2015 02 27_ research on car painting quality control based on fmea and spc v5

I

摘要

质量专家所使用的术语“标准”涵盖了很多内容，比如指标、规格、量具、报表、

分类、分段、分组或者行为。管理标准提出了组织培训、质量审核、质量管理系统的需

求。全球汽车制造业要求世界一流的产品质量、生产力和竞争力以及持续改进。为了达

到这个目标，许多汽车制造企业使用质量控制工具来提高产品质量从而达到零缺陷和较

高的客户满意度。当今，有很多质量工具被应用到快速解决问题中，但是我们需要找到

又快又有效的解决方法。

本文的重点在于潜在故障的识别；生产过程中可能会发生故障，会导致车辆报废、

返修，影响内部生产和质量目标（缺陷控制率）。在全面研究生产过程和生产数据（故障

原因、故障率和数据）的基础上，FMEA发现了在汽车喷涂过程中具有较高风险优先级的

薄弱环节，这就要求通过识别和处理缺陷来降低风险从而提高汽车表面喷涂的过程质量。

对于分析汽车表面缺陷的改进，SPC工具在缺陷可视化方面更有效。SPC图表是制造业用

于了解、控制和提高生产过程的数据的时间序列图，它虽然建立在统计理论领域基础上，

实践者使用和解释起来也很容易。

为了实现汽车表面涂装零缺陷的目标，本文应用 PFMEA 技术对缺陷分优先级，统计

分析造成缺陷的原因，通过持续改进过程控制缺陷。

关键词：质量管理，FMEA，SPC，控制图，质量改进控制，优化的过程

II

Abstract

Quality professionals use the term “standards” to mean many things, such as metrics,

specifications, gages, statements, categories, segments, groupings or behaviors. Management

standards address the needs of organizations in training, quality auditing and

quality-management systems. The global automotive industry demands world class levels of

product quality, productivity and competitiveness as well as continual improvement. To

achieve this goal many vehicle manufacturers company using quality control tools to improve

the quality of the product with zero defects and highly satisfied to the customer. Now days,

there are lot of quality tools applied to solve the problem quicker but it’s still the fact to find

out good and efficient solving way.

This thesis papers emphasis on identification of potential failure; failures may

encountered in the production process and its will leads to car scrap, rework and influence of

the internal production and quality target (defects control rate). After the complete study of

manufacturing process and production data -failure causes, failure rate and data etc. FMEA

discover the weak processes in the form of higher risk priority number in the manufacturing of

the car painting process, which required reducing by identifying and implementing of the

defects and this will improve the process quality of the painting surface of the car. To analysis

the improvement of the car surface defects SPC (Statistical process control) tools are more

efficient where can easily visible the defects trends.SPC chart are chronological graphs of

process data that are used in manufactures industries to help understand, control and improve

process and that although based in statistical theory area easy for practitioners to use and

interpret.

In order to orient goal of zero defects of the car surface use the PFMEA technique to

prioritized the defects and statistically analysis the roots cause of the defect and control the

defects through continues improvements process.

Key Words: Quality management, FMEA, SPC, Control technology, Quality improvement

Control, Optimization process

III

Table of Contents

1.1 Importance of the quality management in the automotive industry…………………..2

1.2 Goal and significance of the FMEA & SPC.................................................................. 3

1.3 Quantitative quality management ................................................................................. 4

1.4 Development of the FMEA and SPC ............................................................................ 5

1.4.1 Oversease development ....................................................................................... 5

1.4.2 Internal development ........................................................................................... 7

1.5 Research of the SPC and FMEA models ...................................................................... 7

2.1 Introduction of the FMEA methods .......................................................................... 10

2.2 FMEA approach .......................................................................................................... 11

2.3 Implementation methods for FMEA ......................................................................... 12

2.4 The interaction between SPC system and FMEA repository ...................................... 16

2.5 Significant of the SPC in the manufacturing process.................................................. 17

3.1 Identify the potential defects through painting process .............................................. 20

3.1.1 Car painting process methods ........................................................................... 21

3.1.2 Process related factors of paint performance .................................................... 24

3.2 Quality aspect of the painting process ........................................................................ 27

3.3 Process Monitoring and Regulation ............................................................................ 30

4.1 Data collection and statistical analysis ....................................................................... 32

4.2 Potential root cause and risk analysis by FMEA ........................................................ 34

4.3 Reflow SPC measurement data .................................................................................. 37

4.4 Evaluation of the data ................................................................................................. 38

4.5 Defects control system ............................................................................................... 39

摘要............................................................................................................................... ……...I

Abstract ………………………………………………………………………………………II

CHAPTER1 INTRODUCTION… ………………………………………………………………..1

CHAPTER2 SPC AND FMEA METHODOLOGY……………………………………………………..10

CHAPTER3 PAINTING PROCESS & DEFECT ANALYSIS………………………………………20

CHAPTER4 DATA ANALYSIS AND DISCUSSION………………………………………………...31

Master's Degree Dissertation of Shenyang University

IV

CHAPTER5 - CONCLUSION …………………………………………………………………....44

References …………………………………………………………………………………45

Research project ………………………………………………………………………….48

Acknowledgement.………………………………………………………………………….49

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Chapter1 Introduction

1.1 Importance of the quality management in automotive industry

Considering the incessantly increasing requirements to the quality of products and

process, it is necessary to improve a quality-oriented management in all types of

manufacturing company. In addition to diverse technical requirements are also considering

the requirements of the national, international and company specific norms. The company

must not only fulfill the requirements of the quality, but also the requirement of safety,

environment and economy. As following some aspect of the manufacturing quality

management and their integration manufacturing process will be introduced. Usually

technological advance will lead to process improvement with time and could ultimately

approach the states of the Zero-defect. In the tremendous, competition, survival of the fittest

is the law of competition in the market. The manufacturers need to use what kind of products,

entirely by the market to make a fair conclusion. Automotive products only “high quality

low cost “in order to dominate the market, and seek survival and development of space. In

such a climate conditions, automobile production quality, efficiency, resilience has become

hard in pursuit of the goal of the manufacturers and the increasingly fierce market

competition, forcing the manufacturers must continue to introduce new varieties, while

meeting the needs of users [1]

. In order to quickly seize the market, car manufacturers must

be more variety, fast-paced, high-quality mixed production , what products the market

needs ,we can as fast as the best products to the market[ 2 ]

.

In automotive company, Paint shop top coat inspection line is one of the important areas

to produce the car smoothly without major defects formation. It’s very common fact that, in

the top coat inspection line can highly influence the production rate and efficiency if there is

no control of the defects and solving of the root cause of the defects origination. For rational

and effective use of top coat inspection line, we must solve the problem and must control the

defects to get the high quality results of the automotive cars.

1.2 Goal and significance of the FMEA & SPC

Since market competition goes higher day by day extremely, each car plant must

continue to introduce new models to meet different user needs. In order to achieve the largest


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profit of the product, we must do everything possible to reduce input costs and the cost of

production models, so SPC and FMEA process methods, will promote the further

development of its manufacturing technology. The complexity of the equipment, costly

materials and wrong process standard will increase the rate of the production and influence

the target of the production. Most of the automotive company’s one of the big issue is the

repairing cost and repairing rate out of control[3]

.As China's major automobile gradually

enrich our product range, high cost performance SPC and FMEA technology will have

broad application prospects.

Mass production system is important for the all automotive company in order to get the

high value of the production. After the lean production method invented in Japan, People is

beginning to thinking about the quality, cost, and efficiency. At the beginning time the USA

automotive car always prefer to the Mass production but after the lean production theory

using globally all automotive car company peoples thinking how to reduce the cost , how to

achieve the zero defects and satisfied the customer to sell the car with low price and with the

tremendous quality [4]

.

In order to satisfied the customer requirement many of the research about the quality

control methodology and in this title the main focus will be how to control the defects with

SPC control model and find out the defects root cause of the defects and get the solution as

well as get the better quality of the products.

Goal of the SPC and FMEA model

(1) In the automotive company the processing time is very short .If the car take lot

processing time then the cycle time will getting longer and the production rate will get

lower. ,The SPC and FMEA model will help to solve the problem and lead to mass

production in a short time and put into the market, So that enterprises in the market occupies

more components and get opportunities[5]

.

(2) The materials cost is higher and the equipment is costly. The development of the

new model can control the defects which will increase the line efficiency. If the paint shops

top coat creates small kind of defects which will lead to increase the production cost and

efficiency as well as waste the lot of time. According to the monthly view the most of the

time waste in the top coat line because of the defects and which increasing the repairing rate

and operator do the overtime everyday which creates the labor cost as well as put into


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production, human, energy consumption, etc. but it can save considerable costs. Under

normal circumstances, the new models will help to reduce the cost of the labor, shorting the

time, reduce the materials cost without changing the production line of station, operating the

number of workers, equipment, also remained unchanged. After using the new technology it

will greatly saving the cost of production, and equipment, electrical and other kinds of

resources can be more fully utilized. Transformation of production lines required for a

relatively short time, usually require only 4-6 months, the newly developed mass production

models in a short time, and put into the market, so that enterprises in the market has more

weight and get opportunities[6]

.

(3)Statistical process control (SPC) is an important real-time online method by which a

production process can be monitored and control plans can be monitored and controls plan

can be initiated to keep quality standard within acceptable limits .Statistical quality control

provides offline analysis of the big picture such as what was the impact of the previous

improvements [7].

(4) The FMFA is an important tools which can help us to find out the root cause and

solve the problem according to the defects priority and SPC help us to find out the control

methods and evaluating the trends of the values and which can easily understand the

situation of the line and according to this situation find out the solution way [8].

In the paint shop plant, as the equipment is different, in the same station the working

procedure is different, even the working time is different, in order to each of the different

process on the specified position to complete the work of specified parts, not only need to

consider the limited stations but also I can get to the need to install the parts, but also need to

consider the workers' assembly time of the match, for example, will require assembly time

models and the need to assemble a longer time interval shorter models with order to balance

the assembly time. So the assembly shop of mixing production is very sensitive to the

production line balancing [9]

.

1.3 Quantitative quality management

A good quality management approach should provide warning signs early in the project

and not only towards the end, when the options available are limited. Early warnings will

allow timely intervention. For this, it is essential to predict values of some parameters at

different stages in the project such that controlling these parameters in project execution will


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ensure that the final product has the desired quality. If these predictions can be made, then

the actual data during the execution of the process can be used to judge whether the process

has been effectively applied. With this approach, a defect detection process does not finish

by the declaration that the process has been executed – the data from process execution is

used to ensure that the process has been performed in a manner that its full potential has

been exploited.

The concept of defect removal efficiency can be used for quantitative management of

quality, though these measures have some limitations for quality management [10-11]

.Infosys

implements quantitative quality management through defect prediction. In this approach, the

quality goal is set in terms of delivered defect density. Intermediate goals are set by

estimating the defects that may be detected by various defect detection. In other words, once

the quality goal has been set, the defect levels at different stages are estimated such that if

the estimates are met then the target quality will be achieved. Then for process management,

the predicted defect levels become the benchmark against which actual defect levels are

compared to evaluate if the development process is moving in the direction of achieving the

quality goal. The effectiveness of this approach depends on how well we can predict the

defect levels at different stages of the project. At Infosys, defect patterns observed in past

projects are used for predicting defect levels. Through this approach, phase-wise control can

be established. However, this level of control is too “macro” for a project as a phase is too

large an activity, and a finer or more “micro” control is needed such that corrective and

preventive actions can be taken quickly. This is achieved by employing SPC technique to the

two quality control activities that detect the maximum defects –reviews and unit testing. For

employing SPC, based on past data, control limits are established for key parameters like

defect density, coverage rate, etc [12]

.

1.4 Development of the FMEA and SPC

1.4.1 Internal development

SPC was pioneered by Walter A. Shewhart at Bell Laboratories in the early 1920s.

Shewhart developed the control chart in 1924 and the concept of a state of statistical control.

Statistical control is equivalent to the concept of exchange ability developed by

logician William Ernest Johnson also in 1924 in his book Logic, Part III: The Logical

Foundations of Science. Along with a gifted team at AT&T that included Harold Dodge and

http://en.wikipedia.org/wiki/Exchangeability

http://en.wikipedia.org/wiki/William_Ernest_Johnson


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Harry Romig he worked to put sampling inspection on a rational statistical basis as well[13]

.

Shewhart consulted with Colonel Leslie E. Simon in the application of control charts to

munitions manufacture at the Army's Picatinney Arsenal in 1934. That successful application

helped convince Army Ordnance to engage AT&T's George Edwards to consult on the use of

statistical quality control among its divisions and contractors at the outbreak of World War

II. W. Edwards Deming invited Shewhart to speak at the Graduate School of the U.S.

Department of Agriculture, and served as the editor of Shewhart's book Statistical Method

from the Viewpoint of Quality Control (1939) which was the result of that lecture. Deming

was an important architect of the quality control short courses that trained American industry

in the new techniques during WWII. The graduates of these wartime courses formed a new

professional society in 1945, the American Society for Quality Control, which elected

Edwards as its first president. Deming traveled to Japan during the Allied Occupation and

met with the Union of Japanese Scientists and Engineers (JUSE) in an effort to introduce

SPC methods to Japanese industry [14]

.

In china many of the manufacturing company using the SPC model to solve the process

problems and all automobile company using the FMEA technique to find out the root cause

of the defects and take a preventive action plan to reduce the cost and improve the quality of

the product with the less repairing rate [15]

.

1.4.2 Overseas development

The major concern of this paper is to provide a review of the use of SPC techniques in

batch production. Data transformation is considered as one of the most important activities

when implementing SPC in such an environment. Other activities include focusing attention

on the process rather than on the product and the use of standardized control charts (SCCs)

in place of traditional charts. Aspects of data transformation are dealt with especially with

regard to explaining the mechanism of data transformation and selecting as well as

evaluating several transformation techniques[16]

.Statistical process control (SPC) using

Shewhart-based control charts is not appropriate in the presence of autocorrelation, a

problem often predominant in surface mount manufacturing. These charts are not able to

detect instances of process improvement or deterioration. Hence, careful examination is

needed on the appropriate use of Shewhart models. Alternative modeling strategies and

control schemes are required for an effective process monitoring implementation. This

research is motivated by the quality and reliability concerns in SMT manufacturing. The

http://en.wikipedia.org/wiki/W._Edwards_Deming

http://en.wikipedia.org/wiki/Japan


6

objective is to re-examine the adequacy of existing SPC set-up and explore viable

alternatives for a more effective [17]

.

Implementation to date, literature addressing statistical tools and SPC in manufacturing

company has been few and far between.The traditional Shewhart u-charts and c-charts have

been applied to monitor defects of wave-soldering process (Tong, 1990) and the reflow

soldering process (Montgomery, 1997).Goh (1991)investigated the use of run rules for

process control that is applicable to the wave-soldering process.In essence, control of the

process is based on frequency of defectives rather than the occurrence of a specific number

of defects in any defective. However, his study considered only processes with low average

defect rates[18]

.Ermer and Hurtis (1995) proposed an extension to Goh’s (1991) methodology

by considering processes with higher defect rates. Rowland (1992) also highlighted the

limitations of Shewhart attribute charts in SMT, especially for low defect rates. Besides

adopting pareto analysis to identify the most regularly occurring defect types, alternative

solutions using moving sum and its variants, together with a combination of Poisson and

binomial distributions are proposed. These techniques are useful as they can provide early

warning of a change in the process behavior.Albin and Friedman (1992), on the other hand,

disputed the use of Pareto charts in ranking the relative importance of defect types [19]

.

misleading results may arise due to clustering of defects and high variability-to-mean defect

ratios.The assumptions of Poisson model for defect distribution need to be validated and the

authors recommended yield loss methods to measure the more significant defects. In fact,

more works related to design of experiments (DOE) are reported where classical planned

experiments were performed to determine the influence of various printing parameters on the

solder paste height in the solder paste deposition process (Gopalakrishnan and Srihari, 1998),

or to identify the critical factors that affect the yield of wave-soldering process (Lim, 1990).

On the other hand, Gagne, Quaglia and Shina (1996) investigated both the effect of different

paste formulation and the effect of solder reflow parameters using Taguchi’s orthogonal

arrays.More recently, Messina (1999) reiterated the importance of statistical methods to deal

with excessive variation in surface mount processes, and presented a comprehensive review

of some alternatives to Shewhart models.As for the automated component placement process,

published literature on the use of statistical methods for process control is almost nonexistent.

Research activities in this area mainly centered on component sequencing and assignment,


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set-up management and operational planning, and component partitioning problem and

retrieval problems [20]

.For example, Bard, Clayton, and Feo (1994) developed algorithms for

minimizing component placement times using nonlinear integer programming. Ball and

Magazine (1988) proposed a decomposition approach of determining optimal plan for

component sequencing. Furthermore, Lin and Tardif (1999) investigated the problem of

optimizing component partitioning under uncertainty constraints [21]

.

1.5 Research of the SPC and FMEA models

SPC was pioneered by Walter A. Shewhart at Bell Laboratories in the early 1920s.

Shewhart developed the control chart in 1924 and the concept of a state of statistical control.

Statistical control is equivalent to the concept of exchange ability developed by logician

William Ernest Johnson also in 1924 in his book Logic, Part III: The Logical Foundations of

Science [22]

. Along with a gifted team at AT&T that included Harold Dodge and Harry Romig

worked to put sampling inspection on a rational statistical basis as well. Shewhart consulted

with Colonel Leslie E. Simon in the application of control charts to munitions manufacture

at the Army's Picatinney Arsenal in 1934. That successful application helped convince Army

Ordnance to engage AT&T's George Edwards to consult on the use of statistical quality

control among its divisions and contractors at the outbreak of World War II. W. Edwards

Deming invited Shewhart to speak at the Graduate School of the U.S. Department of

Agriculture, and served as the editor of Shewhart's book Statistical Method from the

Viewpoint of Quality Control (1939) which was the result of that lecture.

Failure modes and effects analysis (FMEA) is one potential tool with extended use in

reliability engineering for the electrical and electronic components production field as well

as in complicated assemblies (aerospace and automotive industries). The main purpose is to

reveal system weaknesses and thereby minimize the risk of failure occurrence. The FMEA

technique is used in the design stage of a system or product (DFMEA) as well as in the

manufacturing process (PFMEA). Currently, the implementation of quality systems (such as

ISO 9001, QS9000, TS 16949, etc.) requires the establishment of preventive procedures;

therefore, the use of risk analysis methods, such as FMEA, is mandatory [23-25]

. Modern

companies require successful implementation and operation quality-management systems in

order to develop strong customer/supplier relationships, increase profitability, and contribute

to development and growth. Modern quality systems converge to become total quality


8

management, based on management commitment, people involvement, process management,

and continual improvement. The recently revised ISO 9000 quality-management system is

based on the following eight management principles.

(1) Customer focus

(2) Leadership

(3) People involvement

(4) Process approach

(5) Systems approach

(6) Continual improvement

(7) Factual decision making

(8) Organization/supplier mutually

(9) Beneficial relationships

One of the most important quality management techniques is FMEA ,Its devoted to

minimizing the risk of the failure and understanding what actions need to be taken as a result

of significant unplanned events .The development of a rigorous FMEA ensures preventive

action have been identified prior to an incident and are implemented without delay[26-30]

.For

indentifying the defects with the FMEA tool its very helpful to analysis the results with the

fishbone diagram and also use the 5S(who,what,when,where why), technique to find the

initials problems of the line and finally getting the preventive control with the SPC tools.

Before begin the analysis it’s very important to understanding the process flow and working

steps [31]

.

1.6 Development of the research

In addition, there is lot of research in the quality control field to improve the production

rate, reduction of the cost and improve the efficiency. The research not limited only the

domestic also huge development in the overseas. There is a lot of quality control methods

has been studied during the several decades but in the automotive company the research

application related to practices . In order to get the better quality of the product there is only

continuous improvement process and reduce the repair rate in the automotive company. For

the automotive company ,it’s very important to find out the root cause of the each defect and

print out long term solution because the defects is very sensitive in the car surface . So ,after

researching the many research papers , here will be introduce the new way to find out the


9

defects solutions . For the defects analysis here will use the FMEA methodology to find out

the most priority of the defects and use the fishbone diagram to analysis the origin of the

defects. After figure out the main reason of the defects there will use SPC tool identify the

performance trends. This factor is combined to assign prioritization for SPC implementation.

This exercise that should be monitored on a periodic basis via an enhance method.

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Chapter2 SPC and FMEA methodology

Failure mode and effects analysis (FMEA) has long been used as a planning tool during

the development of processes, products, and services. In developing the FMEA, the team

identifies failure modes and actions that can reduce or eliminate the potential failure from

occurring. Input is solicited from a broad group of experts across design, test, quality,

product line, marketing, manufacturing, and the customer to ensure that potential failure

modes are identified. The FMEA is then used during deployment of the product or service

for troubleshooting and corrective action. The standard FMEA process evaluates failure

modes for occurrence, severity, and detection (Chrysler Corp., Ford Motor Co., and General

Motors Corp., 1995). The multiplication of these values leads to what is known as the risk

priority number (RPN) .RPN = Occurrence * Severity * Detection

2.1 Introduction of FMEA Methods

FMEA is a reliability tool, which requires identifying failure modes of a specific

product or system, their frequency and potential causes. According to Fiorenzo Franceschini

and Maurizio Galetto(2001),the life cycle of a product is analyzed by an inter-functional

work team[32]

.Daimler Chrysler, Ford and General Motors are jointly developed an

international standard named SAE J1739-2006 documentation for FMEA.This document

provides general guidance in the application of different types of FMEA[33]

.First, the

potential failure modes and potential causes are identified along with its effects and then the

current controls are determined [34]

.FMEA method is used to calculate RPN for each failure

mode and then proposed recommended actions to reduce the RPN [35]

. The basic steps are to

identify the root causes and potential problems that could occur, and then derive RPN which

can direct improvement effort to the areas of greatest concern. Actions are then undertaken

to reduce the risk presented by the failure mode [36]

.FMEA was developed at Grumman

Aircraft Corporation in the 1950 and 1960s and it was first applied to the naval aircraft flight

control systems at Grumman. Since, then, it has been extensively used as a powerful

technique for system safety and reliability analysis of products and processes in wide range

of industries [37]

.Xiuxu Zhao presented a new approach for enterprises which combined

Statistical Process Control (SPC) with FMEA knowledge library.


11

FMEA is primarily quality planning tool. It is used to develop features and goals for

product and process, in identifying critical of product/process factor, designing customaries

the potential problems, establishing the control to prevent the errors and prioritizing the

process submit to ensure reliability.FMEA most commonly applied but not limit to design

(DFMEA) and manufacturing process (PFMEA).

Design failure mode and effect analysis (DFMEA) identify the potential failure of

design before they occur.DFMEA then goes to establish a potential effects of the failures,

there causes, how often and when they might occur and their potential seriousness.

Process failure mode and effect analysis (PFMEA) is systemized group of activities

intended to recognized and evaluated the potential failure of a product/process and its effect

identify action which could eliminate or reduce the occurrence or improve the defect ability,

document the process and track change to avoid the potential failure cause.

2.2 FMEA approach

FMEA is carried out by a cross-functional team of experts from various departments.

Normally, a team is formed at the planning stage of a new product based on a concurrent

engineering approach. The team analyzes each component and subsystem of the product for

the failure modes. Then, the potential causes and effects are determined.

The risk of each failure is prioritized based on the risk priority number (RPN). RPN is a

decision factor based on three ratings: Severity (S), Occurrence (O) and Detection (D).

These ratings are scaled with numbers between 1 and 10 [38]

. The analysis starts from the

basic structure of the system and particularly from those system elements for which accurate

information about failure mode and its causes are available. By analyzing the functional

relationships among these elements, it is possible to identify the possibility of propagation of

each type of failure to predict its effects on the production performance of the entire system.

This is an inductive method to analyze failure modes using down-top methodology [39]

.The

FMEA is a formalized but subjective analysis for the systematic identification of possible

root causes and failure modes and the estimation of their relative risks. The main goal is to

identify and then limit or avoid risk within a design. Hence, the FMEA drives towards higher

reliability, higher quality and enhance safety [40]

.FMEA concentrates in identifying the

severity and criticality of failures. FMEA is a fully bottom-up approach [41]

. Risk Priority

Number, which is the product of the severity, occurrence and detection ratings is calculated


12

as RPN = S x O x D. The RPN must be calculated for each cause of failure. RPN shows the

relative likelihood of a failure mode, in that the higher number, the higher the failure mode.

From RPN, a critical summary can be drawn up to highlight the areas where action is mostly

needed [42-43]

.The RPN is re-calculated after the failure has been addressed.The revised RPN

confirms the effectiveness of the corrective active undertaken.

2.3 Implementation methods for FMEA

Implementation starts with the FMEA planning and cross function team and creation for

FMEA development and the evaluation of the results. From the Fig. 2.1 shows that process

FMEA model which has 11 basic requirements that’s are heading requirements ,process

methodology, process functions, potential failure mood , potential effect of failure, severity,

causes of failure , risk priority number ,detection and actions. After preparation of the team

and planning next step is to delay with the manufacturing process and identification of each

step process and documentation in the FMEA sheet .Standard FMEA sheet is develop by the

IATF (international automotive task force which is given below:

Fig.2.1Potential failure mode and effects analysis Process FMEA model

(1) Heading requirement

Item: Indicated the name and number of the year of the system, subsystem and

component for which the process is being analyzed.

Model of the year: Enter the intended model of the year and program that will be use.

Core team: List of name of the core team members. It’s recommended that all team

members name, department, telephone number and address etc be included on a distribution

list and attach to the FMEA.

Process responsible: Enter the department or the group and also include the supplier

number.


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Key date: Enter the initial FMEA due date and the date should not exceed the schedule

the start of the production.

Prepared by: Enter the name of the name, telephone number, company of the engineer

responsible for prepare of the FMEA

FMEA date: Enter the date the original FMEA was compile and the latest version of the

date.

(2) Process/methodology steps

From the fig. 2.2 implemented that’s process methodology of the FMEA which is 8

process steps such as description of the process , identify potential failure mode, describe the

effects of the failure ,determine the cause , detection of process, calculated RPN , action plan

and action results. A process methodology step is given below:

Fig. 2.2 Basic process steps of the Process FMEA

Indentify the functions of the scope. Ask, “What is the purpose of this system, design,

process or service? What do our customers expect it to do?” Name it with a verb followed by a

noun. Usually it will break the scope into separate subsystems, items, parts, assemblies or

process steps and identify the function of each. Process identification characteristics come

from the process diagram .A product characteristic is a feature such as dimension, size, form,

location , orientation ,location , texture , coating , hardness ,strength, appearance, reflectivity.

(3) Process function


14

Indentify the functions of the scope. Ask, “What is the purpose of this system, design,

process or service? What do our customers expect it to do?” Name it with a verb followed by a

noun. Usually it will break the scope into separate subsystems, items, parts, assemblies or

process steps and identify the function of each. Process identification characteristics come

from the process diagram .A product characteristic is a feature such as dimension ,size ,

form ,location , orientation ,location , texture , coating , hardness ,strength, appearance,

reflectivity.

(4) Potential failure mode

For each function, identify all the ways failure could happen. These are potential failure

modes. If necessary, go back and rewrite the function with more detail to be sure the failure

modes show a loss of that function. Potential failure modes is define the manner in which the

process could potentially fail to meet the process requirement .it’s a description of a non

conference at the specific operation .it can be cause associated with a potential failure mode

in the subsequent (downstream) operation or effect associate with a potation failure in a

process operation .how ever preparation of FMEA, the assumption may be made that the

incoming part /materials are correct.

(5) Potential effect of failure

Potential effect of failure is defined as the effect of the failure mode on customer. The

customer in this content could be next operation, subsequent operation or location, the dealer,

the vehicle owner. Each must be consider when assessing the potential effect of failure.

(6) Severity

Severity is an assessment of the seriousness of the effect and refers directly to the

potential failure mode being studied. The customer in process FMEA is both internal and

where appropriate, external customer. The severity ranking is also an estimate of how

difficult it will be for the subsequent operation to be carried out to its specification it

performance, cost and time. The ranking and suggested criteria are based on IATF manual of

FMEA version 3. A common industry standard scale uses 1 to represent no effect and 10 to

indicate very much severe with failure affecting system operation and safety without

warning.

(7) Cause of failure mode

Identify the cause for each failure mode .A failure cause is defined as a design weakness


15

that may result in a failure. The potential causes for each failure mode should be listed in

technical terms and not in terms of symptoms. Examples of potential causes included

improper torque applied, improper operating conditions, too much solvent, improper

alignment, excessive voltage.

(8) Occurrence

The occurrence is the assessment of the probability that the specific cause of the failure

mode will occur. A numerical weight should be assigned to each cause that indicates how

likely that cause is (probability of the occurrence). For that failure history is helpful

increasing the truth of probability .therefore historical data stored in database can be used

and questions like the following are very helpful to solve this problem.

What statistical data is available from previous or similar process designs?

Is the process a repeat of a previous design or have there been some change?

Is the process design completely new?

Has the environment in which the process is to operate changeable?

Have the mathematical or engineering studies been used to predict failure

A common industry standard scale uses 1 to represent unlikely and 10 to indicate

inevitable.

(9) Detection

The detection steps distinguish between two steps of detection. On one hand to

indentify the current control process. Current control process is mechanism that prevent the

cause of the failure mode from occurring or which defect the failure before it reaches the

customer. The engineer should now identify testing analysis, monitoring and other

techniques that can or have been used on the same or similar products / process to detect

failure.

The other things are to assess the probability that the proposed process controls will

detect a potential cause of failure or a process weakness. Assume the failure has occurred

and then assess the ability of the control to prevent shipment of the part with that defect, low

occurrence does not mean low detection. The control should detect the low occurrence. In

the Tab. 2.1 explain about the qualitative scale of severity, occurrence and deduction. The

rank has been distributed 1-10 and each rank has the deferent scale of the severity,

occurrence and deduction methods which is given below:


16

Tab.2.1 Qualitative scale for severity, Occurrence and Deduction.

(10) Risk priority number (RPN)

The risk priority number is a mathematical product of the numerical severity,

probability and detection rating.

RPN= (severity * occurrence * detection)

The RPN is use to prioritize items that require addition quality planning action. If the

RPN number high that mean the occurrence of the failure is high.

(11) Actions

Determine recommended action to address potential failures that have a high RPN.

These actions could include specific of different components or materials, de-rating, limiting

environmental stresses or operating range, redesign of the item to avoid the failure mode,

monitoring mechanisms and inclusion of backup system [44]

.

2.4 Significant of the SPC in the manufacturing process

The utility of statistical process control (SPC) methods has received growing interest in

the healthcare community to help improve clinical and administrative processes.SPC charts

are chronological graphs of process data that are used in many other industries to help

understand , control, and improve processes and that, although based in statistical theory,

Rank Severity Occurrence Deduction Resolution

1 None Almost Never Almost certain If the numerical value falls between two

Numbers always select the higher number. If

the team has a disagreement in the ranking

value the following may help.

1. If the disagreement is an adjacent category,

average out the difference. For example, if

one member says 5 and someone else says

6,the ranking in this case should be 6 (5 and

6are adjacent categories. Therefore 5 + 6 = 11,

11/2 = 5.5)

2. If the disagreement jumps one category,

then consensus must be reached. Even with

One person holding out, total consensus must

be reached. No average, no majority.

Everyone in that team must have ownership of

the ranking. They may not agree 100Percent,

but they can live with it.

2 Very minor Remote Very High

3 Minor Very Light High

4 Very Low Light Moderately High

5 Low Low Moderate

6 Moderate Medium Low

7 High Moderately

High

Very Low

8 Very High High Remote

9 Serious Very High Very Remote

10 Hazardous Almost

certain

Almost

impossible


17

are easy for practitioners to use and interpret. The objective of this article is to provide an

overview of SPC charts, the different types and uses of control charts, when to use each chart

type, their statistical performance, and simple methods for determining appropriate sample

sizes. The intended audience includes practitioners and healthcare researchers seeking either

an introduction to these methods or further insight into their design and performance.

Methods for dealing with rare events and low occurrence rates also are discussed. Methods:

Recent empirical examples are used to illustrate appropriate applications of each chart type,

sample size determination, and chart performance. Sensitivities are calculated and tabulated

for a wide range of scenarios to aid practitioners in designing control charts with desired

statistical properties.Control charts are valuable for analyzing and improving clinical process

outcomes. Different types of charts should be used in different applications and sample size

guidelines should be used to achieve the desired sensitivity and specificity. SPC is both a

data analysis method and a process management philosophy, with important implications on

the use of data for improvement rather than for blame, the frequency of data collection, and

the type and format of data that should be collected.When dealing with low rates, it also can

be advantageous to collect data on the number of cases or the amount of time between

adverse events, rather than monthly rates.

2.5 The interaction between SPC system and FMEA repository

In practice of quality engineering exists possibility presentation of range quality

researching and estimation methods on background of life cycle product. In this kind of

system this methods are divided on [45]

:

（1）Preparations of production methods: Quality Function Deployment, Failure Mode

and Effect Analysis (FMEA), The old and new quality tools, Benchmarking.

（2）Quality control and inspection methods uses in production process: Statistical

Process Control, Failure Mode and Effect Analysis, Shainin Method, Taguchi Method,

AQLMethod.

Among these groups of method exists and works information system which is

connected with realization of quality intentional activities. Among replaced quality

researching methods we favor expert methods, one of them uses more and more often -

FMEA method in automotive company. This method is especially instructed at working and

production of product, because makes possible recognition of potential defect with such


18

advance, so that we can eliminate them across usage of preventive centers yet before

beginning of production. FMEA method can be use not only to analysing of reasons of

defects formation already ascertained, but also in aim of prevention to defect, which

potentially can step out in new product [46]

.FMEA is realized in three principle stages:

preparations, execution of proper analysis and also introductions and superintending of

preventive activities .Behind help created of FMEA sheet we can execute estimation of

activity, persistence, safeties, reliabilities and describe possibility reparability in existing

circumstances of leadership process. Evidencing all of researches and estimation, which are

showed in FMEA sheets, contributes to realizations format condition of project reviews.

Evidencing all of researches and estimations, which are showed in FMEA sheets, contributes

to realizations formal condition of project reviews .In the same time when we use in our

company FMEA method we can estimate quality capability of process and creating control

chart type. This kind of activities name Statistical Process Control. SPC involves using

statistical techniques to measure and analyse the variation of process. Most often used for

manufacturing processes, the intent of SPC is to monitor product quality and maintain

processes to fixed target [47]

.

Statistical quality control refers to using statistical techniques for measuring and

improving the quality of processes and includes SPC in addition to other techniques, such as

sampling plans, experimental design, variation reduction, process capability analysis and

process improvement plans. SPC is used to monitor the consistency of processes used to

manufacture a product designed. It aims to get and keep process under control [45, 46]

. Due to

usage SPC we can say, that process is stable controllability, when variability in process is

exclusively result of chance causes because in process step out systematic causes of

variability [48]

.Industrial experiences of implementations statistical regulations of processes

show that later advantages from usage of method SPC in decisive degree depend on

thorough preparations.SPC can’t be implement to production in such manner in which one

begins exploitations new devices measuring. SPC is method and because demand deeply

well-thought-out, stage preparations, perintended by management methods of with projects

just like FMEA.Using those methods in manufacturing industry introduced on example of

own researches of select production process of automobile industry. The analysis embraced

to operation in case of more often defects in this steps process.


19

Fig. 2.3 Principle of quality control based on FMEA and SPC

Fig.2.3shows the relationship about the FMEA and SPC. From the fig. we can

emphasize that at the input collection the data based on 5M methods and then analysis by the

SPC trends of the defects frequency. After analyzing the defects priority use the FMEA tools

to identified the root cause of the defects and get the FMEA repository. Finally takes the

process control of the defects.

20

Chapter3 Painting process and defect analysis

3.1 Identify the potential defects through painting process

The paint shop is one of the most complex production areas of vehicle manufacture.

From today’s perspective, the most important paint application procedures can be found here,

involving a relatively long process chain. In the paint shop, the highest demands are made on

the functional and visual quality of the painting, on the productivity of the painting

installations, and on the environmental compatibility of the processes. These are responsible

for the high degree of automation that can be found in automobile painting. In most paint

shops, the individual coating processes are classified into coherent functional fields. They

are arranged in such a way in the layout of the painting installation that a material flow

results that is as simple and logical as possible, in relation to the connection of the paint shop

to the neighboring production areas, the body shop, and the assembly line. A standard

coating line (see Figure 3.1.1) for painting 60 units per hour is about 2 km long. The dwell

time of a body is between 6 and 11 hours. About 30–50 people are employed per shift in a

fully automated paint shop, mainly for maintenance, process control, and trouble shooting.

The process chain includes value-adding and non value-adding scopes of work. Non

value-adding jobs are typically manual jobs, for instance, repairs of body shop faults,

sanding and polishing, cleaning, smoothing, and repainting. A future objective is to eliminate

non-value-adding jobs completely, or at least reduce them to the minimum extent possible.

Value-adding processes have reached a high degree of automation today and it is expected

that full automation will be achieved in the future [49]

.

The increasing pressure for reduction in costs is reflected in the effort to reduce the cost

per unit (CPU). This has led to innovations in the customer–supplier relationship and in the

painting process. The standard painting process, which has been used for years by all

Original Equipment Manufacturers：OEMs), consists of the steps primer, base coat 1,

basecoat 2, and clear coat. Consolidated processes are now being introduced which involve

shorter process times, where either the primer application is dispensed with, or where all

coats are applied wet-on-wet, without intermediary drying (see Figure 3.1.2).Surface coating

technology is going through an exciting time. The purpose here is clear-cost reduction,

environmental compliance and improved quality [50]

.

Chapter3-Introduction of paint process

21

3.1.1Car painting process methods

（1）Pretreatment；

（2）Electro coating；

（4）Sealing and underbody protection；

（3）Paint application；

（5）Function layer and Base coat application；

（6）Clear coat application；

（7）Cavity and wax application；

From the fig. 3.1 can see the general process steps of the automotive paint shops. At the

beginning car enter from the body shop to the pretreatment area and after that car goes

through the baking booths and sealing, UBS sealing process. After drying the sealing of the

car its goes into the primer sanding area and finally goes though the base coat and clear coat

application system. After applying the final coat car goes to the sanding, wax and foaming

line and finally handover to the assembly shop. For clear idea of the painting process steps

below figure given below:

Fig. 3.1 Process steps in modern automotive paint shops.

From the fig. 3.2 shows that there is 3steps film build on the car surface which is base coat 1 ,

base coat2 and clear coat. Each automotive car painting company has their own process but

the basic standard process steps can be identified by the below figure.


22

Fig. 3.2 Standard painting process in different automotive paint shops.

Pretreatment consists of the steps of precleaning, degreasing, purging, and

phosphating.Precleaning removes the rough contaminations. Degreasing solubilizes grease,

for example, deep-drawing greases, oil, wax, and other contaminations acquired from the

earlier working processes.Phosphating following after a purging process, serves as a

temporary corrosion protection, and improves the adhesiveness of the paint film when it is

applied.

Electrocoat paints are water soluble (suspensions of binders and pigments in DI

(deionized) water) with only low proportions of organic solvents (approximately

3%).Electrocoating covers all dip painting processes, where the paint precipitates on the

work piece owing to chemical conversion and associated coagulation of the binder.

The overlapping, spot-welded metal sheets must be sealed in such a way that no

humidity can penetrate between the metal sheets and water in the vehicle interior, which may

lead to corrosion there. On the weld seams, high viscous Polyvinylchloride (PVC) material is

mostly sprayed as paths with airless application or extruded by flat stream nozzles. The

underbody protection also serves as protection from corrosion, mostly for areas exposed to a

high strain because of stone chips. It is applied partially two-dimensionally, for instance, in

wheel arches and in the rocker panel area.

The primer surface which is called BC1 applied on top of the electro coat protects the

cataphoretically ectrocoating film from ultra violet (UV) radiation, serves as a surface

smoothing primer for the following top coat film, and reduces the risk of damage to the

layers below, in case of stone chips. Bumps and faults stemming from the body shop like


23

grinding remains can be repaired by sanding the primer coat. The primer is applied with the

high-speed-rotating application with electrostatic charging of the paint material. For reasons

of volatile organic compounds (VOC) emission, hydro primer materials are mostly used in

Europe and powder, to a certain degree, in North America. A further reduction of emissions

has been achieved with the development of two different processes.

The function layer combines the characteristics of the primer and the base coat material.

It is matched in color to the following base coat material, which is then only applied in one

coat on the wet or flashed off function layer. This is also valid for the metallic effect material.

In this process, the entire process chain consists only of four paint applications cathodic

electrocoating, function layer, base coat, and clear coat, compared to five layers for the

conventional metallic painting cathodic electrocoating, primer surface, basecoat 1, base coat

2, and clear coat. Apart from the emission reduction, this process has the advantages of the

reduced installation investment and overheads owing to the omission of one painting line. A

disadvantage is the fact that faults from the body shop and the cataphoretic electrocoat

process that are not eliminated after the cataphoretic electrocoat can only be processed after

the top coat painting. The top coat is applied after a thorough cleaning of the entire car body.

The prevalent process for the top coat application is the application of a waterborne base

coat, followed by a clear coat. One- and two component high-solid clear coats are mainly

used as clear coats. For waterborne clear coats, powder clear coats, and water-dispersed

powder clear coat systems, so-called powder slurries are formed and so these could not

capture any significant market share.2 wet, 2 coat 1 bake (3C1B), compressed compact

process, in the IPP (2) process the flash off time is verifying with the condition of different

company .it varies 55-80 degree and time is3- 6 min and after flash off the cooling time is 3

min approximately. The oven temperature after clear coat is 144 degree and time is 20

min .UV transmission rate is ≤0.1% when wave length is 290-380nm≤0.5% when wave

length is 380-400 nm ≤1% when wave length is 400-500nm.

Solid base coats are applied as a single coat, using high-speed-rotating atomizers.

Metallic effect paints are applied in two coats, the first coat with high-speed-rotating

atomizers, the second, usually pneumatically. The reason for the second pneumatic

application lies in the desired effect of the painting, which can be reached to the required

extent only in certain application cases with high-speed-rotating atomizers. Also, the

repairing process is more easily accomplished owing to the fact that repair of top coats,


24

especially in the field, is carried out manually by pneumatic guns. It can be expected,

however, that the electro statically supported application of both coats will prevail in the near

future. With the clear coats, there has been an increase in development activities towards

achieving high scratch resistance. These, and other equally important features, are achieved

by paint formulations that are linked with a higher degree of polymerization by means of UV

radiation. The top coat application is followed by a quality control check. Here, the paint

film is examined for faults like dirt inclusions, wetting disturbances, runners, and other such

defects. Additionally, the film thickness and the visual parameters like color shade, gloss,

and leveling are measured regularly.

The corrosion protecting measures are finalized with the sealing of the cavities with

wax materials. For this, two procedures are usually followed – spraying and flooding. For

spraying, special nozzles are inserted in the cavities, and an exactly measured quantity of

material is sprayed inside each cavity. For flooding, the cavities are filled with flooding wax,

under pressure.

Fig. 3.3 Typical layout of the paint shop.

3.1.2 Process related factors of paint performance

The reliable, objective, and reproducible measurement of the quality-relevant data like

film thickness, color shade and leveling are absolute requirements for a quality-oriented

process-control system. From fig. 3.4 shows that the film thickness distribution on a surface

is subject to a more or less distinct fluctuation that is caused by many factors. The main

factors are the application technology, the setting of the atomizer parameters, the number of

overlaps of the individual spraying paths and spray-booth conditions. In the paint surface

there are various factors that can influence the paint quality. According lab analysis, paint

surface affected by the process parameter, environment, dosing factors, equipments, manual

operational Etc. After long research and experience from the different car manufacturing


25

company the paint main defects oriented by the customer which is orange peel, hiding power,

sagging ,pinholes popping, wetting, Structure hiding ,overspray absorption, redesolving

attacking, cloudiness mottling, effect color, structure etc.

Fig. 3.4 Process related factors of the paint performance.

According to the customer feedback and comparing with the different car

manufacturing it has been concluded that there is branch of defects which has highly

tendency of the car surface technology. As reference, from BMW group defect standard (Ref:

GS97003) is shown in the fig.3.5.Car surface has been evaluated in the five main sections

which is A, B, C, D, E type and defects type has been identified with the different type such

asBI4,BI5, BI6, BI7,BI8 . A type area defects range must not exceed the >2 mm and not

more than 4 BI7 defects at the same areas. In the B area the standard is not more than 2 BI6

defects and the range is not exceed >2mm. Hood and four door down side is the C type area

and which customer can’t see the defects easily and the defects rate is not more than 6 BI6

defects in the one parts . Four door cutout inside, Hood door inside and trunk lid inside is the

D type area and E type area is fuel flap inside and engine compartment and trunk lid inside

which is determine that’s car paint has not been peel off from the surface and no corrosion

adhesion on the surface. So from the fig. 3.5 can easily understand the surface defects type

and its range.


26

Fig. 3.5 Shows defects evaluation standard corresponding to surface area.

Paint function defects evolution standard for process parameters factors:

Tab. 3.1 shows that main four regular type defects on the car surface and to evaluate the

defects such as color tolerance, paint appearance, film build and gloss has their own standard

and each car manufacturing company set their standard according to the customer

requirements .In the figure shows the 4 types of regular defects which is corresponding (ref:

GS97003) from the BMW company.

Tab. 3.1 Defects type with surface description

Type of defects Defects description

Color tolerance DE=<1.4 (good),DE<1.7(Accepted)

DE>1.7 out of tolerance

Paint Appearance

Horizontal Vertical

N1

<6.0

6.0<X<7.0

7<x<8

>=8

N3

<6.0

6.0<X<7.0

7<x<8

>=8

N1

<3.2

3.2.<X<4.2

4.2<x<5.2

>=5.2

N3

3.7

3.7.<X<4.7

4.7<x<5.7

>=5.7

Film build

Horizontal ≤90 (bad)

>100≤125

(good)

>125(bad)

Vertical ≤90 (bad)

>100-<120

(good)

>120(bad)

Gloss DOI>90(good)

Fig.3.6 is the defects evaluation standard of the car painting surface. In the car surface

has lots of type of the defects but in the BMW car manufacturing company there is 28 type


27

of defects which has potential influence on the car surface and which is determine by the

experiment from the lab results. There is certain kind of defects such as scratch, damage,

chip paint, bulge, waviness adhesive residue which is occur by the damages on the paint

surface and also oriented by the Body in white. During the paint application some defects

cause the paint process such as paint structure, missing paint coat, contact damage, Haze,

clear coat drop. In the reworking process some defects also cause the paint defects such as

sanding spot, polishing through, sanding stains, sanding groove, masking edges. All the

defects determine with the P0/P1,P2,S1,S2 area and also implemented the defects type such

as BI8,BI7,BI6,BI5,BI4.

Fig. 3.6 Defects evaluation standard (ref: GS97003).

3.2 Quality aspects of painting process

The management level of a paint shop requires constantly updated data and facts about

the state of the painting installation, to be able to make decisions based on the facts available.

From the fig. 3.7 it emphasize that there is 4 section of the quality aspect in the paint shop

such as by machine, internal audit, manual checking and customer feedback. These may be

short-term decisions such as introduction of extra shifts, or changes in operations owing to a

high repair rate, or long-term measures like change of a subcontractor owing to quality


28

problems. The system accesses the data from the process data recording and consolidates

them to the required management data. The data feedback from different module which is

depending on the machine, manual checking, internal audit and customer feedback. Quality

manual inspection is carried out by different measuring device such as color measurement

device, film build device, appearance measuring device, gloss measuring device. Aside

Quality online measuring system AQM is control by the trained qualified specialist which

data monitor by the quality database and processed immediately and shows on the work

piece, according to their place of measurement .IPSQ system use to input the defects online

during the manual operation by the qualified operator .They can be used both for a 100%

quality inspection of individual work pieces and for installation and process optimization, as

well as for statistical evaluation and trend analyses. In order to make the process

standardized need to organized the audit according to the international standard and need to

figure the out the actual deviation of the process capability and process performance relevant

to the standard. Internal and external audit is one of the important data which can help to

evaluate the customer satisfaction and help to improvement the process and take corrective

action immediately. Form the figure we can understand the quality management module in

the paint shop.

Fig. 3.7 Quality control methods in the Painting process

From Fig. 3.8 shows the Quality gate in the different working station and offline

checking of the care and section audit area in the paint shop. During the production if there is

any deviation of the process parameters or equipments instant can figure out the root cause


29

from the quality gate and continue checking till is back to the normal batch production. Each

working station has the internal target as hourly put, repair rate which is help us to figure out

root cause incase of any tolerance of the production .

Fig. 3.8 Quality control gate in the Painting process

Fig. 3.9 Online AQM measurement data output for the car appearance

Fig. 3.9 shows the results of the automotive coating surface measurement data which is

control the surface defects as film build, paint structure, color measurement. All this three

important surface factor is measuring by the robots technology and get a initially results of

the car surface and can see the color deviation from the standard. The measuring requirement

is according to the production batch of the color and if their some non conforming product

found initially test the certain amount of car to figure out the defective cars and analysis the

measuring data by the responsible engineers. In order to make sure the data of the


30

automotive measuring equipment is in control also measuring car with the manual device to

compare with AQM data in order to make sure the capability of the process performance is

in range.The Automatic painting installations with units like process equipment,

environmental equipment, conveyors, robots, and application equipment are complex

systems whose controllability is subject to the performance of the total process and the

coating result. Therefore, the functionality and the operability of the control-technology

equipment are essential, and high demands are made on the appropriate control technology.

The most important factors are listed below:

• Open, modular, and flexible architecture

• Compatibility with international standards

• Process-orientated

• High uptime

• Convenient, clearly arranged viewing system on PC basis, uniform operating

philosophy

3.3Process Monitoring and Regulation

The complexity of automatic painting installations and the large number of different

process parameters makes it complicated for the plant operator to maintain a high quality of

production, and for the service personnel to eliminate defects without delay. Systems that

support the operator in the diagnosis, optimization, and monitoring of the processes are

already in use. New systems are being developed to further improve on these, by taking into

consideration quality-oriented control of the painting processes and process parameters. The

linking up of such systems with all levels of the process and the installation, and with the

control technology necessary for doing so, makes them very effective tools [51]

.

As shown in Fig. 3.10, the structure of the quality and process control methods mainly

contains three steps:

Step 1: Function step: It makes real time data acquisition and analysis in the

manufacturing process. It can output the statistical analysis results in the form of quality

report. Input the data of manufacturing process into the SPC system. Data mainly collect in

the basis of the Manual inspection, Audit feedback (internal and external audit), automotive

measuring feedback (AQM, IPSQ system).

Step 2: Data evaluation: It implements the FMEA process, which conducted by the


31

experts coming from different area .The knowledge and experience of experts will be

extracted by the brain storming activity. Then, The FMEA results will be transformed into

FMEA knowledge according with specific method and put into FMEA repository.

Step 3: Risk Priority: It’s designed to store the data collected by SPC system and find

out the potential root cause after priorities the specific repository and take immediately

control plan and corrective action in order to improvement of the quality.

Fig. 3.10 A specific control based on FMEA repository and SPC system

32

Chapter4 Data analysis and Discussion

4.1Data collection and statistical analysis

In order to get the defects frequency rate use the SPC control chart. Its help to figure

out the highest frequency of the defects that influence of the process during the production.

Fig. 4.1 shows the defect frequency range within five calendar week. Calendar week1 shows

that among the defects inclusion is one of the most higher falling rate per unit and its one of

the reason for the scraping of the car and influence the TAKT time during the production and

its directly influence the production target . In the TOP coat line each car defects setting

target is 10defects but from the data we can see that inclusion defects mostly influence the

target. To analysis the defective car from the total production, Take the sample as a 5

subgroup and each group check the 10 car as a sample.

Fig.4.1 Diagram of the weekly percentages of the non-conformities

Pareto charts are graphical demonstration of the occurrences, with the most frequently

occurring event to the left and less frequent occurrence to the right. The Pareto charts in Fig.

4.2 shows the occurrences of defects in a painting process organization. 78% of the defects

in the surface are inclusion, followed clear coat drop at16%. The from the chart can see that

these two types of defects are the most prevalent.

In the final inspection line, a certain number of cars are rejected due to Inclusion

scratches, chips, bends, clear coat drop, popping or dents. In order to evaluated the defects

frequency use Pareto chart to see which defect is causing most of the problems. Operator

Chapter 4- Results and Discussion

33

checks the each car surface and put the information into the IPSQ system .so from the fig.

4.2, we can see that inclusion is one of the top problem in the car surface.

Fig. 4.2 Pareto diagram for the surface defects trends in the TC

Ishikawa analysis to figure out the potential causes of the inclusion defects:

Fig.4.3 Ishikawa diagram prepared for investigation of cause of the particles on surfaces

These diagrams depict an array of potential causes of quality problems. The problem

(the head of the fish) is displayed on the right, and the bones of the fish—representing the

potential causes of the problem—are drawn to the left. Potential causes are often categorized

as materials, equipment, people, environment, and management. Other categories may be

included as appropriate. Useful in brainstorming the causes of problems (including potential


34

problems) from multiple perspectives, these diagrams should include all possible reasons for

a problem. When completed, further analysis is done to identify the root cause. Fig. 4.3 is an

Ishikawa diagram to figure out the root cause of the particle issues in the top coat line. From

this issues need to priorities the possible causes that may influence the inclusion defects on

the car surface. To eliminate this defects, first need established a team which integrated by

the relevant departments as core team.

4.2 Potential root cause and risk analysis by FMEA

FMEA method is applied in painting technological process, so the severity (SEV) of

risk occurrence, the probability (OCC) of risk occurrence and the probability of risk

detection (DET) are determined. All assessments are expressed by numerical values

From 0-10, as shown in Tab. 4.1.

Tab. 4.1 Numerical values of the severity, probability &risk detection

By these numerical value can be calculated the value of Risk priority Number (RPN) with

equitation (1):

RPN = O × S × D (1)

The ranking of RPN is present in Tab. 4.2. Tab. 4.2 General indication of the risk

FMEA worksheet creation, there have been used data from: Department for control and

quality assurance, Maintenance department for equipment interventions, Production

Very small Small Medium Strong Very strong

1 2-3 4-5-6 7-8-9 10

BI8 defects and

online rework

without

production

target

influences

BI7 defects car need

to repair in rework

area and no

customer complaint

without quality risk

BI6 defects

which need to

major rework and

partially

influence

production target

BI5 or BI4

defects with

customer

dissatisfied

and has

quality risk

May be

endangering the

machine or

operator without

warning.

Value of RPN Evaluation of the risk

>100 Significant

10<RPN<100 Less significant

<10 Negligible


35

Department and IT department.

Fig

. 4.4

FM

EA

anal

ysi

s fo

r In

clusi

on d

efec

ts i

n T

op c

oat

pro

cess

Fig

. 4.4

FM

EA

anal

ysi

s fo

r In

clusi

on d

efec

ts i

n T

op c

oat

pro

cess


36

Fig.4.5 Line plot chart for evaluation the RPN rate before and after the corrective action.

FMEA is made in each step of the production process of paint shop, and there are

determined some potential causes of failure function in separate phase.In Fig.4.5 FMEA

Worksheet is presented for the process of production of Top coat line inclusion defects

reasons, prepared on 11/14/2014.

FMEA analysis shows that RPN has higher value of 245 in the process of manual

inspection of the car surface, RPN rate is 126 in the process steps roller bed and skid

inspection and Lab test results process steps RPN is 128. As the risk value priority is higher

of 100, the risk in the 1st, 3rd and 5

th step (process of inspection, roller and skid, lab test)

from the production process is considered as significant, while in the rest of the steps the

value of the RPN ranges between 8-100. Therefore, it is considered as less significant or

insignificant. If surface inclusion is determined during the control measurement of the

inspection process and small opportunities for the detection i.e. DET=5. While in the daily

roller bed and skid inspection process and lab test process the fault is obvious and the

probability that the product with defects will be distributed is low (DET=2-3).The value of

RPN shows in plot chart (Figure 4.1.4), it can be immediately concluded that the 1st,3

rd and

5th

process cause of the diagram is considerably higher in relation to the other phases and

after take action the RPN rate is in control rate and mean value is 5.8 that is negligible

according to the RPN rating scale .so the process is in the control limit.


37

4.3 Reflow SPC measurement data

To verify that the process has been improved and need to analysis that how efficient the

FMEA during the production process, it’s necessary to reevaluate the data falls in the TOP

coat line. From the figure 4.5 shows that after RPN action improvement inclusion trends is

going down 18 to the 5 defects in the car surface which can easily understand that new

improvement actions could be proposed toward the minimization of the RPN . From the

figure 4.6 C-chart shows that average inclusion trends rate is 3.94 which are in the control.

The data is collection after the corrective action taken which improvement is obvious.

Fig. 4.5 Diagram of the weekly percentages of the non-conformities after corrective action

Fig. 4.6 C -chart for inclusion defects after the corrective action.


38

4.4 Evaluation of the data

FMEA is a very effective risk analysis method for a company but it is not obligatory to

use but if any organization uses it must get several benefits as it is mentioned in this report.

In automotive company, they use only Design and Process FMEA and some qualitative part

of criticality analysis. To complete an FMEA analysis, it is necessary to make a cross

functional group from different departments of the company. The team will be composed of

experienced and devoted person will search for failure mode, cause, effect, severity,

occurrence, detection etc. together. Brainstorming is very necessary for this FMEA

worksheet. It is also required to find the proper way to lessen the failure mode. Severity

ranking remains almost same if the failure mode is not eliminated. In FMEA worksheet, if

severity ranks 10 or 9, it shows red mark (Red marks suggest for quick preventive work).

There will be an acceptable RPN limit for any company. It may differ for different

companies. Painting process has a grand limit of 100 RPN. The FMEA team needs to see

after the action was taken for the design or process whether the RPN value is less than 100

or not (first part of figure-6).One will get a graph of RPN of before (red marked) and after

action (blue marked).Second part of figure-6, this part comes automatically after the first

part of figure-6 is finished. Here it is possible to compare the performance development by

FMEA process. In the second part of figure-6, it is seen that before the action was taken the

RPN value was 150-260 but when the corrective action was taken the RPN values plunged

exponentially from 150-260 to 30-100. If it is not less than 200, the FMEA team is instructed

to take necessary corrective action and will have to compare the RPN value of before the

action was taken and after the action was taken. In criticality analysis, the occurrence data’s

are plotted in X-axis and severity data’s are plotted in Y-axis. As a result there are four zones

for considered according to the position of failure modes named: confirmed critical

characteristics which have maximum severity points, confirmed significant characteristics,

RPN- Top 20% by Pareto and annoyance region that’s severity points are low but occurrence

ranking is high(fig.4.4). From these zones the FMEA team can decide that which failure

modes should be prioritized more. According to Fig.4.5, the zones should be considered

respectively, confirmed critical characteristics zone, confirmed significant characteristics,

annoyance region and RPN-Top 20% by Pareto.As first priority is for severity then


39

occurrence, detection consecutively. RPN-Top 20% by Pareto means which 20% failure

mode should be prioritized of 100% (fig.4.5). Top 20% failure modes should be considered

as the most part of the zone is very acceptable. The report consists some differences between

FMEA and FMECA. Importantly, FMEA is used for system and FMECA is used for process.

FMEA is the primary steps to generate FMECA. FMECA is just FMEA with criticality

analysis. In FMEA multiple analysis levels (Sub-FMEAs) can be possible. On the other hand,

FMECA does not account for multiple-failure interactions, meaning that each failure is

considered individually and the effect of several failures is not accounted for. FMECA is

time consuming than FMEA.So companies are not very sincere to perform FMECA after

performing FMEA. Parker Hannifin, Borås is performing FMEA analysis if the organization

is asked from the top management of company but it is not hampering of their quality of

analysis. As a result, the main difference between the company findings and the theoretical

finding of this report is: Parker Hannifin is using a grand limit for RPN value and it is 200. If

severity ranks 10 or 9, it marks red for alarming the design or process. In criticality analysis,

the company is only performing the qualitative part (avoiding quantitative part).

4.5 Defects control system

It is the simplicity of this system that makes it so effective.

1) Huge emphasis is placed on

2) Classification of the defect

3) Communication of the problem

4) Action on that problem

From the Fig.4.7 shows the how to classification the defects during the analysis and for

the defects control .Defects classification begin from the process. If the product rejected its

cause two reasons one of is unusual and another is normal cause. Most of the unusual cause

should influence three causes such as most critical, critical and serious.


40

Fig. 4.7 Defect classification methods for the corrective action.

Any manufacturing process has only two possible outcomes: acceptable product or

rejected product. Rejected product can also be classified into two groups: ‘normal’ (meaning

typical rejects) and ‘unusual’ (abnormal in either nature or magnitude). In most companies,

normal rejects are already managed through systems designed to capture cost or output

losses (scrap and re-work systems). What can be missing in the management of quality is

effective treatment of abnormal events. Such events may occur at relatively low frequencies

(for example, monthly rather than daily). Without a systematic approach to their

management great risk can be present to outgoing quality. It is not safe to take comfort from

the low frequency and assume low risk. NSK developed the XYZ system to effectively deal

with the threat of unusual product events occurring in manufacturing operations. The system

borrows core principles from FMEA (Failure Mode Effect Analysis) - although the nature of

the implementation and how it is applied practically in the work place is believed to be

unique.


41

Three levels of unusual defect are distinguished:

1) Serious

2) Critical

3) Most critical

The level of ranking applied to any particular product defect is estimated from a simple risk

evaluation (FMEA based):

(SEVERITY x WHERE FOUND x FREQUENCY).

For instance, in the manufacture of bearings, a crack could contribute to a serious

breakdown. Engineers detail all the separate process steps and note what could happen and

the outcome should that defect ever reach the end customer. They then try to find ways in

which they can detect such outcomes in the existing process. Based on this evaluation a

rating level is given to each problem (X, Y or Z):

X = Low risk, or higher risk but detected early in process

Y = Medium risk detected before final detection mechanisms

Z = High criticality defect anywhere in the process

Emphasis is placed on the escalation of action where problems of greatest potential

effect are discovered in plant.

The system exists to keep any problems within the company, and to prevent escapes to

the market. Customers want reliable, consistent products – first time, every time: they are not

interested in how well you manage a quality problem that you have allowed to get out! When

problems are detected in plant they are ranked according to the XYZ matrix. This document

is the guts of the system: containing the expert knowledge relating to the types of defect

possible and their potential detection position.


42

Fig. 4.8 Defect classification matrix for the process sequence.

From this‘database’ any employee can quickly and easily determine an accurate

ranking for any concern. Generating this matrix is the key activity in XYZ implementation,

needing input from all functions involved in the manufacturing process. Once completed it

needs only infrequent update according to changes in process methods or to reflect new

insight from external feedback. A benefit of applying this matrix is the generation of

consistency across sites in a large organization where similar processes are applied. Utilizing

simple pro-forma documents, the vital step of communicating the concern can start. It is a

very simple systemThe four-part document is rapidly routed around the organization

structure, across department boundaries and hierarchies – in both manufacturing and quality

functions.

Fig. 4.9 Defect communication route.


43

Note the particular emphasis on the Z problem: it must be reported within 30 minutes.

There must be a management meeting within 60 minutes. This urgency is the key to

consistently high levels of quality control. That rapid communication, via hard copy

documents, is not dependent on somebody reading an email, but is personally delivered to

the appropriate person for immediate action. This is well beyond what is required by

accreditation standards (QS 9000 or ISO 9000).If the defect is not critical but might reduce

performance; it is generally classified as a Y problem, and drives a meeting of group leaders

within a day. Less critical problem(X problems), although auctioned promptly, are reviewed

weekly through the supervisory levels to ensure follow-up has taken place. This means

management attention is always focused to the critical few (Z level). The XYZ system can

be applied to any process – whether it is making bearings, cars, ice lollipops or providing a

service – it has a broad application. The most important point is that communication is great,

but action is more important. In a safety-critical product like bearings, only one standard is

allowed: perfection. There is no passing the buck. A Total Quality Culture is in operation.

There are many versions of it, but success relies on practical as well as conceptual

understanding. It also means that the whole supply chain has to be involved.

44

Chapter5 Conclusion

The application of a FMEA reveals the hidden process weaknesses, leading to the

quantification of failure related indicators/failure risks and the creation of a prioritization

matrix for further improvement actions. Risk reassessment and further preventive action

planning could lead to effective risk minimization. The use of a FMEA can also be applied

successfully in various other business sectors (e.g., supplies, sales, financial), leading to

continual improvement and increasing the bottom-line results. After execution of the process

FMEA for inclusion defects problem, it is clear that FMEA is most useful tool to identify

potential failures reduces those effects by implementing control plans. Hence it can be

heavily improve the quality of the product and enhance product performance. FMEA

execution is only present potential failure and ask to implement preventive measure to stop

occurrence of failure and enhance product and process performance so it identification and

implementation of prevention technique for potential failure is very important.

(1)The application of appropriate methods and techniques for monitoring and quality

control in painting process, will allow managers scientific approach in the quality assurance

and production of high quality products at minimum costs.

(2) Based on the results of FMEA and Pareto analysis, the source of poor quality is

identified and it’s reduction of 80% of the top 1 defects. The corrective action is taken and

the required accuracy in top coat line is achieved.

(3) With the combination of the FMEA and SPC method figure out the excellent tools

for organizations self-assessment and tend to improve performance of top coat defects. From

the input of the data of the combination model has the potential influence in the output

results. So it’s concluded that utilization of the combination methods not only increase the

production efficiency but also saving the cost with planned target.

45

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Academic Research

[1] Masud M. Research on the measurement analysis and improvement system according to

the ISO9001 in the automotive industry [J]. Journal of Quality Technology:Theory,

Applications and Practice, 2015,27 (2):162-168.

49

Acknowledgement

In the process of research and writing papers from start to finish getting unconditional

support, careful guidance and help from Professor Dr.Zhang Xinmin and his vast knowledge

of broad vision gave me a deep inspiration. In the paper of complete process, instructors

provide detailed references to the professional standards set strict demands to me, from the

topic, given the title, has been repeatedly modified in the final paper.Prof.Dr.Zhan Xinmin is

always responsible to give me a profound and detailed guidance to help me develop ideas,

careful coaching and valuable encouragement. More than two years of academic thinking in

science realistic attitude toward research, extensive deep academic level, creative, make me

a stronger in deepen knowledge in the quality filed . Loving care and support of classmate

during study period led me to the successful completion of their studies. During my learning

period who help me and give me lot of encouragement toward to success would like to

express my deep respect and heartfelt thanks.

Here, I also expressed deep gratitude to my entire instructor during graduate school!

2015 02 27_ research on car painting quality control based on fmea and spc v5

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