Automotive Parts Industry Research Articles

A Neuro-Fuzzy Risk Prediction Methodology in the Automotive Part Industry

A Neuro-Fuzzy Risk Prediction Methodology in the Automotive Part Industry

Optimizing Logistics: Developing An Efficient Tracking and Delivery System for Automotive Spare Parts

In the automotive spare parts industry, efficient supply chain management is the backbone of operational success. Amidst this complex ecosystem, companies face challenges in delivering fast, reliable, and competitive services, accommodating a constantly evolving consumer base with discerning preferences and rising expectations. This article aims to identify challenges in developing tracking and delivery scheduling applications for the automotive spare parts industry and improve system performance by introducing effective solutions. The research adopts a system development approach using the Waterfall method to produce a responsive and user-friendly web application, followed by functional testing using Black Box and evaluation using the System Usability Scale (SUS). Development of the tracking and delivery scheduling application using the Waterfall method resulted in a reliable and responsive application, with all system functionalities running smoothly. SUS testing indicated that the application has a good level of usability, with an average score of 77.5 out of 100. This study successfully provides relevant and efficient technological solutions to overcome operational barriers in the automotive spare parts industry, with the potential to enhance customer satisfaction and solidify the company's position as a pioneer in the automotive aftermarket sector. However, further improvements in application usability can be achieved through future iterations guided by user feedback and additional usability testing.

Analysis of Performance Comparison between K-Nearest Neighbor (KNN) Method and Naïve Bayes Method in Reward for Honda Motorcycle Salesman Tour

Honda Indako Trading Coy Krakatau is a company in the automotive and spare parts industry. As the main dealer of Honda motorcycles and spare parts for North Sumatra and Aceh, the company faces challenges in boosting sales and maintaining employee loyalty. To address this, the company offers a reward salesman tour for employees who meet certain criteria. However, the current evaluation system is too simple and does not fully capture the quality of employees, especially their product knowledge and involvement in company campaigns. This study aims to solve these issues using data mining techniques, specifically the Naïve Bayes and K-Nearest Neighbors (KNN) methods. These methods were chosen for their accuracy and simplicity. The K-Nearest Neighbor method (K=11) showed an accuracy of 94.04%, a precision of 83.78%, and a recall of 96.87%, while the Naïve Bayes method showed an accuracy of 81.81%, a precision of 72.00%, and a recall of 81.25%.

Enhancing Quality Control in the Indonesian Automotive Parts Industry: A Defect Reduction Approach Through the Integration of FMEA and MSA

Enhancing Quality Control in the Indonesian Automotive Parts Industry: A Defect Reduction Approach Through the Integration of FMEA and MSA

Analysis of the Effect Current Ratio on Return on Assets at PT Astra Otoparts TBK.

This study makes an important contribution in understanding the relationship between current ratio and return on assets at PT Astra Otoparts Tbk. Through the use of a simple linear regression test on financial statement data for the period 2015-2022, this study intends to explain the extent to which the current ratio affects the company's return on assets. Current ratio, as the independent variable, is used as an indicator of the company's ability to meet its short-term obligations, while return on assets, as the dependent variable, reflects the company's level of profitability. The results show that, although the current ratio has a positive influence on return on assets, the influence is not statistically significant. In other words, the increase in current ratio does not contribute significantly to the increase in return on assets at PT Astra Otoparts Tbk. The findings can provide valuable insights for company management in designing financial strategies, especially in terms of managing short-term assets and liabilities. In the context of the automotive and spare parts industry in Indonesia, where PT Astra Otoparts Tbk operates, an in-depth understanding of the factors that influence return on assets is crucial. The results of this study can serve as a basis for similar companies to evaluate and improve their financial performance, optimize asset allocation, and manage short-term liabilities more effectively. Further research and the integration of other factors in financial analysis can help shape a more holistic and sustainable business strategy amidst changing market dynamics.

PROSES PEMBUATAN PLATE HOOK FUEL LID MENGGUNAKAN MESIN STAMPING PRESS

When starting to do practical work at PT Persada Selaras Indonesia several problems were found, one of which was why the SPHC-PO material was used in the production of Plate Hook Fuel Lid and how the production process was used Stamping Sheet Metal Press in the production process using the Blanking and Bending processes Based on the process of making the Plate Hook Fuel Lid, this practical work has the goal of knowing the working process of the Stamping Press machine. The methods used in this practical work are the process of observing, summarizing and recording data from sources and hard copies from PT. Persada Selaras Indonesia After carrying out the methods systematically obtained several results from practical work, including being able to make a product using a Stamping Press machine and recognizing the flow of the production process in the automotive part industry

A STUDY ON INVENTORY MANAGEMENT” AT MULTITEK AUTO PARTS IN DODDABALLAPUR.

The study on inventory management at Multitek Auto Parts addresses the critical importance of efficient inventory management practices within the automotive parts industry. Multitek Auto Parts, a prominent player in this sector, faces challenges in maintaining an optimal balance between supply and demand while minimizing costs and ensuring customer satisfaction. This research delves into the various strategies employed by Multitek Auto Parts to manage their inventory effectively, considering factors like demand forecasting, procurement methods, stock control techniques, and technology integration. The study not only explores the company's successes and best practices but also highlights potential areas for improvement. By analyzing the inventory management practices at Multitek Auto Parts, this study contributes valuable insights to both academic literature and industry professionals, shedding light on the intricacies of inventory optimization in a competitive automotive parts market. Keywords: Inventory management, Supply chain, Optimization, Inventory control, Demand forecasting, Stock levels, Ordering policies, Reorder point, Safety stock, Just-in-time (JIT),MEconomic order quantity (EOQ) etc.

A hybrid integrated multi-criteria decision-making approach for risk assessment: a study of automotive parts industry

PurposeThis paper aims to enable the analysts of reliability and safety systems to evaluate the risk and prioritize failure modes ideally to prefer measures for reducing the risk of undesired events.Design/methodology/approachTo address the constraints considered in the conventional failure mode and effects analysis (FMEA) method for criticality assessment, the authors propose a new hybrid model combining different multi-criteria decision-making (MCDM) methods. The analytical hierarchy process (AHP) is used to construct a criticality matrix and calculate the weights of different criteria based on five criticalities: personnel, equipment, time, cost and quality. In addition, a preference ranking organization method for enrichment evaluation (PROMETHEE) method is used to improve the prioritization of the failure modes. A comparative work in which the robust data envelopment analysis (RDEA)-FMEA approach was used to evaluate the validity and effectiveness of the suggested approach and simplify the comparative analysis.FindingsThis work aims to highlight the real case study of the automotive parts industry. Using this analysis enables assessing the risk efficiently and gives an alternative ranking to that acquired by the traditional FMEA method. The obtained findings offer that combining of two multi-criteria decision approaches and integrating their outcomes allow for instilling confidence in decision-makers concerning the risk assessment and the ranking of the different failure modes.Originality/valueThis research gives encouraging outcomes concerning the risk assessment and failure modes ranking in order to reduce the frequency of occurrence and gravity of the undesired events by handling different forms of uncertainty and divergent judgments of experts.

RETRACTED ARTICLE: Network Attribute Analysis and Competitiveness Evaluation of Auto Parts Industry Cluster for e-Commerce Platform

The automotive parts industry cluster is a complex operating system, and it is no longer possible to use a simple theory to make a scientific and reasonable explanation for the parts industry cluster. In view of this, the study takes the automotive parts industry cluster as the research object, innovatively invokes the theory of organizational ecology and constructs a competitiveness analysis mechanism based on population co-evolution. The study conducts performance analysis and simulation tests on the constructed model, integrating the CS–AHP evaluation method to evaluate the competitiveness of the parts industry cluster. The performance comparison results show that the research method has a minimum training error of 0.0108, when the number of iterations of the system is 69th. This method has a stable loss function value at the fifth iteration, which is a stable convergence state earlier than the GA algorithm, differential evolution and distribution estimation algorithm. The A-level index score of the off-line platform auto parts industry cluster is 0.5174, which is significantly greater than 0.5. The competitive cooperation effect, technological innovation effect and cluster culture scores of the e-commerce platform are 0.5885, 0.6899 and 0.5329, respectively, which are significantly higher than those of the off-line. The above results show that the accuracy of the research algorithm is higher than that of the off-line industry. The above results show that the accuracy of the research algorithm is better, which can make a reasonable scientific basis for the auto parts industry and carry out competitiveness evaluation. To a certain extent, it can provide technical reference for the future development of the auto field industry.

A methodology for the strategic design of city logistics networks and its application in Turkish automotive spare parts industry

City logistics approaches and modeling struggles have a significant role in urban areas in increasing the efficiency of logistics operations and reducing traffic jams and their environmental effects. By developing an effective distribution network for cities, it is possible to compete with the changing world and satisfy flexible customer requirements. In this study, as a real-world case, a city logistics model for Istanbul metropolitan area is designed using multi-objective linear programming that considers the different objectives of the stakeholders in cities by integrating the fuzzy Choquet integral technique in a multi-level distribution network for the automotive spare part industry. This paper makes decisions regarding the amount of product flowing among the echelons, the amount of stock to be kept in the warehouses, and the product delays allowed. While minimizing the transportation cost, holding cost and emission levels during these decisions, the study also aims to maximize the service quality in the warehouses. The model is applied to a logistics network of fifty demand points and thirty time periods which can be considered a middle or large-scale problem. In the model, it is also decided to transport the products with electric or fuel vehicles. In the transport sector, electric vehicles are the key to meet future needs for social, health and other human services. The results are discussed under different scenarios. This research allows the use of such a model in making strategic decisions for the distribution network design in big cities.

Critical factors of knowledge management to boost the competitiveness of SMEs: The case of automotive parts industry in Guadalajara, Mexico

New development structures and competitiveness are based on using information as raw material and knowledge as a strategic resource, and it is necessary to rethink organizational strategies to add excellent value to the organization through knowledge management. Through knowledge management, organizations encourage individuals to develop their work by contributing ideas and, simultaneously, avoid "knowledge leakage" when people leave the organization. The study examines the relationship between knowledge management and the level of competitiveness of manufacturing SMEs in the automotive parts industry in the metropolitan area of Guadalajara. From the results, it is found that knowledge management increases the competitiveness of SMEs in the automotive parts industry. The limitations and future studies are also discussed.

Exploring the Relationship Between Circular Economy Practices and Growth in Manufacturing SMEs

The circular economy has been acknowledged as key for manufacturing firms, wishing overcome challenges, particularly relates it to business growth. However, the transition to linear economy at circular economy has been slow in literature, particularly there are relatively few studies that have focused on the relationship of circular economy practices and growth of small and medium-sized manufacturing companies, for this reason this study's main objective is to fill this existing gap in the literature. In addition, a self-administered questionnaire was distributed to a sample of 400 companies in the automotive and auto parts industry in Mexico, analyzing the data set using confirmatory factor analysis and structural equation models. The results obtained follow that the circular economy has a significant positive impact on the growth level of small manufacturing firms in the automotive and autoparts industries.

한국의 대(對)인도네시아 수출경쟁력 분석 및 한·인도네시아 CEPA 활용방안에 관한 연구

Purpose: This study analyzes the export competitiveness of Korean products in the Indonesian market. It suggests ways to use the Korea-Indonesia CEPA.
 Research design, data, and methodology: Export statistics on the main products in auto parts and the steel and petrochemical industries are extracted in terms of HS 4 units from the International Trade Centre Trade Map. The Trade Specialization Index (TSI) is calculated for Korea and Indonesia, and the Market Comparative Advantage (MCA) index is calculated for Korea and ASEAN countries in the Indonesian market.
 Results: From analyzing the TSI, Korea is dominant in the Indonesian market. Under the MCA index, compared to ASEAN countries, Korea had an absolute advantage in steel products. However, the petrochemical sector is competitive, and the auto parts industry is inferior.
 Conclusions: The automotive parts industry and the steel products industry are predicted to increase their competitiveness, but the analysis showed it will not be easy. In addition, the petrochemical sector should be more aggressive in marketing Korean companies by using the KI-CEPA, because local companies in Indonesia are increasingly competitive.

Links between components of business continuity management: an implementation perspective

PurposeThis research aims to examine the influences of preceding implementation phases on succeeding phases of business continuity management (BCM) comprising leadership, strategy, planning, application and maintenance.Design/methodology/approachData were gathered from 216 automotive parts manufacturers in Thailand. Descriptive statistics were employed to measure the maturity level of BCM implementation components. Path analysis of structural equation modeling was used to test hypotheses.FindingsThe study's findings found that the intensity of BCM elements decreased following the implementation phases. Leadership and strategy had the highest mean score, while maintenance had the lowest. Preceding phases had significant positive effects on succeeding phases. The direct impact of leadership on maintenance was much weaker than its indirect impact through strategy, planning and application.Originality/valueThis is one of the first examples of empirical research to investigate the sequential links between preceding and succeeding BCM implementation components. Strategic BCM elements and systematic implementation can improve and sustain BCM in the automotive parts industry in Thailand.

Microstructure and Mechanical Properties of Pack Carburized AISI 1020 Steel Using Na2CO3 and CaCO3 Catalysts

AISI 1020 steel is categorized in low carbon steel which widely used for automotive parts industry and construction because its characteristic like high ductility, relatively low hardness value, and high formability. In continuously usage for long time, this steel tends to be worn down because its low surface hardness value. The surface hardness is congruity to wear resistance of AISI 1020 steel. In this research, the experimental method of pack carburizing process was carried out by heating AISI 1020 steel samples packed along charcoal with catalysts variation of Na2CO3 and CaCO3 till temperature 900 oC and hold it for 4 hours to effect diffusion carbon mechanism in surface treatment. Thereupon, AISI 1020 steel samples was fast cooled by using distilled water. The selection of different catalyst variation according to diffusion capability which will be expected to enhance AISI 1020 steel’s microstructure and mechanical properties. From this research, it obtained that pack carburized AISI 1020 steel using Na2CO3 possesses significant microstructure transformation which will affect to the highest hardness value increment (505,4 HV) and the lowest wear rate decrease (0,00821 mm3/minute). Thereby, pack carburized AISI 1020 steel using Na2CO3 also exhibits good wear resistance characteristic so that can be used in long lifetime.

The effects of the Toyota Way on agile manufacturing: an empirical analysis

PurposeThe purpose of this research is to examine the impact of the Toyota Way (TW), TW pillars (i.e. continuous improvement, and respect for people), and TW elements (i.e. challenge, kaizen, genchi-genbutsu, respect, and teamwork) on agile manufacturing (AM) and AM elements (i.e. responsiveness, capability, speed and flexibility).Design/methodology/approachData were collected from 216 automotive parts manufacturers. Multiple and linear regressions were used to test the hypotheses.FindingsThe study found that overall TW and both pillars have significant effects on overall AM and all AM elements, except for the influence of continuous improvement on speed and flexibility. No individual TW element can improve every AM element. TW and AM are not mutually exclusive. To improve AM, managers should apply TW as a set of integrated technical and personnel elements rather than as isolated elements.Originality/valueThis study is one of the first to hierarchically explore the effects of socio-technical TW, TW's individual pillars and elements on overall AM and each AM element in the automotive parts industry. Findings from this research can be used to develop a socio-technical lean system to be integrated with AM more effectively leading to successful leagile manufacturing.

Evaluation performance of time series methods in demand forecasting: Box-Jenkins vs artificial neural network (Case study: Automotive Parts industry)

Production planning is a vital activity for manufacturing companies in managing any kind of organizational operations. One of the most important and vital tools that are considered necessary in production planning is forecasting future production demand. One of the most widely used approaches in demand forecasting is time series analysis. Also, two widely used methods in time series analysis are Box-Jenkins and Artificial Neural Network (ANN) approaches. In this study, the performance of these two methods to the types of errors and based on the concepts of multi-criteria decision making (MADM) has been investigated. These two methods are implemented for a product family in the automotive industry, and then the findings are compared and analyzed. The results showed that the Box-Jenkins method (Arima) provided much better predictions, which means that this method presented better results for 6 out of 8 products.

China's foreign direct investment in Mexico's auto parts-automotive industry:

In 2020 China displaced the United States as the main country of origin of cross-border M&A type investments and ranked fourth as the origin of new greenfield projects. In the regional context, since 2010 Mexico appears as the second destination of Chinese direct investment directed to manufacturing and as the first destination in the automotive auto parts industry (AAI). The article examines the determinants of Chinese direct investment in Mexico from a regional perspective and from the case study of the Chinese multinational Minth based on Aguascalientes, Mexico. The results allow us to conclude that the growing presence of direct investment by Chinese private companies in the AAI is explained by the favorable prospects for demand generated by the presence of global assemblers in Mexico and geographic and institutional variables such as the proximity whit United States, the agglomeration economies presence and benefits of the United States-Mexico-Canada Agreement (USMCA).

SWEEP ALGORITHM IN CVRP TO OPTIMIZE DELIVERY AUTOMOTIVE SPARE PART

The CVRP to solve many optimization and application problems distribution especially of the automotive spare parts industry, West Java, Indonesia is presented has 120 customers who aim to optimize and maximize the capacity and cost of vehicles owned, namely 10 colts 6 diesel type vehicles. Vehicle routes are compared against the existing daily distribution routes showing that significant savings can be gained on the daily cost of transportation-related expenses. The objective of this research is to find a set of optimal routes that minimize the number of vehicles required and total distance traveled for all vehicles to serve customers with a result from 10 to 9 using vehicles with a total distance increase from the Sweep method of 253.8347 km and cost benefits or cost savings with a total usage cost of Rp 17.800.000 to be Rp 17,709,503 in cost efficiency of 4.47% or Rp 90,496.58 a day.

Systems failure analysis using Z-number theory-based combined compromise solution and full consistency method

Financial and time constraints force managers to put limited failure modes in priority to implement corrective and preventive actions. Thus, how prioritization can be done more constructively is of particular importance. This study aims to introduce an improved Failure Modes and Effects Analysis (FMEA) technique based on an extension of the Combined Compromise Solution (CoCoSo) method and the Full Consistency Method (FUCOM) to assess and prioritize failures in a production process. These developed methods called Z-CoCoSo and Z-FUCOM rely on the Z-number theory. They can consider uncertainty and reliability simultaneously in determining the weights of risk factors and the value of these factors in the studied problem. The proposed approach can cover some shortcomings of the conventional FMEA technique employed in identifying potential failures before their occurrence. Applying this approach enables experts to consider different weights for risk factors and uncertainty in the risk assessment process and provides them with a reliable ranking with high separability. Implementing the introduced approach for a real case study in the automotive parts industry has been compared with FMEA and other existent versions of the used methods demonstrating its reliable prioritization.