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Utilization of robotics/AI in logistics
Nittsu Research Institute & Consulting, Inc. (NRIC)
October 2016
1.The concept of the use of robotics 2.Autonomous systems in logistics and manufacturing
1.The concept of the use of robotics
Copyright (C) 2016 Nittsu Research Institute and Consulting, Inc. Proprietary & Confidential 2
(1) NRIC: Who we are
• 50-year old research institute specialized in logistics
• Subsidiary of Nippon Express, Japan’s largest 3PL
• Contribute and help improvement in logistics industry
• Employees: 75
Copyright (C) 2016 Nittsu Research Institute and Consulting, Inc. Proprietary & Confidential 3
3PL employee
Management
Trade terms, operation
Cargo volume forecasting
MHE research & advice
Emerging markets research
Inside warehouse improvement
Inventory reduction
Delivery network optimization
Warehouse location optimization
Cross border trade trial
Market entry research & advice
Shock, temp./humidity tests
Packing test
Carbon dioxide reduction
Research
Consulting
Education
Engineering
“L”ogistics
Goods needed, amount needed, place needed
Network (node and link)
Demands for more labour force
Same day, Pin-point time delivery, Redelivery
Shortening lead-time
Need for additional services
Increasing demand for high quality
Avoid the industry due to lots of overtime work
Low pay compared to other industries
Harsh work environment
Stricter driving licensing policy implemented
(2)Environment: Conflicting forces in logistics industry
Copyright (C) 2015 Nittsu Research Institute and Consulting, Inc. Proprietary & Confidential 4
Population aging rate(above 65 years old)
Total population
:between 65 and 74 years old:75 years of age or older :between 15 and 64 years old :between 0 and 14 years old
Results Estimation×10,000
(Population)
Wage of Road freight business
Average Wages
¥314,054/month
¥297,233/month
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13
×10,000Yen
Declining and aging population
Low and decreasing pay in logistics industry
Increasing unpopularity/obstacles
In a long-term, Japan may have to shift to the European model, but what would be the
social impact in near future?
How does the role of the man change?
(3) Difference: Human or Machine?
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The main constituent of the work
is machine, human supports
machine
Advantages Easy to standardize
Operator experience not needed
Easy to educate
Decrease in labour force
Easy to collect data
Disadvantages Handle-able goods is limited
Difficult to change work method
Large initial investment
The main constituent of the
work is human, machine
supports human
Advantages Relatively easy to handle variety of
goods (shape, size)
Work method can be changed
flexibly
Small investment
Disadvantages Depends on operator’s capability
Difficult to standardize
Education needed
Work load gets smaller, but does not
get to zero.
Weakness for standardization?
(3) Difference: Human or Machine?
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Unpacking of air cargo
Loading to the container
In Japan, wearable machine is preferred…….Because of easy introduction
Experiments performed by NRIC
Reference: In the case of Europe
Copyright (C) 2016 Nittsu Research Institute and Consulting, Inc. Proprietary & Confidential 7
HAL Suit Stuttgart Exo-Jacket
Robot suit for supporting and enhancing its wearer’s physical abilities
Lower limb and full body type
Developed by Cyberdyne Inc. and the University of Tsukuba
Lightweight suit to support the back and arm
Scheduled for market introduction in about 2018
Developed by Fraunhofer IPA
© NRW Japan K.K.
(4) Robotics in Logistics(Human Substitute Robot)
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Unspecified
Third-party
Uncontrollable
Logistics
Specified
“Homemade”
Controllable
Manufacturing
Goods
Product Design
Plan
Manufacturing difficultyWe should consider how to take advantage of the human ability
Key Point(in logistics):Machine・・・”Shape” ”Strength” “Center of Gravity” recognition of the object
that can not be estimatedHuman・・・・Operation the machine can not determine
And Putting more difficult task than PickingPicking ⇒ Recognition of the objectPutting into storage ⇒ Recognition of the yard environment
(4) 10 years from now,
• What will be the view of logistics workplace?
• What kind of innovations are expected?
• How should we be prepared for the changes?
Copyright (C) 2016 Nittsu Research Institute and Consulting, Inc. Proprietary & Confidential 9
?
We will continue to explore
2.Autonomous systems in logistics and manufacturing
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© Fraunhofer • Seite 11
Tim Brandl
October 6th 2016
AUTONOMOUS SYSTEMS IN LOGISTICS AND MANUFACTURING
© Fraunhofer • Seite 12
Fraunhofer-Gesellschaft, the largest organization for applied research inEurope
Wertheim/Bronnbach
Mannheim
Karlsruhe
Pfinztal
Ettlingen Stuttgart
Freiburg
Kandern
Efringen-Kirchen
Alzenau
Würzburg Bayreuth
Erlangen, Nürnberg, Fürth
Regensburg
Straubing
Augsburg
Weßling
München, Garching
Freising
Prien
Holzkirchen
Bremen
Teltow
WildauPotsdam-Golm
Cottbus
BremerhavenHamburg
Kassel
Frankfurt
Darmstadt
Rostock
Oldenburg
Hannover
Braunschweig
Goslar
Göttingen
MünsterLemgo
PaderbornDortmund
Schmallenberg
Gelsenkirchen
Duisburg
Oberhausen
Köln
Euskirchen
AachenWachtberg
Bonn, Sankt Augustin
Kaiserslautern
Saarbrücken
St. IngbertSulzbach
Leipzig
Chemnitz
Freiberg
Dresden, Moritzburg
Zittau
Magdeburg
Halle
Schkopau
Leuna
Itzehoe
Lübeck
ErfurtJena
HermsdorfIlmenau
Berlin
Sulzbach-Rosenberg
Remagen
67 institutes and independent research units
More than 24,000 staff €2.1 billion annual research budget totaling
2/3 of this sum is generated through contract research on behalf of industry and publicly funded research projects
1/3 contributed by the German federal and Länder governments in the form of base funding
International cooperation
Institute
Other Facilities
Headquarter
© Fraunhofer • Seite 13
1981
Founded260
Scientists
250Doctoral candidates
and student assistants
Cooperations include:HSG St. Gallen (Switzerland),
Georgia Tech (USA),Lissabon (Portugal),
Shanghai (China), Rio de Janeiro (Brasil),
Istanbul University (Turkey)
25million €
Revenue
Thereof 54% from Industry, trade and services
The Fraunhofer Institute for Materialflow and Logistics IML –Data and Facts
© Fraunhofer • Seite 14
On the road to Industrie 4.0: Automation
Complete automation of physical processes
Human flexibility as the key for adaptability and changeability in Industrie 4.0
Autonomization on the basis of smart and decentralCyber-Physical Systems
INDUSTRIE
≠ 4.0 =
© Fraunhofer • Seite 15
Industrie 4.0: The necessity for the change of management
Conventional Automation Pyramid
Organized hierarchically Deterministic System modification through
customizing Application-specific solutions
Flexible and changeable Highly decentralised Non-deterministic Multi-Agent-System Cloud-based Situation-specific solutions
Transformationof management
Migration ofCyber-Physical Systems
ERPStrategy
Command LevelPlanning
Operational LevelControl & Monitoring
© Fraunhofer • Seite 16
Sample technologies for Industrie 4.0
3D Printing
Swarm IntelligenceIntelligent Containers AutoID-Applications
Automated PlanningLogistic Drones
© Fraunhofer • Seite 18
Cellular Transport Systems
Example Self-Organisation & AutonomyResearch Project SMART FACE
Intelligent ContainerSolution for low-
volume manufacturing with many variants
http://www.internet-der-dinge.de/en/projects/smart-face.html
Smart Face Demonstrator
Copyright (C) 2016 Nittsu Research Institute and Consulting, Inc. Proprietary & Confidential 19
Contact
Tim Brandl
(Representative for Fraunhofer IML)
Business Development Unit
NITTSU Research & Consulting, Inc. (NRIC)
E-Mail: tim.brandl@iml.fraunhofer.de
Internet: https://www.iml.fraunhofer.de/en.html
Dr. Fumihiko Inoue
Senior Consultant
Advanced Technology Unit
NITTSU Research & Consulting, Inc. (NRIC)
E-Mail: inouef@soken.nittsu.co.jp
Internet: https://en.nittsu-soken.co.jp/