INFLUENCE OF EXPECTED RISK AND DEFECTS ON VEHICLE RECALL IN THE AUTOMOBILE INDUSTRY: A QUALITY DIAGNOSTIC PERSPECTIVE

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International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 11, November 2018, pp.1725 1731, Article ID: IJMET_09_11_180 Available online at http://www.iaeme.

1 International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 11, November 2018, pp , Article ID: IJMET_09_11_180 Available online at ISSN Print: andISSN Online: IAEME Publication Scopus Indexed INFLUENCE OF EXPECTED RISK AND DEFECTS ON VEHICLE RECALL IN THE AUTOMOBILE INDUSTRY: A QUALITY DIAGNOSTIC PERSPECTIVE Parveen Roja.M, Geethanjali.N and Sindhya.R Associate Professor, Department of Management Studies, PSNA College of Engineering & Technology, Dindigul, Tamilnadu, India ABSTRACT Quality is the implied norm of the modern era. That too reliability and safety features of the automobile vehicles could not be compromised which could result in risking lives. But even with the latest technologies, research and development initiatives of the automobile manufacturers, the defects still persist in the components and procedures adopted in manufacturing the cars. It results in failure in performance of cars that shatters the customer expectations and dissatisfies the customers leading them to complain about their vehicles. Hence some automobile manufacturers resort to recall their defective vehicles for setting right the defects. The current study focuses on finding the effect of the expected risk, categorical and component failures on recall of cars. The study found the safety devices a failure is high followed by mechanical failures. Keywords:, recall, category, component, risk Cite this Article: Parveen Roja.M, Geethanjali.N and Sindhya.R, Influence of Expected Risk and Defects on Vehicle Recall in the Automobile Industry: A Quality Diagnostic Perspective, International Journal of Mechanical Engineering and Technology, 9(11), 2018, pp INTRODUCTION In the technology-prone world, customers want every product to be updated to satisfy them. It requires every organization to be quality-conscious. That too, in automobile industry the reliability is not expected only in performance but also has its direct impact on the life of the travelling passengers. For those kind of products, it is very much essential to undergo the reliability testing, burn-in testing, stress testing, conducting simulations, studying failure modes to address them and reduce the effects of such failures and conducting fault-tree analysis to be pro-active in preventing those identified failures. Automobile companies are known for their quality initiatives who adopt all these techniques and tools to increase the quality of end product and prevent these failures. But still the automobile industry ends up with product failures that may result in the risk of crash, fire or injuries. Automobile vehicles are the editor@iaeme.com

2 Influence of Expected Risk and Defects on Vehicle Recall in the Automobile Industry: A Quality Diagnostic Perspective combination of mechanical, electrical, electronic and software components. The current study analyzed the recall of cars to find the effect of the failures in any of these components that has the probability of resultant risky outcomes. Recalls are the last resort of manufacturers to restore the quality and reinforce the customer satisfaction. But still recalls are openly publicized that creates a sense of doubt in the minds of the customers. Recalls indicate the nonconformance of vehicle quality to the expected standard, norms and design. Even the leading manufacturers are not exception to it. The reputation earned for many years as the manufacturer of quality product is shattered with the failures. The trustworthiness of the recalled models is questioned. Even the new versions, new products or even the existing products from the same manufacturer are subjected to this doubt as to their reliability in performance and safety. Recalls are normally initiated by the manufacturers to address the customer complaints. Recalls result as the reverse logistics that reverses the flow of information, product and the cash. It involves complex procedures involving time and energy. Recalls result in high costs to the manufacturers since the rectification of defects is done free of cost to the customers. It increases the irrecoverable financial loss to the manufacturers. Vehicle failures uncompromised costs to the customers that may result in property loss, physical injury and even death of their kith and kin and that even ended up the manufacturers landing up in courts of law. Hence manufacturers had to face the litigation costs as well. Since recall is the reactive steps to pacify the affected customers, it has to be handled with utmost care. Otherwise, it would lead to high dissatisfaction among the customers and affect the customer retention and sales to the manufacturers. The more the time taken for recall, the higher the dissatisfaction would be. 2. LITERATURE REVIEW Base et al. (2007) has found that the increasing trend in the cars recall and the recall rates differ among the car manufacturers. Kamrul Ahsan (2013) has analyzed the trend of car recalls and found that the customer complaints even about the leading cars that ends up in recall. Yong-Kyun Bae and Hugo Benitez-Silva (2013) have studied the effect of automobile recall in lessening of crash and injuries. They concluded that accident rate decreases in the first year of recall of new model vehicles. John Ni and Xiaowen Huang (2017) have studied the recall lead time from discovery of failure to official announcement and found that it took longer time for the recalls on external reports, suppliers failure, design defects and that includes many models. 3. METHODOLOGY The study is done based on the secondary data of recalled cars collected from the public and private websites for the period from August to October 2018.The study is a descriptive research focused on finding the important types of failures that has the probability of risk resulting in vehicle recall by the manufacturers. The research model of the study considers the crash and fire as the high category and injury as the low risk category. The expected risky outcome is the criterion variable and the types of failure are the predictor variable that initiates the recall editor@iaeme.com

3 Parveen Roja.M, Geethanjali.N and Sindhya.R Figure 1 Research model on vehicle recall 4. RESULTS AND DISCUSSION The effect of expected risk, categorical and component failures on recall was analyzed the hypothesis tested in this study are: H1: There is no significant difference in the effect of component failures on recall. H2: There is no significant difference in the effect of failure categories on recall. Both H1 and H2 are rejected, since the significance value is.000 (p<.05). Hence the there is significant difference in the effect of failure of categories and components that results in recall. Table 1 Model Summary of regression Model R R Square Adjusted R Square F Sig 1.863a b a. Predictors: (Constant), Risk, Category, Component 1 Model Table 2 Regression coefficients a Unstandardized Coefficients B Std. Error Beta Standardized Coefficients t Sig. (Constant) Component (x1) Category (x2) Risk (x3) a. Dependent Variable: Recall The resultant equation would be y= x x x3 The regression results show that recall is directly related with the component failure, categorical failure and the expected risk factor. Every unit increase in the categorical failure results in time s higher recall. Every unit increase in component failure results in time s higher recall. Every unit increase in expected risk results in time s higher recall. Hence the expected risk of life is the most important factor that is considered for recall followed by the categorical failures and component failures editor@iaeme.com

4 Influence of Expected Risk and Defects on Vehicle Recall in the Automobile Industry: A Quality Diagnostic Perspective Table 3 ANOVA post-hoc test on categorical failures (I) Category (J) Category Mean Difference (I-J) Sig. Mechanical Electrical *.000 Electronics *.000 Software *.000 Safety accessories *.000 Information *.000 Table 4 ANOVA post-hoc test on component failures (I) Component (J) Component Mean Difference (I-J) Sig. Airbag Camera *.000 Battery *.000 Brake *.000 Brake light *.000 Canister purge valve *.000 Capacitors *.000 Convenience charge cord *.000 Crankshaft sensor *.000 Crash protection plate *.000 Cross member *.000 Door striker bolts *.000 Driveshaft *.000 Electronic Power steering Gearbox *.000 Engine control software *.000 Exhaust gas *.000 Fuel pump *.000 Gearbox ventilation hose *.000 Head lamp *.000 Heating mats *.000 Lane keeping assist *.000 Latch *.000 Occupant classification system *.000 Power relay assembly * editor@iaeme.com

5 Parveen Roja.M, Geethanjali.N and Sindhya.R (I) Component (J) Component Mean Difference (I-J) Sig. Mechanical Power steering pump drive belt adjuster pulley *.000 Power train controller *.000 Rear differential *.000 Relay *.000 Seatbelt *.000 Spot welds *.000 Springs *.000 Supplemental restraint system control unit *.000 Track bar bracket *.000 Upper control arms *.000 Valve block assembly *.000 Weight rating *.000 Window bonding *.000 Wiring harness *.000 Table 5 Categorical s leading to recall Electrical Electronics Software Safety accessories Information Total Recall The results of ANOVA show that there exists significant difference among the categories in failure (F= , p=.000 <.05). The Tukey post hoc test discloses that Safety devices failure is leading (p=.000<.05) and is followed by mechanical failures. The results of ANOVA show clearly that there exists significant difference among the components in failure (F= , p=.000 <.05). The Tukey post hoc test discloses that airbag failure is leading (p=.000<.05) followed by defects in seatbelt, canister purge valve, wiring harness and brake failures editor@iaeme.com

6 Influence of Expected Risk and Defects on Vehicle Recall in the Automobile Industry: A Quality Diagnostic Perspective Figure 2 Components and Categorical defects leading to recall of cars 5. MANAGERIAL IMPLICATIONS The exploding airbags and failure of airbag inflation are found to be the common causes for the airbag failure. Hence utmost care has to be taken to improve the airbag inflator system and the seatbelt pretensioner. The mechanical failures could be brought down focusing to reduce defects in canister purge valve and break system. The electrical failures could be minimized by reducing the wiring harness defects. The electronic failures could be brought down by reducing the relay defects. With the automated driving getting popularized among the luxury vehicles, software malfunctioning has to be reduced to increase the reliability of such vehicles. Complete information about the cars has to be disclosed to the certification agencies and to the customers. 6. CONCLUSION The study concluded that safety devices malfunctioning and the expected high risk of life results in high recall of cars followed by mechanical failures. The defects in the components leading to the recall have also been discussed. The automobile manufacturers could pay more attention to these categories and components applying the fault tree analysis to find the reasons for these defects in detail and undertake the failure mode and effects analysis to prevent these errors. Those measures recommended in the failure mode and effect analysis could be implemented and the results could be monitored. Recall could not complement the quality and could affect the reputation, customer retention and sales turnover editor@iaeme.com

7 Parveen Roja.M, Geethanjali.N and Sindhya.R REFERENCES [1] Ahsan, Kamrul. (2013). Trend Analysis of Car Recalls: Evidence from the US Market. International Journal of Managing Value and Supply Chains /ijmvsc [2] Bae, Yong Kyun & Benitez-Silva, Hugo. (2013). the Effects of Automobile Recalls on the Severity of Accidents. Economic Inquiry /j x. [3] Bates, H. et al. (2007). Motor vehicles recalls: Trends patterns and emerging issues. The International Journal of Management Sciences,. 35(2): [4] John Ni and Xiaowen Huang (2017). Discovery to Recall in the Automotive Industry: A Problem Solving Perspective on Investigation of Quality s. Journal of Supply Chain Management. 54(2). [5] Jiuchang Wei, Ming Zhao, Fei Wang & Dingtao Zhao (2016). The effects of firm actions on customers responses to product recall crises: Analyzing an automobile recall in China. Journal of Risk Research. 19(4). [6] Hilary Bates and Nick Oliver (2004). Motor Vehicle Recalls: Trends, Patterns and Emerging Issues. ESRC Centre for Business Research, University of Cambridge Working Paper No [7] NHTSA [8] editor@iaeme.com

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