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Copyright of Journal of University of Anbar for Pure Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soft robots often draw inspiration from nature to navigate different environments. Although the inching motion and crawling motion of caterpillars have been widely studied in the design of soft robots, the steering motion with local bending control remains challenging. To address this challenge, we explore modular origami units which constitute building blocks for mimicking the segmented caterpillar body. Based on this concept, we report a modular soft Kresling origami crawling robot enabled by electrothermal actuation. A compact and lightweight Kresling structure is designed, fabricated, and characterized with integrated thermal bimorph actuators consisting of liquid crystal elastomer and polyimide layers. With the modular design and reprogrammable actuation, a multiunit caterpillar-inspired soft robot composed of both active units and passive units is developed for bidirectional locomotion and steering locomotion with precise curvature control. We demonstrate the modular design of the Kresling origami robot with an active robotic module picking up cargo and assembling with another robotic module to achieve a steering function. The concept of modular soft robots can provide insight into future soft robots that can grow, repair, and enhance functionality. [ABSTRACT FROM AUTHOR]

The increasing automobile repair industries (ARIs) with spray facilities have become an important volatile organic compound (VOC) pollution source in China. However, the VOC health risk assessment for long-term exposure in ARIs has not been well characterized. In this study, though sampled VOCs from 51 typical ARIs in Beijing, the relationship between emission patterns, average daily exposure concentrations (EC), and health risks was comprehensively analyzed with the health assessment method. Results showed that concentrations of 117 VOCs from the samples ranged from 68.53 to 19863.32 μg·m−3, while the ARI operator's daily VOC inhalation EC was 11.24–1460.70 μg·m−3. The organic VOC (OVOC) concentration accounted for 73.16 ~ 94.52% in the solvent-based paint workshops, while aromatics were the main VOC component in water-based paint spraying (WPS) workshops, accounting for 70.08%, respectively. And the method of inhalation exposure health risk assessment was firstly used to evaluate carcinogenicity and non-carcinogenicity risk for sprayers in ARIs. The cumulative lifetime carcinogenic risk (LCR) for 24 sampled VOCs were within acceptable ranges, while the mean hazard index (HI) for 1 year with 44 sampled VOCs was over 1. Among them, ethyl alcohol had a high carcinogenic risk in both mixed water-based paint (MP) and solvent-based paint workshops. The mean HI associated with aromatics were 2.88E − 3 and 4.30E − 3 for 1 h in MP and WPS workshops. O-ethyl toluene and acetone are VOC components that need to be paid attention to in future paint raw materials and spraying operations. Our study will provide the important references for the standard of VOC occupational exposure health limits in ARIs. [ABSTRACT FROM AUTHOR]

The object of the study: the process of determining and managing ergonomic risks at workplaces when performing professional activities on the example of truck drivers. The problem lies in uncertainty when making decisions in occupational safety and health management systems. The hypothesis of the study was the possibility of assessing ergonomic risks in the occupational safety management systems of organizations based on the identification of regularities between the load index, typical working postures when performing operations and the intensity of joint movements. An ergonomic risk assessment algorithm was developed, taking into account the load index, which includes a sequence of eleven steps, which can be conditionally divided into three groups. The first is determination of the intensity of joint movement. The second is the determination of the impact of activity and the duration of the production task. The third is determining the impact of environmental factors. An assessment of the ergonomic risk of drivers was carried out for three types of production work: driving a vehicle, replacing a damaged wheel, and repairing a car. At the same time, the ergonomic risk assessment algorithm takes into account the worker’s individual state of health and environmental factors, as well as experience and work experience. It has been established that there is a high level of ergonomic risk during car maintenance due to the highest total load index, which is 30 % higher compared to other types of work of vehicle drivers. The practical application consists in the development of a universal check list of drivers based on an algorithm to determine the ergonomic risk of workers at workplaces, which consists of 11 steps. [ABSTRACT FROM AUTHOR]

The present study develops a computerized maintenance management system (CMMS) for vehicles that aims to improve specific capabilities (competitiveness and customer service) of an automobile repair shop. The maintenance plan is supported by a five-step methodology in which the shop is assessed and the processes and techniques are adapted for preventive and corrective maintenance performed on the automobile units. Tasks and good work practices are standardized. The service offered is rearranged by developing a maintenance management software (CMMS) that is imbedded in the tasks performed at the repair shop for both preventive and corrective maintenance. As a result, the degree of facilities utilization is greater than 70% while the percentages of absenteeism, inactivity, and unproductive work are between 5 and 10%. In conclusion, implementing the maintenance management system developed here is highly efficient and is supported by technology and standardized maintenance processes. [ABSTRACT FROM AUTHOR]

The detection of carbon deposit degree is of great significance to the maintenance of automobile engine. Due to issues with poor feature aggregation, inter-class similarity, and intra-class variance in carbon deposit data with a small number of samples, model-based discriminative approaches cannot be widely implemented in the market. In order to overcome this technical barrier, the article examines the impact of DCNNs (Deep Convolutional Neural Networks) level on the recognition effect of the degree of carbon deposit, introduces a dropout structure and data enhancement strategy to lower the risk of overfitting brought on by the small dataset, and suggests a recognition method based on the kernel of dual-dimensional multiscale-multifrequency information features to enhance the differentiation characteristic. After experimental testing, the accuracy of this method is 86.9 %, the F1-score is 87.2 %, and the inference speed is 190 FPS, which can meet the practical requirements and provide basic support for the large-scale promotion of the model discrimination. [ABSTRACT FROM AUTHOR]

This article explores the relationship between DNA damage, DNA repair, and mutagenesis. It specifically focuses on the behavior of RNA polymerase (RNAP) at sites of DNA damage and its impact on gene transcription. The research, conducted using a mutagen-induced mouse tumor model and mathematical modeling, suggests that RNAP often bypasses DNA lesions during transcription and does not resume transcription at the site of stalling after DNA repair. Additionally, the article discusses a study on the genetic changes in liver tumors caused by a specific chemical treatment. Whole genome sequencing revealed that lesions not repaired before DNA replication led to mutations in the tumor cells. The study also found that highly expressed genes had fewer mutations. These findings have implications for understanding mutagenesis, DNA repair, and the development of cancer. [Extracted from the article]

We investigated the ecological validity of performance measures from a computer-based assessment tool that utilises scripted video vignettes. The intended purpose of this tool is to assess the maintenance and repair skills of automotive technician apprentices, complementing traditional hands-on assessment formats from the German journeymen's exams. We hypothesise that the ability to correctly judge repair actions shown in videos is a good predictor of the ability to perform corresponding actions in hands-on scenarios. Apprentices in the third year of vocational training carried out repairs on real cars or car systems, while experts rated their performance. After this, they worked on our computer-based tests, which utilise videos of very similar repairs. The correlation between video judgement and hands-on performance was lower than expected for most repair actions as well as for overall scores, indicating insufficient ecological validity of the test score interpretations. However, the findings are promising for developing future tests, as the results for some repair actions indicate it is generally possible to develop ecologically valid video-based items focusing on hands-on skills. We discuss the results in the light of a validation framework that combines validity evidence from different sources for the same assessment tool. Finally, we hope our findings contribute to a broader discussion about the psychometric quality of exams. [ABSTRACT FROM AUTHOR]

In a traditional industry, automotive paint repair is dominated by manual labor, which has problems such as high labor intensity, low efficiency and poor consistency. Combining the experience of manual sanding, the algorithm of generating the damaged car surface repair sanding area was designed based on the extraction of the damaged car surface contour. Firstly, the edge detection operator and convex hull algorithm were used to extract the contour of the damaged paint surface, then the convex package algorithm was used to pre-generate the contour, and then the contour was improved to generate the final car surface repair sanding area. By comparing the actual manual sanding area and the algorithm-generated sanding area, it shows that the sanding area generated by the algorithm is more accurate and meets the basic sanding requirements, which can provide a theoretical basis for the realization of automated sanding. [ABSTRACT FROM AUTHOR]

The level and distribution of Polycyclic Aromatic Hydrocarbon (PAHs) in soil, fruit, and leaf from within automobile repair workshops in Nsukka metropolis was assessed. The PAHs concentrations were evaluated using Gas Chromatography-Mass Spectrophotometer (GC-MS). The health risk was assessed using incremental life cancer risk (ILCR) and mutagenic effect and the possible sources of the PAHs were estimated by the diagnostic ratio. The results showed that the concentrations of the PAHs in soil, fruit, and leaf ranged from 0.003 to 0.564, 0.011 to 0.070, and 0.020 to 0.120 µg/kg, respectively. The mean PAHs concentration for soil, fruit, and leaf are 0.229842, 0.034059, and 0.043091 µg/kg, respectively. The TEQs were generally within the acceptable limit stipulated by Agency for Toxic Substances Disease Registry–ATSDR (100 µg/kg) for non-pollution and low toxicity. The incremental lifetime cancer risk (ILCR) for the seven prominent carcinogenic PAHS indicated that Benzo(a)pyrene and Dibenz(a,h)anthrance, being the most toxic were above the acceptable limit of 1 × 10−4 showing possible carcinogenic effects to humans with children being the most vulnerable. Although the concentration of PAHs in this study is lower than many similar cases, they have a high risk of carcinogenesis. In contrast, the Mutagenic Equivalent Quotient (MEQ) values were generally within the acceptable value. Benzo(a)pyrene and Dibenz(a,h)anthrance were the most contributors signifying possible alternation/modification of DNA in humans. The Diagnostic ratio showed that pyrogenic combustions could be the main sources of PAHs in the studied area. Therefore, it is evident that Nsukka automobile repair area is gradually being contaminated with PAHs. [ABSTRACT FROM AUTHOR]

In spite of increasing importance of servitisation for the success of automobile organisations, the factors that influence it are not well researched. In this paper, we discuss the important issue of computing service quality of an automobile organisation and put forward a graph theory-based methodology to evaluate the factors affecting the quality in the servitisation practices to propose a critical service quality index (CSQI) to measure the same. The application of the proposed methodology is demonstrated in three Indian automobile organisations. This ensures the validation of the proposed approach and also helps to evolve select key recommendations for improving servitisation quality in the Indian automobile organisation. This research advances the present body of knowledge by making three-fold contributions. First, it delivers an organised methodology for quantification of services on adoption of servitisation in an automobile manufacturer and integrates the results obtained in the form of a critical service quality index. The proposed methodology is equally beneficial for assessment and classification of a set of manufacturers. Second, it demonstrates an application of methodology for three Indian automobile organisations to develop select key recommendations which can be seen as a first attempt in the field of servitisation in the Indian context. Finally, the paper proposes a conceptual framework for addressing servitisation challenges and extends key recommendations for improving competitiveness of an automotive organisation through servitisation. [ABSTRACT FROM AUTHOR]

Manufacturing organizations are thriving for the implementation of sustainable practices during the entire lifecycle of their products. Maintenance is an indispensable activity in the lifecycle of automobiles that consumes time, energy, money, and resources. There is considerable waste generation, energy consumption, and pollution during automobile maintenance. Hence, sustainable maintenance initiatives by garages can substantially contribute to environmental protection. However, the majority of the garages in developing countries, including India, are far behind in sustainable maintenance initiatives. This paper develops a framework for the assessment and comparison of sustainable maintenance performance of automobile garages in India based on a hybrid approach. The sustainable maintenance performance attributes are identified through literature and garage surveys. The weightage of each sustainable maintenance performance attributes is established through analytic hierarchy process. The methodology of preference ranking organization method for enrichment evaluations is used for comparing and ranking various garages according to their sustainable maintenance performance. The interrelationships among sustainable maintenance performance attributes are established through decision making trial and evaluation laboratory which segregates them into cause and effect groups. The inferences would be helpful to the garage management to initiate actions for the improvement of sustainable maintenance performance and contribute to the environment benign initiatives. [ABSTRACT FROM AUTHOR]

In this study, a queue management model/software was developed for automobile repair shops. This software minimizes both waiting time of customers, and idle time of workers. The software groups all jobs done in an automobile repair shop into three sections: mechanical, electrical and air conditioning (A/C) sections. The developed software prioritizes all jobs performed in a typical automobile repair shop in terms of urgency, using the 'shortest processing time' scheduling approach. The jobs are then ranked and assigned to workers based on number of available workstations. Also, expected time of delivery of the job is estimated by the software. The software was tested using data obtained over a two weeks period and percentage reduction in waiting time was found to range between: 0.889-0.122, 0.895-0.25 and 1-0.167 for the mechanical, electrical and A/C sections respectively. In the mechanical section, servicing/replacement of piston and rings and changing/servicing of gear box were discovered to be the jobs with maximum delivery time (15 hrs) while changing of engine belt was seen as the job with the least delivery time (0.3 hrs). For the electrical section, changing of alternator, with delivery time of 3 hrs 30 mins and changing of headlamp and fuse breakage with delivery time of 0.15 hrs are the jobs with maximum and minimum delivery times respectively. For the A/C section, changing of freezer with delivery time of 10 hrs and refilling of gas with delivery time of 0.10 hrs are the maximum and minimum respectively. Implementation of this research will reduce time wastage experienced by customers, idle time at service facilities, frustration caused by unnecessary queue, and encourage allocation of resources accordingly. [ABSTRACT FROM AUTHOR]

Material selection has a decisive effect on the performance of products fabricated using hybrid additive-subtractive manufacturing (HASM). Current research is mainly focused on improving the mechanical properties of laser cladding layers (LCLs), but ignoring their subsequent machinability. To select appropriate material for repairing automobile panel dies and molds, the thermophysical properties, forming quality, friction property, and milling machinability of LCLs with different combinations of substrate and powder are comprehensively evaluated by using technique for order preference by similarity to ideal solution (TOPSIS) method. The results show that the thermophysical properties of the four powders are similar to those of their substrates. Thus, the forming quality of all LCLs is relatively good, and firm metallurgical bond is formed between the coatings and substrates. It provides a basic guarantee for the realization of HASM. On the other hand, although the forming quality and friction property of Fe-based LCLs are better than those of Ni-based coatings, their performance of machined surface quality and tool damage rate is too poor. The results indicate that it is necessary to take the subsequent machinability as an indicator of material selection in HASM. Finally, according to multi-indicator evaluation of HASM process by using TOPSIS method, Ni60 powder is determined to repair the automobile panel dies and molds. Compared to Fe60 powder, which is the most likely traditional choice when only considering the forming quality and properties of LCLs, Ni60 powder can simultaneously guarantee the performance of repaired parts and the manufacturing efficiency of HASM. [ABSTRACT FROM AUTHOR]

The increasing complexity of vehicle design, the use of new engine types and fuels, and the increasing intelligence of automobiles are making it increasingly difficult to ensure trouble-free operation. Finding faulty parts quickly and accurately is becoming increasingly difficult, as the diagnostic process requires analyzing a great amount of information. Therefore, we propose an approach based on association rules, a machine learning technique, to simplify the defect detection process. To facilitate its use in a real repair company environment, we have developed a web service that allows a repairman to simultaneously identify nodes with a high probability of failure. We have described the structure and working principles of the developed web service, as well as the procedure for its application, which resulted in the discovery of several useful non-trivial rules. We have presented several rules resulting from the use of this interactive tool, which allow repairers to detect possible defects in the relevant components, during the diagnostic process, quickly and easily. These rules are also well supported and can be used by procurement departments to make tactical decisions when selecting the most promising suppliers and manufacturers. The methodology developed allows the evaluation of the effectiveness of changes in the design and technology for the manufacture and operation of individual vehicle components, analyzing the change in the composition of parts combinations over time. [ABSTRACT FROM AUTHOR]

Automated assessment of car damage is a major challenge in the auto repair and damage assessment industries. The domain has several application areas, ranging from car assessment companies, such as car rentals and body shops, to accidental damage assessment for car insurance companies. In vehicle assessment, the damage can take many forms, from scratches, minor dents, and major dents to missing parts. Often, the assessment area has a significant level of noise, such as dirt, grease, oil, or rush, which makes accurate identification challenging. Moreover, in the repair industry, identifying a particular part is the first step in obtaining an accurate labor and part assessment, where the presence of different car models, shapes, and sizes makes the task even more challenging for a machine-learning model to perform well. To address these challenges, this study explores and applies various instance segmentation methodologies to determine the best-performing models. This study focuses on two genres of real-time instance segmentation models, namely, SipMask and YOLACT, owing to their industrial significance. These methodologies were evaluated against a previously reported car parts dataset (DSMLR) as well as an internally curated dataset extracted from local car repair workshops. The YOLACT-based part localization and segmentation method outperformed other real-time instance mechanisms with an mAP of 66.5. For the workshop repair dataset, SipMask++ reported better accuracy for object detection with a mAP of 57.0, with outcomes for A P I o U =. 50 and A P I o U =. 75 reporting 72.0 and 67.0, respectively, whereas YOLACT was observed to be a better performer for A P s with 44.0 and 2.6 for object detection and segmentation categories, respectively. [ABSTRACT FROM AUTHOR]