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Examines the conceptual design of robotic assembly systems in conjunction with the analysis and optimization of the product and process design. Explains how an integral assembly model is utilised to study the relationships between assembly variables which play a role in each stage of the design process. Outlines the characteristics and benefits of the concentric design process and explains the total productivity concept. Concludes that the integral assembly model, which underlies the concentric design process, provides the opportunity to store product, process and system data and can therefore be considered as a reference model for product development and process planning as well as for the design and analysis of assembly systems.

The development of reconfigurable modular production systems is one of the crucial factors for manufacturers to sustain their competitive advantage in areas such as precision assembly. To ensure the effective and cost efficient configuration and successive reconfigurations it is of critical importance to involve all stakeholders in the decision‐making process. The reported research is targeting the development of an integrated Web‐enabled decision‐making environment that supports some of the key assembly system engineering stages from user requirement specification to system implementation. The focus is on the design of assembly workstations based on detailed process requirements with a target of developing highly efficient and cost‐effective solutions. The paper presents an application framework for collaborative distributed design supported by domain ontologies and is illustrated using an industrial case study.

High precision assembly processes using industrial robots require the process parameters to be tuned to achieve desired performance such as cycle time and first time through rate. Some researchers proposed methods such as design-of-experiments (DOE) to obtain optimal parameters. However, these methods only discuss how to find the optimal parameters if the part and/or workpiece location errors are in a certain range. In real assembly processes, the part and/or workpiece location errors could be different from batch to batch. Therefore, the existing methods have some limitations. This paper aims to improve the process parameter optimization method for complex robotic assembly process.

In this paper, the parameter optimization process based on DOE with different part and/or workpiece location errors is investigated. An online parameter optimization method is also proposed.

Experimental results demonstrate that the optimal parameters for different initial conditions are different and larger initial part and/or workpiece location errors will cause longer cycle time. Therefore, to improve the assembly process performance, the initial part and/or workpiece location errors should be compensated first, and the optimal parameters in production should be changed once the initial tool position is compensated. Experimental results show that the proposed method is very promising in reducing the cycle time in assembly processes.

The proposed method is practical without any limitation.

The proposed technique is implemented and tested using a real industrial application, a valve body assembly process. Hence, the developed method can be directly implemented in production.

This paper provides a technique to improve the assembly efficiency by compensating the initial part location errors. An online parameter optimization method is also proposed to automatically perform the parameter optimization process without human intervention. Compared with the results using other methods, the proposed technology can greatly reduce the assembly cycle time.

The purpose of this paper is to demonstrate the impact of the component assemblies redesign on the material handling costs associated with the facility layout and also, on the productivity of the assembly process. Component assemblies are the sub‐assemblies that are incorporated into the manufactured house as it progresses on the assembly line.

Floor assembly is used as an example to demonstrate the impact of the component assembly redesign process. A step‐by‐step process of assembling a floor in the case study factory is described and changes to the process are proposed. The existing and redesigned floor assemblies are analyzed using the factory layout analysis models and the production simulation models.

The proposed redesign resulted in a small savings of less than 1 per cent in the material handling costs and a substantial savings of around 20 per cent in the production time.

The work described in this paper is based on the existing floor assembly process in a case study factory. Due to the practical limitations, material handling routes and production activities associated with the redesigned assemblies were estimated. The results from this research show that redesign of component assemblies can provide potential avenues of savings for the manufactured housing industry. Such analysis can be performed for any component assembly individually or in combination with other assemblies in order to realize potential savings with relatively minor changes.

Production‐related research in manufactured housing has traditionally focused on either improving the facility layout or the assembly line process but not the combined impact of these two aspects. This paper presents a possible approach to investigating the combined impact by analyzing the impact of redesigned floor assembly.

Electrical defects cover an important part of assembly defects and strongly affect the vehicle system performance. Almost 40% of assembly defects are classified as human errors and electrical connection failures represent a significant part of them. Humans still remain a cost-effective solution for the flexible manufacturing systems with increasing product complexity. So, understanding human behaviors is still a challenging task. The purpose of this study is to define, prioritize and validate the critical factors for the complexity of electrical connector plugin process.

The critical variables were defined by the expert team members. The required number of measurements and variables were revised resulting preliminary analysis of binary logistic regression. After the revision of measurement plan, the list of critical input variables and the mathematical model were defined. The model has been validated by the fitted values of the residuals (FITS analysis).

To the best of the authors’ knowledge, this is one of the limited studies, which defines the critical factors for electrical connection process complexity. Female connector harness length, connector width/height/length differences, operator sense of correct connector matching and ergonomy were defined as the factors with the highest impact on the failure occurrence. The obtained regression equation strongly correlates the failure probability.

The obtained mathematical model can be used in new model development processes both for the product and assembly process design (ergonomy, accessibility and lay-out).

The obtained risk factors demonstrated a strong correlation with assembly process complexity and failure rates. The output of this study would be used as an important guide for process (assembly line ergonomy, accessibility and lay-out) and product design in new model development and assembly ramp-up phases.

Driven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality control methods play an essential role in the quality improvement of assembly products. This paper aims to review the development of data-driven modeling methods for process monitoring and fault diagnosis in multi-station assembly systems. Furthermore, the authors discuss the applications of the methods proposed and present suggestions for future studies in data mining for quality control in product assembly.

This paper provides an outline of data-driven process monitoring and fault diagnosis methods for reduction in variation. The development of statistical process monitoring techniques and diagnosis methods, such as pattern matching, estimation-based analysis and artificial intelligence-based diagnostics, is introduced.

A classification structure for data-driven process control techniques and the limitations of their applications in multi-station assembly processes are discussed. From the perspective of the engineering requirements of real, dynamic, nonlinear and uncertain assembly systems, future trends in sensing system location, data mining and data fusion techniques for variation reduction are suggested.

This paper reveals the development of process monitoring and fault diagnosis techniques, and their applications in variation reduction in multi-station assembly.

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.

This study aims to deliver an approach of how lightweight robot systems can be used to automate manual processes for higher efficiency, increased process capability and enhanced ergonomics. As a use case, a new collaborative testing system for an automated water leak test was designed using an image processing system utilized by the robot.

The “water leak test” in an automotive final assembly line is often a significant cost factor due to its labour-intensive nature. This is particularly the case for premium car manufacturers as each vehicle is watered and manually inspected for leakage. This paper delivers an approach that optimizes the efficiency and capability of the test process by using a new automated in-line inspection system whereby thermographic images are taken by a lightweight robot system and then processed to locate the leak. Such optimization allows the collaboration of robots and manual labour, which in turn enhances the capability of the process station.

This paper examines the development of a new application for lightweight robotic systems and provides a suitable process whereby the system was optimized regarding technical, ergonomic and safety-related aspects.

A new automated testing process in combination with a processing algorithm was developed. A modular system suitable for the integration of human–robot collaboration into the assembly line is presented as well.

To optimize and validate the system, it was set up in a true to reality model factory and brought to a prototypical status. Several original equipment manufacturers showed great interest in the system. Feasibility studies for a practical implementation are running at the moment.

The direct human–robot collaboration allows humans and robots to share the same workspace without strict separation measures, which is a great advantage compared with traditional industrial robots. The workers benefit from a more ergonomic workflow and are relieved from unpleasant, repetitive and burdensome tasks.

A lightweight robotic system was implemented in a continuous assembly line as a new area of application for these systems. The automated water leak test gives a practical example of how to enrich the assembly and commissioning lines, which are currently dominated by manual labour, with new technologies. This is necessary to reach a higher efficiency and process capability while maintaining a higher flexibility potential than fully automated systems.

Manufacturing errors, which will propagate along the assembly process, are inevitable and difficult to analyze for complex products, such as aircraft. To realize the goal of precise assembly for an aircraft, with revealing the nonlinear transfer mechanism of assembly error, a set of analytical methods with response to the assembly error propagation process are developed. The purpose of this study is to solve the error problems by modeling and constructing the coordination dimension chain to control the consistency of accumulated assembly errors for different assemblies.

First, with the modeling of basic error sources, mutual interaction relationship of matting error and deformation error is analyzed, and influence matrix is formed. Second, by defining coordination datum transformation process, practical establishing error of assembly coordinate system is studied, and the position of assembly features is modified with actual relocation error considering datum changing. Third, considering the progressive assembly process, error propagation for a single assembly station and multi assembly stations is precisely modeled to gain coordination error chain for different assemblies, and the final coordination error is optimized by controlling the direction and value of accumulated error range.

Based on the proposed methodology, coordination error chain, which has a direct influence on the property of stealthy and reliability for modern aircrafts, is successfully constructed for the assembly work of the jointing between leading edge flap component and wing component at different assembly stations.

Precise assembly work at different assembly stations is completed to verify methodology’s feasibility. With analyzing the main comprised error items and some optimized solutions, benefit results for the practical engineering application showing that the maximum value of the practical flush of the profiles between the two components is only 0.681 mm, the minimum value is only 0.021 mm, and the average flush of the entire wing component is 0.358 mm, which are in accordance with theoretical calculation results and can successfully fit the assembly requirement. The potential user can be the engineers for manufacturing the complex products.

To identify operations and logistics issues which are critical for the operational performance in modular assembly processes.

Based on case studies of Volvo Cars, Toyota, and Saab, the paper identifies operations and logistics issues that are critical for the operational performance of modular assembly processes. The issues are used for extending our understanding of the design and operation of modular assembly processes.

The issues identified concern production planning, deviation handling, assembly flow balance, small unit disadvantages, and module flow control. They reveal that a modular assembly process design brings structural disadvantages related to the dispersion of activities and resource needs. The issues also demonstrate the need for extensive coordination across the interfaces of the decoupled parts of the process.

The findings will mainly be relevant for firms that design and produce complex products involving several technologies and that use company‐specific modules as is the case in the automotive industry, for instance.

Operations and logistics managers may use the findings in order to design and operate modular assembly processes, provide input to the design of modular products, analyze operations and logistics issues before the firm decides to go modular, or not.

Complements existing research on modular assembly processes by outlining structural disadvantages and explaining the need for extensive coordination in such processes.