Lean Production Meets Big Data: A Next Generation Use Case

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Information about Lean Production Meets Big Data: A Next Generation Use Case
Technology

Published on February 5, 2014

Author: Datameer

Source: slideshare.net

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 data

© 2013 Datameer, Inc. All rights reserved.

View Full Recording You can view the full recording of this webinar at: http://info.datameer.com/Online-Slideshare-LeanProduction-Meets-Big-Data.html © 2013 Datameer, Inc. All rights reserved.

About our Speaker Conny von Ludwig Conny 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 Speaker Conny von Ludwig Conny 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 Speaker Stefan Groschupf Stefan 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.

Lean and Flexible Enterprises Corporate strategy Effectiveness Division / product strategy Suppliers Customers Doing the right things Functional area strategy Development strategy Purchasing strategy Production strategy Sales strategy Organization Efficiency Processes Management process Development Purchasing Production Supporting processes Products © 2013 Datameer, Inc. All rights reserved. Sales Doing things right

Why Lean Production Increase: Productivity Customer Satisfaction Ability to: Deliver Just-in-Time Produce customized products Lean production is the enabler for profitable and sustainable growth © 2013 Datameer, Inc. All rights reserved.

The “Lean Production” Philosophy “Perfection has been reached, when nothing can be taken away, not when nothing can be added.” - Antoine de Saint Exupéry Customer satisfaction Quality Cost 5% of activities create value Types of waste Overproduction Transportation Wait times Rework/defects Transit time Inventory Over processing Delivery Service © 2013 Datameer, Inc. All rights reserved.

How Waste Can be Identified Process Product Redundancy Inventory Bottlenecks Numerous interfaces Work flow disruption Inconsistent documents Duplicate handling Exceed performance requirements Unnecessary range of functions Volume of unused variants © 2013 Datameer, Inc. All rights reserved. Organization Complex structures Unclear responsibility Wasted employee capabilities Wrong employee attitude

Principles More Important than Methods Synchronization Value Orientation Objectively measurable Value from customer’s perspective Waste is avoided Think in processes, not departments Processes are linked Supply and demand are aligned Core Elements of Lean Enterprise Measurable objectives and results Top-down target setting Bottom-up problem solving Transparency © 2013 Datameer, Inc. All rights reserved. Standards facilitate improvement Pursuit of perfection Always question achievements Perfection

Vision of Just-in-Time, 5R Information Material Part Part Time Right Quality + Time Right Quality Place Place Quantity Quantity © 2013 Datameer, Inc. All rights reserved.

Overall Processes Raw material Machines People Information Input Good Information Process Use information from process for improvements © 2013 Datameer, Inc. All rights reserved. Output

Value Stream Material & Information Flow PPS Order Information flow Shipping order Customer Supplier Process Material flow Focus of improvements today Info Process Process Info Shipping Info Process Info Information replace waste (e.g. inventory) © 2013 Datameer, Inc. All rights reserved. Process information data: Logistic Quality Maintenance Personnel Production planning Process performance Lean indicator: Throughput time

Value stream with Material- and Information flow Information flow Material flow Focus of improvements today Info Information replace waste (e.g. inventory) © 2013 Datameer, Inc. All rights reserved. Info Info Process information data: Logistic Quality Maintenance Personnel Production planning Info Process performance Lean indicator: Throughput time

Improvement Process: 8 Success Factors Willingness to change CIP organization Methods/tools Training Process Vision Workshop/ Project Plan Key Performances Indicator Communications © 2013 Datameer, Inc. All rights reserved.

Factors of a Lean Shop Foreman Quality assurance Work / shift Relieved of all duties throughout the workshop CIP Trainer Engineering/Planning Logistics Union rep CIP Trainer Workshop organization Training of participants Procurement of methods Coordination of stabilization © 2013 Datameer, Inc. All rights reserved. Participants Idea generation Improve concept development Measure implementation Knowledge contribution Presentation

Improving Processes with Big Data Good Results Competitive organizations provide lower product costs, increased quality & profits ✔︀︁︂︃︄︅︆︇︈︉︊︋︌︍︎️ Good Processes These results must be directly & indirectly optimized (sustained) for improvement Ac Good Employees Employee competency will implement these plans successfully © 2013 Datameer, Inc. All rights reserved. t Pla Ch eck Do n

Improvement Processes Define Define the opportunity Understand process and performance Measure Analyze Improve Control 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 © 2013 Datameer, Inc. All rights reserved.

Summary Big Data provides new approach for process optimization Provide easy to use tool to analyze & improve processes Focus not only on visible wastes but also systems Think through processes with cross-functional analysis Measure results for measurable decisions (important in implementation) Sustainability Datameer is so easy to use that even employees can analyze processes and improve them. © 2013 Datameer, Inc. All rights reserved.

Demo © 2013 Datameer, Inc. All rights reserved.

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 ? © 2013 Datameer, Inc. All rights reserved.

Use Case • Correlate sensor data from multiple sources • Maintenance ticketing databases • Machinery log files © 2013 Datameer, Inc. All rights reserved.

Total Operating Time No scheduled for production A Available time B Measure C Theoretical production D Real production E Real production F Good products Failure Idle Time Minor Stops Speed Loss Scrap Rework OEE = B/A x D/C x F/E Availability Efficiency © 2013 Datameer, Inc. All rights reserved. Quality

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