scholarly journals Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3520 ◽  
Author(s):  
Adrian Korodi ◽  
Denis Anitei ◽  
Alexandru Boitor ◽  
Ioan Silea
Keyword(s):  
Image Processing ◽  
Fault Detection ◽  
Experimental Model ◽  
Manufacturing Industry ◽  
Electronic Control Unit ◽  
Low Cost ◽  
Control Unit ◽  
Raspberry Pi ◽  
Automotive Manufacturing ◽  
The Impact

The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In the automotive industry, the Electronic Control Unit (ECU) manufacturing ends with complex testing, the End-of-Line (EoL) products being afterwards sent to client companies. This paper proposes an image-processing-based low-cost fault detection (IP-LC-FD) solution for the EoL ECUs, aiming for high-quality and fast detection. The IP-LC-FD solution approaches the problem of determining, on the manufacturing line, the correct mounting of the pins in the locations of each connector of the ECU module, respectively, other defects as missing or extra pins, damaged clips, or surface cracks. The IP-LC-FD system is a hardware–software structure, based on Raspberry Pi microcomputers, Pi cameras, respectively, Python and OpenCV environments. This paper presents the two main stages of the research, the experimental model, and the prototype. The rapid integration into the production line represented an important goal, meaning the accomplishment of the specific hard acceptance requirements regarding both performance and functionality. The solution was implemented and tested as an experimental model and prototype in a real industrial environment, proving excellent results.

scholarly journals IoT Based Automatic Tyre Sorting System

2019 ◽  
Vol 8 (4) ◽  
pp. 10828-10832
Keyword(s):  
Image Processing ◽  
Manufacturing Industry ◽  
Research Work ◽  
Outer Core ◽  
Raspberry Pi ◽  
Process Time ◽  
Geometrical Parameters ◽  
Outer Diameter ◽  
Sorting Process ◽  
Sorting System

Tyre segregation is one of the indispensible processes in tyre manufacturing industry. In tyre manufacturing industry various size of tyres are examined at segregation unit at a time. Till today the tyre segregation process is done manually which increases the manpower and process time. Tyre sorting is the process of segregating the tyres from different sizes. The sorting process is based on the Geometrical parameter (Inner Diameter, Outer Diameter, Outer Core button Design) of the tyre. This research work is aimed to automate the sorting process of different tyres using Image processing and IOT. This pioneering work depicts a prototype of segregation system which includes the image processing segment to categorize the type of tyres which are fitted for various vehicles. The proposed system consist of Conveyor system, Raspberry pi -3 controller, tyre collecting bin, Servo motor and Image processing camera. This system camera monitors the incoming various tyres from the conveyor, based on the geometrical parameters of the tyres they are segregated and placed in the appropriate tyre collecting bin and the same information is shared to the database through IOT. The proposed model is observed to be very efficient with its counterpart.

scholarly journals Impact of Thermal Throttling on Long-Term Visual Inference in a CPU-Based Edge Device

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2106
Author(s):  
Théo Benoit-Cattin ◽  
Delia Velasco-Montero ◽  
Jorge Fernández-Berni
Keyword(s):  
Ambient Temperature ◽  
Low Cost ◽  
Critical Role ◽  
Frame Rate ◽  
Raspberry Pi ◽  
Maximum Throughput ◽  
External Temperature ◽  
Active Cooling ◽  
The Impact

Many application scenarios of edge visual inference, e.g., robotics or environmental monitoring, eventually require long periods of continuous operation. In such periods, the processor temperature plays a critical role to keep a prescribed frame rate. Particularly, the heavy computational load of convolutional neural networks (CNNs) may lead to thermal throttling and hence performance degradation in few seconds. In this paper, we report and analyze the long-term performance of 80 different cases resulting from running five CNN models on four software frameworks and two operating systems without and with active cooling. This comprehensive study was conducted on a low-cost edge platform, namely Raspberry Pi 4B (RPi4B), under stable indoor conditions. The results show that hysteresis-based active cooling prevented thermal throttling in all cases, thereby improving the throughput up to approximately 90% versus no cooling. Interestingly, the range of fan usage during active cooling varied from 33% to 65%. Given the impact of the fan on the power consumption of the system as a whole, these results stress the importance of a suitable selection of CNN model and software components. To assess the performance in outdoor applications, we integrated an external temperature sensor with the RPi4B and conducted a set of experiments with no active cooling in a wide interval of ambient temperature, ranging from 22 °C to 36 °C. Variations up to 27.7% were measured with respect to the maximum throughput achieved in that interval. This demonstrates that ambient temperature is a critical parameter in case active cooling cannot be applied.

The Application of CAN Bus Microcontroller MC9S08DZ60 in Automotive Electronic Control Unit

2013 ◽  
Vol 694-697 ◽  
pp. 2608-2611 ◽  
Author(s):  
Yi Wang ◽  
Li Ren He
Keyword(s):  
Real Time ◽  
Software Design ◽  
Can Bus ◽  
High Reliability ◽  
Electronic Control Unit ◽  
Low Cost ◽  
Control Unit ◽  
Scientific Basis ◽  
Electronic Control ◽  
Automotive Electronic

Take the microcontroller MC9S08DZ60 which integrated CAN controller for example, the design of automotive electronic control unit was introduced, meanwhile shown the hardware structure and software design processes. This circuit has characteristics of simple hardware, low cost, high reliability, real-time. It has provided a scientific basis for the development of the CAN communication electronic control unit based on MC9S08DZ60 microprocessor.

FPGA – Raspberry pi Interface for low cost IoT based image processing

2017 ◽  
Vol 10 (4) ◽  
pp. 219
Author(s):  
Santosh Kumar ◽  
Madhu Shah ◽  
Arjun Singh
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Raspberry Pi

In-Cylinder Pressure Measurement: Requirements for On-Board Engine Control

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Fabrizio Ponti
Keyword(s):  
Data Storage ◽  
Control Strategies ◽  
Electronic Control Unit ◽  
Low Cost ◽  
Low Frequency ◽  
Control Unit ◽  
Engine Control ◽  
Cylinder Pressure ◽  
Diagnostic Strategies ◽  
Denox Catalysts

During these last years, passenger vehicles have been equipped with an increasing number of sensors, in an effort to monitor and control their behavior in terms of global performance and emissions. This, together with constantly increasing electronic control unit computing power and data storage capabilities, allowed the development of more efficient engine-vehicle control strategies. In this perspective, new sensors will be employed as soon as their use will be shown to be necessary to design new engine control and diagnostic strategies, and their cost and expected life will be compatible with on-board application. A sensor that has been largely studied in recent years is the in-cylinder pressure one: advanced engine control strategies that make use of the signal coming from such a sensor have been investigated, while reliable and low-cost sensors are being developed to survive for the vehicle life the harsh on-board environment. The signal coming from the in-cylinder pressure is, in fact, very rich in information and could be used, for example, to improve engine torque management (by directly computing the instantaneous indicated torque), to improve air∕fuel ratio control, misfire and knock detection capabilities, engine emission estimation (to be used for DeNOx catalysts purging management as an example), residual gas fraction estimation, etc. Many sensor concepts have been developed, although none seems to actually fully meet both the precision and low-cost requirements necessary for on-board application. This work deals with defining the sensor precision characteristics necessary to effectively implement the aforementioned engine control and diagnostic capabilities improvements. In particular, it will be shown that only the low-frequency signal content has to be precisely measured and is critical for certain application. In addition, the importance of a correct reference of the in-cylinder pressure signal is discussed, and a novel methodology to quickly obtain this information once the engine has been setup with a proper in-cylinder pressure sensor is discussed.

scholarly journals Development of a Resistance Spot Welding Process Using Additive Manufacturing

Metals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 555 ◽  
Author(s):  
Márcio Batista ◽  
Valdir Furlanetto ◽  
Sérgio Duarte Brandi
Keyword(s):  
Additive Manufacturing ◽  
Tensile Stress ◽  
Resistance Spot Welding ◽  
Spot Welding ◽  
Manufacturing Industry ◽  
Low Cost ◽  
Welding Process ◽  
Chemical Compositions ◽  
Automotive Manufacturing ◽  
Resistance Spot

For several decades, the electrical resistance spot welding process has been widely used in the manufacturing of sheet metal structures, especially in automotive bodies. During this period there was no significant development for this welding process. However, in recent years, in order to meet the demand for lighter, economical, and low-cost vehicles, the automotive manufacturing industry is undergoing a revolution in the use of high strength steel sheet combinations, chemical compositions, and of different thicknesses. In this context, the present work focuses on the study and development of a new resistant spot welding technology using additive manufacturing (AMSW) in zinc-coated steel sheets, used in the automotive industry. As a comparison, spot welding was also performed by the conventional resistance spot welding process (RSW). The results showed that the spot welding process using additive manufacturing (AMSW), through the optimized parameters, compared to the conventional resistance spot welding process (RSW), was 34.47% higher in relation to the shear tensile stress, as well as 28.57% higher tensile stress with a perpendicular load to the weld spot. The indentation or thermomechanical mark on the surface of the sheet was imperceptible to the visual inspection, producing a smooth face in the spot region.

scholarly journals THE IMPACT OF DIGITALIZATION ON HUMAN RESOURCE MANAGEMENT PRACTICES IN THE AUTOMOTIVE MANUFACTURING INDUSTRY

2021 ◽  
Vol 56 (5) ◽  
pp. 524-537
Author(s):  
Neeta Jayabalan ◽  
Zafir Khan Mohamed Makhbul ◽  
Sudhashini Nair Senggaravellu ◽  
Muthaloo Subramaniam ◽  
Nurliana Adliah Binti Ramly
Keyword(s):  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Manufacturing Industry ◽  
Management Practices ◽  
Industrial Revolution ◽  
Core Competencies ◽  
Automotive Manufacturing ◽  
Hrm Practices ◽  
The Impact

The advancement of digital technologies such as electronic devices, information systems, mobile or internet technologies, etc., which is presently known as the Fourth Industrial Revolution, generates real opportunities for organizations to focus their activities on core competencies and achievable goals. It was inevitable for human resource management (HRM) to adopt such an advancement that drastically influenced businesses’ work and management. Digital technology has caused the total re-evaluation and improvement of the procedures and systems concerning different capacities throughout businesses, and the HR role is not an exception. Therefore, this study aims to investigate the impact of digitalization technologies on HRM practices in the automotive manufacturing industry in Malaysia. Recruitment and selection, training and development, and performance appraisal and compensation are the main HRM practices identified as independent variables. A total of 203 respondents were selected for an online survey among employees in the automotive manufacturing industry in Pekan, Pahang. The results show a significant relationship between digitalization technologies and all human resource practices addressed in this study except compensation where the data was obtained and examined using IBM SPSS (Version 27) statistical software. The findings of the study revealed that HRM practices have a significant association with digitalization technologies and, occasionally, with the current and future needs of industrial revolution in manufacturing the industry; further studies can widen their scope to other industries in making Malaysia a developed nation holistically from political and socio-economic perspectives.

Stiffness Optimization of Control Unit of Vehicle Using Vibration Technique

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Suraj Sadaphale ◽  
C. S. Wagle ◽  
K. K. Dhande
Keyword(s):  
Electronic Control Unit ◽  
Control Unit ◽  
Current Control ◽  
Electronic Systems ◽  
Electrical System ◽  
Vehicle Engine ◽  
Vibration Technique ◽  
In The Beginning ◽  
The Impact ◽  
Engine Management

All modern automotive engines are controlled by an ECU. Engine efficiency, combustion, and emission characteristics are all affected by ECU tuning or tune-up. The electrical system in automobiles has evolved over time, and it now incorporates automatic machine control of automotive mechanics. In the beginning, a car’s electrical system consisted solely of primitive wiring technologies for supplying power to other parts of the vehicle. Engine management design specifications for the electronic control unit (ECU). Electronic systems are an unavoidable part of Engine management due to legislation requiring lower pollution, as well as the need for improved efficiency, fuel economy, and continuous diagnosis. The ECU of a TOYOTA Soluna car was used in this project for research and experimentation. ANSYS 19 software will be used to perform a modal and harmonic analysis of the current control unit. After that, different stiffener patterns will be added to improve the vibration characteristics of the ECU housing. We will finalize the stiffener pattern based on the FEA results. The FFT analyzer and the impact hammer test will be used to conduct experimental vibration testing.

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