Application of Statistical Quality Tools in the Root Cause Analysis of Industrial Management Errors in Small-Scale Industries pertaining to the Automotive Sector

International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2163
Issue 04, Volume 4 (April 2017) (SPECIAL ISSUE) www.ijirae.com
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Application of Statistical Quality Tools in the Root Cause
Analysis of Industrial Management Errors in Small-Scale
Industries pertaining to the Automotive Sector
Venkatesh Vaman Baliga and Aditya Dinker Hosangadi
Department of Mechanical Engineering
M.S.Ramaiah Institute of Technology, Bangalore, India
Abstract- The primary objective of this paper is to define and illustrate several quality issues that are commonly faced by
the automotive sector in India, and offer potential corrective measures to these problems using specific statistical quality
control tools. While the organised automotive sector has been highly successful over the past two decades, advancement
and improvement in the automotive sector have been hindered by a variety of issues related to the quality of their
products and services. This sector is crucial to the development of the Indian economy and plays an instrumental role in
the supply chain of the major players in the industry. The paper provides a comprehensive review and illustration of the
causes attributed to the inefficiency of the sector, and potential solutions to these issues, thereby enabling them to
ascend to the standards of organised service sectors.
Keywords: Statistical Quality Control, Lower Tier Suppliers, Automotive Components
I. INTRODUCTION:
Over the past few years, the Indian automotive and production sectors have been instrumental in boosting India’s economy
for a continued period of time, contributing to approximately 7% of its GDP. The automotive sector accounts for about
30% of the manufacturing sector in India. Despite several positive upturns in production techniques and optimization,
immense scope of improvement remains in the field of quality management, especially in the automotive sector. Although
several quality models and techniques have been employed at a number of companies, the quality of the products produced
in the country is not comparable to that of other leading automotive exporters in the present global market. Fallacies such
as these result in customer dissatisfaction which has in turn prevented the sector from obtaining a definitive cutting edge,
and may create further problems in the near future. In order to assess the impact of quality management on the success of
an industry, it is imperative to obtain accurate feedback from the customers of the same. In this regard, the data collected
from a survey conducted by KPMG illustrates that respondents at the customer end clearly prioritise the quality of service
and products. (Fig.1.1) The success of established automotive conglomerates serves as a testament to the importance of
quality management.
Fig. 1.1: KPMG India Customer Survey

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Therefore, the automotive industry can truly transform into a global market leader by ensuring significant improvement in
the implementation of proven quality models and standards. While taking into consideration the strengths of the automotive
sector, this paper focusses on the problems and challenges faced by the industry in the current market scenario.
1.1 RESEARCH OBJECTIVE:
This paper aims to assess the current level of quality management in the automotive sector in India and attempt to provide
solutions to several challenges faced by the sector today, while taking into account the financial and operational constraints
involved in implementing these solutions.
1.2 RESEARCH METHODOLOGY:
The methodology adopted by the paper is based exclusively on observations and studies conducted at automotive
companies across the country. A number of established methods have been implemented to measure the level of quality
management in various companies. This paper has been complemented by the use of several standard quality tools such as
the SWOT Analysis and the Ishikawa diagram.
II. SWOT ANALYSIS:
Prior to providing solutions to the problems existing in the automotive industry, it is essential to possess a thorough
understanding of the sector, including its current strengths and weaknesses. A SWOT analysis is a simple and effective tool
used to assess the strengths and weaknesses of a process, system or organisation, and has been conducted to describe both
the positive and negative aspects of the automotive sector. The analysis makes it evident that despite several obstacles, this
sector has several opportunities to improve.
2.1 STRENGTHS:
1. Availability of land
2. Established manufacturing and production base
3. Availability of human resources and skilled labour
4. Export subsidies and the recent influx of automotive giants in the domestic market
2.2 WEAKNESSES:
1. Limited product knowledge at worker and managerial level
2. Inability to adopt advanced production techniques
3. Relatively poor infrastructure
4. Lack of investment in R&D
2.3 OPPORTUNITIES:
1. Increasing demand for automotive products
2. Expansion into foreign markets
3. Opportunities to implement advanced quality models
4. Low cost of labour in the Indian market
5. Immense scope for expansion
Fig. 3.1: Ishikawa diagram of problems in the automotive sector
2.4 THREATS:
1. Competition from countries like China, Myanmar etc
2. Development of advanced technology patented by foreign companies
3. Appreciation of Rupee
4. Volatility of fuel prices and government regulations such as excise duty, etc.

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By providing an unbiased view of current scenario from a technical and financial point of view, the SWOT Analysis
reveals a pressing need to implement quality management techniques in rural markets and the automotive sector.
III. CAUSE AND EFFECT ANALYSIS:
To develop a better understanding and categorisation of the problems in the automotive sector and the impact of these
problems on the productivity of the industry, a cause and effect analysis has been conducted using an Ishikawa diagram,
shown in Fig. 3.1.The Ishikawa diagram categorises and pinpoints a number of specific problems that exist today in the
industry. To truly understand the magnitude of some of these problems, it is required to discuss them in further detail. The
most critical issues are explained as follows:
1. PERIODIC CALIBRATION OF MEASURING INSTRUMENTS:
Measuring instruments in most manufacturing companies are rarely calibrated. These issues may result in faulty products
being dispatched as good products, or vice versa. In both scenarios, customer dissatisfaction is caused, either due to defects
in the product or increased service time.
2. LACK OF PROBLEM SOLVING MIND-SET:
The middle management in the automotive sector is primarily focussed on production rates and deadline requirements.
However, in several cases, it is found that a slight increase in quality or first pass yield for large volumes of production can
result in sizeable monetary benefits. To achieve these quality standards, specific TQM concepts must be applied by every
single employee of the company.
3. LACK OF PRODUCT KNOWLEDGE:
Most companies in the country import designs from foreign countries and export manufactured products. Therefore,
employees and managers of the company are not concerned with the exact working of the product and its applications. This
gives rise to a number of obstacles in the root cause analysis of defects.
4. ADAPTING TO A CHANGING MARKET:
The automotive sector in India is undergoing a period of transition, with the advent of hybrid vehicle technology and use of
cleaner fuels. Accordingly, the mind-set and techniques employed by the management to produce components that can
cater to these changes in demand must adapt accordingly.
5. LACK OF EMPLOYEE MOTIVATION:
Machine level workers in today’s automotive industries suffer a lack of motivation to pursue problems related to quality
management. Problem solving can be accelerated by encouraging these workers to provide their own inputs in the problem
solving process.
6. CHAIN OF DEFECTS:
One defect can create a chain of deviations and affect the overall performance of the product. These deviations involve
field issues as well as operational and supply chain issues.
Field issues include technical defects such as engine seizure, whereas operational problems such as time lag and improper
inventory control impede production.
7. MIX-UP OF COMPONENTS:
Most automotive products are assemblies of several components. Due to negligence and other related causes, there have
been several cases of a mismatch or interchange of components in assemblies. This results in large volumes of defective
products being produced.
8. CONFLICT BETWEEN THE PRODUCTION TEAM AND THE QUALITY DEPARTMENT:
In most industries, priority is given to achieve the production volume by the specified date, and an ongoing investigation on
product defects can be delayed due to unavailability of men and machinery.
9. IMPROPER PACKAGING AND DISPATCH:
Weak polythene covers and improper packaging results in defective components being received by the customers. Products
with sophisticated components need to be subjected to vibration testing to simulate the Indian road conditions to avoid
resonance and consequently, a catastrophic failure.
IV.STATISTICAL QUALITY CONTROL
The quality tools mentioned in the paper provide a detailed description of some of the current tools currently implemented
by the automotive industries. The data and graphs included in the paper are samples derived from hypothetical experiments,
with the sole purpose of providing a comprehensive understanding of the Statistical Quality Control tools that can be
implemented effectively and at low cost by the automotive sector. A total of 6 tools have been described as follows with
suitable examples:
1) PARETO ANALYSIS: The Pareto chart is a common quality tool used across large production companies and OEMs, mainly
to solve production related problems. This is a low cost tool that can be easily applied at the lowest levels of management.
The Pareto analysis has proven to be one of the best forms of utilisation of data in the field of total quality management.
A sample Pareto Analysis of internal rejections for a given process is shown in Fig. 4.1.

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Fig. 4.1: Sample Pareto Chart
2) ISOPLOT:
After identification of any given issue, the first step towards solving it involves measurement of a response parameter of a
set of sample products. The accuracy and precision of these measurements are crucial to the solution of the problem. To
this end, isoplots can be effectively used to check for measurement variation in any given measuring instrument. A ratio is
calculated and specific standards are applied to arrive at a reliable conclusion. This technique can easily be applied at low
cost and requires limited training. Fig. 4.2(a) and 4.2(b) illustrate the isoplots drawn for two random sets of data. A capsule
is drawn using all but two extreme data points. The process variation is measured along the horizontal axis, while the
measurement variation is taken across the width of the capsule. A discrimination ratio – the ratio of process variation to
measurement variation – can be calculated to obtain an idea of the extent of variation in the measuring instrument.
Fig. 4.2 (a), (b): Isoplots for sample data sets
3) BOX PLOTS:
While isoplots are used to check the accuracy of a single measuring instrument, box plots can be used to measure the
accuracy and repeatability of multiple instruments on a single graph..
Fig. 4.3: Box plot for sample data set

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There exist several scenarios in the industry where experimental trials entail the measurement of several hundreds of
samples. In such cases, it is imperative to measure the parameters of these samples across multiple measuring instruments.
Box plots are a commonly used statistical tool to measure the net measurement variation across a multitude of measuring
instruments. Fig. 4.3 shows a standard boxplot, which uses data of arbitrary flow rates of a specific product measured first
at the machine and consequently at 4 different inspection stations. Consider a hypothetical variation of 45cm3
/min obtained
across these stations. The values of variation for each machine can then be compared with suitable control limits to assess
the precision of measurement across various machines.
4) HISTOGRAM:
Histograms can be used at minimal cost by the automotive sector to consolidate large amounts of data and analyse them.
Specific control limits can be assigned to the histogram to analyse samples that do not conform to a given specification. In
addition to an analysis of the distribution, histograms can also be used to assign specific causes to different ranges of the
distribution. This method is purely statistical and involves little to no cost.
Fig. 4.4: Histogram for sample data set
Fig. 4.4 illustrates a sample histogram for fluid (drop) leakage from a given product per unit time. A normal distribution
can be plotted and suitable steps can be taken to ensure statistical process control.
5) 5-WHY ANALYSIS:
This is a popular method used in several leading automotive companies to pinpoint the root cause of a given problem. The
method requires brainstorming sessions and considerable skill, but direct expenses are negligible. The 5-Why method
involves time dedicated by the employees to assign causes to specific problems. Containment actions to each of these
problems can also be formulated and implemented. The solutions that result from this analysis are highly specific to the
given problem. Therefore, the thought process involved in analysing a given problem may not be effective to analyse a
wide variety of other issues.
Fig. 4.5: RCA for sample problem
Fig. 4.5 illustrates the methodology used to conduct the 5-Why analysis, and clearly presents its inherent advantages.

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6) 5S METHOD:
The 5S method is a management tool that can be applied to any industry. It involves a 5 point procedure of Sort, Set-in-
order, Shine, Standardise and Sustain. This method ensures extremely efficient workplace management, and can be
implemented at zero cost.
V. POTENTIAL SOLUTIONS:
In addition to Statistical Quality Control tools, several additional solutions can be implemented to solve specific problems,
as well as increase the overall quality of products and services. Although initial investments are required to implement
some of these solutions, the net increase in quality obtained over a period of time will prove to be extremely profitable to
the sector. These solutions are listed as follows:
1) TOOLS AND MEASUREMENTS:
• Highlighting common mistakes and means to correct them
• Keeping track of measured values and finding deviations and their causes
• 5S for tools, especially sorting, to reduce overall lead time
• Periodic calibration (checking the checker)
• Stringent quality inspection at vendor level
2) GOVERNMENT INITIATIVES:
• Quality awareness programs
• Sector specific certified courses for labourers
• Collaboration with ITI and technical training institutes to enhance influx of skilled labour
3) WORKFORCE MANAGEMENT:
• Periodic internal audits
• Implement OSHA and offer remuneration to attract labour.
• In-house job rotation for the labourers
• Centralized database linked to every precision machine
VI. CONCLUSION
The main objective of this research was to offer specific remedies to the quality issues faced by the automotive sector in
India. This sector generally serves as a supplier to multinational automotive companies and OEMs, and plays a vital role in
the economic ecosystem of the country. This directly implies that an effective implementation of the solutions and tools
presented by the paper will ensure a cumulative and substantial increase in the overall quality of products and services in
the automotive sector. In addition, this paper reveals further scope for future research to develop innovative and cost
effective methods to implement these solutions in the lower tier suppliers of the automotive industry. The results of this
research also directly benefit the society as an increase in quality of the sector will result in an exponential increase in
customer satisfaction within the automotive industry.
VII. REFERENCES
[1].Sachin Borgave and Chaudhari J.S, “Indian Auto Component Industry: Challenges Ahead” published in International
Journal of Economics and Business Modeling, Vol. 1, Issue 2
[2].RajnishKatarni and Satyendra Sharma, “Measurement of Service Quality of an Autmobile Service Centre” presented at
the 2010 International Conference on Industrial Engineering and Operations Management, Dhaka Bangladesh
[3].KPMG India, “The Indian Automotive Industry: Evolving Dynamics”
[4].Keki R. Bhote and Adi K. Bhote, World Class Quality: Using Design of Experiments to make it happen, Second Edition

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