Tire Manufacturing Industry Research Articles

TPMS-based auxetic structure for high-performance airless tires with variable stiffness depending on deformation.

A novel auxetic structure applicable to airless tire spokes is designed based on the primitive-type triply periodic minimal surface (P-TPMS) to have higher stiffness through deformation under compressive force. For becoming higher stiffness by deformation, an unit cell of auxetic structure is proposed and its characteristics according to design parameters are studied. Based on the parametric study, a rotated primitive-type auxetic structure (RPAS) is designed, and the deformative behaviors of an airless tire with the RPAS spokes are compared with a generally used honeycomb spoke. Simulation and experiment results show that the designed RPAS tire exhibits more stable behavior through higher rigidity depending on the deformation state when compressed on flat ground and obstacles. This variable stiffness characteristic of RPAS tires can be advantageous for shock absorption and prevention of large local deformations. Also, the manufacturability of the designed auxetic structure is evaluated using real rubber-based additive manufacturing processes for practical application in the tire manufacturing industry.

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 & 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 & 18% with ASSO. An average of 50% decrease in TMHC and 25% reduction of CO2 emission rate in GLD have been achieved.

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.

Multi criteria decision analysis for the identification of feasible rubber waste management alternatives for tire manufacturing industry: a Sri Lankan case study with TOPSIS and SWING

Multi criteria decision analysis for the identification of feasible rubber waste management alternatives for tire manufacturing industry: a Sri Lankan case study with TOPSIS and SWING

Mapping the TQM implementation approaches and their impact on realizing leadership in Indian tyre manufacturing industry

PurposeThis paper attempts to investigate the approaches used for implementing total quality management (TQM) practices and study its impact on ABC India Limited (Name changed), a tyre manufacturing industry for realizing leadership in the Indian market. The other objectives are to explore the key issues faced by the company before TQM and study the benefits achieved after TQM implementation.Design/methodology/approachA conceptual case study research methodology has been utilized in this paper. The industry was facing some major business challenges such as low productivity, financial issues and low market presence since 1996. To overcome these issues, the top management of the industry adopted TQM as a business improvement tool and started its implementation in 2008.FindingsA good number of improvement initiatives under four TQM approaches such as management approach, development approach, improvement approach and involvement approach were performed systematically and strategically. As a result of the successful implementation of TQM initiatives, the industry received the most prestigious quality award namely Deming Prize in 2017.Research limitations/implicationsWith the implementation of the TQM philosophy in the industry, it gained the top market position, the customer satisfaction score increased from 75 to 81, market presence increased from 7.2% to 26.3% and the percentage participation of employees increased by 73.5% within a period from 2009 to 2016.Originality/valueThe novelty of this research is to consider a case-based approach that will be helpful in promoting the utilization of the TQM philosophy in other industries for gaining competitive advantages.

EFFECTIVENESS OF DECOY WATER TREATMENT ON REACTIVATORS AT PT GOODYEAR INDONESIA Tbk

PT Goodyear Indonesia Tbk is a tire manufacturing industry whose main need is the provision of water for steam boiler decoys. This water is obtained from groundwater and surface water such as river water which is then treated in a reactivator using one of the coagulants, namely PAC, so that impurities from river water can be removed, so the water is cleaner and can be used for steam boilers and does not interfere with a further decoy water treatment. This study aims to determine the effectiveness of water treatment in reactivators to be a reference for further treatment considerations at PT Goodyear Indonesia Tbk. The test result data showed the efficiency value between the inlet and outlet and compared it with the control limit set by the company. The efficiency test parameters consist of pH, conductivity, clarity measurement, and color measurement. Based on the results of efficiency calculations, several test parameters show that water treatment in reactivators at PT Goodyear Indonesia Tbk is still good and has a high-efficiency value.

Modified Resource-Constrained Project Scheduling to Minimize Idle Time for Banbury Mixing Process: A Case Study in the Tire Manufacturing Industry

Abstract The Banbury mixing process (BMP) is to supplies the specific characteristic compounds for the tire manufacturing process. Idle time in the BMP was a problem caused by the aging process between mixing steps and the limited space for processing, measured in pallets. In this study, the resource-constrained project scheduling model (RCPS) is modified in case of the objective function and the input value of resource constraint to minimize idle time (SST). The complete minimization (Cmax) is changed from minimizing the starting time of the last job to the starting time of all jobs. In addition, the non-limited resource is defined as the input for the space capacity to reduce the idle time. As the results, the SST can provide the schedule that make less 5 time periods of idle time. Moreover, when considering the relationship between mixing and aging, aging process that is scheduled from SST starts immediately comparison to Cmax that some of aging process are not. Furthermore, the effect of the quantity of pallets was also examined. Although the non-limited resource does not make any delay to the schedule but the limited quantity is not. When pallets are limited, aging jobs were significantly impacted, with the last aging pallet being delayed. To reduce delays, it prepares an adequate supply of pallets that is close to or equal to its requirement that is defined by the non-limited resource. Further research combining the scheduling of the BMP with the tire manufacturing process and more techniques to modify RCPS are applied.

Modelling of roller conveyor for the simulation of rubber tire tread extrusion

Abstract The extrusion of large or heavy technical rubber profiles is usually assisted by a conveying device. Such a device can be a conveyor belt or a series of rollers, and its use is necessary mainly for being able to achieve the process. Within the context of numerical simulation of extrusion flows, a conveying device brings additional downstream constraints to the flow governing equations. In the present paper, we propose a simple engineering approach for modelling a roller conveyor used in rubber tire tread extrusion, and we apply it to the extrusion simulation of a flat tire tread profile as typically encountered in the tire manufacturing industry.

Impact of green practices through green product and service innovation: sustainable product-service system performance model

ABSTRACT Today, the manufacturing industry faces worldwide challenges, ecological hazards, climate change, and the use of non-renewable natural resources, so industry players are manoeuvring in a sustainable direction. In this case, green manufacturing practices are used as a starter to contribute to products and services that can help achieve sustainable development goals. The research aims to explore green practices with empirical evidence in the literature and expert opinions of tire manufacturing industry practitioners. The study proposes a framework of key factors: TMC (Top Management Commitment), PPP (Pollution Prevention Practices), and PSP (Product Stewardship Practices) that can affect GPSI (Green Product Service Innovation) significantly affect SPSSP (Sustainable Product-Service System Performance). The study used statistical analysis to calculate the minimum sample size with (G*Power 3.1), the results were 205 respondents adequate, and structural model analysis using Structural Equation Modeling (SmartPLS 4.0). The results show that TMC and PSP significantly affect SPSSP, but PPP does not affect SPSSP. The findings also suggest that the relationship between key factors and SPSSP can be mediated by GPSI. The recommendations of this study provide suggestions to top management for the adoption of GPSI as a novelty in green manufacturing, and as value creation for sustainable development achievements.

Multi Criteria Decision Analysis for the identification of feasible rubber waste management alternatives for tire manufacturing industry: A Sri Lankan case study with TOPSIS and SWING

Multi Criteria Decision Analysis for the identification of feasible rubber waste management alternatives for tire manufacturing industry: A Sri Lankan case study with TOPSIS and SWING

예측 모델 기반 섀플리 값을 이용한 타이어 설계 인자 분석

In the tire manufacturing industry, factor analysis plays a crucial role in deriving design candidates that can increase tire performance by deriving design factors, including variable importance and directions of design change. Typically, expert knowledge and finite element analysis (FEA) are necessary to derive design factors. However, they required a high computation load. Although several studies have been performed using machine learning and variable selection methods, they have limitations in recommending design change directions for each variable. In this study, we propose a predictive model coupled with Shapley additive explanations (SHAP) for tire design factor analysis. We first construct a predictive model using tire design data, and then applied SHAP for deriving important variables and directions of design change. To demonstrate the effectiveness of our methodology, we evaluate the design candidates using FEA. Results show that our methodology is effective for a tire factor analysis.

A Plant Simulation approach for optimal resource utilization: A case study in the tire manufacturing industry

In this study, the resource allocation and vital manufacturing processes in the tire manufacturing industry was comprehensively optimized. The paper deals in detail with the Banbury mixing process, which produces homogeneous rubber materials for tire components. In addition, the mixing process models were established by the Plant Simulation software to validate and compare scenarios and experiments with realistic production constraints. Discrete empirical distribution (dEmp) was proposed for population data. Various scenarios were created for different resource and process. Experiments were set as different group of compound set. Experiment manager was used as a tool to set up scenarios and the experiments to provide alternative results. The study results display the production time and machine utilization. The shortest production time of experiment results represents the best group of each scenario. As results, the scenario, which BB1 is changed from non-productive Banbury mixer to special Banbury mixer along with the normal process is combined with second special process, provides the suitable production volume which can reduce of total production time for 8.06 %. Our study provides a variety of the resource utilization of a Banbury mixing process and suggests an efficient optimization method for production performance improvement.

머신러닝 및 베이지안 최적화를 이용한 타이어 최적 설계

Product design optimization plays an important role in the manufacturing industry. In the tire manufacturing industry, design optimization process traditionally involves generation of tire design candidates and quality prediction by using finite element analysis (FEA). However, this traditional process requires expert’s experiences to derive design candidates that satisfies target quality. In addition, FEA requires a lot of time to obtain the prediction results although it provides accurate predictive performance. To overcome these issues, we propose Bayesian optimization based on a predictive model for the tire design. We train a model that can predict multiple quality variables and perform Bayesian optimization that can optimize numerical and categorical variables simultaneously. Results show that the proposed method can effectively predict and optimize the tire design with reduced time complexity.

Designing and fabricating nanopolymer composites beyond traditional polymer nanocomposites toward fuel saving of automobile tires

Polymer nanocomposites (PNCs) are widely used in automobile tire manufacturing industry. Concerning the long-standing energy crisis, designing and fabricating PNCs with both high strength and low energy consumption has gained numerous scientific interests. Inspired by nanoparticle-based supramolecular materials, the processed nanoparticles (NPs), as one of the synthetic monomers to build polymer chains, can essentially enhance the strength and stability of the filler network, thus achieving high strength and low energy consumption in the novel PNCs. Herein, in contrast to traditional filling methods, the novel PNCs were constructed by embedding nanoparticles into polymer chains through coarse-grained molecular dynamics simulations. The structural, dynamic, mechanical and viscoelastic properties influenced by the content and size of the NPs are systematically explored. Compared to traditional polymer nanocomposites (tPNC), this novel PNCs exhibits a relatively higher glass transition temperature (Tg) at the same content of the NPs, attributed to the constraint of the NPs chemically bonded onto the chain backbone. By calculating the number of neighbor NPs and polymer beads around each NP, this novel PNCs possess a much better dispersion of NPs and a thicker interfacial polymer adsorbed layer than that of tPNC system. Interestingly, the formation of a zigzag-interlock structure with an intermediate strength, namely between the physical and chemical interaction, allows for a more prominent mechanical reinforcing efficiency than tPNC. Moreover, the NP size and the crosslink density play an important role in tailoring the mechanical properties. Finally, the dynamic mechanical properties of this novel PNCs, such as the loss factor and hysteresis loss, exhibit a much smaller energy dissipation than those of the tPNC, which is attributed to much lower friction between NPs-polymer brought by the more stable filler network. In general, our work confirms that this novel PNCs is an excellent candidate to exceed the traditional PNC by possessing a more significant nano-reinforcing effect and a much less dynamic hysteresis, opening a good avenue for the design and fabrication of next-generation elastomer nanocomposites tailored for green automobile tires.

Assessing Human Performance Influencing Factors through LINMAP and Bayesian Belief Networks

This study aims at identifying and ranking the performance influencing factors (PIFs) that cause error in human operations. The failure weight and rate for the tasks carried out by each operator were investigated. Assessing these factors reduces human error, hence increasing safety, efficiency and job satisfaction. The methods of linear programming technique for multidimensional analysis of preference (LINMAP) and Bayesian Belief Networks were used to investigate an aircraft tire manufacturing industry. All operators in the workshops were evaluated. Based on data analysis, the tasks of each operator were weighted and the potential error rate of each task was obtained. PIFs for each workshop were ranked and prioritized so that the factors having most influence can be easily distinguished and the tasks where the operators have the highest rate of failure, can be identified. The probability of human error was obtained and in a predictive model, it can be determined that when an error occurs, which factors are most influential in its occurrence. The method utilized does not include copious pairwise, exhausting and at times confusing comparisons for operators.

Study of bladder release agent formulas and methods to evaluate their efficiencies by using reciprocating tribometer

Bladder is one of the most important components in tire manufacturing process. In tire industry, methods to prolong bladder service-life and good bladder coatings for non-stick surface has been acquired. Bladder coated with good release agents can help reducing nonconforming products and increasing production efficiency. In this work, semi-permanent release agent formulas were studied. A new method to evaluate release agent efficiency by using a reciprocating tribometer were also carried out. Polydimethyl siloxane (PDMS) release agent formulas were developed with and without polymethyl hydrogen siloxane (PMHS). Effects of metal salt cure catalyst were also studied. In this work, method of release efficiency test was developed by using a reciprocating tribometer according to ASTM G133-05. It can be used to determine coefficient of friction of the coated surface and durability of the coatings. Coating durability test was also confirmed by repeating compression molding test to determine the number of release cycles. It was found that film durability was improved by adding the metal salt catalyst and PMHS. As the PMHS loading was increased, film endurance was improved to an optimum loading. Friction coefficient of the coatings could be related to the mold release ability and durability of the release agents. The technique can be used to estimate the service-life of the coated bladders. It can be used as a guideline for development of mold release agents in tire manufacturing industry.

Competitive scheduling in a hybrid flow shop problem using multi-leader–multi-follower game - A case study from Iran

It is logical that organizations pay more attention to their major customers which have more impacts on their abilities or benefits. In many real cases, decision makers in scheduling system must prioritize the sequence of processing orders according to the agent of orders while the classic production scheduling do not have the ability to consider the relationships between agents. These problems can be modeled by the Stackelberg problems in the field of game theory. In this study, an agent-based hybrid flow shop problem is formulated by using the multi-leader multi-follower mathematical model. Each level is evaluated by Nash equilibrium and Nash bargaining with the new co-evolutionary and genetic algorithm. The proposed model is validated in a real case problem in the tire manufacturing industry. The results show that Nash equilibrium is superior to Nash bargaining for all agents.

The Moderating Impact of Team Tenure on Team Trust - Team Performance Relationship with Relevance to Executive Level Employees of Sri Lankan Tyre Manufacturing Industry

Even though, many determinants of team performance are found in extended literature, team trust and the moderating effect of team tenure is little investigated in Sri Lankan context, and it has not been studied yet. Bridging the gap in this context, the current study assessed the moderating impact of team tenure on team trust and team performance relationship in Sri Lankan tyre manufacturing industry. The current study was conducted as a cross-sectional study among a sample of one hundred and ninety-two executive level employees selected from four major tyre manufacturing organizations following the stratified random sampling technique. Primary data were collected using a standard questionnaire distributed via Google form. The collected data were analysed with the support the SPSS employing correlation, regression, descriptive statistics and process matrix. It is found that team tenure does not moderate the relationship between team trust and team performance, and also founded that strong positive relationship between team trust and team performance. Moreover, team trust impact positively on team performance and team tenure does not impact team trust and team performance separately. It is recommended to tyre manufacturing organizations to facilitate more open communication and information sharing in order to improve executive level employees trust within teams, which in turn, will affect their team performance. Future researchers can use other variables like organizational support, team diversity, and personality as moderators of their study.

Analysis and Defect Improvement Using FTA, FMEA, and MLR Through DMAIC Phase: Case Study in Mixing Process Tire Manufacturing Industry

In line with the increasingly fierce industry competition, all companies strive to make continuous improvements to increase added value and reduce waste which will impact the company's ability to maintain its existence in the future. One of the problems found in the tire manufacturing industry is the quality problem of the occurrence of defects in the mixing process which is dominated by the viscosity out standard on the compound steel breaker. In this study, analysis and improvement of the defect problem were carried out using Fault Tree Analysis (FTA), Failure Mode and Effect Analysis (FMEA), and Multiple Linear Regression (MLR) to test the correlation between the root causes found to the main problem. Based on the results of the analysis found thirteen root causes where the factor of variation in material viscosity and the suitability of determining the design process has the largest Risk Priority Number (RPN) value and has a strong correlation to defects that occur based on hypothesis testing. Furthermore, improvements are made using the DMAIC method on all factors that affect the occurrence of defects. As the result, the improvement can be effective in reducing the defect to 34.5% and achieve the expected target.

Treatment of gaseous emissions from tire manufacturing industry using lab-scale biofiltration pilot units

Continuously seeking the improvement of environmental protection, the limitation of exhaust emissions is of significance for the tire manufacturing industry. The aim of this study is to assess the potential of biofiltration for the treatment of such gaseous emissions. This work highlights that biofiltration is able to remove both hydrophilic and hydrophobic compounds within a single pilot unit of biofiltration. Due to Ethanol/Alkanes ratios (95/5 and 80/20), high performance levels were observed for low EBRT (16 and 12 s). After twenty days of stable running, the dynamic of stratification patterns could be explained as a result of species coexistence mechanisms. While its impact on performance has not been observed under stable operating conditions, the use of an adsorbent support such as granular activated carbon (GAC) could be relevant to promote system stability in the face of further perturbations, such as transient regimes, that are problematic in full-scale industrial applications.