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Integrating digital design and Additive Manufacturing through BIM-based digital support - A decision support system using Semantic Web and Multi-Criteria Decision Making
Digital manufacturing methods have been successfully used in different industries for years and have since had a positive effect on the development of their productivity. These methods offer significantly greater design freedom and make it possible to develop shape-optimized and function-activated components. In the construction industry, however, these technologies are only being used reluctantly, even though additive methods could make resource-efficient construction possible. The possibly decisive disadvantage of these methods is that a significantly higher granularity of product and process information is required, thus significantly increasing the planning effort. A circumstance that the framework described in this study, fabrication information modeling (FIM), could significantly mitigate by linking digital fabrication and BIM-based digital building design via a digital chain. For this purpose, FIM provides a methodology with which the information of a digital building model can be detailed, component by component, in a fabrication-aware manner. Based on the open exchange data format IFC, the FIM framework integrates seamlessly into the BIM context and enables automated detailing of the design information.
Lightweight mortar extrusion enables the production of monolithic exterior wall components with improved thermal insulation by installing air chambers and reduced material demand compared to conventional construction techniques. However, without reinforcement, the systems are not capable of bearing high flexural forces and, thus, the application possibilities are limited. Furthermore, the layer bonding is a weak spot in the system. We investigate a reinforcement strategy combining fibers in the mortar matrix with vertically inserted elements to compensate the layer bonding. By implementing fibers in the extruded matrix, the flexural strength can be increased almost threefold parallel to the layers. However, there is still an anisotropy between the layers as fibers are oriented during deposition and the layer bond is still mainly depending on hydration processes. This can be compensated by the vertical insertion of reinforcement elements in the freshly deposited layers. Corrugated wire fibers as well as short steel reinforcement elements were suitable to increase the flexural strength between the layers. As shown, the potential increase in flexural strength could be of a factor six compared to the reference (12 N/mm² instead of 1.9 N/mm²). Thus, the presented methods reduce anisotropy in flexural strength due to layered production.
Extrusion-based additive manufacturing (AM), or three-dimensional (3D) printing, has matured into a set of advanced methods to automate the construction of large-scale concrete structures, while minimizing cost and material waste. However, current AM data models are inadequate for 3D concrete printing due to insufficient incorporation of information on the relationships between process, material, and geometry, which may cause redundancy, information loss, and inconsistencies. Aiming at improving AM data modeling for concrete printing, this paper proposes a metamodeling approach for AM of concrete structures, referred to as "printing information modeling", which takes advantage of building information modeling (BIM). As will be shown in this paper , the BIM-based printing information model, serving as a metamodel, incorporates the digital data triplet of process, material, and geometry parameters to generate computer numerical control (CNC) commands that may readily be used for concrete printing. A validation test is performed, which instantiates the printing information model, using a BIM model, for generating CNC commands , enabling optimal digital data exchange from BIM models to concrete printers. As a result of this study, it is demonstrated that printing information modeling adequately defines the information required for AM of concrete structures using a BIM-based approach, showing promising potential to improve current AM data modeling efforts.
Additive Manufacturing (AM) and Building Information Modelling (BIM) are emerging trends for which it has been claimed that both increase both efficiency and productivity in the construction industry. The aim of this study is to synthesise and aggregate the literature addressing BIM integration in the AM of concrete structures and to exploit the joint value creation potential.
This study firstly applies a mixed-review method in order to achieve mutual corroboration and interdependency between quantitative and qualitative research approaches. Bibliometric mapping is applied to identify, map and synthesise the relevant literature. Scoping review is used to examine the extent, gap, range and nature of the research activity. Afterward, a cross-situational analysis, TOWS2 Matrix, is proposed and applied to exploit the joint value creation potential of different aspects of AM and BIM.
The study reveals a substantial interest in this field. However, progress in terms of integration is slow compared to the rapid development in interest in the two trends individually. The literature discusses or conceptualises such integration at building-scale, while prototyping or PoC processes are only rarely employed. The study identified 12 joint value creation potentials through the integration of BIM in AM for concrete structures, which can create value by enabling more optimised designs, automated construction processes, and data analytics that can apply throughout the building life-cycle process.
The advancements of BIM integration in the AM of concrete structures are analysed and joint value creation potentials are proposed. The study proposes a cross-situation analysis that can be applied to structure joint value creation potentials from the multi-dimensional integration of different factors and topics, especially for emerging technologies.
The application of additive manufacturing (AM) in construction has been increasingly studied in recent years. Large robotic arm- and gantry-systems have been created to print building parts using aggregate-based materials, metals, or polymers. Significant benefits of AM are the automation of the production process, a high degree of design freedom, and the resulting potential for optimization. However, the building components and 3D-printing processes need to be modeled appropriately. In this paper, the current state of AM in construction is reviewed. AM processes and systems as well as their application in research and construction projects are presented. Moreover, digital methods for planning 3D-printed building parts and AM processes are described.
Purpose
Additive manufacturing (AM) has been increasingly used in various applications in recent years. However, it is still challenge when it comes to selecting a suitable AM process. This is because the outcome may vary due to not only different materials and printers but also different parameters and post-processes. This paper aims to develop an efficient method to help users understand trade-offs and make right decisions.
Design/methodology/approach
A hybrid method is proposed to help users select appropriate options from a large-scale and discrete option space in an interactive way. First, the design-by-shopping approach is applied to allow users exploring and refining the option space. The analytical hierarchical process method is then used to capture customers’ preferences. After analyzing the results of different normalization methods, a modified Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach is proposed to rank solutions and provide suggestions.
Findings
The usefulness of proposed method is illustrated in a case study. The results show that it can help customers understand performance distributions and find most suitable options accurately. The ranking of the modified TOPSIS method is more reasonable.
Originality/value
Due to the complexity of AM technologies, the process selection is considered at the parameter level. A new system framework is proposed for decision support. The TOPSIS method is modified to achieve a stable performance.
Additive manufacturing (AM) of construction materials has been one of the emerging advanced technologies that aim to minimise the supply chain in the construction industry through autonomous production of building components directly from digital models without human intervention and complicated formworks. However, technical challenges needs to be addressed for the industrial implementation of AM, e.g. materials formulation standardization, and interfacial bonding quality between the deposited layers amongst others. AM as one of the most highlighted key enabling technologies has the potential to create disruptive solutions, the key for its successful implementation is multidisciplinary effort in synergy involving materials science, architecture/design, computation, and robotics. There are crucial links between the material design formulations and the printing system for the manufacturing of the complex 3D geometries. Understanding and optimising the mix design for fresh rheology of materials and sufficient adhesion/cohesion of interface can allow the incorporation of complexity in the geometry.
Incomplete, imprecise and large volume of data generates the concept of knowledge base. Knowledge base which is collection of facts, procedures and meaning is much better than database because it provides the power of reasoning, with the help of which the complicated questions are solved. Knowledge representation is a method to encode knowledge, beliefs, action, feeling, goals, desires, preferences and all other mental states in the Knowledge base. Semantic web defines standards for exchanging knowledge via coherent knowledge base. To develop a good knowledge base it is necessary to have good knowledge representation. For this reason, knowledge representation is our main consideration. This paper gives an overview on knowledge representation aspects in the context of semantic web.
In Design by Shopping, designers explore the design space to gain an insight into trades, and feasible and impractical solutions, as well as to learn about alternatives before optimization and selection. The design space consists of multidimensional sets of data and, in order to select the best design from among numerous alternatives, designers may use several different graphs. In this study, we test to find the most appropriate graph to indicate the best solution corresponding to a set of objectives represented by a design scenario (1). A further constraint is that this must be done in the shortest possible time (2). Three graph types are tested in three different design scenarios where one car has to be chosen from a total of 40. A response quality index is proposed which computes the quality of a designer’s choice for any given scenario. In total, 90 tests with 30 participants were performed. The parallel coordinates plot proved to be the best graph for selection in Design by Shopping.
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The present work addresses particle bed binding by selective cement activation as an additive manufacturing process for cement-based materials in construction industry. Its focus is the effect of material and process on the microstructure and macroscopic properties of the hardened material. As macroscopic properties, strength and dimensional accuracy are characterized. The structure of the printed material is investigated on the micro scale by quantifying porosity and homogeneity of the layers.
It is shown that material and process parameters such as the w/c-ratio, particle size distribution of the aggregates, addition of methylcellulose as well as the method of water application (spraying or jetting) have a significant effect on the properties of the additively manufactured specimens. Furthermore, the results clearly demonstrate the importance of a thorough analysis of the underlying mechanisms at the micro level for a comprehensive understanding of the material and process-related influences.
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Shotcrete 3D Printing (SC3DP) is a novel robot-guided AM technology developed at Technische Universität Braunschweig in the environment of the Digital Building Fabrication Laboratory (DBFL). For successful automation, it is crucial to understand and redefine the entire concrete spraying process with all its interdependent parameters. This paper presents the basic principles of the SC3DP technology together with the results of a comparative study on the influence of the two concrete printing techniques extrusion and SC3DP on the interlayer bond strength. In particular, the effect of different time intervals between the deposition of two adjacent layers regarding mechanical properties (bond strength) is investigated. As will be shown, the SC3DP method allows convenient mechanical properties although the printed samples exhibit distinct anisotropies. The reasons are discussed based on investigations of the air void distribution by micro CT and mechanical test results.
Design for additive manufacturing (DFAM) provides design freedom for creating complex geometries and guides designers to ensure the manufacturability of parts fabricated using additive manufacturing (AM) processes. However, there is a lack of formalized DFAM knowledge that provides information on how to design parts and how to plan AM processes for achieving target goals. Furthermore, the wide variety of AM processes, materials, and machines creates challenges in determining manufacturability constraints. Therefore, this study presents a DFAM ontology using the web ontology language (OWL) to semantically model DFAM knowledge and retrieve that knowledge. The goal of the proposed DFAM ontology is to provide a structure for information on part design, AM processes, and AM capability to represent design rules. Furthermore, the manufacturing feature concept is introduced to indicate design features that are considerably constrained by given AM processes. After developing the DFAM ontology, queries based on design rules are represented to explicitly retrieve DFAM knowledge and analyze manufacturability using Semantic Query-enhanced Web Rule Language (SQWRL). The SQWRL rules enable effective reasoning to evaluate design features against manufacturing constraints. The usefulness of the DFAM ontology is demonstrated in a case study where design features of a bracket are selected as manufacturing features based on a rule development process. This study contributes to developing a reusable and upgradable knowledge base that can be used to perform manufacturing analysis.
The fabrication of novel reinforced concrete structures using digital technologies necessarily requires the definition of suitable strategies for reinforcement implementation. The successful integration of existing reinforcement systems, such as steel rebar, rods, wires, fibres or filaments, will indeed allow for printed concrete structures to be designed using standard structural codes. However, reinforcement integration has to be compatible with either the specific printing technique adopted for the structural element production or with its shape. This paper provides a systematic overview of a number of digital fabrication techniques using reinforced concrete that have been developed so far, proposing a possible organization by structural principle, or place in the manufacturing process.
Robotic construction through concrete 3D printing is an in-progress revolution in construction industry. While
significant progress is made on hardware related challenges, software and information related issues of such
innovative system are less discussed. In this paper, a software platform is proposed for data retrieval and analysis from BIM models and utilizing it efficiently during various stages of the process. While the general idea of using BIM for automated construction has been mentioned before, the implementation details (the focus of this paper) were not previously discussed. To this aim, a framework is proposed to integrate BIM into an automated construction system. A Planning and Operations Control Software for Automated Construction (POCSAC) is developed as a major enabler for a seamless integration of BIM and Contour Crafting. The interoperation between different components of the construction system and BIM platform are designed to maximize the realized benefits through synergy of the two technologies.
Design for additive manufacturing (DFAM) gives designers new freedoms to create complex geometries and combine parts into one. However, it has its own limitations, and more importantly, requires a shift in thinking from traditional design for subtractive manufacturing. There is a lack of formal and structured guidelines, especially for novice designers. To formalize knowledge of DFAM, we have developed an ontology using formal web ontology language (OWL)/resource description framework (RDF) representations in the Protéegée tool. The description logic formalism facilitates expressing domain knowledge as well as capturing information from benchmark studies. This is demonstrated in a case study with three design features: revolute joint, threaded assembly (screw connection), and slider-crank. How multiple instances (build events) are stored and retrieved in the knowledge base is discussed in light of modeling requirements for the DFAM knowledge base: knowledge capture and reuse, supporting a tutoring system, integration into CAD tools. A set of competency questions are described to evaluate knowledge retrieval. Examples are given with SPARQL queries. Reasoning with semantic web rule language (SWRL) is exemplified for manufacturability analysis. Knowledge documentation is the main objective of the current ontology. However, description logic creates multiple opportunities for future work, including representing and reasoning about DFAM rules in a structured modular hierarchy, discovering new rules with induction, and recognizing patterns with classification, e.g., what leads to "successful" versus "unsuccessful" fabrications.
Additive Manufacturing (AM) technologies enable the fabrication of parts and devices that are geometrically complex, have graded material compositions, and can be customized. To take advantage of these capabilities, it is important to assist designers in exploring unexplored regions of design spaces. We present a Design for Additive Manufacturing (DFAM) method that encompasses conceptual design, process selection, later design stages, and design for manufacturing. The method is based on the process-structure-property-behavior model that is common in the materials design literature. A prototype CAD system is presented that embodies the method. Manufacturable ELements (MELs) are proposed as an intermediate representation for supporting the manufacturing related aspects of the method. Examples of cellular materials are used to illustrate the DFAM method.
- F Jalaei
- A Jrade
- M Nassiri
Jalaei, F., Jrade, A. and Nassiri, M.: 2015, INTEGRATING DECISION SUPPORT SYSTEM
( DSS ) AND BUILDING INFORMATION MODELING ( BIM ) TO OPTIMIZE THE
SELECTION OF SUSTAINABLE BUILDING COMPONENTS, Information Technology
in Construction, 20, 399-420.