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This paper aims to present a design methodology to enable product design for ease of assembly. It is corroborated by means of a case study. The methodology is based on standard time data. This enables quick computation of assembly time as well as comparing different design options for ease of assembly.

Component design that is easy to assemble is likely to take less time and vice versa. Assembly time is a function of product design attributes such as geometric shape, weight, center of gravity, type of material, number of fasteners and types of fasteners. The methodology uses standard data to achieve its objective. Numeric scores are developed for each design feature based on the aforementioned design attributes. This enables not only computation of assembly time for a brand new product but also comparison of two or more alternative design configurations from the point of view of ease of assembly.

The value of the system is corroborated by means of case studies of actual product designs. It is demonstrated that changing any of the underlying design attributes (such as type of fastener used, number of fasteners used, material of the component and component shape) is likely to result in changing the amount of time taken to assemble the product. The scoring system facilitates the quick computation of assembly time

The amount of time to assemble a product before the product is ever designed is facilitated by this system. Assembly time is a direct function of product design attributes. Process time is calculated using standard data, specifically, the Methods Time Measurement (MTM) system. This is accomplished by converting design features into time measurement units (TMUs). Assembly cost can then be easily computed by using assembly time as the basis. The computation of assembly time and cost is important inasmuch as its role in influencing productivity. This is of obvious value not only to the designer but the company as a whole.

The purpose of this paper is to present a new generic Petri net (PN) model based on assembly plan for assembly sequence optimization. The model aims to allow modeling the flexible assembly system (FAS) configuration, determining the optimal work in process, lead time, throughput, and utilization of each station. Moreover, it aims to show assembly features (AFs) as being useful in assembly sequence planning.

Sophisticated knowledge of AFs is used to get very few feasible assembly sequences (ASs) rather than all possible ASs for a product. A PN model is developed to find out the near optimal assembly sequence out of the sequences obtained from the AF knowledge. It is also used for design and performance evaluation of FAS. Multiple optimization criteria are used for assembly sequence optimization, keeping in view the line balancing. The PN is optimized using weighted‐WIP when the throughput is bounded by the utilization of the bottleneck machines.

The results achieved from the example show a considerable reduction in the number of feasible ASs for a product. The PN optimization gives minimum WIP corresponding to the maximum production rate. Moreover, the PN model pushes more inventories to the initial assembly phase.

The proposed PN can be easily extended for inclusion of dual kanban, where the managers may adjust the number of kanban cards as per the requirement.

Managers may use the concept of multiple AFs in order to design and operate robot assembly that will result in more efficient sequence planning. Using the PN model, the assembly manager may design, analyze, evaluate, and even optimize the layout of the FAS for minimum WIP, maximum throughput, and reduced lead time. The determination of total WIP, total number of stations in the assembly line, and the number of servers at each station may be helpful in the factory floor management. Line balancing may result in the highest efficiency and the shortest idling time along with ease of management and supervision.

This paper provides a clear insight into how a large reduction in the number of feasible ASs for a product can be obtained using the knowledge of AFs. It also presents a new PN model used for assembly sequence optimization and design and performance analysis of FAS.

The purpose of this paper is to develop an assembly modelling approach to be applied with a software package, to assist in the design and assembly of special purpose machines (SPMs).

A database of SPM elements was established, and an assembly relationships graph was created. Mating conditions were identified between the SPM elements, and their assembly constraints were extracted and implemented in SolidWorks application programming interface.

The implementation of this assembly modelling approach was validated by selecting SPM layouts as examples. A significant reduction in the assembly time was achieved compared to the traditional assembly procedure for the same examples.

This is a new application of assembly modelling that assists engineers and designers in the design and assembly processes of SPMs. This approach can also be applied to other machine tools with similar attributes.

This paper aims to consider a problem of assembly sensitivity in a multi-station assembly process. The authors focus on the assembly process of aircrafts, which includes cabins and inertial navigation system (INSs), and establish the assembly process state space model for their assembly sensitivity research.

To date, the process-related errors that cause large variations in key product characteristics remains one of the most critical research topics in assembly sensitivity analysis. This paper focuses on the unique challenges brought about by the multi-station system: a system-level model for characterizing the variation propagation in the entire process, and the necessity of describing the system response to variation inputs at both station-level and single fixture-level scales. State space representation is used to describe the propagation of variation in such a multi-station process, incorporating assembly process parameters such as fixture-locating layout at individual stations and station-to-station locating layout change.

Following the sensitivity analysis in control theory, a group of hierarchical sensitivity indices is defined and expressed in terms of the system matrices in the state space model, which are determined by the given assembly process parameters.

A case study of assembly sensitivity for a multi-station assembly process illustrates and validates the proposed methodology.

The purpose of this paper is to propose a novel method of coaxial optical precision alignment based on surface roughness and reflectiveness matching.

The micro-assembly experiment system set-up was constructed according to the principle of the coaxial optical alignment. The coaxial optical alignment error is theoretically analyzed and calculated. When the prism orthogonal alignment mechanism produces the error of 0.001°, the theoretical deviation was less than 0.87 μm and the actual experimental micro-assembly platform assembly accuracy exceeded 3 μm. A peg-in-hole precise assembly of punching pin micro-assembly experiment was done in order to validate feasibility of this method.

The results indicate that coaxial optical precision alignment could be used for the assembly of complex micro-heterogeneous system which is integrated by similar devices, such as 3D complex micro-structures, silicon micro-electro-mechanical system (MEMS) devices and non-silicon MEMS devices with flat structure.

The paper provides certain methodological guidelines for MEMS for high precision automatic assembly of complex 3D micro-structures.

The purpose of this paper is to review the automated assembly technology at the Assembly and Automation Expo. While assembly is the feature show, it combines with manufacturing of electronics, plastics and medical devices at the same venue.

In‐depth interviews with exhibitors of automated systems, system integrators as well as suppliers of related components motion elements, laser markers.

Automated assembly continues to become more flexible, modular, as well as better suited for smaller lot orders and includes more real‐time inspection capabilities.

The paper shows that new products to be assembled are driving those who provide automated assembly systems to create better solutions. These include solutions that are more cost‐effective, faster and include more quality assessment and tracking as part of the automation.

The benefits of integrated design and manufacturing systems in mid to high volume production are widely accepted. The low production volume, large component size and high complexity product domain is less well served by this technology. Examples of this kind of product are machine tools, ships, aircraft and buildings. Design for assembly techniques are a method by which design and manufacture can be integrated and aid the realization of full‐process concurrent engineering. Quantifies the significance of this product domain to the UK economy, describes the particular nature of these designs for assembly processes, reviews existing work in the field and specifies the problems encountered. Defines an industrial and academic solution programme. Proposes an integrated approach to applying design for assembly to this repetitive direct engineering domain.

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 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 study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.

By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed.

By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components.

The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.