jasco design tool for automotive heat...

Proceedings of KGCOE-MD2005: Multi-Disciplinary Engineering Design Conference

Kate Gleason College of Engineering Rochester Institute of Technology

Rochester New York February, 2006

Copyright © 2006 by Rochester Institute of Technology

R·I·T

MERIT 06433

JASCO DESIGN TOOL FOR AUTOMOTIVE HEAT EXCHANGERS

Mark Cirillo – Project Manager/ME

John Crouse - ME Jason Magoon – ME

Joel Berg – Project Mentor

ABSTRACT

The JASCO Design Tool is created for the explicit use of

the JASCO Corporation in order to minimize the prototype design phase and maximize productivity to attract new business. In order to do so previous designs created through trial and error are analyzed, deconstructed, and reconstructed to determine the necessary relationships and assumptions that are inherently accepted from previous tool designers. By quantifying these assumptions the JASCO Senior Design Team is able to produce a fully parametric 3-Dimensional CAD model that accurately depicts the heat exchanger fin creation process and allows for future tool development as new technologies and processes are developed. INTRODUCTION

JASCO Precision Machining (JASCO) sells radiator and

heat exchanger tooling to the automotive market. These tools look like thin saw blades and are assembled into sets called rolls. Two rolls, similar to two gears, are used to slit and form fins that assemble into radiator and heat exchanger components. Currently, JASCO receives tool design prints from customers to produce the blade disks, test the tools, check the formed fin and regrind the blades to fix any discrepancies between the formed fin and the fin prints. This process is very time consuming, inefficient and expensive. JASCO is looking to develop design capability in-house and wants to investigate a tool design project that will enable the company to produce parts to print the first time.

Figure 1: Sample Tool Setup



In order to develop the necessary relationships incorporated into the fin forming process a study of both gear design and sheet metal forming practices was performed. Previous studies performed in house by JASCO provide a starting point into the overall tool design process that is unique to this market. Companies such as Delphi, Visteon, and Valeo have performed, published, and perfected design tools for this market. The knowledge base built by these companies is a trade secret however resulting in the need for the JASCO Senior Design Team to develop these secrets for the JASCO Corporation so that the company can better perform in the world market.

The design tool has been created in Unigraphics NX3. The result is a fully parametric 3-Dimensional assembly that enables JASCO to input critical dimensions from customer fin prints which will in turn modify the final tooling prints. The design tool includes variability parameters that allow for tweaking of the tool-part relationships to account for variations in the process, material, and other unknown variables. This allows JASCO to iterate the design process to make sure the tool is capable of manufacturing parts that meet print. Empirical data can then be collected to establish dimensional trends in the process and allow JASCO to create a feedback loop and adapt the tool to these trends. Engineering analysis was performed on the fins in order to identify as much process and material variation as possible and incorporate these findings into the design tool.

DESIGN PROCESS

In order to tackle this problem, it is most important to

develop criteria around which to base the overall concept.

Performance Criteria: 1) The design must be capable of producing parts that meet the

customer’s dimensional requirements to within an acceptable and previously agreed upon tolerance range.

2) The design must parametrically adapt to design modifications proposed by the customer.

3) The design must be able to be applied to new customers’ proposals and specifications.

4) The design must have an uncomplicated user interface. 5) The design must be properly documented to explain

capabilities and constraints. During brainstorming sessions two approaches became

readily apparent; a computer spreadsheet program (Microsoft’s Excel) or a fully developed 3-Dimensional CAD assembly (Unigraphics NX3).

Due to its availability and ease of use, the idea of incorporating Microsoft’s Excel program into the design tool development was considered. The benefits of this approach are that the basic infrastructure is already in place to make immediate use of the final tool, cost, and that it can meet all the required performance criteria.

The overwhelming power of the Unigraphics NX3 software package makes it a perfect choice in developing an all encompassing design tool. This CAD package has the ability to meet all of the performance criteria while allowing for future

development and design iterations to take place. The program allows for constant growth within the scope of this project and also provides a foundation to expand out into various other realms of metal forming processes.

Due to the nature of the forming process, unpredictable variability makes it difficult to reach the dimensional goals of the fin print. With customer process variation, certain input parameters cannot be documented or controlled resulting in possible dimensional issues beyond the scope of the design tool. A lack of information on dimensional and tolerance capability of the process also adds another unknown to the final fin geometry.

The forming blades are not cheap to manufacture; so the high cost of the manufacturing process adds risk. High precision manufacturing is needed to create the tools which add time and cost to each individual forming blade. The non-linear nature of the process makes analysis difficult. Due to plastic deformation, large displacement, and contact analysis a very complicated and involved simulation must be preformed in order to correctly model the forming process.

Figure 2: Fin forming process

Due to multiple unknowns in the actual production of the

fins, it is difficult to accurately model the forming process. Some questions to consider are:

When does the material start to peel off of the tool? Does stretching of the material occur? How do the lead in and pull out tensions of the material

affect the part dimensions? Is the design center-to-center distance being held

properly? Are there inconsistencies in the material composition? Is the part being deformed when it is pulled off of the tool? Are there other unknown variables affecting the process? These questions must be answered in order to build a

robust design tool.



PRELIMINARY DESIGN A fully parametric 3-Dimensional assembly enables

JASCO to input critical dimensions from the customer fin prints which will in turn modify the tool parameters. It includes variability parameters that allow for tweaking of the tool-part relationships to account for variations in the process, material, and other unknown variables.

Before developing the 3-Dimensional Model, a relationship between opposing teeth on the rolls must be made. Since the entire apparatus replicates the meshing of twin gears, the basis of the design tool is built upon time tested gear design formulas. The principles of pressure angle, backlash, and tooth meshing are all incorporated into the dimensional and geometric constraints of the model.

Gear design is not the only criteria to be incorporated into the overall design. The twin rolls are not designed to mesh with each other. The gear system is designed with spacing between the rolls to allow for fin material to pass through. In order to model the interaction between the two rolls and the aluminum fin material, sheet metal bending and neutral axis theory was applied. For example, in sheet metal design a known characteristic of most metals is that when the bend radius is greater than three times the material thickness, the neutral axis stays in the middle of the material, resulting in a K-factor of 0.5. This has been incorporated into the design.

Using Math Data Tools built into Unigraphics NX3, a 3-Dimensional parametric fully associative assembly that captures the customer design intent, internal manufacturing process, incorporates an engineering feedback capability, and simplifies the final tooling design and production process was created.

Figure 3: Master Layout – All parametric associations developed

Figure 4: 3-D tooling assembly

Figure 5: Neutral used as parent for half and regular tools

Figure 6: Associative Drawing Environment and established relationships



Figure 7: Associative Drawing Environment and established relationships

The fin is created as a 3-Dimensional parametric fully

associative assembly in order to minimize redundant modeling, to enable efficient design changes, and to parametrically associate the fin to the forming tools.

Figure 8: Fin modeled as assembly

Figure 9: Individual Louvers modeled, assembled, united, and mirrored to form final fin.

Figure 10: Conditional expressions allow for automatic forming and deforming of fin.

An adjustment parameter “Black Box” approach was

designed between the part and the tool to allow for feedback of process variation into the design tool. These “Black Box” parameters can be modified to incorporate empirical data, engineering analysis data, dimensional analysis results, etc…

PART DIMENSIONAL INPUT


BLACK BOX

BLACK BOX

TOOL DIMENSIONAL OUTPUT


INPUT DIMENSIONS MODIFIED TO INCORPORATE MANUFACTURING

FEEDBACK


FEEDBACK



BLACK BOX

BLACK BOX





BLACK BOX

BLACK BOX




FEEDBACK


FEEDBACK

ENGINEERING MODEL The final iteration of the design tool is a fully parametric 3-

Dimensional assembly incorporating data from finite element analysis and a design of experiments (discussed next section).

Figure 11: Graphical User Interface to link all parametric associations in one location

All that must be done is to input customer data into the visual parametric editor. The fully associative geometry already



created will change into exactly what the customer has specified. From this fully associated geometry, the program will update and modify the already created drawings for the tool blades into what is used to make the required blades to manufacture the fin. All the operator will have to do is change the part number and print out a brand new drawing.

The 3-Dimensional assembly can also be used in a computer aided manufacturing type of environment that will allow JASCO to write programs for their computer numerically controlled machines directly from the geometry of the model.

Also, the parametric design tool has the capability to account for any variation in the process. This area is where JASCO will input any new variables related to fin height and the new parameters will integrate with the existing geometry to form the desired fin.

EXPERIMENTAL SET-UP AND PROCEDURE

Exactly what happens to the tip radius as the part is

initially formed by the tool, compressed, pulled apart and compressed again must be experimentally determined. As the material is fed into the tool, all three forms of non-linear deformation are taking place. They are:

1. Plastic deformation 2. Large displacement 3. Frictional Contact The deformation that occurs as the fin is compressed,

pulled apart and compressed again is non-linear and has been analyzed. It is recognized that a pre-stress condition exists and occurs during the initial forming process; this condition has not been accounted for.

To fully understand exactly what is happening to the tip radius and overall fin height during the processes the fin is subjected to, the team decided to pursue two courses of action. First, a Design of Experiments (DOE) analysis procedure has been developed and performed.

Material thickness, die radius, and center to center distance are variable inputs into the system in order to produce a certain fin radius output. All three of these input variables can be modified by JASCO during the experimental process and the data recorded in an Excel spreadsheet the team has developed along with statistical analysis built into MiniTAB.

The DOE consists of two predetermined center to center distances, two tool radii, and two material thicknesses. A total of eight material runs are made varying the parameters and the produced parts are analyzed for radius of curvature and overall fin height. These results are then statistically analyzed to determine the effects of each parameter individually and the effect of combined variables. This process allows for a systematic approach to developing hidden relationships between variables in a controlled environment with minimum input of time and resources.

Figure 12: DOE Data Collection

A non-linear Finite Element Analysis performed on the fin

was also used to verify the experimental results. The team received a sample of two different fin and tool geometries to analyze in order to incorporate real world data into the ANSYS program. The results of this analysis are used to verify the location of the neutral axis during forming, in predicting spring back, and the pre-stress condition created by the forming process as the fin enters the density stations. It also allows for the effect of end tension upon the forming process to become apparent since the team does not have access to an entire production line setup.

Figure 13: Initial Step

Figure 14: Intermediate Step



Figure 15: Final Step DATA ANALYSIS

The following graphs are the result of statistical analysis

performed by the MiniTAB statistics program.

Effect

Pe

rce

nt

0.0060.0050.0040.0030.0020.0010.000-0.001-0.002-0.003

99

95

90

80

7060504030

20

10

5

1

A C -to-CB Tool RadC Mat Th

Factor Name

Not SignificantSignificant

Effect Type

BC

C

Normal Probability Plot of the Effects(response is Rad, Alpha = .05)

Lenth's PSE = 0.00045 Figure 16: Probability Plot for Radius of Curvature

Mat Th

Me

an

0.00510.0033

0.033

0.032

0.031

0.030

0.029

0.028

0.027

0.026

0.025

InitialFinal

Too l Rad

Interaction Plot (data means) for Rad

Figure 17: Interaction Plot between Material Thickness and Tool Radius The following Excel tables are the product of statistical analysis performed to validate the MiniTAB program’s findings and

also provide a numerical association between variables and their importance.

SS Df MS F Alpha Conf.

Factor A 0.0 1 0.00 37.52 0.103 90%

Factor B 0.0 1 0.00 112.8

9 0.060 94%

Factor C 0.0 1 0.00 10764

.06 0.006 99%

Factor D (AB)

0.0 1 0.00 39.06 0.101 90%

Factor E (AC)

0.0 1 0.00 1.27 0.463 54%

Factor F (BC)

0.0 1 0.00 2081.64

0.014 99%

Factor G (ABC) 0.0 1 0.00

Total 0.0 7 Table 1: Analysis of Radius of Curvature

SS Df MS F Alpha Conf.

Factor A 0.0 1 0.00 0.07 0.832 17%

Factor B 0.0 1 0.00 1.39 0.448 55%

Factor C 0.0 1 0.00 0.17 0.752 25% Factor D

(AB) 0.0 1 0.00 0.10 0.808 19% Factor E

(AC) 0.0 1 0.00 0.97 0.505 49% Factor F

(BC) 0.0 1 0.00 0.00 0.999 0% Factor G

(ABC) 0.0 1 0.00 Total 0.0 7

Table 2: Analysis of Overall Fin Height Df = Degrees of freedom SS = Sum of Squares Alpha = F-test probability MS = Mean Sum of Squares F = F-test characteristic

RESULTS AND INTERPRETATION

Using pure theoretical analysis through gear design and

sheet metal bending theory, the design tool is capable of achieving approximately 90% dimensional accuracy. The purpose of the design of experiments and finite element analysis is to gain as much of that last 10% of dimensional accuracy as possible. This data and the derived relationships are then incorporated into a black box correction factor.

DOE analysis of the fin radius of curvature confirmed assumptions previously made during the design process. The radius is affected primarily by changes in material thickness and the resulting material to tool radius interaction. Also, center to center roll distance plays a large roll in the final formed radius.

DOE analysis of the fin height did provide an interesting primary factor in the resulting part. According to the data, the tooling radius plays the most significant role in fin height. This result is a false positive however as the overall roll diameter changed as the result of the regrinding of the radius. The



interaction between roll center to center distance and material thickness does confirm previous assumptions and is the primary driving factor behind formed fin height.

The relationships discovered and confirmed by the design of experiments provide great insight into the fin forming process. The jewel of the process is an empirical relationship that is uncovered between theoretical fin height and actual fin height. While more runs and data would help to refine the result, the actual fin height is approximately 5% taller than the theoretical result. This realization is a favorable result as the fin height can be reduced during production by increasing the roll center to center distance.

CONCLUSIONS

The primary focus of the design tool is to enable

production tooling capability for producing a formed fin to customer specified dimensions. The fin height is critical to the overall production of heat exchangers to maximize braze contact area which in turn increases the overall system heat transfer capability. This is why JASCO has approached RIT and the Multidisciplinary Senior Design Program. Currently JASCO has very limited design capability which requires multiple iterations of tooling in order to produce a single fin type to print. Due to the expensive tooling costs and the variables associated with each customer’s fin production methods, the need for a fully integrated design tool is apparent. This design tool gives JASCO full design and feedback capability that allows the company to pursue new contracts and thrive in an ever-changing industrial environment.

The resulting design tool is ready for a production environment. The tool is able to produce final designs within 95% dimensional accuracy of the final fin and allows for production variance to be incorporated over time. It is an intelligent tool that will approach 100% dimensional accuracy as it is used and further iterations and data corrections are incorporated into the overall program. All of this is incorporated into a simple, easy to use graphical interface that any computer literate person with some CAD knowledge can use.

RECOMMENDATIONS FOR FUTURE WORK 1. Build production ready tools using the design tool to

further verify its applicability to designs of varying diameter, center to center distance, and fin height.

2. Continue Finite Element Analysis activities focusing on the pre and post-forming operations that the fin material is subjected to in order to further understand the process and incorporate this data into the design tool.

3. Perform a Design of Experiments increasing the number of inputs (center to center distance, end tension, material properties, material thickness, and tip radius) and also using various tooling designs (various diameter tooling).

4. Develop dimensional analysis capabilities for JASCO (What tolerances can they hold? What accuracies?) and develop sophisticated inspection capabilities for both the tools and finished fins.

5. Develop a density station test and possibly invest in an entire production station in order to perform in house fin creation and testing.



BIBLIOGRAPHY

Mechanics of Materials; Beer, Johnston, DeWolf. McGraw-Hill Science/Engineering/Math; 3 edition (July 9, 2001)

Design of Machine Elements; Spotts, Shoup, Hornberger.

Prentice Hall; 8th edition (October 14, 2003) Marks Standard Handbook for Mechanical Engineers;

Avallone, E.A.; Baumeister, T., III; 10th edition McGraw-Hill 1996

Machinery’s Handbook; Jones, Horton, Ryffell. Industrial

Press; 26th Edition (2000) Bendworks, The Fine Art of Sheet Metal Bending

www.massey.ac.nz/~odiegel/bendworks/bending.pdf Handbooks:

ANSYS: Basic Structural Nonlinearities Training Manual for Release 5.6

ANSYS: Basic Structural Nonlinearities Workshop Supplement for Release 5.6 ANSYS: Advanced Contact and Bolt Pretension

Training Manual for Release 5.6 ANSYS: Advanced Contact and Bolt Pretension

Workshop Supplement for Release 5.6 ANSYS Tutorial for Release 8.0

ACKNOWLEDGEMENTS

JASCO Precision Machining, specifically Mr. Dave Krieger and Mr. Nate Theriault, for providing the project, material, and machining support necessary to make this project a success. Dr. Wayne Walter for his guidance and knowledge as team coordinator and faculty advisor. Mr. Joel S. Berg of Impact Technologies for ANSYS and FEA support above and beyond the call of duty. Mr. Avinash V. Sarlashkar for providing insight into the FEA analysis and guidance on the design of experiments. Dr. Joseph G. Voelkel for his insight and assistance in the design of experiments analysis. The RIT Mechanical Engineering Machine Shop Staff for their assistance and providing tools necessary to complete rudimentary analysis on the fin forming process. Mr. Tim Landschoot for providing onsite testing and measuring assistance necessary to complete the design of experiments.

jasco design tool for automotive heat...

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