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A CASE STUDY IN KNOWLEDGE-BASED CAD MODEL AUTOMATION. Thesis Defense Andrew Lowe. Background. What is Knowledge-Based Engineering? Growing industry adoption Late Adopters Large bureaucracies, slow change No direct contribution to revenue stream. Background and Research Question.
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A CASE STUDY IN KNOWLEDGE-BASED CAD MODEL AUTOMATION Thesis Defense Andrew Lowe
Background • What is Knowledge-Based Engineering? • Growing industry adoption • Late Adopters • Large bureaucracies, slow change • No direct contribution to revenue stream
Background and Research Question • What is Knowledge-Based Engineering? • Growing industry adoption • Late Adopters • Large bureaucracies, slow change • No direct contribution to revenue stream • Does a cost-benefit analysis of CAD modeling automation yield a high enough resource savings relative to the resources invested in the application’s development to justify its use in industry?
Significance • Great potential for saved resources in partner company • Possible impetus for greater KBE focus in partner company • Possible impetus for more widespread KBE adoption in similar companies. • Cost of automation relative to benefits not quantified
Literature Summary • KBE • Basic principles, industry implementation • No discussion of financial savings or cost • CBA • Basic formula, breakdown of formula • Identification/estimation of intangible benefits • Eliciting expert knowledge • Complex Surfaces • Mathematical basis and troubleshooting errors
Research Type • Two phase project • Development of application • Analysis of implementation • Resource savings • Surveys/Interviews • Cost-Benefit Analysis
Development Methodology • Project specs already in place • Solid creation/validation • Additional features • Cyclic design/validation scheme • Development time recorded
CBA Methodology • Once effected areas are identified, benefit to those areas must be quantified • More use of interviews and questionnaires • Many tangential effects will in intangible in the context of CBA • Sum total benefit and total costs
Progamming: GUI • Overarching goal: Simplicity and supportability • Inputs grouped into required/optional file input and text input • Optional groups collapsed by default • Execution buttons not active until required values entered
Programming: File Parsing • ASCII files with Cartesian points • Organization different for each file type • Blade file • Surface normal file • Flowpath file/spline reference file • Differing format forces additional complexity in code • Only similarity in code for opening file • Loops for organizing data into usable format vastly different with little code reuse
Programming: Geometry • Three geometry types • Blade/Splitter • Surface Normals • Flowpath/Spline reference • Blade Geometry • Input points organized by face • Splines made for forward three faces, trailing edge • Surfaces made from splines • Surfaces knit into solid • Individual face surfaces made for FEA integration
Geometry (cont’d) • Surface normals • Points organized by pressure side/suction side • Subdivided by hub/tip • Splines made between hub/tip on each side • Flowpath/Spline reference • Simple list of points • Spline made from points
Programming: Ancillary Features • Variety of text and numeric embedded data • Simple coding • Similar to variable declaration
Programming: Documentation • Fully-commented code • More in-depth than typical commenting • Targeted toward novice users • Detailed flowchart • Short overview/introduction document
Data Collection: Participant Identification • Initial interview PLM project manager • Overview of impeller design process • Identified where application would affect process • Areas finalized in follow-up interview • Prospective participants approached by company point of contact • Positive respondents forwarded to researcher • Final participants: 3 modelers, 5 engineers, 1 analysis integration expert, 1 project manager
Data Collection: Interviews • With one exception, interviews conducted over the phone • Interviews started with explanation of application and a few basic questions • How do you see this affecting your area? • How would you use the application? • How would the application save or cost you time? • Additional questions based off their responses • Follow up interviews conducted after receiving new information from other participants
Modeler Interviews • Focused mainly on modeling consistency • Large amounts of wasted time troubleshooting unfamiliar models • Get called away from current work to troubleshoot their own models • Only about 1 hour per iteration in direct labor savings • Much larger time savings from not having to reconstruct adjacent geometry with each iteration
Engineer Interviews • Reduced idle/wait time • More process control • More design iterations • 3-5 total currently, 15-20 possible in one night with automation • Higher quality • More in-spec options for customers • Confirmation of modelers modeling consistency concerns
Analyst Interviews • Analysis integration process • Automated meshing • Allows for batch modeling/FEA runs • Time savings data for both • Provided proprietary document confirming and expounding upon their points • Confirmed modeler/engineer concerns and data
Project Manager Interviews • Wide-view design process information • Participant identification • Go-between with high-level non-participants • Employment cost data • Other financial data • New information for follow-up interviews
Data Analysis: CBA • Total Benefit = Gross Benefit – Gross cost • Gross Benefit = Quantifiable Benefit + Intangible benefit (A) • Gross Cost = Quantifiable Cost + Intangible Cost (A)
CBA: Cost • Four ways of interpreting quantifiable cost • Interviews yielded no information hinting at additional real or intangible costs
CBA: Benefit • Three ways of evaluating benefit: • Current process with dumb solid macro • Frequently-used process with spline creation automated • Completely manual process • Numbers calculated using time savings estimates from participants and company’s $100/hr average cost of employment
CBA: Intangible Benefits • Many intangibles lacked data for proper estimation • Lower error cost from modeling inconsistency • Higher quality/more customer options from multiple iterations • Lower operating costs running batch at night • Decreased time to market
Intangible Benefits (cont’d) • Decrease in overall project time from elimination of engineering/FEA/modeling bottlenecks • Possibly greater than two weeks • Estimated based on publicly available defense contracts • 40% share in $2.4 billion, 6.5 year project • IDA estimated 11% profit margin • $356,000 per-day savings • $3.56 million two-week savings
CBA: Results • Analysis without intangible benefits:
CBA Results (cont’d) • Most cost-effective development method: in-house employee • For benefit to be seen from direct labor savings, must be used in batch or over multiple projects • Chart provides baseline minimum benefit, as not enough data could be gathered to support intangible benefits as a guaranteed non-zero value
CBA Results (cont’d) • Intangible benefits potentially dwarf quantifiable benefits • Application has high potential to provide net benefit • Could pay for most expensive development cost in a few hours of reduced project time • Time savings over three days delivers an order of magnitude ROI on its own • Does not take into account the other non-estimable intangibles. • Due to lack of information, intangibles cannot be assumed to be non-zero, should be stated in a 0-maximum format
Conlusions • Does CAD automation show a high enough cost/benefit ratio to merit wider industry implementation? • Yes • Tangible cost data was for single project • Re-use over multiple projects compounds savings and provides net benefit from direct labor savings alone
Conclusions (cont’d) • Factoring in intangible benefits, total savings becomes massive • Potential order-of magnitude ROI • These savings compound over multiple projects as well, potentially reaching two orders of magnitude ROI • Thesis evaluated a single automation routine for a fraction of a single part, use of automation on multiple parts could increase potential benefits even higher.
A CASE STUDY IN KNOWLEDGE-BASED CAD MODEL AUTOMATION Thesis Defense Andrew Lowe