International Journal of Mechatronics and Manufacturing Systems (4 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.
Automatic Alignment and Location of Multiple Fiducial Marks
by Chuen-Horng Lin, Chih-Chin Wen, Jr-Wei Chen
Abstract: This paper proposes a method for the automatic alignment of reference fiducial marks (RFM) on light-emitting diode (LED) wafer images, and for locating the position of RFMs on LED wafer images, liquid crystal display (LCD) images, hand-held electronic device (HED) images, LCD cross images and LED square cross images.
This paper proposes methods for the alignment and location of fiducial marks (FM) on two types of FM images. FM images of the first type include LED wafer images, LCD images and HED images. Among these, in this paper, FMs are identified by alignment using RFM. FM images of the second type include LCD cross images and LED square cross images. For these images, the cross points and angles between lines are captured by alignment. In addition, this paper proposes the artificial measurement method (ArtTMM) and the mechanical measurement method (MeaMM) in order to make mechanical positioning-related decisions. To validate the properties and the robustness of the proposed methods, MeaMM is used for the HED image, and ArtMM is used for other images.
The automatic RFM alignment method for the LED wafer images achieves effective alignment of FMs on the upper layer, while FMs on lower layers enable simple RFM user selection. RFMs on the LCD and HED images are selected by artificial means. The results achieved by the proposed matching, alignment methods are compared with those achieved by manual image matching in order to evaluate the accuracy and performance of the alignment methods. Computer image processing skills, appropriate CCD equipment, quantity, image capture technology, and glazing mode are used to develop high speed, high precision, and high stability automatic positioning technology in this paper.
Keywords: fiducial mark; reference fiducial marks; automatic detection; automatic location.
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.