GO MOBILE I N T E R N A T I O N A L C O L L A B O R A T I V E R O - PowerPoint PPT Presentation

COLLABORATIVE ROBOTS GO MOBILE I N T E R N A T I O N A L C O L L A B O R A T I V E R O B O T I C S W O R K S H O P 2 0 1 6 4 M A Y 2 0 1 6 - B O S T O N , M A

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I CR W 2016 - BO STO N, MA AVERAGE AGE ON THE FORTUNE 500 LIST 60 12 YEARS YEARS 1950 2015 Source: Richard Foster, The Creative Edge, Deloitte

I CR W 2016 - BO STO N, MA C H A N G E I S N E C E S S A R Y & I N E V I TA B L E

I CR W 2016 - BO STO N, MA OV E R T H E N E X T D E CA D E 
 3 . 5 M I L L I O N 
 U S M A N U FA C T U R I N G J O B S 
 W I L L B E N E E D E D 
 W I T H A P P R OX I M AT E LY 
 2 M I L L I O N 
 L I K E LY TO G O U N F I L L E D Source: The Skills Gap in US Manufacturing, Deloitte + Manufacturing Institute

I CR W 2016 - BO STO N, MA T H E M A N U FAC T U R I N G S E C TO R I N T H E U. S . H A S N OT G R O W N A S FA ST A S T H E R E ST O F T H E E CO N O M Y A N D, A S A R E S U LT, I T S S H A R E O F TOTA L O U T P U T H A S FA L L E N F R O M 2 4 % I N 1 9 7 0 TO 1 2 % TO DAY Source: The Skills Gap in US Manufacturing, Deloitte + Manufacturing Institute

I CR W 2016 - BO STO N, MA “You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.” B U C K M I N ST E R F U L L E R A R C H I T E C T, I N V E N TO R , D E S I G N E R , A U T H O R M E N S A P R E S I D E N T

I CR W 2016 - BO STO N, MA THE EXISTING MODEL M AT E R I A L H A N D L I N G ACCO U N T S F O R : 13% 25% 25% 45% 55% 75% 75% 87% P R O D U C T I O N CO ST E M P LOY E E T I M E FAC TO R Y S PAC E P R O D U C T I O N T I M E Source: Concordia University

I CR W 2016 - BO STO N, MA C H A N G E I S H A P P E N I N G A S W E S P E A K

I CR W 2016 - BO STO N, MA BIG DATA SMART FACTORY INTEROPERABILITY INDUSTRY 4.0 VERTICAL NETWORKS CYBER PHYSICAL SYSTEMS INTERNET OF THINGS (IOT)

ABOUT 25 BILLION OBJECTS WILL BE INTERCONNECTED BY 2020. TODAY, THERE ARE 3.8 BILLION SUCH OBJECTS G A RT N E R

I CR W 2016 - BO STO N, MA “Humans can typically create one or two good models a week; Machine learning can create thousands of models a week.” T H O M A S H . DAV E N P O RT, A N A LY T I C S T H O U G H T L E A D E R E X C E R P T F R O M T H E W A L L S T R E E T J O U R N A L C L E A R PAT H C O N F I D E N T I A L

I CR W 2016 - BO STO N, MA W H AT D O E S T H I S M E A N F O R M A N U FAC T U R I N G ?

I CR W 2016 - BO STO N, MA S M A RT E R FAC TO R I E S

I CR W 2016 - BO STO N, MA R E A L LY ?

I CR W 2016 - BO STO N, MA MATERIAL TRANSPORT RIGID = LINEAR

I CR W 2016 - BO STO N, MA MATERIAL TRANSPORT RIGID FLEXIBLE = + LINEAR NON-LINEAR

I CR W 2016 - BO STO N, MA MOBILE ROBOT != COLLABORATIVE

I CR W 2016 - BO STO N, MA MANIPULATE TRANSPORT

I CR W 2016 - BO STO N, MA COLLABORATIVE ROBOTS REMOVE THE FENCE SELF-DRIVING VEHICLES REMOVE THE TRACK

I CR W 2016 - BO STO N, MA SELF-DRIVING VEHICLE = COLLABORATIVE

BUILDS MAPS WITH ONBOARD LASERS NO NAVIGATION INFRASTRUCTURE REQUIRED 20x

I N D U ST R Y 4 . 0 ERP A P I O P S D A S H B O A R D O T T O F L E E T F L E E T M G M T “ “ W E B A P P

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I CR W 2016 - BO STO N, MA W H AT D O E S T H I S M E A N F O R M A N U FAC T U R I N G ?

I CR W 2016 - BO STO N, MA P R O C E S S A N D D E V I C E W I L L B E I N S E PA R A B L E

I CR W 2016 - BO STO N, MA WA N T E D : C H A M P I O N S 
 A N D T H O U G H T L E A D E R S J O I N T H E S E L F - D R I V I N G R E V O L U T I O N W W W. OT TO M OTO R S . CO M

I CR W 2016 - BO STO N, MA QUESTIONS? J O I N T H E S E L F - D R I V I N G R E V O L U T I O N W W W. OT TO M OTO R S . CO M