PartnerCaseStudyFord_FINALv2

7/30/2019 PartnerCaseStudyFord_FINALv2

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Although variety is the spice o lie, its the bane o manuacturing companies.Designers and engineers must account or inevitable variation, minute or other-wise, in products coming o the manuacturing line. Some companies, like Ford,prepare or variation rom the start o their product development cycle. Others

cross their ingers, start manuacturing, and clean up the mess later.

To understand the problems that variation can present, one must remember thatnothing manuactured is ever perect. Computer-aided design (CAD) data repre-sents theoretical nominal design intent the ideal not the actual quality or perormance o the product that is shipped to the customer. CAD does not manuac

ture anything; real-world manuacturing and assembly processes do. The act thaa design looks right in CAD doesnt mean its going to build right in the plant.

A product as simple as a one-inch diameter cylinder is never exactly one inch in

diameter in real lie. It comes out o the actory slightly thick, thin or out o roundDepending on the product designers speciied tolerances (and the plants capabity), the variance can be so dramatic that, when combined with other variable parthe resulting product ails.

Risk looms with every design. By some accounts, as much as hal o scrap andrework stems rom poor tolerance and variation management. And companiesspend enormous sums on the cost o poor quality, including redesign, engineerinchange orders, recalls, warranty, liability, release/launch delays, chronic manu-acturing problems, and tarnished brand names. An estimated eight out o 10 SixSigma critical to quality issues boil down to controlling dimensional variation.

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Its one thing to take a calculated design risk and come up short, explains BobGardner, CEO o Varatech, a company that has created tolerance and assemblybuild analysis sotware called Sigmund to address the problem. Its another iyou are totally blind-sided with problems at launch because o lack o insight onvarious critical relationships between variable parts. This is what happens i qualbuild objectives are not deined up ront and tolerance data, i any, is simply spri

kled on arbitrarily at the end o a design. This situation can be very expensive.

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Its critical to deine quality build objectives up ront, according to Gardner, whodeines them as important assembly relationships that will aect it, inish, andunction. Ask yoursel: what are the important traits o your product that translatinto quality? For the body o a luxury car, one indicator o quality might be that aball bearing can roll smoothly along the seams every time. That would be a qualibuild objective. Quality build objectives inluence how the product will perorm an

how problem-ree it will build in production.

Leading engineering teams derive quality build objectives rom sources like competitive assessment, benchmark studies, marketing requirements, quality unctio

deployment (QFD) analysis indings, user requirements, ailure analysis, and manals like the Machinery Handbookor mechanism relationships.

Once quality build objectives are identiied and quantiied to produce measurable

targets, these targets will drive the design. For example, Ford Motor Companyuses Varatechs Sigmund in ork-in-the-road studies to determine which o sevedesign concepts are most capable or robust relative to variation, geometric senstivity, and meeting the pre-deined quality build objectives. Quality build objectivedetermine which Sigmund-powered studies are required Worst Case, ModiiedRSS, and Monte Carlo Tolerance. These studies traditionally have been perormeby hand or spreadsheet, without any linkage to the CAD sotware used in thedesign, making it arduous to develop, update, and maintain all tolerance/variatio

inormation. Sigmund, by contrast, makes it easy or designers to demonstrate wobjective CAD-driven data that the design is capable o meeting all quality buildobjectives beore design/tooling release. Teams can avoid all the delays and signiicant cost associated with poor quality rom the start, and have a reerence bato return to i necessary.

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Ford uses Sigmund with SolidWorks 3D CAD sotware to ensure superior qual-ity. Glenn Reed, a Ford mechanical technical expert based in Dearborn, Mich., isa power user. He uses SigmundWorks, SigmundABA and SolidWorks to checknew designs rom global suppliers and sta engineers or inotainment systemsincluding DVDs, CDs, and radios. He ensures they meet unctional intent and buobjectives prior to tooling release.

Reed starts work on a design by importing an IGES, STEP, or Parasolid ileinto SolidWorks sotware. SolidWorks is a powerul tool or importing designs whatever the source cleaning them up, and making them parametric usingFeatureWorks, he says.

Bermo Inc. die design

What Sigmund is really doing is

orchestrating product development,

Reed says. Opinions too often set

product directions, but objective data

trumps opinion. With objective data,

theres nothing to argue about.

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Then he turns to SigmundWorks, Varatechs analysis product or SolidWorks.As a SolidWorks Certiied Gold Product, SigmundWorks is ully integrated with

SolidWorks and operates within its interace. To evaluate quality, Reed runsthrough thousands o what-i scenarios at a time, tweaking dimensions, tolerancand variations at will.

SigmundWorks helps us deine and understand our build requirements romthe outset, Reed says. We understand the downstream impact o each eature,

dimension, and tolerance in a design on the cost, complexity o manuacturing, aassembly.

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For example, Reed used SigmundWorks to conduct hole-pattern-to-screw-boss-pattern studies on an interace in the new 2009 Fo Flx between the electron

inish panel (EFP) and center inish panel (CFP). The studies were designed toensure the parts assemble together successully and maintain uniorm spacingaround the buttons.

The EFP is located to the CFP using a two-way locator and a our-way locator asecured with 17 asteners. The initial SigmundWorks hole pattern match analysi

showed problems with ive percent o the assemblies using original 3mm diametscrew holes in the EFP. The holes were incrementally increased to 3.8 mm usingthe pattern match analysis until 100 percent projected build was achieved. Thistype o hole-to-pin match analysis is virtually impossible to do by hand, Reed saWith Sigmund, we simply derived what was needed rom a size and positional toerance viewpoint to ensure proper assembly. It was easy and very ast.

In another case, Ford was able to validate that a CD player assembly was peroring as intended exceptwhen operated with discs that were excessively warpedEven though exposing a disc to heat or sunlight is technically the customers au

Ford used SigmundWorks and SolidWorks to alter dimensions o the disc guideto make the system more robust to ensure proper disc loading and ejecting withslightly warped discs. Ford thus avoided even the perception o a design law.

In another instance, Ford discovered slightly wobbly radio knobs on a new carmodel that was just about to be launched. Its a small matter with absolutelyno impact on unction but it makes a large impact on perceived quality. UsingSigmundABA assembly build analysis sotware, Ford pinpointed a hidden geomric sensitivity in a tiny clearance between two mating parts that was the culprit. other words, a small gap created a large wobble because the assembly relationsmagniied its impact (think o how a minor cant o the wrist can move the tip oa sword by a ew eet). Ford was able to identiy and easily close another eature

interace to reduce the wobble. Objective data rom Sigmund analysis providedconidence to modiy the production injection mold tooling.

Ford typically runs at least 5,000 Sigmund-powered virtual simulated builds on a

assembly design. Its as i the plant were building 5,000 prototypes, all slightly d

erent based on all possible combinations o variations within permitted tolerancSigmund then plots a histogram o the builds. I, in an early design, 20 percent othe builds ail, the edges o the histogram show the out-o-spec builds in red. Blmeans within spec. Sigmund has is the ability to identiy nominal design mistakeand assembly process mean-shits in advance.

Its compelling to see Sigmund animate an assembly design. The powerul sotwcycles through thousands o virtual builds, vividly illustrating all the possible variations minute and not so minute that can aect the inished component. Its adramatic representation o how perection in design is a myth in production.

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Ford also uses Sigmund to complement other types o analysis, including initeelement analysis. FEA geometry is typically based on a nominal model that willnever exist. Adding real-world component and assembly variation to FEA geometminimizes the typical dierence between simulation results and testing. Sigmundconsiders real-world component and assembly variation and provides realistic reresentations o deviated real-world manuactured geometry. Sigmund thereore

enables the development team to analyze what is actually going to be produced more accurate representations o product perormance as it leaves the plant doo

The example at let o a sheet metal radio chassis shows how original tolerancespermit a non-square box that can create mechanism issues. FEA analysis (usingNEiWorks) o the radio chassis enclosures nominal geometry showed one result

Sigmund real-world deviated enclosure geometry caused the FEA results to besigniicantly dierent. Once manuactured, the compound eects o variationand loading on assemblies could put a signiicant number o these chassis outo square and onto the scrap heap. Ford was able to head o the problem with aquick tweak to its design.

At Ford, Sigmund drives concept evaluation, design, material selection, quality pgram, supplier, and process selection, Reed says. In act, Ford has created a ne

rule aecting all suppliers. Prior to tooling release, suppliers must conduct WorsCase, Modiied RSS, and Monte Carlo Tolerance studies using simulation sotwato demonstrate build objectives. It goes without saying that I like the idea.

Although it takes some time and eort to perorm tolerance and assembly buildanalysis at the outset o a project, that eort pales in comparison to the cost andeort o scrap, rework, warranty claims, and recalls.

What Sigmund is really doing is orchestrating product development, Reed saysOpinions too oten set product directions, but objective data trumps opinion. Wecan now say, Here are designs A, B, and C and the accompanying Sigmund studies. As you can see, Design B wont meet the objective, so youve got to relax yoquality standard or pick between A or C. With objective data, theres nothing to

argue about.

SigmundWorks is a SolidWorks Certified Gold Product, SigmundABA for SolidWorks a

SigmundABA Kinematics for SolidWorks are Solution Partner products. Ford relies on

Varatech and authorized SolidWorks reseller DASI Solutions for ongoing software traini

support and implementation.

For more inormation.

Ford Motor Company: www.ord.com

Varatech Inc.: www.varatech.com

Dassault Systmes SolidWorks Corp.: www.solidworks.com

DASI Solutions: www.dasi-solutions.com

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The fgure above shows typical Sigmund reporting:

1) View o documented build objective, which can

also be an inserted AVI showing the animated

variability o the assembly.

2) Statistics report providing top-level inormation

like percent out o spec, Cpk, and PPM, or parts

per million or Six Sigma, along with advanced

statistical data.

3) Build objective sensitivity study providing ranking

order (by percent contribution to the objective) o

all component tolerances and assembly variations.

4) Graphic histogram indicating where the popula-

tion o simulated values occurred relative to theirspecifc build objective spec limits. The histogram

also reveals the distribution type and indicates

whether a mean-shit exists, which can oten be

caused by assembly process.

Frd Mr Cmaddrss: Cusmr Rls Cp.o. Bx 6248Drbr , Mi 48126p: 800-392-3673www.frd.cm

Dssul Ssms SldWrs Cr.300 Br avuCcrd, Ma 01742 USap: 1 800 693 9000ousd US: +1 978 371 5011eml: [email protected]

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PartnerCaseStudyFord_FINALv2