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Determining Capable Production Processes for New Product Ramp-up using Semantic Web Technologies Stefan Biffl 1, Estefania Serral 2, Roland Willmann 3.

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Presentation on theme: "Determining Capable Production Processes for New Product Ramp-up using Semantic Web Technologies Stefan Biffl 1, Estefania Serral 2, Roland Willmann 3."— Presentation transcript:

1 Determining Capable Production Processes for New Product Ramp-up using Semantic Web Technologies Stefan Biffl 1, Estefania Serral 2, Roland Willmann 3 Vienna University of Technology Institute of Computer Aided Automation 3 Institute of Software-Technology and Interactive Systems 1 Christian Doppler Laboratory „Software Engineering Integration for Flexible Automation Systems“ KU Leuven 2 Department of Decision Sciences and Information Management

2 Outline  Motivation and Problem Statement  State of the Art and Research Approach  Cake Baking - The Reference Use Case  Knowledge based Ramp-up of Products (K-RAMP)  Conclusions and Next Steps

3 Outline  Motivation and Problem Statement  State of the Art and Research Approach  Cake Baking - The Reference Use Case  Knowledge based Ramp-up of Products (K-RAMP)  Conclusions and Next Steps

4 Scope of Work Product Ramp-up Remote Capacity Ramp-up Discrete Production

5 Motivation Volume on Market Time to Volume First Part on Market Time Ramp-up Yield Product Ramp-up Costs Duration Quality  Difficult to Predict  Weak Knowledge Exchange  Fails of ~50% of all Enterprises  Weak Knowledge Exchange Time to Market  Ramp-up Project

6  Ramp-up Process Motivation Product Ramp-up  Weak Knowledge Exchange Knowledge Based Ramp-Up of Products K-RAMP Determine Reusable (Semi-Finished) Products and Process Segments at Target Production System Derive New Process Setup From Existing Process Setup Recommend Results For Process Qualification at Target Production System K-RAMP Shall Actively Drive the Ramp-Up of a New Product  Ramp-up Project

7 Reuse of Existing Knowledge – Trial 1 ? Delicious Chocolate Gloss! How do you make it? 1.Temperature 4 to 5 on the hotplate 2.Put water pot on hotplate 3.Wait 15 minutes 4.Put pot with chocolate in the water pot 5.Whipping for 5 minutes 6.… Unable to Reuse Existing Knowledge

8 Reuse of Existing Knowledge – Trial 2 Ahh – a hot water-bath That is clear Delicious Chocolate Gloss! How do you make it? 1.Make a hot water-bath 2.Whipping the chocolate in the hot water-bath until chocolate is liquid 3.… Knowledge For Making a Hot Water-Bath Exists And Can Be Reused

9 Outline  Motivation and Problem Statement  State of the Art and Research Approach  Cake Baking - The Reference Use Case  Knowledge based Ramp-up of Products (K-RAMP)  Conclusions and Next Steps

10 Challenge of New Product Ramp-up  The Situation in Discrete Production of Many Industries is Similar But More Complex  Inter-disciplinary Ramp-up Team –Product, Process, Equipment, Quality Engineering –Line Management, Corporate Management  Ramp-up Teams Deal With Existing Knowledge For Reuse –Existing Semi-Finished Products (or Consumables) –Existing Processes Which Create Similar Semi-Finished Products –Development and Qualification of New Processes or New Machines  Knowledge Exchange Among Team-Members is Critical  Ramp-Up Not Actively Supported by Software-Tools

11 Challenges of K-RAMP  Common Generic Concept of Knowledge –Common Structure of Knowledge at Source and Target Production System –Generic, Independent of Specific Processes and Production Systems  Integration of Product and Process Knowledge with Quality Measurements of Target Production System –Data Volume –Linking Semantic Knowledge and Quality Measurements –Valuable History of Quality Data  Searching Within Quality Data for Opportunities for Reuse –Dynamic Setup of Data-Mining Based on Product Specification  Calculation of Performance Indicators for Validation of Recommendations –Dynamic Setup of Calculations Based on Product Specification

12 Approach  Proof of Concept –Reference Product and Process (Transfer of Baking a Chocolate Cake) –Simulated Quality Measurements  Interactive Tools for Planning, Specification and Verification –Enterprise Architect – Planning –Protégé 4.3 – Knowledge Base and Reasoning (Pellet) –Magnum Opus, Version – Association Rule Mining –MiniTab 17 – Calculation of Performance Indicators  Manual Execution of the Process  Validation of Results with Respect to Reusability  Iterative Improvement of Knowledge Base and Reasoning

13 Product Process Example Use Case – Knowledge Transfer Between Bakeries Structure and Specifications of Product To Transfer Original Bakery Target Bakery K-RAMP Process Setup Quality Data of Product To Transfer Process Setup Quality Data of Existing Baking Processes Structure and Specifications of Existing Products Process Setup Quality Data of Existing and new Baking Processes Structure and Specification of Existing Products and Transferred Product Initial StateResulting State

14 K-RAMP Partial Models Characteristics Product Process :Characteristic :Specification :SpecificationRange :PhysicalUnit :ProductClass :Product :ProducedPart :QualificationState :ProcessClass :ProcessSegment :ProcessJob :ProcessSetup QualityControl :AssociationSearchSetup :AssociationRule :AggregationFunction :CapabilityIndex

15 Specialization of K-RAMP K-RAMP Baking Source-BakeryTarget-Bakery General Model Branch-Specific Model Location-Specific Models General Conceptual and Instance Models Common Product Classes, Specifications, Characteristics, Process Classes Individual Process Segments, Products, Produced Parts and their Measurements

16 Outline  Motivation and Problem Statement  State of the Art and Research Approach  Cake Baking - The Reference Use Case  Knowledge based Ramp-up of Products (K-RAMP)  Conclusions and Next Steps

17 Transfer of Chokolate Cake Baking Product Class / Products  Requirements Requirement-1: Reflective, Dark Brown, Crispy Chocolate Surface With Bitter-Sweet Taste Requirement-2: Soft, Succulent, Dark Brown, Fruity Apricot-Chocolate Taste Product-Class-1: Chocolate Gloss Product-Class-2: Two Layered Sponge Dough With Center Apricot Jam Layer How Shall the Product Function? How is the Product Designed? Product Classes support Requirements Variation of Satisfaction of Requirements due to Individual Specifications of Products

18 Transfer of Chokolate Cake Baking Product Specification  Requirements Product-Class-1.1: Bitter Chocolate Product-Class-1.2: Gloss How Shall the Product Function? How is the Product Designed? Requirement-1.1: Dark brown Chocolate Surface With Bitter-Sweet Taste Requirement-1.2: Reflective surface Requirement-1.3: Crispy surface Requirement Specification Reflectivity: … Uniformity: … Product Class Specification Viscosity: … Flow Value: … Is There Already a Product of Type “Gloss” Which Meets Specification Ranges Is There Already a Product of Type “Gloss” to be Adjusted in Order to Meet Specification Ranges

19 Transfer of Chokolate Cake Baking Process Specification  Product Specification Product-Class-1.1: Bitter Chocolate Product-Class-1.2: Gloss How Is the Product Created? How is the Product Designed? Process-Class-1.1: Provide Bitter Chocolate Process-Class-1.2: Provide Gloss Product Class Specification Viscosity: … Flow Value: … Process Setup Water/Sugar Ratio: … Temperature: … Duration: … Is there a Process of Type “Provide Gloss” Which Creates “Gloss” Within Expected Specification Ranges Is There a Process of Type “Provide Gloss” Which Could be Adjusted In Order to Meet Specified Ranges

20 Outline  Motivation and Problem Statement  State of the Art and Research Approach  Cake Baking - The Reference Use Case  Knowledge based Ramp-up of Products (K-RAMP)  Conclusions and Next Steps

21 K-RAMP – Recommendation of Preliminary Process Plan Product Hierarchy Process Hierarchy Requirements Recommended Process Plan for Target Production System Chocolate Cake Provider Chocolate Gloss Provider Chocolate Sponge Dough Provider Bitter Chocolate Provider Gloss Provider Chocolate Cake Chocolate Sponge Dough Bitter Chocolate Gloss Chocolate Gloss Chocolate Gloss Provider Chocolate Cake Coating Chocolate Gloss Chocolate Sponge Dough Chocolate Sponge Dough Provider Chocolate Gloss Bitter Chocolate Gloss Bitter Chocolate Provider Gloss Provider provides requires

22 Some Terminology of Quality Management Good Parts are All Parts Within the Requested Specification Limits (Specification Range) Population of % within Specification Limits is equivalent to Process Capability Index (cp k ) of 1.43 is equivalent to Defective Parts 11.7 ppm If Specification Range of Product-1 is Within the Specification Range of Product-2 (LSL 1  LSL 2 and USL 1  USL 2 ) Then All Good Parts of Product-1 Satisfy Product-2 Specification Range as Well (Semi-Finished) Product is Qualified if FPY > Target Is There Some Systematic Process Setup to Achieve an Appropriate Yield for Tighter Specification Limits of Product-1 (a New Product) Specification Limits LSL 2 USL 2 LSL 1 USL 1

23 K-RAMP Process Overview Reusable Existing Semi-Finished Products Flag Produced Parts of Super Class If Within Specification Range Clustering of Flagged Produced Parts Calculate Yield Per Group With Respect to New Product Gather Produced Parts in Groups Based on Clusters Drop Groups Where Yield Below Threshold Recommend Process Setup Recommend Semi- Finished Product Recommend Need For New Process Development no clusters yes no clusters some groups left no groups left

24 Outline  Motivation and Problem Statement  State of the Art and Research Approach  Cake Baking - The Reference Use Case  Knowledge based Ramp-up of Products (K-RAMP)  Conclusions and Next Steps

25 Conclusion  Automated Determining of Reusable Products and Processes Possible  For Simple Use Cases  External Applications Required (Rule Mining, Statistics)  Hybrid Architecture  OWL2 and SWRL Seems Not Sufficient for Reasoning  JENA  Rework of Ontology

26 Next Steps  Addressing Reasoning for Closed-World Questions –Non-Qualified-Product \ Qualified-Product  Declaration of new Classes or Restrictions Through Reasoning –If there is an Association Rule X with hasContext {Y, Z} then there is a Restriction X with onProperty hasContext value {Y, Z}  More Complex Use Cases –Sequence of Production Process Segments  Consideration of Regression Functions Between Process Specification and Produced Parts’ Measurements  Detailed Concept For User Interaction

27 Roland Willmann –

28 K-RAMP - Target RPrdC (Chocolate Cake)PrcC (Coating Chocolate Gloss) 21 Chocolate Cake Coating Chocolate Gloss Requirements Bill of Materials BoM Process Hierarchy Resulting Process Plan in Target Production System R-1: Reflective, Dark Brown, Crispy Chocolate Surface R-2: Soft, Succulent, Dark Brown, Fruity Apricot- Chocolate Taste R1.1: Dark Brown Chocolate Surface R1.2: Reflective Surface R1.3: Crispy Surface PrdC-1: Chocolate Gloss R-2: Two Layered Chocolate Sponge Dough With Center Apricot Jam Layer PrdC-1.1: Bitter Chocolate PrdC-1.2: Gloss PrcC-1.1: Provide Bitter Chocolate PrcC-1.2: Provide Gloss PrcC-1: Provide Chocolate Gloss PrcC-2: Preparing Chocolate Sponge Dough with Center Apricot Layer

29 K-RAMP Find Produced Parts Within Specification Range Initial Situation Assumption Actions to be Performed Product Class Chocolate is Qualified at Target Bakery Product Class Bitter Chocolate is Non-Qualified at Target Bakery Bitter Chocolate Specification Range Tighter Than Chocolate’s Produced Parts of Chocolate are Available A Subset of Produced Parts of Chocolate are in Specification Ranges of Bitter Chocolate If There is Some Non-Qualified Product Class X And There is Some Qualified Super-Class of X Then Declare Restriction of Produced Part Instances Within Specification Range of X. Produced Parts Hold Values for Each Characteristic

30 K-RAMP Find Systematic Process Setup Initial Situation Assumption Actions to be Performed Existing Produced Parts Within Specification Range of Bitter Chocolate Produced Parts Refer Process Setup (a.k.a. Process Context) Query Produced Parts of Chocolate Within Specification Range of Bitter Chocolate  Good Parts Query Produced Parts of Chocolate  Totality Query Classes of Referenced Process Context  Left Hand Side (LHS) of Association Rules Query Asserted Association Rule Setup  Right Hand Side (RHS) of Association Rules Good Parts  IN Totality – Good Parts  OUT

31 K-RAMP Find Systematic Process Setup Resulting Association Rules for New Product Class MT-01 & O-01 & S-03  IN [Coverage=0.043 (11); Support=0.031 (8); Strength estimate=0.659; Lift estimate=2.31; Leverage= (4.9); p=0.0850] S-01 & MT-01 & O-01  IN [Coverage=0.051 (13); Support=0.031 (8); Strength estimate=0.571; Lift estimate=2.00; Leverage= (4.3); p=0.213] O-01 & S-02 & MT-02  IN [Coverage=0.051 (13); Support=0.027 (7); Strength estimate=0.505; Lift estimate=1.77; Leverage= (3.3); p=0.267] S-01 & O-01 & MT-03  IN [Coverage=0.066 (17); Support=0.035 (9); Strength estimate=0.504; Lift estimate=1.77; Leverage= (4.2); p=0.235] O-01 & S-02 & MT-03  IN [Coverage=0.059 (15); Support=0.031 (8); Strength estimate=0.504; Lift estimate=1.77; Leverage= (3.7); p=0.262] Action to Perform For Each Association Rule X Declare Restriction of Produced Part Instances Based on LHS (a.k.a. Process Context) of X

32 K-RAMP Calculating Initial Capability Indexes and Yields MT-01 & O-01 & S-03 S-01 & MT-01 & O-01 O-01 & S-02 & MT-02 S-01 & O-01 & MT-03 O-01 & S-02 & MT-03

33 K-RAMP Calculating Initial Capability Indexes and Yields MT-01 & O-01 & S-03 S-01 & MT-01 & O-01 O-01 & S-02 & MT-02 S-01 & O-01 & MT-03 O-01 & S-02 & MT-03 Yield Cacao : 99% Yield Sugar : 78% Yield Total : 77% Yield Total : 53% Yield Total : 38% Yield Total : 60% Yield Total : 56% Action to be Performed For Each Restriction X Caused by an Association Rule Calculate Yield Total With Specification Range of Product Class Which is Associated With Association Rule

34 K-RAMP Recommendation for Ramp-Up Team MT-01 & O-01 & S-03 S-01 & MT-01 & O-01 O-01 & S-02 & MT-02 S-01 & O-01 & MT-03 O-01 & S-02 & MT-03 Yield Total : 77% Yield Total : 53% Yield Total : 38% Yield Total : 60% Yield Total : 56% Action to be Performed Query Process Setup Related to Restriction X Caused by an Association Rule Where Yield Total > Yield Threshold And Recommend it as Initial Process Setup For Qualification of New Derived Process

35 K-RAMP Find Produced Parts Within Specification Range :Chocolate ratioCacao: [10, 95]% ratioSugar: [0, 27]% :ProductClass :BitterChocolate ratioCacao: [40, 70]% ratioSugar: [0, 15]% rdf:type At Target-Bakery :Chocolate is Qualified :BitterChocolate is Non-Qualified :Chocolate’s Specification Ranges Envelop Bitter Chocolate’s Specification Ranges Some Produced Parts of Chocolate are in Specification Ranges of Bitter Chocolate :ProducedPart :ProducedPart- BitterChocolate :ProducedPart- Chocolate rdfs:subClassOf K-RAMP Rules of Implication rdf:type rdfs:subClassOf Knowledgebase and Reasoning Protégé 4.3

36 K-RAMP Find Systematic Process Setup :ProducedPart- BitterChocolate :AssociationSearchSetup minLift: 1.0 minSupport: 0.02 minStrength: 0.5 minCoverage: 0.02 :ProducedPart :ProducedPart- Chocolate rdfs:subClassOf :onLHS :onTotality :onGoodParts :BitterChocolate ratioCacao: [40, 70]% ratioSugar: [0, 15]% :onProductClass :Chocolate ratioCacao: [10, 95]% ratioSugar: [0, 27]% rdfs:subClassOf Association Rule Mining Based on :AssociationSearchSetup Instances  External Tool Magnum Opus, Version SPARQL

37 K-RAMP Find Systematic Process Setup :ProducedPart- BitterChocolate :AssociationSearchSetup minLift: 1.0 minSupport: 0.02 minStrength: 0.5 minCoverage: 0.02 :ProducedPart :ProducedPart- Chocolate rdfs:subClassOf :AssociationRule MT-01 & O-01 & S-03 -> satisfies [Coverage=0.043 (11); Support=0.031 (8); Strength estimate=0.659; Lift estimate=2.31; Leverage= (4.9); p=0.0850] S-01 & MT-01 & O-01 -> satisfies [Coverage=0.051 (13); Support=0.031 (8); Strength estimate=0.571; Lift estimate=2.00; Leverage= (4.3); p=0.213] O-01 & S-02 & MT-02 -> satisfies [Coverage=0.051 (13); Support=0.027 (7); Strength estimate=0.505; Lift estimate=1.77; Leverage= (3.3); p=0.267] S-01 & O-01 & MT-03 -> satisfies [Coverage=0.066 (17); Support=0.035 (9); Strength estimate=0.504; Lift estimate=1.77; Leverage= (4.2); p=0.235] O-01 & S-02 & MT-03 -> satisfies [Coverage=0.059 (15); Support=0.031 (8); Strength estimate=0.504; Lift estimate=1.77; Leverage= (3.7); p=0.262] rdfs:subClassOf :hasSetup


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