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The purpose of this paper is to apply firework optimization algorithm to optimize multi-matching selective assembly problem with non-normal dimensional distribution.

In this paper, a multi-matching selective assembly approach based on discrete fireworks optimization (DFWO) algorithm is proposed to find the optimal combination of mating parts. The approach introduces new operator with the way of 3-opt and also uses a stochastic selection strategy, combines the discrete selective assembly problem with firework optimization algorithm properly and finds the best combination scheme of mating parts with non-normal dimensional distributions through powerful global search capability of the firework optimization algorithm.

The effects of different control parameters, including the number of initial fireworks and the coefficient controlling the total number of sparks generated by the fireworks on the evolution performance, are discussed, and a promising higher performance of the proposed selective assembly approach is verified through comparison with other selective assembly methods.

The best combination of mating parts is realized through the proposed selective assembly approach, and workers can select suitable mating parts under the guidance of the combination to increase the assembly efficiency and reduce the amount of surplus parts.

A DFWO algorithm is first designed to combine with multi-matching selective assembly method. For the case of an assembly product, the specific mapping rule and key technologies of DFWO algorithm are proposed.

Dimensional quality of sheet metal assemblies is an important factor for the final product. However, the part tolerance is not easily controlled because of the spring back deformation during the stamping process. Selective assembly is a means to decrease assembly tolerance of the assembly from low-precision components. Therefore, the purpose of this paper is to propose a fully efficient method of selective assembly optimization based on an improved genetic algorithm for optimization toolbox (IGAOT) in MATLAB.

The method of influence coefficient is first applied to calculate the assembly variation of sheet metal components since the traditional rigid assembly variation model cannot be used due to welding deformation. Afterwards, the IGAOT is proposed to generate optimal selective groups, which consists of advantages of genetic algorithm for optimization toolbox (GAOT) and simulated annealing.

The cases of two simple planes and the tail lamp bracket assembly are used to illustrate the flowchart of optimizing combinations of selective groups. These cases prove that the proposed IGAOT has better precision than that of GAOT with the same parameters for selective assembly.

The research objective of this paper is to evaluate the changes from rigid bodies to sheet metal parts which are very complex for selective assembly. The method of IGAOT was proposed to the selected groups which has better precision than that of current optimization algorithms.

The performance of technical institutions in India is reflected through the level of campus placements. It is vital for them to have efficient, effective and robust placement policies. Selective assembly is a technique used in manufacturing industry in improving the quality of assemblies from relatively low-quality components. The purpose of this paper is to develop a methodology using selective assembly approach to improve the quality of placements of technical institutions in India.

The paper presents a conceptual model for campus placement process by integrating Selective Assembly, Taguchi’s quality loss function (QLF) and analytic network process (ANP). The data used in the study was taken through surveys and expert opinions. In this paper, for “Selective Assembly” the terminology, “Selective Recruitment” has been used at appropriate places in the context of technical education.

Selective matching of students’ skills done through ANP minimizes the total loss in terms of opportunity cost. Taguchi’s QLF concept was used to evaluate the total loss, in terms of opportunity cost, and to validate the superiority of selective assembly technique over the conventional selection process.

The paper outlines measures that can help policy makers to successfully implement the suggested methodology to improve the quality of placements.

The application of selective recruitment in the campus placement process is a unique feature in the area of technical education in India. The role of ANP in selective recruitment and assessment of the process through Taguchi’s QLF, illustrate the importance of integrated approach adopted in the selection process.

To design a flexible integrated robotic assembly and rework (remanufacturing) cell for assembly, selective assembly and rework of advanced surface mount components (SMCs) using the generic methodology developed in this paper.

Manual rework procedures are investigated for all advanced SMCs. General and specific component‐related rework considerations are obtained and necessary tooling candidates for automation are determined. This is followed by determination of the specific automated rework procedure and selection of suitable tooling for automated robotic rework and generation and evaluation of design concepts.

The developed methodology, which considers the reflow tool at the centre of the development process, has worked well in designing a flexible integrated robotic assembly and rework cell.

This study identified the rework requirements for advanced SMCs, the essential features for rework reflow tools, criteria for comparing reflow tools, and a generic procedure for design and concept selection.

It provides valuable knowledge for designers of flexible integrated robotic assembly and rework cells for assembly, selective assembly and rework of advanced SMCs.

The purpose of this paper is to propose an assembly coordination modelling approach based on measured data for assembly quality control of multi-constrained objects in aircraft assembly. This approach aims to establish a high-precision digital mirror of physical assembly system in the virtual environment, with which the assembly process in the virtual environment can be performed synchronously with that in the physical world.

This paper presents a realistic geometrical representation model based on measured point cloud, as well as the multiple constraints modelling methods for local and global constraints with the proposed representation model. For the assembly target optimization, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, where the particle swarm optimization and simulated annealing algorithm are combined to calculate the optimal solutions.

As shown in the validation results, the minimum easiness value for easiness model in global optimization is 3.01, while the best value for weighting model by adjusting weights for more than 10 times is 1.94. The results verify that the proposed coordination modelling approach is effective to the assembly of multi-constrained objects, and the optimization model has an obvious advantage over the traditional weighting method.

This paper provides a new idea for the fine control of assembly quality of non-ideal components by introducing the measured data into the on-line assembly process. Besides, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, which overcomes the problem of traditional weighting model wherein the weightings are difficult to determine.

The generic design environment for a flexible printed‐circuit board assemblies (PCBA) remanufacturing cell contains four interrelated complex design domains. Mechanical design domains are really complex and the use of well‐proven mechanical product design methodologies does not help the designer. Hence, this paper aims to develop a generic systematic design methodology for a flexible PCBA remanufacturing cell.

The study investigates the use of conventional mechanical product design techniques for the design of a flexible PCBA rework (remanufacturing) cell. It indicates problems and the weaknesses when conventional product design techniques are used for the development of flexible manufacturing systems (FMS). It then provides a new systematic mechanical design methodology for designing a flexible PCBA rework (remanufacturing) cell. The design methodology is intended to be generic in order to apply successfully to any FMS design.

Conventional product design methodology cannot be used directly for the design of a flexible PCBA remanufacturing cell. Hence, two design methodologies were developed: the generic FMS mechanical design methodology and a specific FMS design methodology for a PCBA rework cell. The first one was developed based on the tasks of the conventional product design process integrated with new design tools. The generic design methodology was then extended to obtain the second methodology for a PCBA rework cell design. Both of the methodologies were applied to a flexible PCBA rework cell design problem. Both design methodologies eliminated unusable design solutions at the early design stages of the conceptual design process and made the design process easier.

The generic and specific design methodologies provide a better design environment, even for less specialized FMS designers.

The design methodologies may help for the commercialization of a flexible PCBA remanufacturing cell that may be used for SM rework and assembly.

Describes how BMW is implementing data matrix technology to trace and track major engine components.

Describes the major production line hardware components of a new system that is being installed at the company's Hams Hall, UK engine plant that will be used in conjunction with Tecnomatix's XFactory intelligent software to provide a comprehensive database both for the purposes of production control as well as for use in service.

The basic hardware elements of the data matrix system have already been proven out at Hams Hall using RVSI's HawkEye 1510 cutting‐edge cameras and data matrix marking machines supplied by Technifor Ltd of Leamington Spa. Technifor, also supplied the 2D data matrix readers and verifiers from RVSI in Nashua, New Hampshire, USA. The XFactory software was installed in the last month of 2004.

Engineers at BMW plan to expand the technology to enable them to use it for selective machining of cylinder heads for various types of engine. Also, as component suppliers to BMW also adopt the technology, data matrix tracking will be used for a large variety of engine components for use in assembly. It also has implications during CMM inspection to quickly identify which machining operations might be faulty.

Data matrix technology offers a low‐cost approach to the tracking and tracing of complex major engine components during both machining and assembly.

BMW claims it is the first automotive engine supplier in the UK to use data matrix technology to track and trace components.

The DEA PRAGMA A3000 robot can be used to perform a quality control function which can be integrated into component manipulation and assembly functions. The authors discuss some of the advantages of performing these functions with the same computer arm and under the same computer supervision.

The purpose of this paper is to explore how rising technologies from Industry 4.0 can be integrated with circular economy (CE) practices to establish a business model that reuses and recycles wasted material such as scrap metal or e-waste.

The qualitative research method was deployed in three stages. Stage 1 was a literature review of concepts, successful factors and barriers related to the transition towards a CE along with sustainable supply chain management, smart production systems and additive manufacturing (AM). Stage 2 comprised a conceptual framework to integrate and evaluate the synergistic potential among these concepts. Finally, stage 3 validated the proposed model by collecting rich qualitative data based on semi-structured interviews with managers, researchers and professors of operations management to gather insightful and relevant information.

The outcome of the study is the recommendation of a circular model to reuse scrap electronic devices, integrating web technologies, reverse logistics and AM to support CE practices. Results suggest a positive influence from improving business sustainability by reinserting waste into the supply chain to manufacture products on demand.

The impact of reusing wasted materials to manufacture new products is relevant to minimising resource consumption and negative environmental impacts. Furthermore, it avoids hazardous materials ending up in landfills or in the oceans, seriously threatening life in ecosystems. In addition, reuse of wasted material enables the development of local business networks that generate jobs and improve economic performance.

First, the impact of reusing materials to manufacture new products minimises resource consumption and negative environmental impacts. The circular model also encourages keeping hazardous materials that seriously threaten life in ecosystems out of landfills and oceans. For this study, it was found that most urban waste is plastic and cast iron, leaving room for improvement in increasing recycling of scrap metal and similar materials. Second, the circular business model promotes a culture of reusing and recycling and motivates the development of collection and processing techniques for urban waste through the use of three-dimensional (3D) printing technologies and Industry 4.0. In this way, the involved stakeholders are focused on the technical parts of recycling and can be better dedicated to research, development and innovation because many of the processes will be automated.

The purpose of this study was to explore how Industry 4.0 technologies are integrated with CE practices. This allows for the proposal of a circular business model for recycling waste and delivering new products, significantly reducing resource consumption and optimising natural resources. In a first stage, the circular business model can be used to recycle electronic scrap, with the proposed integration of web technologies, reverse logistics and AM as a technological platform to support the model. These have several environmental, sociotechnical and economic implications for society.

The sociotechnical aspects are directly impacted by the circular smart production system (CSPS) management model, since it creates a new culture of reuse and recycling techniques for urban waste using 3D printing technologies, as well as Industry 4.0 concepts to increase production on demand and automate manufacturing processes. The tendency of the CSPS model is to contribute to deployment CE in the manufacture of new products or parts with AM approaches, generating a new path of supply and demand for society.

An optical character recognition system is helping with the automatic assembly of automotive parts at Rover's Longbridge plant.