casting product-process-producer compatibility evaluation

Technical paper submitted to the International Journal of Production Research

Casting Product-Process-Producer Compatibility Evaluation and Improvement

AKARTE MILIND M† and B. RAVI∗

Abstract The manufacturability of a cast product depends on process capabilities, which in

turn depend on the facilities of the producer (foundry). Selecting the right

combination of the product, process and producer to simultaneously optimize

functionality and manufacturability considerations is a challenging task. This paper

presents a multi-criteria methodology that integrates the hitherto separate problems

of process and producer selection, by introducing the concept of an ideal foundry.

A set of 25 common criteria (11 objective and 14 subjective type) grouped under

six heads: geometry, quality, production, delivery, facility and other, have been

identified to evaluate the process and the producer. Objective criteria are assessed

using a fuzzy logic approach, whereas a rating method has been employed to

accommodate subjective criteria. Analytical Hierarchy Process has been used to

obtain the relative importance of the evaluation criteria. The methodology is also

useful for benchmarking of foundries, and feedback for improving product-process

compatibility. This is illustrated with an industrial example of a ductile iron yoke

casting.

Key Words: Casting, Design for Manufacture, Manufacturing Processes, Supplier

Selection, Foundry, Analytic Hierarchy Process.

† Department of Production Engineering, SGGS Institute of Engineering & Technology, Vishnupuri, Nanded 431 606 INDIA Phone: (+91-2462) 229 306 Fax: (+91-2462) 229 236 Email: [email protected] ∗ Department of Mechanical Engineering, Indian Institute of Technology, Bombay 400 076 INDIA Phone: (+91-22) 2576 7510 Fax: (+91-22) 022-2572 6875 Email: [email protected] ∗ Corresponding author

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1. Introduction

Casting design elements (part metal, geometry and quality specifications) have a

direct influence on its manufacturability (quality, economy and productivity)

(Gwya 1999). Each metal has unique casting properties, such as pouring

temperature, fluid life, solidification shrinkage and slag/dross formation tendency,

which influence part quality in terms of dimensional stability and internal integrity.

Part geometry directly influences the number and complexity of tooling elements

(mold and cores) and therefore their cost. Stringent quality specifications usually

require better equipment and additional processes, leading to longer production

times. Therefore, an early consideration of manufacturability issues during part

design, when any changes are still easy and inexpensive, enables achieving high

quality, economy and productivity. This however, requires a good knowledge of

the casting processes suitable for making the part, and their capabilities.

A number of casting processes are available today, each with different

capabilities, depending on the part metal and geometry (Bralla 1986, Kalpakjian

1997, Swift and Booker 1997). For example, sand casting process can produce a

minimum wall thickness of 4.8 mm for steel parts, and only 3.2 mm for aluminum

parts (DeGarmo, Black and Kohser 2003). In contrast, pressure die casting process

can give walls as thin as 0.9 mm in aluminum parts. These values, representing the

minimum wall thickness capability of a casting process, will be different for

varying sizes and shape complexity of parts. Other process capability

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characteristics include casting weight, core size, dimensional tolerance, internal

porosity, and production rate.

In practice, the process capabilities also depend on the equipment,

manpower skills, quality management practices, and other foundry-dependent

factors. The process capabilities for a specific set of above factors in a foundry are

refereed to as producer capabilities. The large number of combinations of the

above factors for a single process leads to an even wider range of values for a given

process capability characteristic. For this reason, the capabilities are usually

indicated as a band of values in technical literature. Thus, the minimum section

thickness of sand-cast aluminum parts can vary from 3.0 mm to 5.0 mm for a

casting size up to 300 mm (Bralla 1986). Some process capabilities are described

qualitatively: for example, investment casting gives ‘moderate’ porosity (Swift

1997).

To achieve high manufacturability, the product design and process

capabilities must be compatible with each other. A mismatch between product

requirements and process capabilities will lead to more rejection, rework, costs and

lead time. This can happen when capabilities of the process (ideally, the capabilities

of the specific producer, if known) are not considered during product design.

Most designers are aware of the importance of concurrent product-process

design, but usually unfamiliar with the variety of casting processes, and their

specific capabilities (compounded by their dependence on material and other

factors). Thus, problem features such as excess rib thickness, inadequate fillet

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radius, narrow holes and tight tolerances are quite common in cast parts, which

result in excess weight, unnecessary tooling costs, additional labor and higher

percentage of defects. A systematic approach to evolve process and producer-

compatible product designs is therefore necessary. The main steps in such an

approach will be: (1) selection of an appropriate process and producer, (2)

evaluating the compatibility between product requirements and process/producer

capabilities, and (3) improving the product design for higher compatibility. Only

the first step (process and producer selection) has received some attention from

researchers so far, which is reviewed in the next section. This is followed by our

proposed approach for product-process-producer compatibility evaluation and

feedback for product design improvement.

2. Related Work

Several researchers have worked on the problem of selecting feasible processes

from a library against a set of product requirements. Sirilertworakul, Webster and

Dean (1993) used a multi-criteria approach for screening feasible processes. Others

focused on evaluating the screened alternatives, using various techniques such as

Fuzzy Logic (Giachetti 1998, Lovatt et al 1999), Design Compatibility Analysis

(Yu et al 1993), and Analytic Hierarchy Process (Akarte et al 1999). Darwish and

El-Tamimi (1996), and Er et al (1996) used a knowledge base approach. Chougule

and Ravi (2003) used case based reasoning for casting process planning, where the

casting process of the nearest matching case is retrieved.

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Casting supplier selection has traditionally been driven by cost as the main

criterion. Now non-price criteria such as quality, delivery and overall capability are

becoming equally important. General Motor’s case study on Quad-4 automobile

engine development illustrates the importance of considering the capabilities of

suppliers for their early involvement in product design phase (Ettlie et al 1990).

The new trend is very much in evidence in the automobile and other engineering

sectors (Soman et al 1998). Considerable literature is available on the methods used

for supplier selection, including review articles (Weber et al 1991, and Bore et al

2001). In casting domain, foundries greatly differ from each other in terms of

capabilities, facilities, technology and management, making it quite difficult to

assess and select the best supplier. Analytic Hierarchy Process (AHP), a multi-

criteria decision making tool, has been reported for supplier/vendor selection

(Mohanty and Deshmukh 1993, and Yahay and Kinksman 1999).

The review of literature clearly showed that process and producer selection

problems have been handled as separate decision making situations. This implies

that the process is selected first, and then the supplier foundry is selected depending

upon the process. This however, overlooks the possibility of considering a producer

with a different process, whose capabilities still match the product requirements.

There is also considerable overlap between the sets of decision criteria for the two

problems (Akarte et al 1999, Akarte et al 2001). To the best of our knowledge,

there is no reported work on a common framework for the process and producer

selection problem for manufacturability evaluation, especially in casting domain.

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3. Proposed Approach

An integrated decision methodology, based on a single set of criteria, has been

evolved to overcome the limitations arising from separate selection of process and

producer. To enable selecting and evaluating only the processes (using all the

criteria), the notion of an ideal foundry is proposed. The ideal foundry is defined as

‘the hypothetical foundry having the best-in-class facilities and giving the highest

product-process compatibility compared to real foundries in the same metal-

process group’.

The concept of ideal foundry not only enables finding the most suitable

casting process (ideal foundry) for a given set of product requirements, but is also

useful for evaluating a given foundry (producer) against product requirements, and

for comparing (benchmarking) a real life foundry with the ideal foundry.

The overall methodology for screening and evaluation of producer

(foundry) is shown in figure 1. It is based on AHP, and involves four levels (figure

2). The top level contains the overall objective: product-process-producer

compatibility evaluation. The second level contains six groups of decision criteria:

Geometric Capability (GC), Quality Capability (QC), Production Capability (PC),

Delivery Capability (DC), Manufacturing Facilities (MF) and Other Capabilities

(OC). The third level contains detailed criteria under each of the above groups,

described in the following section. Finally, various alternatives (producers) that are

to be analyzed are placed at the fourth level of the hierarchy.

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[…………………..Insert Figure 1 here……….………..]


4. Evaluation Criteria

In this study, 25 important criteria influencing product-process-producer decision

have been identified after a detailed study of technical literature, discussion with

experts and visits to final assemblers as well as foundries. These are listed in table

1. Out of these total 25 criteria, 11 are of objective type and 14 are of subjective

type.

[…………………..Insert Table 1 here……….………..]

The objective criteria are those that can be easily quantified and expressed

in some dimensionally consistent unit. For example, casting weight and wall

thickness are measured in terms of kilograms and millimeters respectively.

Subjective criteria are difficult to quantify, but are important for decision-making

and are generally characterized by linguistic variables such as ‘LOW’ and

‘MEDIUM’. For example, the level of automation in a foundry can be expressed by

the terms LOW, MEDIUM, HIGH and VERY HIGH. Most of the important criteria

have been included, but the list is by no means sacrosanct, and the hierarchical

framework developed in this work allows introduction of new criteria as well as

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new rating values for the subjective criteria. The six groups of criteria are described

in detail here.

4.1 Geometric Capability

There are five criteria in this group: casting weight, maximum length, minimum

section thickness, minimum core hole diameter and shape complexity. The

minimum values of section thickness and core hole diameter are more important

compared to the maximum value as freezing of melt metal limits the smaller size

that can be easily achieved. The maximum casting length is generally limited by the

availability of tooling equipment. Shape complexity is influenced by a number of

factors such as number of features, curved surfaces and thickness variation. Some

casting processes are suitable for simple shapes (for example, centrifugal casting

for axi-symmetrical parts) and others for complex parts (for example, engine blocks

with multiple cores can be produced by sand casting or gravity die casting with

several sand cores).

4.2 Quality Capability

Quality capability of a casting process or a foundry is mainly evaluated by three

criteria: dimensional tolerance, surface roughness, and porosity & voids.

The tolerance capability of a casting process depends on part size, rigidity

of mold (metal or sand), part metal (its melting temperature and volumetric

shrinkage during solidification), number of cores, loose pieces, location of a critical

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dimension (along or across the parting line) and level of automation. The accuracy

of pressure die casting process, which employs a metal mold, low melting metals

and higher automation level is much better compared to sand casting process.

Surface roughness capability of a casting process depends on die/mold

material and the type of process employed. In sand casting, the size of sand grain,

molding method (high pressure or low pressure) and mold coating influences

surface roughness. In general, the minimum and maximum values of surface

roughness in sand casting are 6.3 to 50.0 µm, respectively, with normal operational

range being 12.5-25.0 µm (Bralla 1986). This is coarse compared to die-casting

(normal range 0.8-1.6 µm).

Shrinkage porosity and voids affect the internal soundness of a casting, and

eventually the strength and functionality of the product. Shrinkage porosity mainly

appears in the last freezing zones inside the casting in the form of cavities, porosity

and micro-porosity. The volumetric shrinkage of the cast metal, filling pressure,

mold heat transfer rates and feeder design influence the level of porosity inside a

casting. Thus an aluminum alloy produced by pressure die-casting has negligible

shrinkage porosity compared to steel casting produced by sand casting. Gas and air

voids inside the casting are caused by improper melting, pouring and filling, which

is influenced by the type of metal (cast iron has higher fluidity than steel), pouring

parameters (rate and temperature) and gating system design. Thus, metal-process

combinations that are less susceptible to shrinkage and voids should be preferred if

the part requires high strength, structural integrity and pressure tightness.

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4.3 Production Capability

Production capability group consists of four criteria namely, quantity, production

rate, flexibility and material utilization. The order quantity and production rate

(quantity per unit time) are two of the most important criteria influencing the

choice of the casting process. Each casting process is associated with a minimum

number of parts that must be produced for economic justification. For example, the

minimum economic order quantity for die-casting is 10,000 units (Swift 1997),

because of the high cost of die equipments.

Process flexibility implies the ability to adopt to the casting design variation

without significant changes in the tooling and process parameters. It is an important

criterion in selecting a process, especially for new product development. In general,

sand casting process is more flexible compared to die casting process as it allows

the use of less costly tooling and equipments, is suitable for producing a few as

well as a large order size, and allows a wide range of casting size and shapes.

Material utilization indicates the overall yield of the process: that is, the

ratio of the total weight of good casting produced to the total weight of metal

melted. This depends on the size of feeders and gates required (which in turn

depends on the metal, process and the casting shape), material wastage, and losses

during melting, pouring and handling. For example, pressure die casting of

aluminum parts allows a much higher utilization compared to sand casting of steel

parts.

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4.4 Delivery Capability

This group comprises three criteria: delivery quantity, delivery frequency and

delivery distance. Delivery quantity is the maximum number of castings that a

foundry can ship in a single instance. Foundries with high delivery capacity will be

able to handle demand changes better than those with small capacity and are

preferred. Delivery frequency is the number of times a foundry can ship orders to

destination, that is, how much frequently an order can be repeated. Foundries with

higher delivery frequency are preferred since they can provide the advantages of

just in time manufacturing.

Delivery distance can be an important criterion in finalizing the alternative

in the situation when two alternatives are equal in all other respects. Naturally, a

foundry located close will be preferred, as this implies lower shipping costs, shorter

delivery time and better delivery assurance, besides other advantages such as lower

inventory levels and better possibility of buyer-supplier cooperation.

4.5 Manufacturing Facilities

Criteria under this group include total production capacity, automation level,

melting facility and supporting facilities for heat treatment, machining and testing.

The production capacity of a foundry is usually expressed by its melting capacity

(for example, 1000 tons per month). This is an important criterion, especially when

the casting size or the order size is large.

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The automation level varies from one foundry to other. A high level of

automation enables higher consistency, accuracy and production rate. This can be

judged by the type of facilities available for sand preparation (manual, sand muller

or sand plant), molding (manual, mechanical or automated), pouring (manual,

controlled or automatic), mold handling (batch transport, continuous by conveyor)

and fettling.

The melting equipment criterion is evaluated based on the type of melting

facilities available in the foundry. The type of furnace should be compatible with

the material and quality requirements of the casting: a cupola may be acceptable for

melting cast iron, whereas induction furnaces are preferred for steel and ductile

iron. In addition to the metal-furnace compatibility, other factors that may be taken

into account while choosing a furnace includes melting cost, melting rate, melting

cycle time, melt capacity requirement, energy consumption and furnace efficiency.

Heat treatment and machining facilities enable value-added services by a

foundry. A wide variety of heat treatment methods are available (ranging from

simple stress relief, which require only few hours, to annealing, which may require

as long as a day or more) that can be used to achieve the desired properties.

Machining facility is important when requirement is for a few samples with

simple operations and secondly when the defects are detected during machining. In-

house machining facility with the foundry enables prompt identification and

correction of defects, thereby eliminating further losses. In both cases, availability

of machining facility with the foundry considerably eliminates the handling cost.

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Testing facilities (sand lab, physical lab, chemical lab, spectrometer and

non-destructive testing (NDT) facilities like radiography, ultrasonic and dye

penetration) available in a foundry enable characterization of materials and casting

during various stages of manufacturing.

4.6 Other Capabilities

This group comprises of four criteria. These are tooling development, CAD/CAM

software, quality certification and quality awards.

The tooling development criterion is important because assemblers of

automobiles and other products today deal with more frequent model changes,

upgrades and new introductions than in the past. This requires foundries to handle

quick development or modification of tooling, which is facilitated by an in-house

tooling development facility, comprising of tool design, fabrication and inspection

facilities.

The CAD/CAM software criterion to evaluate foundries is increasingly

becoming important. The applications include solid modeling, casting process

simulation, NC process planning and coordinate measuring. These enable reducing

the number of trials, improving quality assurance and optimizing the yield, leading

to overall costs and lead-time reduction.

Certification is an assurance by or under the supervision of a competent and

independent organization, that products produced are consistently in conformity

with a standard or specification. This includes ISO 14000, ISO 9000, QS 9000,

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certified supplier and self-certification. Foundries with quality awards will be

preferred over others as these are an indication of past performance.

5. Product-Process-Producer Compatibility Evaluation

Compatibility evaluation for the given product requirements and process/producer

capabilities comprises four steps: (1) screening of feasible alternatives, (2) criteria

relative weight calculation, (3) criteria evaluation, and (4) compatibility score

calculation. These are described next.

5.1 Screening of Feasible Alternatives

Since there can be a potentially large number of metal-dependent casting processes

and producers, it is necessary to screen the alternatives first to reduce the number of

detailed evaluation. This is done by comparing the casting requirements with the

capability of available processes, using a few critical criteria. The criteria include

casting metal type, weight, minimum core hole diameter, minimum section

thickness, quantity and foundry production capacity. The feasible producers are

then short-listed from the various alternatives available for further evaluation.

5.2 Criteria Weights

The relative importance of decision criteria varies from problem to problem and

from one decision-maker to another. The purpose of criteria weight is to express

the importance of each criterion relative to other criteria in a given situation. In

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general, it is difficult for the decision maker to accurately assign relative weights

for a set of criteria by considering all of them simultaneously. The pair-wise

comparison method of AHP eliminates the above difficulty, resulting in more

reliable and consistent weights.

Relative weights are assigned to the criteria using the 1-9 scale of AHP

(table 2). Weights are first assigned to the group criteria and then to individual

criteria in a particular group. The sum of weights of individual criteria in a

particular group is normalized to one. The sum of weights of the six criteria groups

is also normalized to one. Thus, the effective weight of any particular criterion is

equal to the product of its own weight and the weight of the criteria group.


5.3 Criteria Evaluation

The objective of evaluating an alternative performance against each criterion is to

compute the numerical value that is comparable among all criteria. This is essential

to obtain the trade-off among the evaluation criteria. The computation of

performance evaluation of an alternative against a particular criterion depends on

the type of criteria. As described earlier, evaluation criteria are either objective or

subjective type. Alternative performance against objective criteria is achieved by a

fuzzy logic approach, while for subjective criteria a rating approach is used. In

fuzzy logic approach, the range of process capability values is mapped on a

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normalized scale to evaluate its performance against the given casting

requirements. The rating approach enables qualitative judgments to be converted to

quantitative values, by a pair wise comparison of the qualitative terms for a

particular criterion (Saaty 1994-A, Saaty 1994-B).

Objective Criteria: In this work fuzzy representation of process characteristic (for

objective criteria) has been used to determine the degree of compatibility between

the given set of casting requirements and the range of process capability values.

The range of process capability values need to be mapped on a normalized scale of

(0,1), such that every value in this range will represent a compatibility value

between 0 and 1. A higher value (closer to 1) indicates better castability with

respect to the particular design requirement, the value 1 representing the normal

range that is most preferred (figure 3). Beyond this normal range, the ability of

producing the part feature reduces gradually till the extreme limits are reached,

after which the process cannot produce the feature. The process compatibility value

for the design requirement x units is given by:

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Subjective Criteria: For qualitative criteria, attribute values have to be defined. In

most cases, the preference of one attribute value over another is usually clear, but

the extent of preference may require expert input. For example, tooling

development criterion has two values: in-house and outsourcing. In-house tooling

development is always preferred as it allows faster response to the design changes.

However, the extent of preference of ‘in-house’ over ‘outsourcing’ must be

quantified. The relative performance measure of each alternative for subjective

criteria is obtained by quantifying the ratings, which are expressed in qualitative

terms. For example, the rating for quality certification criterion is expressed by the

words ISO 14000, ISO 9000, QS 9000, CERTIFIED SUPPLIER and SELF

CERTIFICATION. To quantify a particular qualitative rating, a pair-wise

comparison of all ratings belonging to that criterion is carried out. The AHP

method of relative weight calculation has been used to obtain the quantitative rating

1 If VMin_desire ≤ x ≤VMax_desire

x - VMin If VMin < x < VMin_desire

VMax - x If VMax_desire < x < VMax

0 Otherwise

Z(x) = VMin_desire - VMin

VMax - VMax_desire

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6 Ni

Sk = ∑ ∑ Wi wi j Pi j k

i =1 j=1

values. These quantitative rating values are then used to calculate the overall

performance of each supplier.

For some criteria such as CAD/CAM software, testing facility, quality

certification and quality awards, a supplier may possess multiple ratings. For

example, a supplier can have physical lab and chemical lab as in-house testing

facilities. Similarly, the foundry may win national as well as international awards

indicating excellent past performance. In such cases, supplier performance for the

criterion is calculated by summing the performance values of all the ratings. For

example, if supplier S1 is having only solid modeling facility, and supplier S2 is

having all four types of software: solid modeling (0.25), process simulation (0.54),

NC process planning (0.14), and CMM (0.07) then the performance of the two

suppliers for the software criterion will be 0.25 and 1.0 respectively.

5.4 Compatibility Score

The overall score of an alternative producer is given by sum of the product of the

performance of the producer in each criterion and the effective weight of the

respective criterion:

where,

Sk = Overall score of kth producer (foundry).

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Wi = Importance (weight) of ith group criteria,

wi j = Importance of jth criterion belonging to ith group,

Pi j k = Performance of kth supplier for jth criterion of ith group.

Ni = Total number of criteria belonging to ith group.

6. Directions for Improvement

The highest overall score of an alternative process or producer only indicates that it

is more compatible compared to others, based on the trade-off among decision

criteria, with respect to the product requirements. However, an individual criterion

may or may not be fully matching (compatibility value closer to or equal to one)

with the respective requirement of the casting design. This implies that the

matching between casting requirements and the chosen process/producer alternative

can be further improved by fine-tuning the design requirement (while ensuring that

the functional requirements are not adversely affected) or by selecting an

alternative process/producer, so that the design values fall within the high

compatibility range of the chosen alternative. The methodology described in this

work allows three types of analysis and directions for improvements, as follows.

Criteria level: The performance evaluation of objective criteria on the scale of (0,1)

indicates the performance of a particular criterion for the given casting requirement.

A score of 1 indicates perfect matching between the casting requirement and

process capability, and therefore no need for any improvements. A score close to 0

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gives a feed back of poor performance and indicates an immediate need for design

improvement with respect to the particular criterion.

Group criteria level: The performance of an alternative at the group level indicates

strength (or weakness) of an alternative compared with other alternatives. This

analysis gives an insight as to how better an alternative as a group and can the

performance of an alternative be improved.

Overall compatibility level: The comparison of overall compatibility score between

ideal foundries helps identify the most suitable casting process. On the other hand,

comparison of overall compatibility score between foundries available in the

database (excluding ideal foundries) indicates the most suitable foundry. In

addition, foundries within a group (example, sand casting) can be compared with

the ideal foundry to identify areas of weakness that can be improved.

The product-process-producer compatibility evaluation model also allows

sensitivity analysis based on the criteria weights and ratings. The model can be

used to perform various ‘what-if’ iterations to analyze the outcome of the model.

Consider ‘what-if’ analysis due to change in criteria weights. Changes in weight

indicate the changed preference. Any variation in weight of an individual criterion

will change its preference (product of weight and evaluation), which will also affect

the overall performance of an alternative. The ‘what-if’ (sensitivity) analysis

enables the user to identify the influence of a particular criterion weight on the

overall performance of an alternative by changing its weight/rating.

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7. Example: Yoke Casting

Yoke – a ductile iron casting (figure 4) has been taken up to illustrate the overall

methodology including process selection, producer evaluation, benchmarking the

producer (with respect to an ideal foundry), and feedback to improve the product-

process-producer matching.


The specifications of the yoke casting are as follows: material=ductile iron,

weight=1.5 kg, maximum size=156.5 mm, minimum wall thickness=6.4 mm,

maximum wall thickness=20 mm, minimum core hole size=19.2 mm, dimensional

tolerance=0.4 mm, surface roughness=6.0 µm, order size=12000 per year, delivery

quantity=1000 castings/order, delivery frequency=1 order/month, production

rate=55 castings/hour.

7.1. Criteria Weights and Evaluation

Consider the estimation of relative weights (table 3) for the delivery capability

group. All the diagonal elements of the matrix are one (as the elements are

compared with themselves). Comparisons in only upper triangular matrix are

sufficient; reciprocal of these values form the lower triangular matrix. In the first

row of the matrix, the importance of delivery quantity criterion is considered equal

(1) over delivery frequency criterion and moderately important (3) over delivery

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distance criterion. Similarly, the second row shows the comparative importance of

delivery frequency over delivery distance.


The relative weights to each criterion are calculated by taking the nth root of the

product of n elements (n=3 in this case) in each row and then normalizing the

resulting values. The consistency ratio for this comparison matrix is 1.58%, which

is well within the acceptable limit of 10%. In this example, delivery quantity

criterion received the highest relative weight (0.44) followed by delivery frequency

(0.38) and delivery distance (0.16). A similar process is followed in calculating the

relative weight for all criteria belonging to each group, as well as weights to the

groups themselves.

For evaluation, the effective weight for each criterion is to be calculated,

given by the product of the relative weight of the criterion itself and the relative

weight of the group criterion to which it belongs. For example, the effective weight

of the minimum section thickness criterion (0.10) is given by the product of its own

weight (0.34) and the weight of geometric capability group (0.31). The complete

listing of relative and effective weights for the yoke casting is given in table 4.


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The next step is to shortlist the feasible alternatives based on the screening

criteria and then obtain the performance of every feasible alternative against each

criterion. Both ideal and real foundries for various metal-process combinations are

considered for this example. These foundries (alternatives) are then screened for

their compatibility to produce the casting. The screening criteria: cast metal (in this

case, ductile iron) eliminated gravity and pressure die casting process alternatives.

Further, only sand and shell molding processes are considered to demonstrate the

example.

Consider the evaluation of four foundry alternatives: SandCastDuctile Ideal,

SandCastDuctile_1, ShellCastDutile Ideal and ShellCastDutile_1. Four values:

minimum, minimum desired, maximum and maximum desired have been used for

fuzzy representation of section thickness (Figure 5). The maximum value is taken

as 10% more than the maximum desired. From figure 5, it is clear that the

compatibility performance of SandCastDuctile Ideal and ShellCastDutile Ideal

foundry is 1 as required value (6.4 mm) is well within the normal range of the

process capability. For SandCastDuctile_1 and ShellCastDuctile_1 foundries, the

required value is just below the normal range and their performance is 0.8 and 0.98

respectively. A similar approach is used to calculate the performance of other

objective criteria.


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To calculate the performance of subjective criteria, initially, quantification

of ratings belonging to that criterion has been carried out as discussed earlier. The

AHP method of relative weight calculation has been used to obtain the quantitative

rating values (table 5). These quantitative values are then used to determine the

performance.


7.2 Process and Producer Selection

The most suitable process for yoke casting is obtained by comparing feasible ideal

foundries. The ideal foundry will have a total score closer to, but not equal to, 1.

This is because ideal foundry will not have the evaluation value 1 for qualitative

criteria such as material utilization, porosity & voids, heat treatment, machining.

For example porosity & void capability can either be LOW, MEDIUM, HIGH, VERY

HIGH and the quantitative values for these ratings are 0.40, 0.34, 0.17 and 0.07

respectively. The porosity & void formation in shell and sand mold process is

HIGH. Thus, the evaluation value for SandCastDutile Ideal and ShellCastDutile

Ideal is 0.17.

The product-process compatibility analysis showed that ShellCastDutile

Ideal foundry has the highest overall score (0.73), closely followed by

SandCastDutile Ideal foundry (0.66) (Refer table 6). The group criteria level

analysis for these two alternatives shows that the ShellCastDutile Ideal foundry

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performed well in the quality capability (0.11) compared to SandCastDutile Ideal

foundry (0.03). In the remaining group, the performance of the two processes is

almost similar.


For identifying the most compatible producer (foundry) for the yoke

casting, four feasible foundries (SandCastDuctile_1, SandCastDuctile_2,

ShellCastDuctile_1 and ShellCastDuctile_2) have been evaluated simultaneously.

Based on the capabilities and facilities, these foundries received the score of 0.60,

0.56, 0.65 and 0.59 respectively, indicating ShellCastDuctile_1 as the most suitable

foundry for yoke. The approach allowed the evaluation of shell as well as sand

mold foundries.

7.3 Benchmarking and Directions for Improvement

Benchmarking of real life foundry should be carried out within the group. In this

example, ShellCastDuctile_1 is the most suitable foundry for the yoke requirements

and therefore it is compared with the ShellCastDuctile Ideal foundry. The group

criteria level analysis for these two foundries shows that ShellCastDuctile_1 has

low (0.09) performance in the quality capability criteria. Similarly, it has performed

poorly in manufacturing facilities and other capability criteria, which is mainly due

to the lack of facilities in the foundry (table 6). Similarly, in quality capability,

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dimensional tolerance (0.14) and minimum section thickness criterion (0.98) in

geometric capability group performed poorly, which can be further analyzed to

improve the compatibility between the yoke requirements and ShellCastDuctile_1

foundry.

The current requirements of yoke for minimum section thickness (6.4 mm)

and dimensional tolerance (0.4 mm) are not within the normal range of

ShellCastDuctile_1 foundry capability (Figure 5). Therefore, the approach gives a

pointer for improving design specifications, where any small increment in the

required value will enhance the compatibility. The final decision of choosing a

particular value for a particular criterion will however be governed by the

functional requirements of the product.

Sensitivity Analysis: Even with equal importance to the group criteria and the

criteria belonging to each group, the shell mold emerged as the most suitable

process (0.76) and ShellCastDuctile_1 (0.63) as the producer followed by

SandCastDuctile_1 (0.61).

8. Conclusion

The proposed product-process-producer evaluation methodology integrates the

hitherto separate problems of process and producer selection, by introducing the

concept of an ideal foundry. The methodology recognizes that the capabilities of

different casting processes are influenced by the cast metal involved, and also by

the facilities of the producer. The ideal foundry represents the best capabilities of a

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given process (for a particular metal) assuming the best possible facilities. This

enables using the same approach (and criteria) for evaluating a process as well as a

producer. The process/producer capabilities have been modeled using fuzzy logic,

to handle the real-life situation of the values falling within a range of normal and

extreme values. The methodology enables relative benchmarking (against other

foundries) as well as absolute benchmarking (against an ideal foundry) of

individual foundries. The compatibility evaluation approach can be easily extended

to other domains of manufacturing after identifying the relevant criteria.

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Table 1: Product-Process-Producer Compatibility Evaluation Criteria

Group Criteria Units/ Rating Values* Weight Kg Maximum length mm Min. section thickness mm Min. core hole diameter mm

Geometric capability

Shape complexity LOW, MEDIUM, HIGH, VERY HIGH Dimensional tolerance mm Surface roughness µm Quality

capability Porosity & voids LOW, MEDIUM, HIGH, VERY HIGH Quantity Number Production rate Number/hour Flexibility LOW, MEDIUM, HIGH, VERY HIGH

Production capability

Material utilization LOW, MEDIUM, HIGH, VERY HIGH Delivery quantity Number Delivery frequency Number Delivery

capability Delivery distance LOW, MEDIUM, HIGH, VERY HIGH Capacity Tons/year Foundry automation LOW, MEDIUM, HIGH, VERH HIGH

Melting equipments OIL AND GAS FIRED, ELECTRIC ARC, INDUCTION, CUPOLA

Heat treatment IN-HOUSE, OUTSOURCING Machining IN-HOUSE, OUTSOURCING

Manufacturing facilities

Testing SAND LAB, PHYSICAL LAB, SPECTROMENTER, RADIOGRAPHY, OTHER NDT

Tooling development IN-HOUSE, OUTSOURCING

Cad/Cam software SOLID MODELING, PROCESS SIMULATION, NC PROCESS PLANNING, CMM

Quality certification ISO9000, QS9000, ISO14000, CERTIFIED SUPPLIER, SELF CERTIFICATION

Other Capabilities

Quality awards INTERNATIONAL, NATIONAL, NIL * Rating values are given in capital letters

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Table 2: Scale of Relative Importance

Intensity Definition 1 Equal Importance 3 Moderate Importance 5 Strong Importance 7 Very Strong Importance 9 Extreme Importance

2, 4, 6, 8 Intermediate Values

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Table 3: Estimating Relative Weights of Delivery Capability Criterion

DQ DF DD Weights

Delivery Quantity (DQ) 1 1 3 0.4434

Delivery Frequency (DF) 1 1 2 0.3874

Delivery distance (DD) 1/3 1/2 1

0.1692

Consistency Ration =0.0158

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Table 4: Relative Weights, Effective Weights and Evaluation of Criteria

Rela

tive

Weig

ht

Gr

oup

Cr

iteria

Re

lative

Weig

hts

Ef

fectiv

e

Weig

hts

Ev

aluati

on

Cr

iteria

Sa

ndCa

stDuc

tile

Ide

al fou

ndry

Sa

ndCa

stDuc

tile_1

Foun

dry

Sa

ndCa

stDuc

tile_2

Foun

dry

Sh

ellCa

stDuc

tile

Ide

al fou

ndry

Sh

ellCa

stDuc

tile_1

Foun

dry

Sh

ellCa

stDuc

tile_2

Foun

dry

0.0820 0.0260 Weight 1.00 1.00 1.00 1.00 1.00 1.00 0.0708 0.0225 Maximum length 1.00 1.00 1.00 1.00 1.00 1.00 0.3428 0.1087 Min. section thickness 1.00 0.80 0.70 1.00 0.98 0.80 0.3161 0.1003 Min. core hole diameter 1.00 1.00 1.00 1.00 1.00 1.00

0.3172 Geometric capability

0.1883 0.0597 Shape complexity 0.20 0.20 0.20 0.26 0.26 0.26 0.2578 0.0578 Dimensional tolerance 0.15 0.06 0.00 0.60 0.14 0.20 0.3015 0.0676 Surface roughness 0.20 0.14 0.17 1.00 1.00 1.00 0.2243 Quality

capability 0.4408 0.0988 Porosity & voids 0.17 0.17 0.17 0.17 0.17 0.17 0.3619 0.0536 Quantity 1.00 1.00 1.00 1.00 1.00 1.00 0.1062 0.0157 Production rate 1.00 1.00 0.50 1.00 1.00 1.00 0.4112 0.0609 Flexibility 0.39 0.39 0.39 0.14 0.14 0.14 0.1482 Production

capability 0.1206 0.0179 Material utilization 0.19 0.19 0.19 0.29 0.29 0.29 0.4434 0.0307 Delivery quantity 1.00 1.00 1.00 1.00 1.00 1.00 0.3874 0.0268 Delivery frequency 1.00 1.00 1.00 1.00 1.00 1.00 0.0693 Delivery

capability 0.1692 0.0117 Delivery distance 0.49 0.32 0.12 0.49 0.12 0.32 0.1628 0.0191 Capacity 1.00 1.00 1.00 1.00 1.00 1.00 0.2707 0.0318 Foundry automation 0.45 0.45 0.26 0.45 0.45 0.18 0.0890 0.0105 Melting equipments 1.00 0.69 0.38 1.00 0.69 0.29 0.1037 0.0122 Heat treatment 0.67 0.67 0.33 0.67 0.67 0.33 0.2730 0.0321 Machining 0.75 0.75 0.75 0.75 0.25 0.25

0.1176 Manufacturing facilities

0.1208 0.0142 Testing 1.00 0.89 0.67 1.00 0.67 0.67 0.3873 0.0478 Tooling development 0.67 0.33 0.67 0.67 0.33 0.67 0.4162 0.0514 Cad/Cam software 1.00 0.93 0.79 1.00 0.93 0.26 0.1170 0.0144 Quality certification 1.00 0.88 0.73 1.00 0.88 0.73 0.1234 Other

Capabilities 0.0795 0.0098 Quality awards 1.00 0.32 0.32 1.00 0.32 0.11

Compatibility Score 0.66 0.60 0.56 0.73 0.65 0.59

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Table 5: Performance Rating Values for Subjective Criteria

Criteria Name

Criteria performance rating

Rating values (%)

Criteria Name

Criteria performance rating

Rating values (%)

LOW 0.0759 SAND LAB 0.1143 MEDIUM 0.2036 PHYSICAL LAB 0.2704 HIGH 0.2573 SPECTROMETER 0.2805

Shape complexity

VERY HIGH 0.4632 RADIOGRAPHY 0.2222 LOW 0.4058

Testing facilities

OTHER NDT 0.1126 MEDIUM 0.3468 IN-HOUSE 0.6667 HIGH 0.1734

Tooling development OUTSOURCING 0.3333

Porosity and voids

VERY HIGH 0.0741 SOLID MODELING 0.2548 LOW 0.1363 PROC SIMULATION 0.5357 MEDIUM 0.1948 NC PROC PLANNING 0.1410 HIGH 0.2754

CAD/CAM software

CMM 0.0685 Flexibility

VERY HIGH 0.3935 ISO-14000 0.3106 LOW 0.0827 ISO-9000 0.4220 MEDIUM 0.1848 QS-9000 0.1462 HIGH 0.2838 CERTIFIED SUPPLIER 0.0741

Material utilization

VERY HIGH 0.4487

Quality certification

SELF CERTIFICATION 0.0471 LOW 0.4923 NIL 0.1049 MEDIUM 0.3240 NATIONAL 0.3177 HIGH 0.1195

Quality awards

IINTERNATIONAL 0.5774 Delivery distance

VERY HIGH 0.0642 ELECTRIC ARC 0.2585 LOW 0.1146 INDUCTION 0.3839 MEDIUM 0.1828 CUPOLA 0.2937 HIGH 0.2557

Melting units

OIL AND GAS FIIRED 0.0638 Foundry automation

VERY HIGH 0.4469 IN-HOUSE 0.6667 Heat

treatment OUTSOURCING 0.3333 IN-HOUSE 0.7500 Machining OUTSOURCING 0.2500

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Table 6: Comparative Analysis for Foundry Capabilities

Group Criteria E

ffecti

ve

Weig

hts

San

dCas

tDuc

tile

Ide

al fou

ndry

San

dCas

tDuc

tile_1

F

ound

ry

San

dCas

tDuc

tile_2

F

ound

ry

She

llCas

tDuc

tile

Ide

al fou

ndry

She

llCas

tDuc

tile_1

F

ound

ry

She

llCas

tDuc

tile_2

F

ound

ry

Geometric capability 0.3172 0.2694 0.2477 0.2368 0.2730 0.2708 0.2513 Quality capability 0.2243 0.0390 0.0298 0.0283 0.1191 0.0925 0.0960 Production capability 0.1482 0.0965 0.0965 0.0887 0.0830 0.0830 0.0830 Delivery capability 0.0693 0.0632 0.0612 0.0589 0.0632 0.0589 0.0612 Manufacturing facilities 0.1176 0.0904 0.0855 0.0690 0.0904 0.0663 0.0493 Other Capabilities 0.1234 0.1076 0.0794 0.0862 0.1076 0.0794 0.0570

Total 1.0000 0.6661 0.6001 0.5679 0.7363 0.6509 0.5978

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List of Figures: Figure 1: Product-Process-Producer Compatibility Evaluation Methodology

Figure 2: Schematic Representation of AHP Model

Figure 3: Fuzzy Mapping of Process Capability Value

Figure 4: Yoke Casting

Figure 5: Evaluating Minimum Section Thickness of Yoke

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Figure 1: Product-Process-Producer Compatibility Evaluation Methodology

OVERALL DECISION GOAL: PRODUCT-PROCESS-PRODUCER

COMPATIBILITY EVALUATIONN

CRITERIA IDENTIFICATION

HIERARCHICAL STRUCTURING OF EVALUATION CRITERIA

SCREENING OF POTENTIAL PRODUCERS

EVALUATE FEASIBLE PRODUCER

OVERALL SCORE CALCULATION FOR FEASIBLE PRODUCER

CHOOSE THE MOST SUITABLE PRODUCER

CREATE DATABASE OF PRODUCERS

RATING APPROACH

QUANTITATIVE CRITERIA

QUALITATIVE CRITERIA

FUZZY LOGIC APPROACH

COMPUTE CRITERIA RELATIVE WEIGHTS

USING AHP

EVALUATE CRITERIA PERFORMANCE

CASTING REQUIREMENTS: MIN SECTION THICKNESS, MIN

CORE HOLE, FINISH, TOLERANCE, PRODUCTION RATE, QUANTITY,

MATERIAL

DATABASE OF RELATIVE WEIGHTS

FEED BACK

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LEVEL 2 Group criteria

LEVEL 1 Overall objective

LEVEL 3 Criteria

LEVEL 4 Alternatives

Figure 2: Schematic Representation of AHP Model

G C

Product-process-producer compatibility evaluation

Q C P C D C MF O C

Flexibility Production rate

Material utilization Quantity

Producer 1 Producer 2 Producer 4 Producer 3

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Figure 3: Fuzzy Mapping of Process Capability Value

VMin VMin_desire VMax_desire VMax

1

0

z (x) ‘X’ unit requirement

Comp

atibil

ity

Process capability

Normal range

Extreme range

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Figure 4: Yoke Casting

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Figure 5: Evaluating Minimum Section Thickness of Yoke

4.8

3.2 1000 1100

1

0

z (x)

Comp

atibil

ity

(A) SandCastDuctile Ideal Foundry

Required Section thickness

6.4

7.0

4.0 1000 1100

1

0

z (x)

Comp

atibil

ity

(B) SandCastDuctile_1 Foundry


6.4

4.5

1.5 50 55

1

0

z (x)

Comp

atibil

ity

(C) ShellCastDuctile Ideal Foundry


6.4

6.5

2.5 50 55

1

0

z (x) Co

mpati

bility

(D) ShellCastDuctile_1 Foundry


6.4

casting product-process-producer compatibility evaluation

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