Manufacturing Technology (ME461) Lecture19

8/12/2019 Manufacturing Technology (ME461) Lecture19

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Manufacturing Technology

(ME461)

Instructor: Shantanu Bhattacharya


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Quality Engineering

Two major determinants of success in any organization aremarket demand and profitability.

The factors influencing and improving the competitive edgeof a company are the its unit cost , product quality and lead

time. The best approach of product quality is to build quality intothe product and process right at the product and processdesign stage.

Quality may also be improved at the production stage. (For

this purpose techniques such as statistical process controlare helpful in reducing the no. of non conforming products,thereby improving the product quality.


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Understanding the Meaning of Quality

Quality is a relative term. It is really in the eyes ofthe beholder.

From functional point of view, product isconsidered to be of good quality if it meets thedesired functional requirements adequately overthe intended period of its use.

As per the American Society of Quality Control:

Quality is the totality of features and characteristicsof a product or service that bear on its ability tosatisfy a given need.


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Quality Costs

One important aspect of the product development process is to translatethe customer requirements into product specifications.

Manufactured products not meeting the specifications should be repaired.

Thus the prime quality costs for supplying satisfactory products to

customers include producing, identifying, avoiding or repairing products

that do not meet customer requirements. Quality costs have been classified in a number of different categories as

follows:

1. Prevention costs

2. Appraisal costs

3. Internal Failure Costs

4. External Failure Costs


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Prevention costs: Prevention cost include all efforts that go into designing and

manufacturing a product that meets customer requirements by preventing non-

conformance. The various elements of prevention costs include activities involving

quality planning and engineering, new product reviews, product and process design,

process control, training , and quality data acquisition and analysis.

Appraisal Costs: These include all those costs involved in measuring, evaluating, or

auditing products, components, and purchased materials to ensure conformance with

the standards and specifications. Specifically, appraisal costs include cost of activities

such as inspection and test of incoming material, product inspection and test, materials

and services consumed and maintaining accuracy of test equipment. Internal Failure Costs: Internal failure occurs when products fail to meet the customer

quality requirements before being shipped to the customers. Internal failure costs

include all the cost elements involved in rectifying this situation. Examples of internal

failure cost elements are failure analysis, scrap, repair, retest, downtime, yield losses

and downgrading of usual specifications.

External Failure Costs: External failures occur when the products do not functionsatisfactorily after being supplied to the customer. Major costs are incurred for activities

such as complaint adjustment and dealing with returned products. Other costs include

warranty charges and liability costs.


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A framework for Quality Improvement To be successful in a competitive business environment, it is important to

deliver products that meet customer requirements with respect to quality,

cost and delivery schedule and also keep on improving the product quality. Where are the opportunities to improve product quality in any product life

cycle?

The product life cycle starts with product planning and continues through

such phases as :

1. Product design

2. Production process design

3. Production

4. Maintenance and product service.

By building in quality right at the design stage the cost of quality controlat the production stage can be considerably reduced.

Therefore, the preferable approach to improving the product quality is to

build quality into the products at the product design stage, followed by

improvements at the process design stage and them at production

engineering, maintenance and product service stages.


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Designing quality into products and

processes

Product design is the prime activity in the process ofrealizing a product. Therefore it has the greatestimpact on the product quality. Loss of quality occurswhen there is a deviation of functional characteristics

of the products from the target values. Taguchi has proposed a philosophy and methodology

for designing quality into products and processes. Hepostulates that the process of designing a product or a

process should be viewed as three phases. System Design, Parameter Design and Tolerance Design


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System Design:

System design is the process of applying scientific knowledge to produce a basic

functional prototype design. In this phase, new concepts, ideas and methods are

synthesized to provide new or improved products to customers. That means that

the basic design concept is established during this phase including selection of

parts, materials and subassemblies.

For example while designing a car the following questions need to be addressed. Like

should the internal combustion engine block be of cast iron or aluminum alloy?

Should the brakes be antilock brakes? The relationship between the inputs and

outputs are established. Also, the functions of parts and subsystems aredetermined during this phase.

Parameter design:

In the parameter design phase, the levels for the products/ process design parameters

are set to make the system performance less sensitive to causes of variation thus

minimizing quality loss. In parameter design wide tolerances on noise factors are

assumed to allow low manufacturing cost, as it is costly to control noise factors.During the parameter design phase the quality is improved without controlling or

removing the cause of variation.

Design of experiments, Simulation and optimization are techniques used during the

parameter stage.


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Tolerance Design:

The tolerance design phase usually follows

the parameter design phase. Qualityimprovement is achieved by tight

tolerances around the chosen target values

of the control factors so as to reduceperformance variations. However, with

quality improvement- that is, reduction in

quality loss- there may be an increase inmanufacturing cost.


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What is Quality loss?

The traditional understanding of quality loss is

shown in the figure 1. The objective in the traditional qualityapproach is to ensure that the manufacturedproducts fall within the specification limits

and are considered to be of good quality.

Those not meeting the specifications are

considered bad in quality and are either

rejected or reworked.

So loss is incurred only when the qualitycharacteristics fall outside the specification

limits.

The modern approach to quality considers

that loss is always incurred whenever the

functional quality characteristics of a

product deviates from its target value,denoted by T, regardless of how small the

deviation is.

The increase in value of functional

characteristics from the target value either

way results in increasing the quality loss.

At the LSL and USL the loss equals the cost of manufacturing or disposal of the product.

Taguchi Loss Function


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Average Quality Loss There is always a variation in the quality characteristic due to

noise factors from unit to unit from time to time during theusage of the product.

If yi ( i= 1,2,3------) is the ithrepresentative measurement of

quality characteristics y, then the average quality loss can be

computed as follows:


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Average Quality Loss


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Common variations of loss functions

Product characteristics are the barometers of quality

of products in the sense that they describe andmeasure the performance of products relative to the

customer requirements and expectations.

From the customer point of view, the loss is minimum

if quality characteristics is at the target value.

However, the expectations of the customers would

differ from product to product, and these can be

characterized when these are at the target values.


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Common variations of Loss functions Nominal is the best when y is at target. Examples

include dimension, viscosity and clearance.

Smaller is better; that is, y tends to zero, where targetis zero. Examples of quality characteristics includewear, shrinkage, deterioration, friction loss, and micro-

finish of a machined surface among others.

Larger is better; y tends to infinity when the target is atinfinity. Examples include fuel efficiency, ultimate

strength, and life.


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Applications of Quality Loss Function:

The quality loss function has been used as a decision support tool in a number of situations .

Determine best factory Tolerances: The loss function can be used to determine economical

factory tolerances:

Example:

Consider the production of automatic transmissions for trucks. The transmission shift point is

one of the critical quality characteristics. Truck drivers would feel very uneasy if the

transmission shift point was farther than the tramsmission output speed on the first to

second gear shift by 35 rpm. Suppose it costs the manufacturer $200 to adjust the valve body

to fix the shift point problem. However, it may cost only $16.40 for labor charges to make

adjustments during the manufacturing and testing phase. Determine the factory tolerances.


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Product Selection :

The loss function can be used to select products asillustrated by the following example.

High-Tech Rotor Dynamics is planning to buy a couple ofthousand bolts to be used in their systems. The systemrequires highly reliable bolts. In case of bolt failure thesystem repair cost is estimated to be $15.00. Twocompanies that offer different kinds of alloys in theirproducts bid to supply the bolts. High-tech decides togo for destructive testing using 20 specimens. Thecriterion used for testing is the ultimate tensilestrength measured in Kgf/mm2. The lowerspecification limit is 11Kgf/mm2The purchase quantityis 20,000. The unit costs of products A and B are $.14and $.13, respectively. Advise high tech rotor dynamicsfor its purchase decision.

D t Ulti t T il St th f


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Data on Ultimate Tensile Strength of

BoltsProduct (Bolt) Ultimate Tensile Strength Data (Kgf/mm2)

A 15.5 13.8 15.1 15.3 13.7 15.5 13.8 15.1 15.2 13.6

14.2 14.1 14.9 14.8 15.5 14.2 14.5 14.6 14.4 15.4

B 15.5 10.8 15.1 16.3 13.7 10.5 13.8 15.1 12.2 17.6

11.2 14.1 11.9 14.8 17.5 14.2 17.5 14.6 18.4 13.4


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R b t D i f P d t d P


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Robust Design of Products and Processes

Robust design is an approach to designing a product or process that emphasizes

reduction of performance variation through the use of design techniques that reduce

sensitivity to sources of variation.

Simply stated we want to achieve the target of quality characteristic but at the

same time we want to minimize the variation in a products functional characteristics

to ensure minimum quality loss.

The target and the variance of a products quality characteristic are affected bycertain variables which can be classified as controllable factors and uncontrollable

factors, also known as noise factors.

Engineered

System

Signal

Factors

Noise Factors

Control Factors

Response

C t ll bl F t


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Controllable FactorsControllable factors are those that can be easily controlled, such as choice of

materials, mold temperature, and cutting speed on a machine tool.

They can be separated into two major groups: factors controlled by the user/operator and factors controlled by designers.

Factors controlled by User/ Operator:

These are also known as signal factors. A signal factor carries the intent to the

system from a customers point of view to attain the target performance or toexpress the intended output.

Consider the steering system of a car. A drivers intent is to change direction. For

this purpose the driver changes the steering wheel position, thus giving a signal to

the automobile to change directions. In this case the signal factor is the angular

displacement of the steering wheel. Other example of signal factors include setting

a remote control button of a television set to control volume and brightness andsettin the tem erature control knob of a refri erator


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Factors controlled by Designers

There are three types of factors in this category:

1. Variability control factors: Those that affect the variability in a response are

called variability control factors or simply control factors. For example, the

transistor gain in an electrical power circuit is a variability control factor.

2. Target control factors: These factors can easily be adjusted to achieve the

desired functional relationship between the user input signal and the

response. For example the gear ratio in the steering mechanism of anautomobile can be selected during the product design stage to get the

required sensitivity of the turning radius to a change in the steering angle.

3. Neutral factors: These are factors that do not affect either the mean

response or the variability in the response. They are also known as neutral

factors. It is important to know these neutral factors, since the cost savingscan be obtained by setting them at their most economical levels.

N i F t


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Noise FactorsNoise factors are, in general, responsible for the functional characteristics of a

product deviating from the target value results in quality loss. Noise factors can

be classified as:

1. Outer Noise: The variables external to a product that affect the product

performance are known as external noise factors. Examples include

variations in temperature, humidity, and dust.

2. Inner Noise: Inner noise is a result of variations due to the deterioration ofparts and materials. Examples include loss of resilience of springs, wearing

out of parts due to friction, and increase in resistance of resistors with age.

3. Between Product Noise: Between product noise is due to the variation in the

product variables from unit to unit, which is inevitable in a manufacturing

process. Examples include material variations.Noise factors, as the name suggests, are uncontrollable factors. Trying to control

noise factors may be a vary expensive proposition, if not impossible.

Taguchis approach to robust design of products and processes attempts to reduce

variability by changing the variability control factors while maintaining the required

average performance through appropriate adjustments in the target control factors.


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l d ff l


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Failure mode effect analysisProcess FMEA is a methodology for evaluating the process for possible ways in

which the failures can occur. The primary objective in process FMEA is to eliminate

potential production failure effects by identifying important characteristics that haveto be measured, controlled and monitored.

The FMEA philosophy is based on the characterization of potential failures.

Failures are characterized by the following tuple: (Occurrence, severity and

detection).

Occurrence: How often the failure occurs?

Severity: How serious the failure is?

Detection: How easy or difficult it is to detect the failure?

Examples of typical failure modes include cracked, dirty, deformed, bent and

burred components; worn tools and improper setup.

Failure mode effect analysis


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Failure mode effect analysisTo implement process FMEA, the following steps may be taken:

Identify the problems for each operation using brainstorming and committee

discussions. Cause and effect diagrams can be used. For example, the potential causesof machine failures could involve mechanical or electrical subsystem failure, tools,

inspection equipments, operators and so forth.

Use flow process charts as a basis for understanding the problem. This provides a

common basis for communication among the committee members.

Collect data. Data collection may be necessary if data are not already available.

Prioritize the problems to be studied. The ranking of priorities is based on the following:

RPN (risk priority number) = occurrence X severity X detection

Use appropriate tools to analyze the problems by making use of the data.

Implement the suggestions.

Confirm and evaluate the results by doing some experiments and ask whether you are

better or worse off or the same as before. Repeat the FMEA as often as necessary.

Real Life Illustration of the Use of Process FMEA


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Real Life Illustration of the Use of Process FMEA

P f FMEA


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Process steps for FMEAThe process involves manual application of wax inside a car door, with the objective of

retarding corrosion.

In items 1 to 8 information such as part identification, names of team members, and date is

provided.Items 9 through 22 systematically describe the process FMEA approach. In this example the

problem of corrosion in car door is considered.

To retard corrosion the manual application of wax is considered. The manner in which this

process could potentially fail to meet the process requirements or design intent is defined by

potential failure mode.

In our example, the failure mode is insufficient wax coverage over the specified surface. We

have to determine the effect of failure in terms of what the customer might experience.

Here it would be the unsatisfactory appearance due to the rust and impaired function of the

interior door hardware.

The next step is to asses the seriousness of the effect based on a severity scale of 1-10.

(Column 12)

We now have to define the potential cause of failure in terms of something that can becorrected or controlled.

For every potential cause the frequency of occurrence should be estimated on a scale of 1-

10. here 10 means that the failure is inevitable.

We now have to access the probability of detection of the cause of failure by current practice.

This is also on a scale of 1-10 where 1 denotes a very low probability.

The next step is to calculate the risk priority no.

Improving product quality during


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Improving product quality duringthe production phase

As dicussed many times the very survival of companies depends on continuous

improvement of quality.

Quality can be designed into a product, as we have seen in the previous section, but

then the product must be manufactured.

During the manufacturing process assignable causes may occur, seemingly at random.

These assignable causes result in a shift in the process to an out of control state,

resulting in an output that may not confirm to requirements.

To produce quality output it is necessary to have a process that is stable or repeatable,

a process capable of operating with little variability around the target or nominal

dimensions of the products quality characteristics.

The idea behind improving quality is to reduce variability and eliminate waste.

Q lit i t


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Quality improvement process


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Histogram


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HistogramSuppose it is needed to produce a shaft within 1+ 0.05 in. On a numerically

controlled turning machine.

The shaft diameters are plotted against frequency as shown in the figure below.

The plot is known as histogram, and it provides information on the central

tendency, spread, and shape.

We see that the distribution of the shaft diameter is symmetric with the mean

around 1 in. and variability between 0.95 and 1.05 in.

Ch k Sh t


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Check SheetA check sheet serves as a useful tool for collecting historical or current operating

data for the process under investigation.

In the early stages of implementation of the SPC, it is important to understand what causes failure of the

system or product performance.

This could be due to a number of defects which even may not affect the product performance but certainly

affects the quality of the products.

For example common product such as spark plug used in a car. Over a period of 5 days a list of spark plug

defects is recorded on a check sheet.

Some defects are due to tool changeovers to different types, as for the raised stud defects.

This check sheet helps in identifying the sources of these defects with respect to time.

We notice that except for dirty cores the defects are not recorded everyday. Cores are supplied from

outside vendors therefore the problem lies in controlling the quality of the incoming part.

Pareto Chart


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Pareto ChartThe Pareto law states that on an average 80 % of the defects stem from 20% of

the causes.

In case of the spark plugs most of the quality problems come from only three outof nine or more problem areas.

A Pareto diagram is helpful in identifying the fact that taking care of these few

problems takes care of 80% of all causes of the problem situation.


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D f t C t ti Di


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Defect Concentration DiagramA defect concentration diagram is a visual representation of the unit under study

showing all possible views with all possible defects identified on it. This type of

representation is useful in understanding the types of defects and their possiblecauses.

Scatter Diagram

A scatter diagram is useful in establishing a relationship between two variables.

The shape of the scatter diagram is obtained by plotting the two variables. It mayindicate a positive or negative correlation between the variables or no correlation

at all.

Such information helps in developing a control strategy for these variables.

Control Chart

Documents

Manufacturing Technology (ME461) Lecture19