluating the results through discussions. Further details of these five phases are depicted in Fig.
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1 and the subsequent paragraphs.
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<Insert Figure 1 about here>
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In the first phase, the current issues in the OSC industry (including limitations and complications
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experienced in the prevalent customer requirement-oriented methods) were diagnosed using an
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extensive literature review. Then, focusing upon achieving effective client intervention in the
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design process as one of the most important variables influencing PBs’ design [85], and effective
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design procedure for PBs was developed in this study. This was achieved by examining the
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inherent potential of the OSC process for client intervention in the design process of such buildings
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to establish a new framework. Such a framework adopts the principles of OSC to maintain a high-
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efficiency rate in OSC but also an anticipated increase in customers’ satisfaction with the final
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product. Additionally, automation of the configuration process was undertaken to enhance the
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design quality of PBs, which can engender higher production and assembly qualities [57,86].
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The proposed framework with the features above can boost the market share of OSC in the AECO
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industry through implementing a purposeful client collaboration and ensuring a high-efficiency
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rate for companies providing PBs. However, it must be emphasised that tackling this problem in
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OSC through lean design methods (which emphasises both production efficiency and customer
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satisfaction [87]) is an enormous and challenging undertaking. PBs are considered a sophisticated
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products is comprising diverse, complex elements. Therefore, an abundance of choice per se is not
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considered an advantage. Conversely, facing too many options sometimes does not necessarily
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manifest as customer’s satisfaction. Rather it may cause customer confusion, impacting their
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decision-making process negatively to own a PB [42].
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Several studies focus upon client requirements in the OSC design process. However, there is a
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shortage of theoretical and practical studies to develop an effective BIM-based framework for the
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design process. As a result, the client requirements and needs for element customisations and
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building configuration have seldom been systematically considered in the design process of such
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buildings. Mohammed [87] presented a data-rich BIM design environment integrated within an
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expert system to develop a set of rules (principles) relevant to the design requirements of PBs, and
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to examine these rules throughout the design process. Although design principles developed in this
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study were based on the client design requirements, the solutions proposed were limited only to
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the Engineer-to-Order (ETO) level of COPD. Li et al. [58] presented a framework in which the
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BIM capabilities were implemented in the production of PBs to facilitate data exchange and
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collaboration throughout the supply chain process using three integrated intelligent solutions.
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Yuan et al. [15] implemented a DfMA model for designing PBs and sought to increase the
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efficiency of the design process using BIM’s parametric capabilities. However, this study [15] did
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not focus on managing client requirements or intervention in the design process. All three studies
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mentioned above implemented BIM capabilities to develop effective frameworks and solutions
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that facilitate design information flow to improve the efficiency of the design and production
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processes for PBs. Despite this scientific advancement, there remains a notable lack of a BIM-
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based framework which incorporates the design and production requirements of PB but also
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embraces the client’s requirements related to different levels of customisation. To develop a
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balanced relationship between these three areas, the present study primarily aimed at developing
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a sound theoretical foundation underpinning an applied framework for client collaboration in
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design process, and to implement some integrated strategies to realise it in such a way that all these
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three key areas are considered from the early stages to the final stages of design. Fig. 2 illustrates
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the three objectives of the present study viz. ‘customer’s satisfaction’, ‘sophistication in design’
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and ‘production efficiency’. These objectives respectively seek to improve the quality of the three
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key areas of marketing, construction and production in the OSC industry.
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<Insert Figure 2 about here>
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Considering the objectives set and based on the research gap diagnosed in the first phase, the
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second phase of this study developed principles (regulations) controlling the client collaboration.
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These principles hinged around three key constructs, namely customisation approach,
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customisation levels, and customisation stages. A BIM-based DfMA design framework was
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developed in the third phase to incorporate the established principles in designing PBs. In the
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fourth phase, to examine the practicality of the proposed collaborative design framework in the
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real AECO world, a Prototype was developed in Revit environment. The integrated approaches
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proposed in the present study were implemented to put the present client-intervention oriented
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framework into practice. In the fifth phase, the results were discussed against the studies conducted
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on the design process in PBs, and client collaboration.
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3.2. Establishing customisation principles
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For this present study, a customisation approach was considered as one of the most fundamental
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guiding principles. Consequently, the allowable rate of client customisation (to control the degree
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of client collaboration in the design process) needed to be determined as a second principle.
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Notably, however, the customisation rate allowed for the different building elements by the
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company is different from the approach the company follows for the customisation of its products.
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Finally, the customisation stages which are to be integrated into the design process were
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determined as the third and last principle based on the two principles developed already, in which
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the stages of the customer’s interaction and needs for customisation are determined
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3.2.1. Customisation approach
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Collaborative customisation [cf. [88]] was used as a basis for the client customisation. According
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to the approach, companies providing customisation OSC services first gather detailed information
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concerning the client customisation requirements and then create various building element models
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based on these requirements. These models can be adjusted and customised to a limited extent
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based on customer requirements. In addition, the company enables the customer to participate in
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the building’s configuration within a controlled range, allowing them to choose from the models
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provided before.
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3.2.2. Customisation levels
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The theoretical continuum with five mass customisation strategies (from pure standardisation to
425
pure customisation) proposed by Lamper and Mintzburg [40] was used to classify the
426
customisation levels allowed for the client. This theory provides the company with a basis for
427
determining the CODP of building elements flexibly that considers diverse variables such as
428
resources, economic and technical considerations.
429
430
3.2.3. Customisation stages
431
11
The three different stages of customisation in the OSC design process are shown in Fig. 3. In the
432
first stage of the proposed procedure, the company's customisation strategies for various building
433
elements are determined. In the second stage, the company allows the customer to determine their
434
customisation requirements based on the customisation limitations specified in the first stage. The
435
client requirements are classified into different customisation levels. Based on the client
436
customisation requirements in the third and final stage, the company provides various building
437
element models and the necessary information concerning their assembly and production. The
438
company then develops the building configuration by selecting from among the alternative
439
building element models provided.
440
441
<Insert Figure 3 about here>
442
443
3.3. Proposed design framework
444
The DfMA framework proposed by Yuan et al. [15] was employed as a basis for the design
445
approach developed in the present study. The customisation principles introduced in Section 3.1.3
446
are integrated with this DfMA process to establish a new design framework. The customisation
447
principles found in the previous section were then incorporated with the DfMA framework. In line
448
with this integration, some rules have been added to this process and some need to be changed. To
449
implement the first stage of customisation, the company must provide customisation services for
450
PBs to determine the desired amount of customisation for all elements used in the building design.
451
Since this determination depends on the company resources, this stage must be performed without
452
the direct participation of the customer and by the company's marketing strategists. However, the
453
company can use surveys of its target market before determining its marketing strategy. However,
454
they must consider the average level of customisation that people apply in the preceding cases and
455
build their strategy based on it. It is also necessary for this strategy to be flexible so that if the
456
market tastes change, the strategy will adapt to the market's new needs. In the next stage, which
457
begins with a contract between a customer and the company, it is necessary to extract the
458
customer's customisation needs within the customisation constraints set by the company before
459
starting work on the design of building elements. These needs are categorised at different levels of
460
customisation for each of the elements used in the building configuration. After this stage, various
461
prefabricated building design experts begin to provide complete design information for these
462
elements. As a result, a comprehensive model of each of these elements is available in building
463
configuration. Finally, in the third and final customisation stage, the prefabricated building is
464
configured using the mentioned elements with the customer's participation. The final model of the
465
configured building is made available for final technical tests. Fig. 4 depicts the developed DfMA
466
framework in this study. The stages directly dealing with the three customisation stages proposed
467
are specified with dashed lines.
468
469
<Insert Figure 4 about here>
470
471
4. Prototype development
472
The proposed DfMA framework (section 3.2) and solutions to implement its stages, especially
473
those which involve the presented customisation stages in the design process, constituted the basis
474
for a prototype development using Revit software. The prototype served two simultaneous
475
purposes: 1) introduce research solutions to put the proposed framework into practice; and 2)
476
examine the framework’s practicality in a real-life project that utilised a BIM tool. A complete
477
12
realisation of the proposed framework is beyond the scope of the present study due to the diversity
478
of building elements in PBs. Therefore, the windows category was used as an illustrative sample
479
to examine the customisation and design functions. In addition to Revit software, the Dynamo
480
plugin available in this software was used for the configuration algorithm’s implementation in the
481
building design process. Moreover, when some of the required functions were unavailable in
482
Dynamo or their production was complex and time-consuming, Python script was used in Dynamo
483
to tackle the problems.
484
485
486
4.1. Determining customisation information
487
488
4.1.1 The company’s customisation strategy
489
The PIM hierarchical model was used as a basis to determine the company’s customisation
490
strategy; this model aligned product architecture levels of each building with their corresponding
491
LoDs. More specifically, the building and category levels were aligned at LoD 100 and LoD 200,
492
respectively, and element type and component levels, which are related to the physical parts of the
493
building, were aligned at LoD 300. Mass customisation was considered the third parameter in the
494
proposed model to determine the company’s CODP levels. Thus, based on the proposed model,
495
the company can simultaneously determine the CODP for each potential element and component
496
from the production and design perspectives. The company’s general customisation strategy
497
assumed that it considers a customised standardisation level as the maximal customisation allowed
498
for window types level with LoD 300 when determining the window specifications. In other words,
499
at the highest level of customisation, the customer can make minor modifications in the standard
500
components of the window, replacing choices made with common structural components and
501
ironmongery.
502
503
Moreover, by limiting the window component level with LoD 300 to pure standardisation, the
504
company allows the customer to customise the window components in terms of features.
505
Customers have to choose among the available standard components offered to them. Determining
506
the company's CODP for windows mass customisation is the first of three customisation stages are
507
presented in section 3.1.3.
508
509
4.1.2. The client’s customisation requirements
510
It is assumed that the customer’s needs for customising windows have been extracted as customer
511
employer’s information requirements (EIR) through questionnaires and have been classified in
512
PIM by customisation experts. Based on this classification, the customer wants the design section
513
to select two of the four building windows related to a living room. Thus, the company classifies
514
these two windows as pure standardisation. However, if the client chooses windows for the rooms
515
from commercially available designs, the company classifies the room windows as segmented
516
standardisation. Moreover, it has been assumed that based on the information available in the EIR,
517
the customer wants the two identical windows for the building’s public space and the other two
518
windows of the two rooms to be identical too. Therefore, in the final model, there are only two
519
types of windows to be used. This is the second stage of the customisation process presented in
520
section 4 above.
521
522
4.2. Design and customisation process
523
13
4.2.1. Specifying design information for configuration stage
524
Once the non-prefabricated construction information model was developed and the DfMA and
525
Split Design analyses were conducted, the exact window specifications to be used could be
526
determined. The window models were designed using the proposed DfMA framework in the BIM
527
environment according to the LoD 300 considered in the PIM model. Because the customer's
528
potential choices are limited to the standard commercially available windows, their Revit models,
529
including their graphical model and manufacturing and assembly information, are downloaded
530
from their manufacturer’s websites and imported into the Revit library. Fig. 5. reveals that the final
531
output of the stages completed so far was four different window models from four different types.
532
As mentioned in section 4.1.2, only two of these four window types were used in the building.
533
Finally, it should be noted that if the customisation level considered for the elements is customised
534
standardisation or more, it is necessary to exclusively design the needed elements based on the
535
client requirements for the window elements, which were already provided in the form of EIR.
536
537
<Insert Figure 5 about here>
538
539
Post window models’ design and manufacturing information were determined through a DfM
540
process (implemented in the BIM environment). The assembly information is derived from the
541
DfA process in the same environment. The proposed framework's DfA process consisted of two
542
main steps: 1) determining assembly limitations; and 2) determining assembly requirements.
543
Accordingly, the proposed prototype examined the assembly limitation between windows and their
544
host wall. Before the configurations process, the allowable choices for windows could be specified
545
based on the host walls. In this way, the host walls could be considered a limiting factor in selecting
546
window types from among the choices offered - assembly limitations are shown in Table 1.
547
Because BIM supports the assembly requirements of all the four types of windows through
548
Assembly Code Parameter (Fig. 6. ), there is no need to redefine this parameter for these types of
549
windows. In addition to windows, the assembly requirements of their host walls are also defined
550
by the same parameter.
551
552
<Insert Table 1 and Figure 6 about here>
553
554
As it can be seen in Fig. 7, the company’s CODP for determining the customisations limits for the
555
building windows (discussed in section 4.1.1) are shown with a solid red line in the PIM model.
556
This model also shows the classification of customer customisation requirements based on CODP
557
levels (discussed in Section 4.1.2). In addition to customisation information, the names of the four
558
suggested windows in which their design models were produced previously in the BIM
559
environment (section 4.2.1) are shown in this figure.
560
561
562
<Insert Figure 7 about here>
563
564
More specifically, so far, in addition to the graphical model of these four windows, their
565
manufacturing and assembly information, along with the assembly requirements of their host
566
walls, have been determined by the BIM authoring tool. Now that their BIM and PIM (containing
567
information concerning window customisation and functional relationships of building
568
14
components) models have been determined, all the necessary information is accessible to develop
569
the building configuration algorithm for customising windows.
570
571
4.2.2. Customisation through configuration algorithm
572
In this stage, it was necessary to develop an algorithm based on two key pieces of information.
573
First was the building product architecture which provides information about the functional
574
relationship among all building elements. The second was the DfA information which provides
575
details about assembly limitations between elements and assembly requirements of each element.
576
For further clarity about the presented configuration algorithm, the following paragraph provides
577
an overview of the development strategies of this algorithm how it relates to these two pieces of
578
information.
579
580
First, the architecture of the PIM model is used to assess the existing functional relationships
581
between the various elements of the building. Second, suppose a functional relationship was
582
determined between a host element (e.g. element A) and a mountable element (e.g. element B). In
583
that case, the technical assembly considerations of each element will be loaded from the DfA
584
section of the design framework. These will set up limits for their assembly relationship. If, in light
585
of the assembly constraints, it is possible to connect or place element B on element A (i.e. there is
586
no limit to the assembly), the assembly information related to the relationship between the two
587
elements will be precisely defined and formulated. In this case, whenever element A is selected as
588
the “host element”, element B will be considered as a “customisation option”. Otherwise, element
589
B will not be introduced as an option for assembly on element A. Consequently, there will be no
590
need to define and formulate the relationship between the two elements. This process is illustrated
591
in Fig 8.
592
593
<Insert Figure 8 about here>
594
595
596
However, providing a configuration algorithm for a whole PB entails a comprehensive
597
understanding of relationships among all building components. Therefore, an algorithm based on
598
the product architecture information available in the PIM (as discussed in Section 4.2.2) specifying
599
the exact functional relationships between the different prefabricated elements was used to develop
600
an integrated strategy for the proposed design framework. The functional relationship available in
601
the product architecture determined the connections between the nodes of the algorithm, which
602
constitute the element types of different categories (refer to Fig. 9). Therefore, choices in the
603
element type section can limit the selection of element types that are functionally related to those
604
choices.
605
606
<Insert Figure 9 about here>
607
608
Moreover, the Dynamo plugin available in Revit software was implemented so that the proposed
609
algorithm could be used to configure the building and its designed window models in this
610
prototype. This configuration process (which is based on the inputs needed to execute the function
611
of creating a window on a host wall in Dynamo) consists of determining three main steps: 1) the
612
host wall; 2) the location of the window on the host wall; 3) the window type. However, to help
613
secure a better grasp of the innovative limiting mechanism as the main functional feature of this
614
15
algorithm, it was assumed that the first two steps were completed, with the primary focus being
615
on the last step of determining the window types. Thus, in the limiting mechanism developed, the
616
input nodes include the host wall and the list of available window types. At the same time, the
617
output contains a filtered list of windows based on the assembly limitations of the selected host
618
wall. Because the necessary function for the extraction of all windows available in the Revit family
619
was not available on Dynamo and its packages, it was required to use Python scripts to create such
620
a function.
621
622
Moreover, to create a node with the function of the limiting mechanism, an attempt was made to
623
define a specific number of window assembly codes for all assembly codes of the host wall
624
choices. Once a given host wall was selected, a list of window types (which have assembly codes
625
matching with the assembly code of the wall) resulted in the output of this node. Fig. 10 shows
626
how Python script was used to develop this function.
627
628
<Insert Figure 10 about here>
629
630
After a list of windows is designed based on the customer's customisation needs and the
631
manufacturing and assembly requirements of PBs are provided, the customer can choose a
632
preferred window type available in the configuration algorithm. Thus the last of the three stages
633
of the customisation supplied in the proposed DfMA framework is completed. Fig. 11 summarises
634
how the window types are selected in Dynamo and installed on the host wall in the Revit
635
environment. This figure reveals that according to the client customisation requirements translated
636
in the form of customisation levels in PIM (Fig. 7), the two southern windows of the living room
637
are selected by the design section. In contrast, the client can decide on windows 3 and 4 from
638
among the four suggested choices. Moreover, because the client’s customisation requirements in
639
PIM entail windows 1 and 2 to be of the same type and windows 3 and 4 similar, the algorithm is
640
programmed to select these windows two by two.
641
642
The proposed algorithm provides a flexible framework for the configuration because its parametric
643
structure allows the design section to make necessary changes even after the customisation stages
644
are completed. If the client decides to change their choices, the proposed algorithm can incorporate
645
the new selections automatically based on the assembly requirements. Moreover, the design
646
section introduces new window types and host walls so that the new choices can be easily added
647
to the Revit Family environment. The new elements are inserted automatically into the relevant
648
inputs available in the Dynamo environment. After the limiting mechanism is updated based on
649
the assembly codes of the newly added elements in the configuration algorithm, they will be
650
available to be selected by the customer or the design section.
651
652
After the configuration and optimisation steps, DfMA tests are performed on the building model
653
again. If the results are confirmed, reliable information on PB's customisation, design, and
654
production is provided in PIM and BIM models. Therefore, the construction and production
655
sections can access the needed information included in these models before projects
656
commencement.
657
<Insert Figure 11 about here>
658
659
5. Discussions
660
16
Over the last few decades, many research studies have emphasised the importance of customer
661
intervention in the design stage, presenting innovative approaches to facilitate customer
662
collaboration [21,89-92]. Because BIM has proved effective in reducing rework and the economic
663
and environmental costs caused by the waste of materials [93-95], it can be implemented as a
664
design tool to simultaneously meet the customer’s requirements and those of the OSC industry
665
[96,97]. In this regard, the literature reviewed uncovered that an increasing body of research
666
studies have emphasised the unique technical data exchange capabilities of BIM along with
667
immersive technologies such as AR and VR through open BIM standards and IFC information
668
format [4,29]. Numerous studies reveal that these capabilities can create innovative solutions for
669
the collaboration among individuals and different parties engaged in such buildings [63,98-100].
670
However, a notable dearth of studies sought to provide a design framework for these buildings; a
671
framework in which due attention is paid concurrently to these buildings' customer requirements
672
and construction efficiency. More specifically, delineating how the customer collaborates with the
673
design section from the early to final stages of the sophisticated design process. One solo research
674
project in this area presented a solution based on providing different building configurations by
675
various pre-designed components and building assemblies designed according to production,
676
construction, and assembly [101]. Yet despite this research, the focus of attention predominantly
677
is upon customer requirements at the configuration level, ignoring the basis for the customisation
678
of building and its components throughout the design process.
679
680
The design framework presented, along with the practical integrated approaches for
681
implementation in OSC industry, can be used as a foundation to determine the client collaboration
682
with the design section of this type of building. Consequently, the results obtained in the present
683
study are relevant to the stages before data exchange between the client and design section and
684
advance previous studies conducted in this area. Compared to the collaboration process defined in
685
BIM standards such as CDE available in PAS 1192-2-2013 standard [81], the collaboration
686
framework proposed is developed specifically for prefabricated buildings and their elements.
687
Moreover, since the present framework enables users to take advantage of an algorithmic process
688
for building configuration with the customer collaboration, many design rework items commonly
689
experienced in traditional client collaboration processes can be avoided. In addition to this, due to
690
the parametric configuration algorithm available for selecting the elements, the time and economic
691
costs imposed by possible future changes are minimised. Finally, because all the assembly
692
requirements are observed in this algorithm, the risk of error occurrence in the assembly stage is
693
minimised. Consequently, the need for design and production rework is considerably reduced.
694
695
However, there are some practical and functional limitations with the research presented. For
696
example, although there are solutions to customise the elements in the proposed framework, it
697
lacks solutions for customising the building layout. The present study’s primary purpose was to
698
develop a theoretical framework for the collaboration of the customer with the design section.
699
Consequently, a prototype was created to examine the proposed model’s practicality. However,
700
the study presented lacks empirical data obtained through implementing the proposed framework
701
in different case studies. Consequently, usability, advantages and disadvantages require future
702
testing on real-life projects.
703
704
Future studies should provide a digital information model that can integrate the PIM model
705
developed with the BIM Model. Integration of the information gathered from the beginning to the
706
17
end stage of the design process can make access to information related to the production, assembly,
707
and customisation of the elements (and their relationship with other elements available in the
708
product architecture) easier all stages the design process. Moreover, cloud-based environments can
709
provide zero-latency communication between the customer and the design section [102]. When
710
the design and customisation information of the elements and the configuration algorithm
711
developed based on the framework proposed is uploaded onto the cloud-based environment, a user
712
interface can be created in the background, which can offer easy access to, and use of the
713
configuration algorithm for the customer. Moreover, BIM and blockchain technology [103-105]
714
can be combined to facilitate smart contracts and payments for the customisation activities in an
715
automated peer-to-peer method. In this way, a customer’s confidence will be augmented like the
716
collaboration offered by the present framework. In addition, to automate OSC industry [106], it
717
seems possible to provide strategies in which the production and assembly information present in
718
the PIM and BIM models can be automatically prepared and exchanged for robotic manufacturing
719
and assembly processes after the design process is completed.
720
721
6. Conclusion
722
This research makes several contributions to the fields of digital design and marketing in the OSC
723
industry. First, a DfMA-based framework was provided and based upon customisation principles,
724
thus enabled simultaneous emphasis to design principles of PBs, and customer satisfaction so that
725
the client can customise building elements and components to the extent permitted by the
726
company. Second, the proposed framework for the building design customisation stage contains
727
an algorithm that allows the client to participate in the building configuration process based on
728
assembly limitations. Third, in addition to the theoretical framework offered, this research study
729
uses the BIM environment for the element design and building configuration process. Moreover,
730
an innovative information model for gathering different types of information concerning PBs and
731
their elements (including customisation, product-oriented and building construction information)
732
was developed to relate the theoretical concepts with these fields' practical and technical issues.
733
734
Compared to the current strategies offered to implement prefabricated construction frameworks,
735
the PIM model provides marketing experts with a product and building-oriented understanding.
736
This feature enables them to determine the company’s customisation strategy for the products they
737
offer from a more comprehensive perspective and to define and classify the acceptable levels for
738
client customisation based on this customisation strategy. Furthermore, the product architecture
739
levels available in this model enable the experts in the DfA section of prefabricated buildings to
740
determine all the available information concerning the functional relationships between the
741
elements and the physical components, which can be used in the design process. In addition, the
742
general information about the elements and components used in this product architecture can guide
743
building element(s) and component(s) design throughout the design process. Finally, the
744
customised PB's product architecture information and manufacturing information in the BIM
745
model can be used as reliable information to start the production process.
746
747
Moreover, the design experts can use LoDs to determine the level of work and care needed to deal
748
with the design details in the design process of elements. Upon conclusion of the design process,
749
the LoDs of the different elements and components included in the product architecture of the
750
customised building can provide reliable information for the construction process to start. The idea
751
of a configuration algorithm was developed to properly use assembly and customisation
752
18
information inside the innovative model to achieve high-quality output. In addition, the assembly
753
requirements determined in the BIM model for the elements were used to automate the provision
754
of customer choices to enhance their satisfaction and mitigate the risk of production and assembly
755
errors (mistakes) caused in customisation and design processes. Indeed, the ultimate purpose of
756
the strategies offered for the best implementation of the present theoretical framework was to
757
encourage customers in the construction market to opt for OSC through meeting their preferences
758
(requirements) while minimising material and time waste. The strategies' practicality was
759
examined by developing a prototype for customising building windows considered a sample
760
category. It was observed that all the proposed methods in the framework for the design and
761
configuration of elements using the Revit tool (considered as the most commonly employed BIM
762
tool) and an intermediate level of coding showed good usability.
763
764
Despite the considerable positive aspects of the present study, there are several limitations.
765
Foremost, this study exclusively focuses on expediting client engagement within PB design, whilst
766
other projects have similar needs and requirements. Although it would be great to generalise the
767
developed framework and algorithm to all types of buildings design, this wasn't feasible to do it in
768
a single study as the fundamentals of collaboration for PBs differ from any other kind of building.
769
This is due to the DfMA approach being a prerequisite of this kind of buildings so that it
770
encompasses all vertical and horizontal relationships among various building elements. Due to this
771
fact, the designed algorithm could not be applied in designing any other kind of building. Second,
772
there is no customisation framework for building layout that considers all the construction
773
requirements and is integrated with other design stages. Nor does a suitable user interface exist
774
that can be used to examine the practicality of the client collaboration with the design section in
775
building configuration. Hence, it is suggested that a communication server and a visualisation
776
environment be used along with a new version of the proposed framework and upgraded strategies
777
such as a simple interface that customers can use with ease to receive immediate feedback on their
778
selections. Finally, it is suggested that the PIM model be digitalised to be fully integrated with the
779
BIM model, which can facilitate the flow of information along with the proposed framework, in
780
general, and in the configuration stage, in particular.
781
782
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783
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[105] E.A. Parn, D. Edwards, Cyber threats confronting the digital built environment, Engineering,
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Construction and Architectural Management 26 (2) (2019), pp. 245-266. doi: 10.1108/ECAM-03-
1094
2018-0101
1095
[106] P. Vähä, T. Heikkilä, P. Kilpeläinen, M. Järviluoma, E. Gambao, Extending automation of building
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construction — Survey on potential sensor technologies and robotic applications, Automation in
1097
Construction 36 (2013), pp. 168-178. doi: https://doi.org/10.1016/j.autcon.2013.08.002
1098
1099
1100
26
1101
1102
Fig. 1. The five-step sequential mixed research methodology and design
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
Fig. 2. Areas and objectives of current research and the desirable relationship between them
1121
1122
Sophistication
in Design
Customer
Satisfaction
Efficiency in
Production
Marketing
Production
Construction
Phase 1
Phase 2
Phase 3
Phase 4
Phase 5
Using related studies
conducted on the OSC
design process
Evaluating the results
through discussions
Developing proof of
concept prototype
Using Revit software
as a
parametric environment
and Dynamo plugin as an
algorithmic environment
Developing a new design
framework
Selecting a reference
framework
Matching the reference
framework with the
customisation principles
Establishing customisation
principles
Customisation approach
Customisation levels
Customisation stages
Identifying the customer
collaboration issues in OSC
design stage
Using an extensive literature
review
27
1123
1124
1125
1126
1127
1128
1129
1130
Fig. 3. Intended stages to customise prefabricated building
1131
1132
1133
1134
1135
Determining
client’s
customisation
requirements
Performing
collaborative
customisation
Stage 1
Stage 2
Stage 3
Determining the
company's
customisation
strategy
28
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
Fig. 4. The proposed DfMA framework for achieving research objectives
1163
Design project
start
Determining
the company’s
customisation
strategy
Determining
And classifying
the client
requirements
Construction information
model of non-prefabricated
building
Split design and DfMA
analysis
Product
architecture
including usable
elements
Check needed parametric
element in BIM
Does BIM own it ?
Create needed
parametric element in
BIM
The needed
parametric
element
BIM element
library
Check needed assembly
information in BIM
Does BIM own it ?
Create needed
assembly information in
BIM
Needed
assembly
information
Building product
architecture
+
Building assembly
information
Configuration of PB with the
client’s collaboration
Optimisation and DfMA
tests
PB construction
information
PB production
information
Construction
project start
Production
project start
Failed
Passed
No
Yes
No
Determining
assembly limitations
of the elements in
the product
architecture
Information
required for
production and
construction
sectors
Yes
29
1164
1165
Fig. 5. Various types of windows usable in the building
1166
Window type A
Window type B
Window type C
Window type D
30
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
Fig. 6. Determining the assembly requirements for the windows using assembly code parameter
1180
31
Table 1 Assembly limitations of different window types and their host walls
1181
1182
Host walls
Windows to be assembled
EXT _ Timber Frame - 250mm - Filled
a) M_Fixed_0915 x 1830mm
b) Intakt-inward_opening_window_2+1_glass_3-light_with_mullion-middle open
c) Window-Horizontal_Sliding-PlyGem_WC-LessHalf_Vent
EXT_ Composite - 250mm - Filled
a) M_Fixed_0915 x 1830mm
b) Intakt-inward_opening_window_2+1_glass_3-light_with_mullion-middle open
c) Window-Horizontal_Sliding-PlyGem_WC-LessHalf_Vent
EXT _ CLT - 150mm
a) M_Fixed_0915 x 1830mm
b) Intakt-inward_opening_window_2+1_glass_3-light_with_mullion-middle open
c) Window-Horizontal_Sliding-PlyGem_WC-LessHalf_Vent
d) Window-Solar_Innovations-Tilt_Turn_SI7251
EXT _ Light Gauge - 200mm - Filled
a) M_Fixed_0915 x 1830mm
b) Intakt-inward_opening_window_2+1_glass_3-light_with_mullion-middle open
c) Window-Horizontal_Sliding-PlyGem_WC-LessHalf_Vent
d) Window-Solar_Innovations-Tilt_Turn_SI7251
1183
1184
1185
1186
1187
1188
1189
32
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
Fig. 7. The PIM model of the building windows
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
Window
number 4
Window
number 2
Product Level
Category Level
Pure standardisation
Customised
Standardisation
Tailored
Customisation
Pure
Customisation
Component Level
Segmented Standardisation
Element Type
Level
Prefabricated
Building
Window
category
Window Components
Window
number 3
Window
number 1
Suggested Windows
A
B
C
D
Fig. 8. The concept of the assembly limitation between building elements
Host Element
Element A
Functional
relationship with
Element B
Element C
Valid
Invalid
Does element A
limit the choice of
element B?
Checking functional
relationship based on building
product architecture
Other mountable
elements
Checking assembly
limitation based on
technical considerations
Assembly condition
Yes
No
If element A is
selected do not
return element B
as an option
If element A is
selected return
element B as an
option
Step 1
Step 2
Step 3
33
1215
Fig. 9. The concept of building configuration algorithm and choice limitations
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
The designed building
elements to be used
in configuration
algorithm
Floor
Ceiling
Exterior walls
Interior non
load-bearing
walls
Internal doors
Exterior wall
windows
Exterior wall
finishing
External doors
Categories:
Element Types:
Functional relationship
based of product architecture:
Interior load-
bearing walls
Window
Door
Wall
Ceiling
Floor
34
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
Fig. 10. Executing the limiting function of the windows based on the host wall using Python
1239
script
1240
1241
1242
1243
1244
1245
Node related to the
limiting mechanism
35
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
Fig. 11. Selecting the preferred windows using configuration algorithm created in Dynamo and
1268
the resulting output
1269
Window selected by design section
Window selected by client
List of usable windows based on the
host wall
Client selection of room windows
List of windows created
in the building model