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The purpose of this paper is to describe challenges the manufacturing industry is currently facing when developing future assembly information systems. More specific, this paper focuses on the handling of assembly information from manufacturing engineering to the shop floor operators.

Multiple case studies have been conducted within one case company between 2014 and 2017. To broaden the perspective, interviews with additionally 17 large and global manufacturing companies and 3 industry experts have been held. Semi-structured interviews have been the main data collection method alongside observations and web questionnaires.

Six focus areas have been defined which address important challenges in the manufacturing industry. For manual assembly intense manufacturing company, challenges such as IT challenges, process challenges, assembly process disturbances, information availability, technology and process control, and assembly work instructions have been identified and hinder implementation of Industry 4.0 (I4.0).

This longitudinal study provides a current state analysis of the challenges the manufacturing industry is facing when handling assembly information. Despite the vast amount of initiatives within I4.0 and digitalization, this paper argues that the manufacturing industry needs to address the six defined focus areas to become more flexible and prepared for the transition toward a digitalized manufacturing industry.

Design is a time-consuming process for mechanical production. Some design structures frequently occur in different products and can be shared by multiple assembly models. Thus, identifying these structures and adding them to a design knowledge library significantly speed up the design process. Most studies addressing this issue have traditionally focused on part models and have not extended to assembly models. This paper aims to find a method for common design structure discovery in assembly models.

Computer-aided design models have a great deal of valuable information defined by different designers in the design stages, especially the assembly models, which are actually carriers of information from multiple sources. In this paper, an approach for discovering a common design structure in assembly models is proposed by comparing information from multiple sources. Assembly models are first represented as attribute connection graphs (ACGs), in which we mainly consider topological information and various attributes of parts and connections. Then, we apply a K-means clustering method based on a similarity analysis of different attributes to classify the parts and connections and transform ACGs of assemblies into type code graphs (TCGs). After this, a discovery algorithm that improves upon fast frequent subgraph mining is used to identify common design structures in assemblies.

A new method was developed for discovering common design structures in assembly models, considering the similarity of information from multiple sources and allowing some differences in the details to keep both commonalities and individualities of common design structures.

Experiments show that the proposed method is efficient and can produce a reasonable result.

This discovery method helps designers find common design structures from different assembly models and shorten the design cycle. It is an effective approach to build a knowledge library for product design that can shorten the design cycle.

Assembly sequence planning (ASP) is a crucial job during assembly process design. However, it is still difficult to reuse the existing solution to solve a new ASP problem. In particular, with the rapid development of digital technologies, the reusable assembly information of an existing solution is not concentrated in one multimedia but dispersed in multiple heterogeneous multimedia, e.g. text, three-dimensional graphics, even images and videos. This paper aims to propose a multimedia case (MC)-based reasoning framework to solve ASP by reusing the existing solution whose assembly information is dispersed in multimedia.

The proposed framework is designed with the introduction of the MC. An MC seamlessly integrates the dispersed assembly information of an existing solution. Under the proposed concept and architecture, the assembly information of an existing solution is extracted to build assembly descriptors of multimedia. Therefore, the MC is captured by organizing the assembly descriptors of corresponding multimedia.

By means of the framework proposed, it is possible to reuse the existing solution whose assembly information is dispersed in multimedia to solve ASP. Moreover, the extraction method of assembly information can flexibly parse most of the multimedia. Finally, the MC has the capability to represent the existing solution by collecting dispersed assembly information.

The proposed framework can discover the similar existing solution and avoid the potential failures confronted in the past so that the feasibility of ASP result can be improved as much as possible.

The construction industry has been criticized for not keeping up with other production industries in terms of cost efficiency, innovation, and production methods. The purpose of this paper is to contribute to the knowledge about what hampers efficiency in supplying engineer‐to‐order (ETO) joinery‐products to the construction process. The objective is to identify the main contributors to inefficiency and to define areas for innovation in improving this industry.

Case studies of the supply chain of a Swedish ETO joinery‐products supplier are carried out, and observations, semi‐structured interviews, and documents from these cases are analysed from an efficiency improvement perspective.

From a lean thinking and information modelling perspective, longer‐term procurement relations and efficient communication of information are the main areas of innovation for enhancing the efficiency of supplying ETO joinery‐products. It seems to be possible to make improvements in planning and coordination, assembly information, and spatial measuring through information modelling and spatial scanning technology. This is likely to result in an increased level of prefabrication, decreased assembly time, and increased predictability of on‐site work.

The role of supplying ETO joinery‐products is a novel research area in construction. There is a need to develop each segment of the manufacturing industry supplying construction and this paper contributes to the collective knowledge in this area. The focus is on the possibilities for innovation in the ETO joinery‐products industry and on its improved integration in the construction industry value chain in general.

The purpose of this paper is to explain a current implementation of a programmable and computational material, Logic Matter, and to describe potential applications for computational materials and self‐guided assembly.

Following an introduction, the paper describes the types of information currently found in architectural construction, then introduces Logic Matter, a building block embodying physical digital logic. Examples of structural optimization and construction scenarios are given, to demonstrate the benefits of programmable and computational physical materials for assembly.

Logic Matter demonstrates a prototype with embedded digital logic and programmability, offering new applications for automated assembly, online material analysis and physical computing.

The paper describes the existing types of architectural construction information and proposes a novel application of programmable and computational material for automated assembly.

The purpose of this paper is to propose a three-dimensional (3D) assembly model retrieval method based on assembling semantic information to address semantic mismatches, poor accuracy and low efficiency in existing 3D assembly model retrieval methods.

The paper proposes an assembly model retrieval method. First, assembly information retrieval is performed, and 3D models that conform to the design intention of the assembly are found by retrieving the code. On this basis, because there are conjugate subgraphs between attributed adjacency graphs (AAG) that have an assembly relationship, the assembly model geometric retrieval is translated into a problem of finding AAGs with a conjugate subgraph. Finally, the frequent subgraph mining method is used to retrieve AAGs with conjugate subgraphs.

The method improved the efficiency and accuracy of assembly model retrieval.

The examples illustrate the specific retrieval process and verify the feasibility and reasonability of the assembly model retrieval method in practical applications.

The assembly model retrieval method in the paper is an original method. Compared with other methods, good results were obtained.

The implied assembly constraints of a computer-aided design (CAD) model (e.g. hierarchical constraints, geometric constraints and topological constraints) represent an important basis for product assembly sequence intelligent planning. Assembly prior knowledge contains factual assembly knowledge and experience assembly knowledge, which are important factors for assembly sequence intelligent planning. This paper aims to improve monotonous assembly sequence planning for a rigid product, intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge is proposed.

A spatio-temporal semantic assembly information model is established. The internal data of the CAD model are accessed to extract spatio-temporal semantic assembly information. The knowledge system for assembly sequence intelligent planning is built using an ontology model. The assembly sequence for the sub-assembly and assembly is generated via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge. The optimal assembly sequence is achieved via a fuzzy comprehensive evaluation.

The proposed spatio-temporal semantic information model and knowledge system can simultaneously express CAD model knowledge and prior knowledge for intelligent planning of product assembly sequences. Attribute retrieval and rule reasoning of spatio-temporal semantic knowledge can be used to generate product assembly sequences.

The assembly sequence intelligent planning example of linear motor highlights the validity of intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge.

The spatio-temporal semantic information model and knowledge system are built to simultaneously express CAD model knowledge and assembly prior knowledge. The generation algorithm via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge is given for intelligent planning of product assembly sequences in this paper. The proposed method is efficient because of the small search space.

This paper aims to propose and implement an integrated augmented-reality (AR)-aided assembly environment to incorporate the interaction between real and virtual components, so that users can obtain a more immersive experience of the assembly simulation in real time and achieve better assembly design.

A component contact handling strategy is proposed to model all the possible movements of virtual components when they interact with real components. A novel assembly information management approach is proposed to access and modify the information instances dynamically corresponding to user manipulation. To support the interaction between real and virtual components, a hybrid marker-less tracking method is implemented.

A prototype system has been developed, and a case study of an automobile alternator assembly is presented. A set of tests is implemented to validate the feasibility, efficiency, accuracy and intuitiveness of the system.

The prototype system allows the users to manipulate and assemble the designed virtual components to the real components, so that the users can check for possible design errors and modify the original design in the context of their final use and in the real-world scale.

This paper proposes an integrated AR simulation and planning platform based on hybrid-tracking and ontology-based assembly information management. Component contact handling strategy based on collision detection and assembly feature surfaces mating reasoning is proposed to solve component degree of freedom.

This paper aims to propose a method to automate the tolerance analyses of mechanical assembly using STandard for the Exchange of Product model data-Application Protocol Part 242 (STEP AP 242) files derived from the 3-D computer-aided design (CAD) models.

Product manufacturing information and mating information available in ISO 10303 STEP AP242 files resulting from the 3-D CAD model of mechanical assembly are extracted. The extracted geometric attributes, geometric dimensioning and tolerancing (GD&T) and mating information are used to automatically generate assembly graph and mating edges required for the tolerance analyses of the mechanical assembly by using the matrix approach.

The feasibility of the proposed method is verified through two mechanical assembly case studies. The results of manual calculations and tolerance values computed by the automated method are very closely matching.

Tolerance analysis is an integral part of product development that directly influences the cost and performance of a product. Apart from the academic interest, the work is expected to have positive implications for the digital design and smart manufacturing industry that involve in the development of solutions for automation of design and manufacturing system functions.

The approach presented in the paper that aids the automation of tolerance analyses of mechanical assembly is an innovative application of the STEP AP 242 file. The automation of tolerance analyses would improve the productivity and efficiency of the product realization process.

The purpose of this paper is to develop a modeling and interactive operating method for virtual assembly (VA) to support assembly process generation based on interactive operation.

This paper puts forward an assembly semantic modeling method for interactive assembly and process generation after the analysis on requirements of operation process generation. Based on this semantic model, methods for semantic generation, semantic processing and assembly motion extraction from interactive operation are presented. Partial process generation of auto engine is proposed to verify the approaches in this paper.

The application shows that assembly semantic modeling and operating methods can support process generation based on VA operations.

The approaches presented in this paper improve the efficiency of assembly process, making assembly process intuitive and natural.