lean production meets big data: a next generation use case
DESCRIPTION
Watch this recording at: http://info.datameer.com/Online-Slideshare-Lean-Production-Meets-Big-Data.html Sensor and robotic data will usher in a new wave of big data opportunities and use cases in 2014. This will be especially true in manufacturing as economic pressure to continuously improve operational efficiencies continue to challenge the bottom line. Join Lean Production Expert Conny von Ludwig (former Porsche Consulting & Lufthansa), and Datameer CEO, Stefan Groschupf as they discuss: -the current manufacturing challenges and how big data analytics can improve these inefficiencies -how to reduce production outages by 10% -a next gen big data analytic use case focused on manufacturing sensor dataTRANSCRIPT
© 2013 Datameer, Inc. All rights reserved.
© 2013 Datameer, Inc. All rights reserved.
View Full RecordingYou can view the full recording of this webinar at:http://info.datameer.com/Online-Slideshare-Lean-
Production-Meets-Big-Data.html
© 2013 Datameer, Inc. All rights reserved.
About our SpeakerConny von LudwigConny von Ludwig is Manager of Continuous Improvement Process at a large car manufacturer in Germany.
He has been in charge of planning and implementing internal projects focused around lean processes at various production plants in Germany.
Prior to this, he was a Lean and Training specialist at Porsche Consulting and Lufthansa Technik.
He has more than 15 years of practical lean production and lean thinking know-how in several industries around the world.
© 2013 Datameer, Inc. All rights reserved.
About our SpeakerConny von LudwigConny von Ludwig is Manager of Continuous Improvement Process at a large car manufacturer in Germany.
He has been in charge of planning and implementing internal projects focused around lean processes at various production plants in Germany.
Prior to this, he was a Lean and Training specialist at Porsche Consulting and Lufthansa Technik.
He has more than 15 years of practical lean production and lean thinking know-how in several industries around the world.
© 2013 Datameer, Inc. All rights reserved.
About our SpeakerStefan GroschupfStefan Groschupf is the co-founder and CEO of Datameer. He is one of the original contributors to Nutch, the open source predecessor of Hadoop, Stefan has been at the forefront of the Hadoop and Big Data market.
Prior to Datameer, Stefan was the co-founder and CEO of Scale Unlimited, which implemented custom Hadoop analytic solutions for HP, Sun, Deutsche Telekom, Nokia and others. Earlier,
Stefan was CEO of 101Tec, a supplier of Hadoop and Nutch-based search and text classification software to industry-leading companies such as Apple, DHL and EMI Music. Stefan has also served as CTO at multiple companies, including Sproose, a social search engine company.
© 2013 Datameer, Inc. All rights reserved.© 2013 Datameer, Inc. All rights reserved.
Effectiveness
Doing the right things
Efficiency
Doing things right
Suppliers
Products
Customers
Corporate strategy
Division / product strategy
Functional area strategy
Organization
Processes
Developmentstrategy
Purchasingstrategy
Productionstrategy
Sales strategy
Management processDevelopment
Supporting processesPurchasing SalesProduction
Lean and Flexible Enterprises
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Why Lean ProductionIncrease:
ProductivityCustomer Satisfaction
Ability to:Deliver Just-in-TimeProduce customized products
Lean production is the enabler for profitable and sustainable growth
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The “Lean Production” Philosophy
Quality
Delivery ServiceCost
Quality
Customer satisfaction 5% of activities create value
“Perfection has been reached, when nothing can be taken away, not when nothing can be added.” - Antoine de Saint Exupéry
Types of wasteOverproductionTransportation Wait timesRework/defectsTransit timeInventoryOver processing
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How Waste Can be IdentifiedProcess
RedundancyInventoryBottlenecksNumerous interfacesWork flow disruptionInconsistent documentsDuplicate handling
Product
Exceed performance requirementsUnnecessary rangeof functionsVolume of unused variants
Organization
Complex structuresUnclear responsibilityWasted employee capabilitiesWrong employee attitude
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Standards facilitate improvementPursuit of perfectionAlways question achievements
Perfection
SynchronizationThink in processes, not departmentsProcesses are linkedSupply and demand are aligned
Principles More Importantthan Methods
Value OrientationObjectively measurableValue from customer’s perspectiveWaste is avoided
Measurable objectives and results Top-down target settingBottom-up problem solving
Transparency
Core Elements of Lean Enterprise
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Vision of Just-in-Time, 5R
MaterialMaterial
Right
Part
Right
Time
Right QualityRight
Place
Right
Quantity
Information Information
Right
Part
Right
Time
Right QualityRight
Place
Right
Quantity
+
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Overall Processes
Process OutputInput
Raw materialMachinesPeopleInformation
Good Information
Use information from process for improvements
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Value Stream Material & Information Flow
PPS
SupplierCustomer
Process Shipping
Shipping order
Order
Process
Process
Process
Focus of improvements today
Info
Info
Info
Info
Information flow
Material flow
Process information data:LogisticQualityMaintenancePersonnelProduction planning
Process performanceLean indicator: Throughput time
Information replace waste (e.g. inventory)
© 2013 Datameer, Inc. All rights reserved.
Value stream with Material- and Information flow
Focus of improvements today
Info InfoInfoInfo
Information flow
Material flow
Process information data:LogisticQualityMaintenancePersonnelProduction planning
Process performanceLean indicator: Throughput time
Information replace waste (e.g. inventory)
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CommunicationsKey PerformancesIndicator
Workshop/Project Plan
Process Vision
Improvement Process:8 Success Factors
CIP organizationWillingnessto change
Methods/tools Training
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ParticipantsIdea generationImprove concept developmentMeasure implementationKnowledge contributionPresentation
CIP TrainerWorkshop organizationTraining of participantsProcurement of methodsCoordination of stabilization
Factors of a Lean Shop
Relieved of all duties throughout the workshop
Work / shift
Logistics
Union rep
ForemanQuality assurance
Engineering/Planning
CIP Trainer
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Improving Processes with Big Data
Good ResultsCompetitive organizations provide
lower product costs, increased quality & profits
Good Processes
Good EmployeesAct
Plan
Do
Check
These results must be directly & indirectly optimized (sustained) for improvement
Employee competency will implement these plans successfully
✔︀︁︂︃︄︅︆︇︈︉︊︋︌︍︎️
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Improvement Processes
Analyze
Measure
Control
Improve
Define the opportunity
Understand process and performance
Search for biggest impact factors on process performance and determine root cause
Develop improvement solution for the critical X’s
Implement the solution and control plan
Define
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Big Data provides new approach for process optimizationProvide easy to use tool to analyze & improve processesFocus not only on visible wastes but also systemsThink through processes with cross-functional analysisMeasure results for measurable decisions (important in implementation)SustainabilityDatameer is so easy to use that even employees can analyze processes and improve them.
Summary
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Demo
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Lean Production• Manufacturing plant• Predictive maintenance• Minimize downtime
• Which robots are failing the most ?
• What part of the day do failures most occur ?
• What is the average length of time between failures ?
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Use Case• Correlate sensor data from multiple sources
• Maintenance ticketing databases
• Machinery log files
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Total Operating Time
Available time No scheduled for production
Measure
A
B
Theoretical production
Real production
C
D
Real production
Good products
E
F OEE = B/A x D/C x F/EAvailability Efficiency Quality
Failure Idle Time
Minor Stops Speed Loss
Scrap Rework
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