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International Journal of Mechatronics and Manufacturing Systems
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International Journal of Mechatronics and Manufacturing Systems (3 papers in press)
Hardware and Software Complex and a Device for Setting Optimal Parameters of the Unit Injector Operation in Diesel Engines by Ildar Gabitov, Samat Insafuddinov, Nail Yunusbaev, Timur Farhutdinov, Albert Sharafeev, Farid Abdrazakov, Filyus Safin, Elmir Gaysin, Ural Makhiyanov Abstract: The purpose of this study is to develop a device for setting optimal parameters of a unit injector operation in diesel engines and to justify its design. The other goal is to create a hardware and software complex with a function of modernizing the adjustment rigs. The study analyzes factors that affect the law of fuel supply in the unit injectors. Findings from this analysis base the calculation methods and the regulation parameters of unit injectors. The adjustment parameters of the fuel supply system (cyclic design in particular) are calculated with regard to the injection chamber pressure using a the suggested hardware and software complex. Keywords: fuel system; unit injector; diesel engine; injection; indication; gas pressure; compression; expansion; simulation of injection.
Special Issue on: Advancements in Mechatronics and Manufacturing Propelling Industry 4.0
An Investigation of Acceptance and E-Readiness for the Application of Virtual Reality and Augmented Reality Technologies to Maintenance Training in the Manufacturing Industry by Helen Scott, David Baglee, Roger O’Brien, Rita Potts Abstract: Virtual Reality (VR) and Augmented Reality (AR) technologies offer new ways of providing training in manufacturing maintenance. The adoption of modern maintenance training practices has the potential to create efficiencies in terms of cost and time to train, while enhancing the quality of learning and maintenance outputs. However, in order to utilise the potential improvements that VR and AR offer in a manufacturing maintenance context, it is first important to understand the specific factors associated with VR and AR readiness and user requirement. The paper will firstly describe the results from a number of interviews conducted within a range of manufacturing companies in the North East of England to establish the state of e-technology readiness and acceptance, with specific emphasis on VR and AR applications. The results will identify how VR and AR might be utilised, relative to the companys needs. Secondly, a new model for maintenance training utilising VR/AR technologies will be described, based upon the initial findings and analyses combining cognitive behavioural models, real world data, and learning theory. Keywords: Virtual Reality (VR); Augmented Reality (AR); Manufacturing Maintenance; Maintenance Training; Technology Readiness; Technology Acceptance; Cognitive Behavioural Models.
Robot-assisted Painting System for Bolt-Nut Pairs by Ran Zhao, Kaiqi Yan, Otto J. Bakker, Svetan M. Ratchev Abstract: To improve line performance and remove unnecessary low-skilled labour, it is essential automate some of the menial work as well as to have a smart assembly line where human workers can closely collaborate with robots carrying out those tedious tasks. The aim of this paper is to develop an automated bolt-nut pair painting system for a small parts assembly line. Bolt-nut pairs painting of aerostructures, in particular legacy products, relies heavily on the skill or rather craftsmanship of the human operator. This process is time-consuming while automated operations with industrial robots can be a more efficient solution. Spray painting robots have been widely used in industry, however, they are not suitable for painting bolt-nut pairs individually because it will cause a significant waste of materials. Thus, it is essential to develop proper tools and automated methods to replace menial work in order to reduce the cost and improve product quality. In this paper, a low-cost and flexible solution for automated bolt-nut pair painting using a painting dabber and machine vision system is proposed. ASense 2 camera is used to capture the 3D model of the parts, and an ABB industrial robot YuMi is programmed to implement the painting automatically. A specific nozzle for the dabber is designed to apply paint on bolt-nut pairs. The results shows that the location of every bolt-nut pair is found successfully, and the accuracy of the normal vectors is enough for robot-assisted painting work. Keywords: Automated bolt-nut painting; Machine vision; Robotics.