5500_tcm78-4324.pdf

Issued by: Siemens PLM Software. © 2010. Siemens Product Lifecycle Management Software Inc. All rights reserved.

Practical implementation of best practices for analysis in a design environment

Maximizing the business impact of technology requires far more than just buying the right point functionality and handing it off to the analysis department. Digital simulation needs to be at the core of every PLM business process because it enables management to make faster, more informed decisions. Overall, increasing use of digital simulation leads to better products that are more salable, have better performance and higher margins, all of which directly benefit the bottom line.

White Paper


White Paper | Practical implementation of best practices for analysis in a design environment | 1 July 2010

2

Contents

Executive summary............................................................................. 3

Introduction........................................................................................ 4

Workflow ............................................................................................ 5

Wizards and knowledge ...................................................................... 7

Simulation Process Studio ................................................................... 8

Example process showing steps, options and a brief description ........ 9

CAE PLM workflow directions............................................................ 13



3

Business initiatives such as Lean Design and Design for Six Sigma demand the use of best practices. However, the restrictions of software complexity, software customization, user training and user CAE knowledge all combine to make this a difficult challenge. This paper describes a new approach to providing a flexible method for the CAE analyst to author guidelines that will keep a designer user (with limited CAE experience) within a safe route through the CAE landscape. This will ensure that the end user obtains realistic and reliable results and frees up the CAE analyst to carry out the more difficult and complex work. Being able to repeat these processes ensures that the analyst and company best practices can be followed.

Executive summary



4

There are two main business initiatives that are being studied, investigated and implemented in current leading product design and manufacturing compa-nies. They are Design for Six Sigma and Lean Design.

The successful implementation of Six Sigma (SS) manufacturing processes has been well proven, but a more recent trend has been to extend this concept into the product design and development phases and was named Design for Six Sigma (DFSS). Implement-ing DFSS involves re-engineering the design and development processes to improve the design quality, and consequently the manufacturing quality. Simula-tion of product performance is an intricate part of improving product quality and must be part of DFSS processes.

Lean Design is all about reducing waste in the design and development process, and is strongly linked to DFSS. There are a number of business drivers that are influenced by Lean Design and are enabled by simulation tools and processes.

1. Fewer physical prototypes

• Simulating product performance is the major influence in reducing the number of physical prototypes that need to be built and tested.

2. Less design and development time

• Design changes driven by simulation result in better, and fewer, decisions being made. This will result in less time and money spent on rework.

• Building and testing fewer physical prototypes reduces development time scales.

• Process efficiency is the major part of achieving Lean Design, which requires companies to reduce the time and effort required to transfer or translate information, improve data accuracy and lower the cost of reworking their data.

3. Reduced bottom line costs

• Higher quality product design leads to reduced material, warranty and component costs.

• Lower R&D costs can be achieved by reducing the number of physical prototypes and physical tests needed during product development.

• Process efficiency leads to reduced ongoing costs in software purchasing, maintenance and training.

This paper will show how these business drivers and the initiatives of DFSS and Lean Design are influenc-ing the use of simulation tools in the short term, and how they will change the way CAE is used in the product lifecycle.

Introduction



5

The business initiatives of DFSS and Lean Design are forcing companies to bring simulation tools to a wider community. It is no longer acceptable that simulation is not used in the product development cycle, and indeed it is now a competitive imperative that companies succeed in this effort.

Many engineering companies design and produce variants or similar products. The analytical work is based upon best practices developed over the years by experienced engineers and analysts. This can result in day-to-day analytical work being reduced to a repeated set of connected steps with small varia-tions. Often, even more non-regular tasks are accomplished using a series of subprocesses. This repeated set of connected steps can be classified as a workflow, as illustrated in Figure 1.

In the past, many different methods have been developed to instill discipline into the simulation workflow, including hard coding these workflow with simplified interfaces, macros or programs. Many of these methods have been successful in saving time and therefore money. However, by their very nature these solutions are inflexible.

A number of industry organizations have been instrumental in promoting best practices, training and education and this has improved the quality of the

simulation workflows while achieving DFSS and Lean Design goals. However, the training and best prac-tices tend to be aimed at the expert analyst and not at the design analyst. There is also the question of trust in, and quality of, the results. Even though a designer analyst is following laid-down guidelines and best practices, there is always a concern that the results may not be valid.

The CAD/CAE vendor-produced software and custom-ized systems are directly aimed at the designer analyst and repeatable workflows, but the software applications have yet to discover the fine line between the needs of the designer analyst and the expert analyst. The programming languages used for macro customization give the user little ability to allow the flexible use of the macro/program. Also, these require an extensive knowledge of the CAD/CAE application(s) and a programming language.

It should also be noted that current attempts to capture CAE workflows are focused on the minutiae of model prep, boundary conditions, meshing, solving, etc. An ever increasing drive is to link different CAE solutions, to manage data and to manage the overall CAE process within product development, becoming an integral part of the product lifecycle management (PLM).

Workflow



6

Design input

Vehicle systemsperformance

simulation

Airflow andcombustion

Valvetrain andengine performance

Rotating andreciprocration

Lubrication andcooling

Head block andexhaust

Vehicle specsand

requirements

Balancerequirements

Powertrain specsperformance and

cooling requirements

Solid modelgeometry

NX

Matlab/TRSAT

Lab data: head gasketcharacteristics

Bearing loads

Flare

Piston rod and crank analysis

Nastran, abaqus,CFDA

Map HTC’s tostructural model

EnSight

Engineperformance(torque, HP)GTPower

Engineperformance(torque, HP)

GTPower

Transient thermalstrucural analysis

Abaqus

Special headand block

Post processingInspect

Piston rod andcrank models

Hypermesh, recipsoft codes

Coolant flow, tetramesh model

Airflow model

Surfseg, ICEM, Hypermesh

Airflow characteristics

Fluent, Star CD, GMTEC

Fluent, Star CD

Performed by analysis group

Performed by analysis group or designing engineer

Information being interpeted and re-entered

GMPT CAE workflow – engines

Coolant flowAnalysis: flow

rate HTC’sHypermesh

Hypermesh

Head and blockFEM model

General Motors Corporation, Daratech Summit, February 2005

Figure 1: Example workflow.



7

The use of wizards is an increasingly popular solution that companies can use to automate their workflows and facilitate their DFSS and Lean Design objectives. Anyone who has installed software on a Windows PC will be familiar with the concept of a wizard. These applications offer a simple user interface to step the user through a series of selections, and then the wizard proceeds to carry out the complicated work of installing the related software. There are many wizards on websites to step users through the process of selecting and ordering new products.

There are also many existing wizards available for specific CAD/CAE systems. Industry-focused wizards have proven themselves to be very effective, includ-ing wizards for:

• Simple linear static part analysis

• Mold tool design

• Progressive dies

• Automotive dies

• Optimization

These CAD/CAE and manufacturing wizards step the user through the workflow, enabling the user to interact with the geometry and its models, as well as to build further geometry, select sizes based on model size and interface with external data files. Options can be presented to the user as a fixed list, including instances where the user can select specific items, such as materials or sizes.

The latest wizards are able to take advantage of the built-in knowledge engines in the CAD/CAE systems. Thus, not only can the wizard step the user through a workflow, the wizard can take advantage of the knowledge built into the design. The example shown in Figure 2 is an optimization wizard where the user can choose from a list of the physical properties of the model that define the optimization goal. As the optimization proceeds, the knowledge engine keeps this value up to date.

The advantages of these wizard applications can be seen in those use cases or industries where the workflow is very well defined, and the variation in use is rigidly bounded. However, in the case of CAE workflows, the use of hard-coded wizards has limited appeal as they often do not match the customer’s best practices.

Figure 2. Example CAD/CAE wizard.

Wizards and knowledge



8

As previously discussed, there are areas where a hard-coded wizard is very effective, but increasingly there is recognition for a need to be able to build custom wizards. This drive has been held back by the need to employ high level programmers to develop the wizard. These skills exist within the software vendor companies, but in general not at the end user customer companies and it is here that the local workflows are needed to suit local best practices.

A new approach is now available to address many of these issues. NX™ Simulation Process Studio software enables the CAE analyst to author guidelines that will provide a designer user (with limited CAE experience) with a safe route through the CAE landscape. This will ensure that the end user obtains realistic and reliable results, and frees up the CAE analyst to carry out the more difficult and complex work. Being able to repeat these processes ensures that the analyst and com-pany best practices can be followed.

Simulation Process Studio does not generate rigid automation like a macro. Instead, it guides the end user down a best practice route to achieve realistic and reliable results. Figure 3 shows the user interface layout of Simulation Process Studio. The black area on the left is the layout area where the user drags and drops the process steps and connects them together. The top right panel shows the properties of the selected component, and the bottom right panel shows the user how it will look when the user runs the wizard. Off-the-shelf drag-and-drop steps, including user-defined branching, leverages the rest of NX CAE and its modeling functionality.

Figure 3: Simulation Process Studio user interface.

Simulation Process Studio



9

1. Initial welcome step defines the solver environment. The default solver environment is the industry standard NX Nastran; other solver options currently supported are MSC Nastran, Ansys and Abaqus.

2. The material selection step allows the author to prompt the end user to select specific material from the presented list. Most of the following steps can be extended using flexible and advanced knowledge rules.

3. This is an example of a user-defined step that can be used to access one, or multiple, functions from anywhere in NX. In this case the author is using the idealize geometry function to allow the end user to simplify the model geometry. For example, the user could remove all holes less than a specified diameter, or remove all blends less than a specified radius. The author documents the best practice in the online help to guide the user to make the correct decisions for the part in question.

Example process showing steps, options and a brief description



10

4. The ideal mesh size controls are available for the author to define at this step. This can be left to the end user to decide or the author can also build enough knowledge into the wizard to force this meshing step to be automatic and remove the choice from the user. In this example, the author has allowed users to specify their own ideal mesh size, or to ask the system to estimate a size based on the geometry.

5. At this stage the author allows the end user to select only a face (or multiple faces) to define the fixed constraint(s); i.e. all DOF are fixed for nodes that eventually lie on this face when the part is meshed. Note that all steps can have specific URL links for best practice documentation; below is the help page that applies to this step.



11

6. The author can guide the user in placing specific types of loads, load orientations and even specific load values. Knowledge rules can add further guidance for the user.

7. The author has decided to have the end user check the completeness of the model. This will present a short report to the user with any errors or warnings highlighted. Should any errors or problems occur, the end user is directed to stop and consult the analyst for advice.

8. The solve can be set to automatically run without the end user being asked. In our example, the author has allowed the user to decide to run the solution. Note in this case, the author has decided to implement a company best practice that prohibits the use of the mesh adaption option.



12

9. The author has numerous options that enable users to determine what result they want to view. In this example, the author has turned on the fatigue, deformation, Von Mises stresses and the answer quality displays. Best practice documen-tation teaches the end user to look at the red, yellow and green quality answer display to see if the answers are reliable. The documentation shows the user how to interpret the other types of display results.

10. If there is a best practice requirement to document all analysis work, then the author can include a reporting step. Optionally, the author can stipulate that screen snapshots of each of the results should be captured and included in the report.

11. At the end of the process the user is given the choice of saving the CAE data associated with this process. This option would let the analyst study the model, boundary conditions and results before sign off. Alternatively, the author can define this as an automatic step by specifying no save; this is feasible since the process is only being used to guide and optimize the design.



13

Companies commonly use multiple CAE systems from different software vendors to perform simulations for use by different disciplines (e.g., structural and fluid simulation applications). One of the most common (but often forgotten or taken for granted) approaches is to link different applications in order to compare physical test results against theoretical analysis assumptions.

Sometimes these different disciplines can be treated independently, but more often they are linked in some way. This can be achieved by using built-in multi-physics applications, linking of solvers using message passing interface (MPI) techniques, and allowing customers to create their own techniques to transfer data between applications. However, in many cases, the link between applications or solvers is not so tightly defined.

All of these situations are part of the product development lifecycle and are considered to be PLM issues. Using the Simulation Process Studio in the PLM context will provide a method of guiding the user through the tasks necessary to link multiple CAE systems from different software vendors. Then, PLM can function as a data and process management backbone that companies can use to achieve their DFSS and Lean Design objectives.

CAE PLM workflow directions

1

About Siemens PLM Software

Siemens PLM Software, a business unit of the Siemens Industry Automation Division, is a leading global provider of product lifecycle management (PLM) software and services with nearly 6.7 million licensed seats and 63,000 customers worldwide.Headquartered in Plano, Texas, Siemens PLM Software works collaboratively with companies to deliver open solutions that help them turn more ideas into successful products. For more information on Siemens PLM Software products and services, visit www.siemens.com/plm.

Siemens PLM Software

HeadquartersGranite Park One5800 Granite ParkwaySuite 600Plano, TX 75024USA972 987 3000Fax 972 987 3398

AmericasGranite Park One5800 Granite ParkwaySuite 600Plano, TX 75024USA800 498 5351Fax 972 987 3398

Europe3 Knoll RoadCamberleySurrey GU15 3SYUnited Kingdom44 (0) 1276 702000Fax 44 (0) 1276 702130

Asia-PacificSuites 6804-8, 68/F Central Plaza18 Harbour Road WanChaiHong Kong852 2230 3333Fax 852 2230 3210

© 2010 Siemens Product Lifecycle Management Software Inc. All rights reserved. Siemens and the Siemens logo are registered trademarks of Siemens AG. D-Cubed, Femap, Geolus, GO PLM, I-deas, Insight, Jack, JT, NX, Parasolid, Solid Edge, Teamcenter, Tecnomatix and Velocity Series are trademarks or registered trademarks of Siemens Product Lifecycle Management Software Inc. or its subsidiaries in the United States and in other countries. All other logos, trademarks, registered trademarks or service marks used herein are the property of their respective holders.

X4 5500 6/10 Cwww.siemens.com/plm

5500_tcm78-4324.pdf

Documents