Automotive Parts Industry Research Articles

A holistic model of dynamic capabilities and environment management system towards eco-product innovation and sustainability in automobile firms

PurposeEnvironmental pollution has emerged as a major concern in the 21st century following the introduction of sustainable development (SD) by the year 2030, whereby one of the predominant goals is related to the manufacturing industry. In Malaysia, the automotive industry is acknowledged as the backbone driving for economic growth and recognised as a source of environmental deterioration. Therefore, eco-innovation is, thus, introduced as one of the efforts for minimised environmental effects, reduced social impact and firm value sustenance. In particular, eco-product innovation is one of the renowned environmental innovation dimensions and displays high adoption and diffusion rates in developed countries due to green awareness and government financial assistance. However, developing countries such as Malaysia show relatively low adoption of such practices amongst companies, whereby most of the efforts are driven by the governments, supplier and customer demands. Therefore, this paper aims to delineate the factors of voluntary initiatives undertaken by the Malaysian automotive and auto parts industry towards eco-product innovation.Design/methodology/approachThe research drew from the micro-level perspective, thus using dynamic capabilities (DC) constructs and environmental management system (EMS) strategy variables. The constructs included technology collaboration, green human resources and eco-culture, while the variables denoted formal EMS and top management support. Survey data were obtained from 242 entities within the Malaysian automotive and auto parts industry, which were subjected to analysis via confirmatory factor analysis and structural equation modelling.FindingsThe findings revealed the moderating role played by eco-product innovation for the association linking EMS strategy and sustainability development, while no moderator effects were observed between DC and sustainability development. Thus, future research can be performed in the meso and macro-level areas by using qualitative research across different sectors.Originality/valueThis paper explicates novel literature content, particularly for the field of eco-product innovation; it positions an empirical analysis from the micro-level perspective regarding the antecedence of DC and environmental strategy towards eco-product innovation and SD, mainly in the automotive industry.

Green Entrepreneurial Orientation and Green Innovation in Small and Medium-Sized Enterprises (SMEs)

Since environmental issues are becoming an integral part of business performances, policymakers and managers have started recognizing the importance of green innovation towards sustainable business performances. The role of the automotive parts industry is crucial in minimizing environmental degradation and promoting sustainable development. Yet few studies have focused on the connection between green entrepreneurial orientation and green innovation that may affect small and medium enterprise (SME) business performance. Therefore, this study aims to analyze the influence of green entrepreneurial orientation on green innovations, and its effects on sustainable business performances in the automotive parts industry in Thailand. The sample consists of 226 SMEs in the automotive parts industry in Thailand. The partial least square method (PLS-SEM) has been used for the analysis of data. The results of the study show that green innovations have the strongest influence on economic and environmental performances. This study contributes to resource-based view theory by incorporating green innovation as a strategic competency of SMEs’ performance. Further, green entrepreneurial orientation and green innovation can assist SME managers in understanding the factors leading to sustainable performance of businesses.

Weight-loss Percentage Improvement of PVC Artificial Leather Products in Automotive Part Industry by Six Sigma

The purpose of this research was to improve the weight-loss percentage of PVC artificial leather products manufactured by the calendering process. It was noticed that the weight-loss percentage was greater than 5% which did not pass the specification given by the Original Equipment Manufacturer (OEM). Hence, the DMAIC Six Sigma methodology was applied to improve the situation. The cause-and-effect matrix and the Failure Mode and Effect Analysis (FMEA) were adopted to identify the potential factors that affect the quality of the products. After that, the design of experiment (DOE) was used to determine significant factors and optimal parameter settings for the production process to prevent a recurrence. The result shown that the average weight-loss percentage was reduced to only 0.9% after applying new parameter settings.

Innovation and SMEs patent propensity in Korea

This paper analyzes the patent propensity as an outcome of innovative activities of regional SMEs. To achieve the aims, we apply robust regression analysis to estimate the models to test 5 research hypotheses using 263 firm level data located at Gwangju region in Korea. Our empirical results show that a firm's industry characteristics, such as machinery and automotive parts industry, is negatively related with propensity to patent innovation. Also, unlike expectations, the InnoBiz firms designated as innovative SMEs by the government are not performing differently than general firms. Only the CEO's academic credentials are positively related with propensity to patent. From the findings, we can conclude that patenting propensity is not directly related with a firm's characteristics but mainly to CEO's managerial strategy. Also, we cannot find evidence for policy effectiveness from public support given to InnoBiz firms as part of the state policy to nurture photonic industry to boost regional economic development. Given the lack of strong policy effects, a new industry policy should be considered to actively promote SMEs innovativeness.

Eco-innovation and the circular economy in the automotive industry

PurposeCircular economy is emerging as a new sustainability paradigm. Similarly, eco-innovation is being recognized as one of the most important mechanisms that allow the transition from a linear to a circular economy in production processes, as there is a strong relationship between eco-innovation (eco-innovation of products, processes and management) and circular economy activities. However, the relationship between eco-innovation and circular economy is an issue that has been isolated and little analyzed in the academic literature. Therefore, this research fills this gap by exploring the interdependence between eco-innovation and circular economy.Design/methodology/approachThe research is conducted through an extensive literature review from where a research framework consisting of two measurement scales, 18 items and three hypotheses were developed. A self-administered questionnaire was distributed and 460 responses were obtained from companies in the automotive and auto parts industry in Mexico. The data obtained were analyzed through confirmatory factor analysis, descriptive statistics and structural equation modeling.FindingsThe results suggest that eco-innovation of products, process and management has a significant positive impact on the circular economy of companies in the automotive and auto parts industry.Practical implicationsThe findings of this research can inform managers in the automotive sector and policymakers when formulating and deploying environmentally sustainable strategies.Originality/valueThis paper fills a research gap by expanding the limited body of knowledge that relates eco-innovation and circular economy and providing some evidence of their relationship. The research also allows the unique characteristics of eco-innovation and the circular economy to be understood within a particular context, growing in this manner the body of knowledge on this field.

Forecasting system using single exponential smoothing with golden section optimization

Puri Wira Mahkota Ltd is a distributor company in the automotive parts industry. Puri Wira Mahkota has an obstacles in preparing weekly order on stock to the primary production unit. They predict total sales of product in the coming period just by using an expectation from stock administration staff then it will be compared with sales data in the previous period without any calculations using a definitive formula. Forecasting calculation could support Puri Wira Mahkota to predict the quantity of product. The purpose of this research is to apply the calculation process that can predict the quantity of product should be produced by the primary production unit every month and also to prevent over stock and out of stock. The method used in the forecasting calculation is Single Exponential Smoothing. To optimize Single Exponential Smoothing we used the Golden Section. The principle of the Golden Section is to reduce the alpha area boundary so it will produce an ideal forecast value with the minimum MAPE (Mean Absolute Percentage Error) level. This research shows the results that the Golden Section finds the optimal forecasting value with a level of MAPE (Mean Absolute Percentage Error) of 43.39%.

Eco-innovation practices’ adoption in the automotive industry

PurposeEco-innovation is a relatively recent construct in the literature, which nowadays more and more researchers and academics consider as one of the strategies that generate a higher level of sustainable and business performance. However, little is known about the influence of eco-innovation practices on sustainable performance and business performance, particularly in the automotive and auto parts industry. Therefore, this paper aims to fill this knowledge gap and explore the aforementioned interdependence.Design/methodology/approachThe influence of eco-innovation practices on sustainable performance and business performance is investigated through a research framework consisting of 5 constructs, 25 items and 6 hypotheses derived from an extensive review of the literature. A self-administered questionnaire was distributed to 460 companies in the automotive and auto parts industry in Mexico. The data were analyzed through a confirmatory factor analysis, descriptive statistics and structural equation modeling.FindingsThe results obtained indicated that eco-innovation practices have a positive influence on both sustainable performance and business performance in the automotive and auto parts industry.Originality/valueThis paper provides further insightful evidence of the influence of eco-innovation practices on sustainable performance and business performance, particularly in the automotive and auto parts industry.

An integrated (1, T) inventory policy and vehicle routing problem under uncertainty: an accelerated Benders decomposition algorithm

ABSTRACT Inventory control and logistics are both important to the success of a supply chain. These problems become highly complicated when the demand of end-users is uncertain. The demand uncertainty could have a considerable destructive effect on a supply chain, e.g. bullwhip effect. Therefore, this paper proposes a two-stage approach to study an inventory-routing problem for a three-echelon single-item supply chain, consisting of suppliers, manufacturers, distributors, and wholesalers. The approach utilizes the ordering policy in the first stage to determine the optimal replenishment ordering quantity of wholesalers under uncertainty. This stage aims to minimize the inventory holding and lost-sales costs. To the best of our knowledge, this is the first application of the policy to an inventory-routing problem. Afterward, a mathematical formulation is proposed in the second stage to study a new vehicle routing problem. This model minimizes the transportation cost. Based on the literature, the vehicle routing problem is NP-hard; therefore, a new accelerated Benders decomposition algorithm is developed to solve large-scale instances of the problem. The algorithm incorporates a modified -optimality accelerator. The computational results show the superior performance of the modified accelerator compared to the conventional one. To evaluate the performance of the accelerated Bender decomposition algorithm, we compare it with the mathematical programming and a Genetic algorithm using twenty benchmark examples. We also introduce and assess a real-case study in the automotive parts industry. Finally, we analyze some key features of the case study to provide managerial implications.

A hybrid multi-criteria decision making model for technological innovation capabilities measurement in automotive parts industry

A hybrid multi-criteria decision making model for technological innovation capabilities measurement in automotive parts industry

Colaboración entre centros públicos de investigación para el desarrollo regional: un análisis de caso en Aguascalientes, México

This article examines the economic, social and political context in which a strategic collaborative project based on the Triple Helix model to boost regional development emerges. The creation of a collaborative effort between public research centers to develop supply chains for the automotive and auto parts industry is taken as an example. It is used the case of the process of creation of the Center of Innovation and Technological Transfer of Aguascalientes for the Automotive Sector (CITTAA), in Aguascalientes, Mexico. The descriptive analysis emphasizes the time it took to set up the proposal, the short duration of a six-year term for the goal of promoting regional economic development, and the difficulties of establishing and promoting articulated collaboration between the actors of a triple helix.

Experimental design to enhance the surface appearance, the internal structure, and the shear stresses of injected and metallized polycarbonate/acrylonitrile–butadiene‐styrene parts

ABSTRACTPolycarbonate (PC) and acrylonitrile–butadiene–styrene (ABS) possess thermal and mechanical properties, which make them materials of choice for automotive components. These properties have presented PC/ABS as an eligible replacement for metals in automotive industry. The aim of this study was to explore a new approach to determine the optimum conditions for obtaining quality and shear stresses of the injected and metalized PC/ABS parts. For this purpose, the following six injection‐molding parameters such as material temperature (137ma), injection pressure (Pinj), holding pressure (Ph), mold temperature (Tmo), holding time (th), and cooling time (tc) were considered at four different values. The effect of the injection parameters studied has been analyzed through the quality and the shear stresses values of the injected and metallized PC/ABS specimens. Optical microscopic and confocal laser scanning microscope (CLSM) results demonstrate that the occurrence of some defects such as weld line, blister, poor adhesion, metal residue, sand scratch. Moreover, scanning electron microscope (SEM) findings show the presence of core defects and solidified pellets. Shear stresses vary between 3.78 and 5.8 MPa for the injected specimens and 4.5 and 6.4 MPa for the metallized specimens. The optimum injection parameter combinations were conditioned by producing flawless injected and metallized PC/ABS parts having a significant shear stress value. Thus, the optimum combinations consists of: a Tma of 260 °C, a Pinj ranging between 30 and 50 bar, a Ph ranging between 20 and 25 bar, a Tmo of 40 °C, a th ranging between 8 and 14 sec. and a tc of 25 sec. These findings may have interesting applications in automotive part industry. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020, 137, 48384.

Single Minute Exchange of Dies as The Solution on Setup Processes Optimization by Decreasing Changeover Time, A Case Study in Automotive Part Industry

Industrial competition nowadays demanding automotive manufacturers to increase productivity and organise lean production to meet all the targets. The rear axle manufacturer, one of the automotive industry in 2018, experienced production constraints that were unable to meet production targets. The Line Housing F as the object of this research had 9 machines that involved setup time for the changeover process out of 24 machines. The setup process was not being standardized, conducted manually and involved readjustment on the engine jig, which would, causes a long changeover time because the process was repeatedly carried out. This study aimed to optimize setup activities in order to reduce changeover time. The Single Minute Exchange of Dies (SMED) method was one of the applicable tools to reduce change over time, by changing the internal activities into external activities. In the final stage, SMED simplified the jig setting process by changing the jig design on the M16.3 machine and parallelizing the setup and process operations of the machine. The final results improved the 33% overall changeover time, from 58.36 to 39.22 minutes.

A hybrid multi-criteria decision making model for technological innovation capabilities measurement in automotive parts industry

Technological innovation capabilities (TICs) are currently one of the essential factors to enhance the competitiveness of enterprises. The measurement of TICs is a complicated decision making process and quite difficult to perform because its assessment involves multi-attribute criteria and the subjective judgements of experts. To solve these problems, this study provides a TICs evaluating model by employing a hybrid multi-criteria decision making (MCDM) technique. This method is an integration of four approaches, consisting of: 1) fuzzy Delphi; 2) fuzzy DEMATEL; 3) analytical network process; 4) technique for order preference by similarity to an ideal solution (TOPSIS). The final results showed the measurement criteria, the interrelationship and the relative important weights among criteria and the ranking of TICs of firms. An empirical study is also illustrated in Thai automotive parts firms as a case study. Furthermore, this study could assist industrial managers to efficiently evaluate TICs and its direction of improvement.

An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures

Identification and prioritization of failure modes in a system and planning for corrective actions are among the most important components of risk management in any organization. Meanwhile, conventional Failure Mode and Effects Analysis (FMEA) is one of the most commonly used methods for prioritization of the failures. Despite the widespread applications of this method in various industries, FMEA is associated with some shortcomings that can lead to unrealistic results. In this study, a proposed approach is presented in three phases to cover some of the shortcomings of the FMEA technique. In the first phase, FMEA is used to identify the failure modes and assign values to the Risk Priority Number (RPN) determinant factors. In the second phase, the Fuzzy Best-Worst Method (FBWM) based on the experts’ opinions is used to measure the weights of these factors. In the third phase, the outputs of the previous phases are used as a basis to prioritize the failures using the proposed Multi-Objective Optimization by Ratio Analysis based on the Z-number theory (Z-MOORA). In addition to assigning different weights to the RPN determinant factors and considering uncertainties of them, the Z-number theory is used in this approach to cover reliability in different failure modes. The proposed approach was implemented in the automotive spare parts industry, and the results indicate a full prioritization of the failures in comparison with other conventional methods such as FMEA and fuzzy MOORA.

La inversión asiática en el sector automotor de la región del Bajío, México

The Asian investment has had an important presence in productive sectors considered motors of the Mexican economy, and the automotive and auto parts industry is one of them . Its economic dynamism has grown especially since the entry into force of the North American Free Trade Agreement (nafTa), in 1994 . Since the 1980s, the economic policy of Mexico had among its objectives the growth of International Trade . In addition, it is considered that foreign direct investment (fdi) is extremely important for the creation of jobs; and although there have been few advances in this aspect; the expectation of creating productive linkages with the Mexican industry persists . Although, according to macroeconomic statistics, progress has been made thanks to this public policy, the truth is that only significant impacts of its location are observed at the regional level .The automotive companies of Asian capital are an essential part of the geographical configuration of the automotive and auto parts industry around the Bajío region, which is considered a very important corridor for it . For this reason, the present work focuses on identifying its size, structure and dynamism in this region since the entry into force of nafTa . Regional economic indicators and the causes that have contributed to the growth of Asian investment in the automotive sector are analyzed .

An Extension of the CODAS Approach Using Interval-Valued Intuitionistic Fuzzy Set for Sustainable Material Selection in Construction Projects with Incomplete Weight Information

Optimal selection of sustainable materials in construction projects can benefit several stakeholders in their respective industries with the triple bottom line (TBL) framework in a broader perspective of greater business value. Multiple criteria of social, environmental, and economic aspects should be essentially accounted for the optimal selection of materials involving the significant group of experts to avoid project failures. This paper proposes an evaluation framework for solving multi criteria decision making (MCDM) problems with incomplete weight information by extending the combinative distance assessment (CODAS) method with interval-valued intuitionistic fuzzy numbers. To compute the unknown weights of the evaluation criteria, this paper presents an optimization model based on the interval-valued intuitionistic fuzzy distance measure. In this study, we emphasize the importance of individual decision makers. To illustrate the proposed approach, an example of material selection in automotive parts industry is presented followed by a real case study of brick selection in sustainable building construction projects. The comparative study indicates the advantages of the proposed approach in comparison with the some relevant approaches. A sensitivity analysis of the proposed IVIF-CODAS method has been performed by changing the criteria weights, where the results show a high degree of stability.

Optimal Supplier Selection Model with Multiple Criteria: A Case Study in the Automotive Parts Industry

Optimal Supplier Selection Model with Multiple Criteria: A Case Study in the Automotive Parts Industry

Explaining variation in the social performance of lean production: a comparative case study of the role played by workplace unions' framing of the system and institutions

AbstractSeveral studies have acknowledged that lean production is implemented in diverse ways across workplaces, thereby generating different outcomes for workers. However, explanations for this variability needs further development. The present article addresses this issue by considering the role played by workplace unions' framing of lean production. It finds that unions' framing is derived from their identities in interaction with available resources in institutional and organisational terms. A case study comparison of the automotive parts industry in Italy and the United States was conducted.

Strategi Peningkatan Daya Saing Produk Suku Cadang Otomotif dan Elektonik Berbahan Karet di PT BesQ Sarana Abadi

In order to spur the automotive and electronic industries to meet domestic needs and compete in the era of globalization, the development of manufacturing industries is not only based on large-scale industries, but also needs to be developed into Small and Medium Enterprises (SMEs). The obstacles faced today are limited capital, human resources (HR), product development and marketing procedures. PT BesQ Sarana Abadi is a small and medium business (UKM) engaged in the business of making rubber parts. In order to improve competitiveness, PT BesQ Sarana Abadi is researched with the formulation of the right competitiveness strategy. The objectives of the study are: (1) to identify factors that influence the competitive advantage of rubber and automotive parts products; (2) analyzing internal and external factors that affect the competitiveness of rubber and automotive parts industry products using the Internal Factor Evaluation (IFE) and External Factor Evaluation (EFE) methods; (3) develop competitiveness strategies for the automotive and electronic spare parts products industry using Internal-External (IE) methods and Strengths, Weakness, Opportunities, Threats (SWOT) and Balance Score Cards (BSC); (4) formulating priority strategies to improve the competitiveness of rubber and automotive parts industry products using the Quantitative Strategic Planning Matrix (QSPM) method. From the analysis results, there are many weaknesses in the company. In this case a high opportunity value causes the company to operate, because in the IFE matrix the value of strength is greater than the value of weakness. In the EFE matrix, the opportunity value is greater than the threat. With the SWOT and BSC methods identified strategies needed, set the priority of the strategy by using the QSPM method.

Development of Soft Skills Learning Management Model for Automotive Parts Industry in Thailand

This research aims to: 1) study the labour competency; 2) design a learning management model; 3) propose a conceptual framework that can be references for further research on soft skills for business management. The learning management model in this research was being designed by a total of 17 Thai specialists and foreign experts in the automotive parts production field, whereby its design was based on the labour competencies studies in the industry and accordingly to the survey results from specialists. Moreover, the model was being incorporated into vocational education curriculums to study its effects. Thus, the study results have shown that the labour competencies in the automotive parts industry are divided into four categories, namely attributes, soft skills, hard skills, and knowledge, while according to the specialists, the learning management model can then be organised into 14 different learning stations for workers in the automotive parts industry.