Tire Manufacturing Research Articles

Perencanaan Perawatan Mesin Building Dengan Metode Reliability Centered Maintenance (RCM)

PT. Bridgestone Tire Indonesia is a tire manufacturing company. Machines that work continuously and lack of stock availability of machine spare parts cause damage and increase maintenance costs. To reduce the occurrence of damage and increase maintenance costs, it is necessary to have an optimal maintenance policy so that the machine can operate well. To overcome the problems in this research using the Reliability Centered Maintenance (RCM) method, the first step is determining the critical components on the machine, preparing the FMEA table based on the function data of the components and maintenance reports and calculating the Risk Priority Number (RPN), then calculating the MTTF and MTTR to determine maintenance and repair intervals and find optimal total maintenance costs. Machine building has the highest frequency of downtime so this research will focus on machine building components. The results of data processing show that the highest frequency of machine damage and total downtime is the cause of hose component failure due to poor hose quality and seal components becoming worn, causing increased frequency of damage, downtime and maintenance costs. Based on maintenance cost calculations using the RCM method, hose and seal components experienced a decrease in costs, namely hose components by 55.13% and seal components by 25.45%. The proposed building machine maintenance for hose and seal components in particular is to carry out scheduled tasks, scheduled exhaust tasks, and default actions with the task category of finding failures and results for maintenance time intervals for hose components of 280.81 hours and for seal components of 134.08 hours.

ARTIFICIAL INTELLIGENCE APPLIED TO QUALITY DEFECTS CLASSIFICATION FOR TYRES

The manufacture of radial tires is complex, and for this reason some defects inevitably end up appearing in the production process. Currently the commonly used defect detection is manual detection, among these techniques are ultrasound testing, thermal detection, X-ray detection, digital holography, among others. The X-ray or technical radiography allows the analysis of all the internal components of the tire, such as the bead structure and the different layers of rubber and cords, whether metallic or textile. The task of detecting defects using X-ray images is done manually, which causes loss of time and costs for the company. Furthermore, it is a subjective, inefficient, time-consuming and even biased process as it requires a high level of concentration and focus. The objective of this work is the digitization of the conventional process of analysis of quality failures in metallic radial tires using algorithms developed with Artificial Intelligence resources, capable of identifying and classifying defects present in X-Ray images. This work presents a brief introduction about what the tire is, as well as the development of the proposed algorithm, using classic image segmentation techniques with a Computer Vision library and two different convolutional neural network structures. Through the comparison, it was verified that the algorithm based on U-Net obtained more relevant results, however, the algorithm based on Mask R-CNN was also promising and could be useful in new works, with a larger database and different settings parameters.

Environmental Impact Prediction of a New Tire Vulcanization Activator.

Zinc oxide (ZnO) is the most common curing activator used to manufacture tires. To minimize environmental impacts by decreasing the zinc content and rolling resistance of tires, ZnO nanoparticles (NPs) anchored on SiO2 NPs (ZnO@SiO2) are currently under development as new activators at the pilot scale. Here, we applied prospective life cycle assessment to predict the impacts on human health, ecosystem quality, and resource scarcity of synthesizing ZnO@SiO2 for the production of passenger car tires at an industrial scale. We found that the life cycle impacts of the synthesis are expected to decrease by 89 to 96% between the pilot and industrial scale. The largest contributors to the synthesis of ZnO@SiO2 were electricity consumption and waste treatment of the solvent. Using the new activator for tire production led to potential reductions of 9 to 12% in life cycle impacts compared to tires that are currently in use. Those reductions were due to the expected decrease in rolling resistance, leading to lower fuel consumption, which outweighed the additional environmental impacts of the synthesis, as well as the potential decrease in lifetime. Our work highlights an opportunity for manufacturers to mitigate their impacts over the full life cycle of the tire.

The influence of palm oil-derived plasticizers and lubricants on the rheological and mechanical properties of styrene butadiene rubber

Researchers have recently focused on green processing aids made from plants and vegetables to avoid the high concentration of polycyclic aromatic hydrocarbons (PAHs) from petroleum-based processing oils, which is hazardous to human health. This paper focuses on the effect of lubricants and plasticisers produced from palm oil on the rheological, mechanical and thermal aging properties of styrene-butadiene rubber (SBR). These lubricants and plasticisers are known as glycerol trioleate (GTO), n-butyl stearate (NBS), ethylene bis-steramide (EBS), ethylene bis-oleamide (EBO), pentaerythritol tetrastearate (PETS) and stearyl stearate. The abrasion performance, visual inspection appearance, and cure characteristics of the lubricants and plasticisers on SBR were examined and compared to processing oil-treated distillate aromatic extract (TDAE), paraffin wax, microcrystalline wax, polyethylene (PE) wax, epoxidised soybean oil (ESBO), and stearic acid. It discovered that rubber compounds based on GTO, stearic acid, and EBS exhibited better abrasion resistance and cure properties than rubber compounds based on processing oil. These samples were selected and subjected to mechanical properties, thermal aging effects analysis and comparison with processing oil. Tensile strength shows that SBR with EBS (22.49 MPa) and EBS with GTO (EBS/GTO; 21.25 MPa) are closely similar to SBR compounds with processing oil (21.02 MPa). The findings imply that EBS and EBS/GTO, green plasticisers and lubricants, are viable alternatives to petroleum-based processing oils while being cost-effective for tire production.

Health Risk Assessment from Exposure to Ambient Volatile Organic Compounds (VOCs) at a Truck Tire Factory in the Yangtze River Delta, China

Occupational health risk assessments of exposure to VOCs still need to be extensively studied to improve the safety standards in the industry. Based on the monitoring of organic pollutants at various workstations in a truck tire factory in Jiangsu Province, both semi-quantitative and quantitative health risk assessment methods were employed to assess health risk levels. The findings indicated that VOCs were categorized into five classes, which included alkanes, aromatics, halocarbons, carbon disulfide, and oxygenated volatile organic compounds (OVOCs). The highest concentration of total volatile organic compounds (TVOCs) was found in shaping workshop; alkanes were the most abundant class (74.2%), followed by aromatics (24.02%) and OVOCs (1.96%). Although the results of the semi-quantitative risk assessment showed that most of the organic compounds had low R values, various kinds of VOCs were detected; particularly, many harmful organic compounds (such as toluene, ethyl benzene) were detected in all the sampling sites. The quantitative risk in the calendering and vulcanizing workshop exceeded the acceptable level; both the carcinogenic risk of ethylbenzene in the tire-strip storage room, and trichloroethylene and perchloroethylene in the calendering workshop were unacceptable. Thus, the calendering and vulcanizing processes in rubber tire manufacturing should be priority-controlled processes.

Anomaly Detection of Tire Tiny Text: Mechanism and Method

Due to the variety of tire specifications and poor contrast, it is difficult for ordinary 2D vision-based methods to accurately and autonomously detect anomalies in the tire text embossed on the tire sidewalls. In this paper, a 3D vision-based autonomous scanning mechanism and method is proposed, including three core components: a three-degree-of-freedom (3-DoF) robotic arm, a high-precision turntable and a composite vision probe. Based on the designed vision probe, the mechanism can autonomously scan the tire sidewall through a series of optimal viewpoints to obtain high-quality tire images even in the absence of tire CAD models. To obtain the optimal viewpoints, an information-driven viewpoint planning method is proposed. Combined with the real-time viewpoint adjustment strategy, the viewpoint of the vision probe is dynamically fine-tuned, which can effectively balance the scanning precision and motion cost. In the text anomaly detection phase, a three-stage tire text anomaly detection method based on deep learning and statistics strategy is proposed, which can accurately detect and recognize tire text, identify sub-mold categories, and judge text anomalies. Experimental results show that the proposed mechanism and method perform well in terms of accuracy ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&gt;$</tex-math> </inline-formula> 96%) and efficiency (time per lap for a tire is less than 9 s); it shows that the proposed mechanism and method have certain industrial application value and can be applied to tire quality inspection of on-line production. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Tire text may be incorrectly embossed during tire manufacturing. Due to the wide variety of tire specifications, poor contrast, and thin text strokes, it is difficult to detect abnormal tire text. In this paper, a 3D vision-based mechanism and method is developed to address this issue. Using a specially designed composite vision probe and scanning method, the mechanism can observe tiny text information on tires of different specifications from multiple angles and directions. By using our tire text anomaly detection method based deep learning and statistics strategy, the mechanism can accurately and robustly detect the region and content of abnormal text. The mechanism is efficient (with a detection time of less than 9 s per lap for one tire) and accurate ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&gt;$</tex-math> </inline-formula> 96%), indicating that it has great potential in the first inspection or quality inspection step of tire manufacturing in industrial scenarios.

STUDY OF CHANNEL OPTIMIZATION OF G TYRE COMPANY IN THE NEW RETAIL FORMAT

G Tire Company, a global leader in tire manufacturing, rapidly expanded its offline retail network upon entering the Chinese market. However, traditional offline retail faces challenges with the emergence of “new retail,” which integrates the internet with physical stores. Rising “new retail” firms like TuHu have impacted G Tire's traditional channels, prompting a need for a “new retail” transformation.&#x0D; This paper reviews literature on “new retail” and the tire industry, analyzing the industry’s development and transformation. Based on research and distribution channel theory, a four-element model for “new retail” channel analysis is proposed. The surveys and analysis revealed issues such as e-commerce impact, dense urban channels, and a lack of brand diversity due to data shortages. Improvement strategies include channel coordination, product enhancement, traditional channel optimization, and management upgrading.

Does the Rubber Meet the Road? Assessing the Potential of Devulcanization Technologies for the Innovation of Tire Rubber Recycling

Innovation is crucial to meet the circular economy goals for tire recycling. Devulcanization, an innovative recycling method of reprocessing tire rubber, offers a pathway towards achieving circular economy objectives. While previous research on devulcanization has primarily focused on technical aspects, this study shifts the focus towards identifying opportunities and barriers for innovation through devulcanization. This research utilizes the Technological Innovation System framework as a basis to analyze the dynamics of innovation within value chains and innovation networks. Across Europe, 36 organizations were identified that develop and utilize devulcanization to transform rubber from end-of-life tires into a valuable resource for new rubber products. In this study, a semi-structured in-depth interview approach was applied to interview 12 organizations that have developed or utilize technologies for the devulcanization of tire rubber. It was found that the development of various devulcanization approaches for diverse types of products has created opportunities for upscaling. To capitalize on these opportunities, organizations need to collaborate throughout the entire value chain of tire production and recycling. Achieving this collaboration requires interventions across the industry.

Estimation of Tire Side-Slip Angles Based on the Frequency Domain Lateral Acceleration Characteristics Inside Tires

The identification and control of tire side slip angle is the key to vehicle stability control. Intelligent tire technology based on the sensing of side-slip acceleration inside the tire provides a novel method for estimating the tire side-slip angle. This study proposed a method to estimate the tire side-slip angle by using the frequency domain lateral acceleration of the tire. First, an intelligent tire testing system was constructed by independently developing a special rim assembly and data collector. A three-axis accelerometer was placed on the right side of the tire, and the acceleration value was acquired by using a wired method with a sampling frequency of 50 kHz. Second, based on the constructed test system, a tire side deflection test was carried out on the Flat Trac bench. Through data analysis, it was found that the lateral acceleration was in the frequency domain of 400 Hz. As the side-slip angle increased from −4° to 4°, the vibration amplitude gradually decreased. Moreover, the vibration amplitude within 0.5~2 kHz was highly correlated with the side-slip angle. Subsequently, the vibration amplitude of the lateral acceleration within 2 kHz was extracted at an interval of 20 Hz as the feature point, and a frequency domain data set FDAy3 was established together with the vertical load and tire pressure. Finally, the support vector machine (SVM) algorithm was employed to make predictions on the data set. The grid search method was utilized to find the optimal parameter values of the model penalty factor c and radial basis kernel function coefficient g, which were 1.4142 and 0.0884, respectively. The results suggested that the root mean square error of the model prediction was 0.0806°, and the maximum estimated angle deviation of the prediction was 0.4587°. Meanwhile, the optimal prediction accuracy and real-time performance were achieved when the number of feature points and the feature frequency band were 25 and within 500 Hz, respectively. The findings of this study confirm that it is feasible to estimate the tire side-slip angle based on the frequency domain lateral acceleration of the tire, which provides a new method for tire side-slip angle estimation.

Evaluation of Energy Performance Indicators and Energy Saving Opportunities for the Italian Rubber Manufacturing Industry

The objective of this work is the energy characterisation and evaluation of the energy efficiency potential of the rubber manufacturing industry in Italy, exploiting the detailed data included in energy audits by large and energy-intensive companies. This sector is divided into two sub-activities: the manufacture of rubber products and the production of tyres. Existing studies are focused mainly on tyre production, and there is a lack of quantitative evaluation of energy indicators that can provide guidance for improving process efficiency. In this work, updated global and specific energy performance indicators (EnPIs) related to the production process and to the auxiliary and general services are defined and evaluated. At the same time, targeted actions and interventions to improve the energy efficiency of the sector are analysed, showing the role of different intervention areas and their cost-effectiveness. The analysis is based on 100 Italian mandatory energy audits of the sector collected according to Art.8 EU Directive 27/2012. The applied methodology made it possible to calculate specific energy performance indicators by considering the overall and sub-process energy consumption of different production sites. Based on a detailed database containing real data from recent energy audits, this study provides an up-to-date and reliable benchmark for the rubber industry sector. In addition, the analysis of energy audits allows the identification of the most effective energy efficiency interventions for the rubber industry in terms of cost-effectiveness and payback time.

Hybridization in meta-heuristic techniques for green layout design in the tyre manufacturing industry: An optimal analysis

To stop or lessen factory pollution, many academics in the field of study have produced a vast array of strategies to achieve optimization goals. But, it is unable to follow a uniform solution for all production facilities. In this research work, green layout design (GLD) is proposed to minimize total material handling cost (TMHC) and CO2 emissions. The green facility layout refers to the facility layout with minimum CO2 emissions and to eliminate unnecessary energy dissipation from material handling equipments &amp; production machineries, as well as plant re-layout in-term on material handling cost. In this study context, a Lagrangian relaxation model has been used at the allocation level. It computes a suboptimal solution to the dual problem in order to obtain a feasible solution. This enhanced algorithm method iteratively tries to minimize the gap between the dual and feasible solutions on minimal of TMHC and CO2 emission rate. It has been experimentally simulated using the MATLAB (Matrix Laboratory) application and upgraded adaptive salp swarm optimization (ASSO), dragon fly optimization (DFO) and Hybrid (combination) of ASSO-DFO evolutionary optimization techniques. The primary focus of this implementation is to control material handling between departments or cells, production flow between departments, energy consumption (electrical and gas consumption for production), and manpower utilization within and across departments. This research has chosen an existing and acceptable designs from targeted tyre manufacturing company in South India. The hybrid ASSO-DFO implementation TMHC differs from ABC by 60%, DFO by 65%, 58% with simulated annealing (SA), and ASSO by 48%. Emission rate decreased by 26% ABC, 21% DFO, and 24% SA &amp; 18% with ASSO. An average of 50% decrease in TMHC and 25% reduction of CO2 emission rate in GLD have been achieved.

Exploring the Effect of Resins of Different Origin on the Structure, Dynamics and Curing Characteristics of SBR Compounds.

The replacement of synthetic and petroleum-based ingredients with greener alternatives of natural origin is an imperative issue in rubber technology for the tire industry. In this study, a glycerin-esterified maleated rosin resin, derived from natural resources, is examined as a potential tackifier in styrene-butadiene rubber (SBR) formulations. A comparison is made with two synthetic resins commonly used as tackifiers in tire manufacturing: a petroleum-derived aromatic resin and a phenolic resin. Specifically, this research investigates how these resins affect the structure, dynamics, and curing characteristics of SBR compounds, which are strictly related to the mechanical and technological properties of the final products. Moving die rheometer and equilibrium swelling experiments are employed to analyze vulcanization kinetics and crosslink density, which are differently influenced by the different resins. Information on the polymer-resin compatibility is gained by differential scanning calorimetry and dynamo-mechanical analysis, while solid-state NMR methods offer insights into the structure and dynamics of both cured and uncured SBR compounds at the molecular level. Overall, our analysis shows that the resin of vegetal origin has a comparable impact on the SBR compound to that observed for the synthetic resins and could be further tested for industrial applications.

Effect of waste tire products on some characteristics of roller-compacted concrete

Abstract Roller-compacted concrete pavement (RCCP) is one of the most durable, economical, and practical solutions for the construction of roads for various heavy-duty purposes. To make RCCP more sustainable, different waste materials have been utilized. These materials were densified silica fume (SF), ground granulated blast furnace slag (S), crumb rubber (CR), and recycled steel fibers (RSFs) from waste tires. The weight percentages of replacement for SF and S from cement were 5, and 27.5%, respectively. CR was utilized as a volumetric replacement of sand with 0, 2, 5, and 10%. As a volumetric addition of concrete, RSF with 0.2, 0.4, and 0.6% was utilized. Water content was 6% for all mixtures. The impact resistance test was performed to evaluate the behavior of RCCP to the repeated load on roads. Also, ultrasonic pulse velocity (UPV) (nondestructive) and abrasion resistance tests were performed to validate roller-compacted concrete (RCC) as pavement. There is a substantial increase in impact energy by using 10% of CR and 0.6% of RSF, compared with that of reference specimens. The use of CR and RSF can improve the abrasion resistance of RCC, and this can ensure its applications in pavements. The relationships between impact, abrasion, and UPV were established, and models have been proposed to predict these relationships.

Life cycle assessment of waste tire recycling: Upgraded pyrolytic products for new tire production

Waste tire (WT) pyrolysis is an attractive option for material and energy recovery. Further upgrading of pyrolytic products demonstrates greater environmental and economic advantages than conventional pyrolysis. However, the advance in economic benefits brought by quality improvement of pyrolytic products is not significant. Therefore, this study proposed the circulation case of upgraded pyrolytic products for new tire production from WTs. This case recycles the products produced from WT pyrolysis into new tire production to establish a closed-loop between end-life and beginning-life of WTs. Three circulation cases using different modification methods of pyrolytic carbon black (CBp) were evaluated by several circular economy indicators. Results show that Case M1 (modified CBp (M-CBp) by physical modification) has the best resource-environmental performance (resource benefit to environmental cost ratio, RBECR), which is 20.35 % and 4.62 % higher than those of Cases M2 (M-CBp by nitric acid modification) and M3 (M-CBp by plasma modification), respectively. Case M3 has the best comprehensive performance (economic profit to environmental cost ratio, EPECR), which is 1.62 % and 2.82 % higher than that of Case M1 and Case M2, respectively. To acquire higher profits, the coupled-circulation case that combined M-CBp and reclaimed rubber for new tire production was further proposed, as reclaimed rubber was a major raw material for tire production with higher profitability. The proposed process recycles more materials into new tire production so that the EPECR and RBECR of coupled-circulation case increase by 55.7 % and 147.7 % as compared to the basic circulation case, respectively. Therefore, the coupled-circulation case demonstrates an efficient pathway for WT utilization. The sensitivity analyses further show that both the replacement rate of M-CBp prepared by plasma modification (M3-CBp) and price of crude oil significantly influence the resource-environmental performance, with the sensitivities reaching 101.3 % and 100 %, respectively. The replacement rate of reclaimed rubber is the most important factor for comprehensive environmental-economic performance, with the sensitivity reaching 44.1 %. Generally, coupled-circulation case can maintain good comprehensive benefits when various influencing factors change within the scope discussed in this paper.

Leaching of tire particles and simultaneous biodegradation of leachables

The fate of organic compounds released from tire wear particle (TWP) in the aquatic environment is still poorly understood. This is especially true near sources where biotic and abiotic transformation and leaching from TWP are simultaneous and competing processes. To address this knowledge-gap an experiment was performed, allowing for biodegradation (a) during the leaching from a suspension of cryo-milled tire tread (CMTT) and (b) subsequent to leaching. Besides measuring the Dissolved Organic Carbon (DOC) content, 19 tire-related chemicals were quantified, and non-target screening was performed by LC-HRMS. The non-inoculated control experiment exhibited a DOC of up to 4 mg g−1, with up to 700 µg g−1 of 1,3-diphenylguanidine (DPG) as the most prominent compound, followed by three benzothiazoles (2-mercaptobenzothiazole (2-MBT), 2-hydroxybenzothiazole (2-OHBT) and benzothiazole-2-sulfonic acid (BTSA); 50 µg g−1 each) and 4-hydroxydiphenylamine (4-HDPA) (50 µg g−1). Biodegradation reduced the DOC by 88 % and the concentration of most organic compounds by more than 85 %. At the end of the experiment hexamethoxymethylmelamine (HMMM) was the most prominent single compounds (18 µg g−1). Non-target screening showed a more complex picture. Another 25 transformation products (TPs) of N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6-PPD) and 44 TPs and derivatives related to DPG were detected in solution, of which 11 and 28 were still present after or formed by biodegradation, respectively. Of these 39 TPs and derivatives, 31 could be detected in road runoff samples. This study provides a more comprehensive picture of the leachables of tire particles that are of environmental relevance. It also outlines that derivatives of tire additives formed during tire production and use may deserve more attention as leachables. The large extent of biodegradation of tire leachables suggests that settling ponds may be a useful treatment option for road runoff.

Assembly of Zinc‐Single‐Site‐Containing Silica Nanoparticles to Supraparticle Powders with Destructibility to Serve as Filler and Vulcanization Activator in Rubbers

AbstractThe vulcanization process is widely used in industry for tire manufacturing. Therefore, zinc oxide is commonly utilized as an activator material, but unreacted zinc oxide remains in the final products and can be released into the environment with a significant impact. To reduce the amount of required zinc and to prevent leaching from tire material, zinc single site‐containing silica fillers are interesting candidates. In these materials, zinc sites are anchored on the surface of silica nanoparticles through their complexation with functionalized aminosilanes. Based on these, a novel powder sample is prepared via spray‐drying. The obtained supraparticles allow for a homogeneous distribution of the filler nanoparticles in the rubber matrix via their disintegration during the incorporation process. All synthesis steps are carried out in ethanol and water, respectively, at very mild temperatures to account for sustainability demands. As core of this study, the role of zinc ions and their amino‐complexation in nanoparticle dispersion stability and in supraparticle formation during spray‐drying is elucidated. Additionally, the superior performance of supraparticles as activator in rubber vulcanization is demonstrated. These show a higher curing efficiency, leading to lower curing time (−70%), higher torque values (+15%), and improved dynamic mechanical properties compared to the conventional ZnO activator.

Climate change management in manufacturing industry: a greenhouse gas inventorisation and mitigation approach

PurposeIndustries worldwide have been striving to serve the increasing demand of consumers alongside providing importance to environmental issues. Yet, there are concern-raising changes on the planet, such as greenhouse gas (GHG) emissions resulting in a temperature rise. India remains a vital party of the United Nations Convention on Climate Change. Henceforth, the paper aims to study the increased emissions of GHG in Puducherry, an Indian Union Territory that faces tremendous pressure owing to its denser population.Design/methodology/approachThe research is designed as a case study conducted in a tyre manufacturing unit in Puducherry. The industrial sector was chosen, as it is the largest contributor (78%) of the total GHG emissions. Case studies were chosen to analyse the GHG emissions and the effects of implementing the policies and imposing interventions over time. The identified areas of improvement, proposed changes and the implemented ones with the results over a three-year period have been discussed.FindingsThe present study’s GHG inventorisation for Puducherry paved the way for preparing mitigation and adaptation plans. A total of 21 and 48 changes were incorporated to conserve fuel and power, respectively. A significant 11% reduction in power consumption and 1,113,008/litres of furnace oil was achieved. This translates to 5,115 tCO2 and 3,306 tCO2, respectively.Practical implicationsThis research will help to improve the importance of climate change management in the manufacturing sector, and it will pave the way for achieving effective sustainable practices.Originality/valueSuch case studies could cumulatively impact the policy directives/ interventions on GHG emissions. Though this seems a small leap, putting them into practice at firm levels would contribute significantly towards achieving Sustainable Development Goals.

Optimization and improving of the production capacity of a flexible tyre painting cell

AbstractOptimization of industrial processes is a constant concern and a main task for many companies in several industry sectors. Based on optimized solutions, the company can decrease manufacturing costs, lead times or, more generally, increase benefit. However, when developing a new process, you must be sure that the new solution will add more value to the initial solution. This, among many others, is one of the main reasons why companies opt, in addition to experimentation, for the use of tools that allow for the virtual prototyping, simulation, and integration of complex and sophisticated processes. Experimentation requires approximation testing, searching for the ideal values of quantity, temperature, etc.; simulation provides industrial processes with test support ranging from flows to robotic systems such as the intelligent software. This simulation software allows to develop programs, add Computer Aided Design (CAD) layouts, and simulate the cycle times of the different tasks to be performed. In this paper, an experimental approach is presented with atomization and fan spray pressure as the study basis and a simulation of the robot-based handling solution used in a tyre production line. The result is an improvement of the painting process, optimisation of the amount of fluid deposited on the tyre, of the processed product, as well as of the running times of the robot.

Explainable attention-based fused convolutional neural network (XAFCNN) for tire defect detection: an industrial case study

Ensuring tire quality is crucial in the manufacturing industry, particularly for race cars, where defective tires present a significant safety risk. Visual inspection for defects in tires is crucial; however, identifying defects in complex, textured tires has been proven to be a challenging task. This paper tackles this challenge by introducing XAFCNN, an Explainable Attention-based Fused Convolutional Neural Network for tire defect detection. XAFCNN’s novel architecture, including a Special Attention Module (SAM) and custom CNN structure, coupled with Grad-CAM visualization, prevents overfitting, enhances local feature mapping, enables detection of small defects, and proffers valuable insights into the model’s reasoning, enabling confident interpretation of its predictions. The model was trained on a dataset from a leading global tire manufacturer, including 38,710 x-ray images of defective tires and 83,985 defect-free tire images, covering 15 defect types and 50 design patterns. The results demonstrate the model’s exceptional performance compared to literature, achieving a recall rate of 86.85%, a precision of 98.5%, an F1 score of 92.31%, and an overall accuracy of 95.40%. This research, with its substantial dataset and high-performing model, advances automated tire defect detection, satisfying the industry’s need for accurate and reliable inspections, ultimately enhancing human safety.

Prioritization of Volatile Organic Compound Reduction in the Tire Manufacturing Industry through Speciation of Volatile Organic Compounds Emitted at the Fenceline

Volatile organic compounds (VOCs), with their ubiquitous presence across numerous global industries, pose multifaceted challenges, influencing air pollution and health outcomes. In response, countries such as the United States and Canada have implemented fenceline monitoring systems, enabling real-time tracking of organic solvents, including benzene. Initially, this focus was predominantly placed on the petroleum refining industry, but it has gradually been broadening. This investigation seeks to identify and analyze the specific VOCs produced in the tire manufacturing sector by utilizing both active and passive monitoring methodologies. The findings of the present study aim to recommend prioritized reduction strategies for specific VOCs. Percentage means the ratio of VOCs detected at the research site. At research target facility A, active monitoring demonstrated the presence of Methylene chloride (20.7%) and Carbon tetrachloride (15.3%), whereas passive monitoring identified Carbon tetrachloride (43.4%) and m,p-Xylene (20.8%). After converting these substances to their equivalent concentrations, we found a noteworthy correlation between the active and passive methodologies. At research target facility B, active monitoring detected n-Pentane (45.5%) and Isoprene (11.4%), while passive monitoring revealed Toluene (21.3%) and iso-Hexane (15.8%). Interestingly, even at sites like warehouses and test tracks where VOC concentrations were projected to be low, we observed VOC levels comparable to those in process areas. This underlines the fact that the dispersal of VOCs is considerably influenced by wind direction and speed. Specifically, in the tire manufacturing industry, emissions of Xylene and 3-Methylhexane, both having high photochemical ozone creation potential (POCP), contribute significantly to air pollution. However, the overall detection concentration in the tire manufacturing industry was detected at a low concentration of less than 2 μg/m3. This is less than 9 μg/m3, which is the standard for benzene, which has strong carcinogenicity regulations. This suggests that additional research is needed on synthetic rubber manufacturing rather than tire manufacturing.