Best-In-Class Solutions for Material Handling · Source: MHI 2017 Annual Report: https: ... •...

Best-In-Class Solutions for Material Handling Presented by Bhaskar Chopra

Manufacturing in America │ March 14-15, 2018

Unrestricted © Siemens 2018 All rights reserved. Community. Collaboration. Innovation.

Before we start… A Penny for Your Thoughts

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Introduction

Bhaskar Chopra

P: 770-549-0249

• Siemens DF MC Strategic Business Developer – Material Handling

• Siemens Drives Digitalization lead

• 8 years Siemens Drives experience, specializing in automotive,

flooring and intralogistics applications

• Possesses ability to dunk on standard NBA hoop


Source

Source: MHI 2017 Annual Report: https://www.mhi.org/publications/report


Robotics &

Automation

Predictive

Analytics

Internet of

Things (IoT)

Disruptive technologies are going to change the market,

but adoption today is low

Potential to Disrupt 2018

Adoption Rate

61%

57%

55%

37%

17%

24%

89%

89%

92%

2024+

Adoption Rate



93% of

companies

struggle to

find qualified

workers

Toughest Workforce Challenges Today:

Finding the right

people

Training and

improving their

skills

Retaining skilled

employees


https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=2ahUKEwiisfPJlcnZAhUJ0WMKHS79BsoQjRx6BAgAEAY&url=https://www.flickr.com/photos/acwa/18419561879&psig=AOvVaw0PHbyIbPnR1Bz31wa8LxBc&ust=1519926494311891


Case Study

Flooring Manufacturer with a 3 AM problem

Biggest fear is a

3 AM failure with

no trained

personnel present

• 325 VFDs (200 on conveyors,

remainder in production)

• Inexperienced maintenance

staff with ~13 month turnover


Consistent data structure ensures comfort with all styles of VFDs

P3

P4

P5

P6

P7

P100

P101

P102

P103

P104

P300

P301

P302

P303

P3

P4

P5

P6

P7

P30

P31

P32

P33

P34

P100

P101

P102

P103

P104

P200

P201

P300

P301

P302

P303

P3

P4

P5

P6

P7

P20

P21

P30

P31

P32

P33

P34

P50

P51

P100

P101

P102

P103

P104

P150

P151

P200

P201

P300

P301

P302

P303

SINAMICS


Portfolio Modularity eliminates the need for reprogramming

during downtime scenarios


Best in Class Installation and Maintenance Strategy

SINAMICS G120 SINAMICS G110M Instead of complete

converter, only defective

components need to

be replaced –

significantly reducing

the number of

spare parts

SINAMICS G120D SINAMICS S120

The SINAMICS converter consists of two components:

the Power Module (PM) and Control Unit (CU)


Easy replacement via automatic parameter download,

no PC required

Power on

Power on

• After power reset, data set of

parameters is automatically copied

from memory card to converter after

replacement

• If a memory card with firmware is used

(standard with SINAMICS S) a

firmware up- or down grade will

automatically be started

• No PC required for converter

replacement


Robotics &

Automation

Predictive

Analytics

Internet of

Things (IoT)




Adoption Rate

61%

57%

55%

37%

17%

24%

89%

89%

92%

2024+

Adoption Rate



Predictive Analytics starts with an emphasis on clear, concise data

Vendor based error

codes

Error codes and remedies

in plain English



1

V20_xxxx

2 3



Online/offline

identification Fault /

alarm quick menu

Parameter editing /

saving

Monitoring status

of converter

Backup and restore settings

to mobile

Quick commissioning

wizard

Run motor in jog mode

or setpoint

Quick overview of fault,

alarm and status

Smart Access options

Product identification Hotline/Support


Control the motor Get control of motor


Confirm safety notes

Close

control view

Change speed and direction

Enable the

control to

start motor



Overview of active faults and alarms Overview of the status bits Automatic creation of status e-mails

Contains information about the drive,

faults and alarms.

Can be directly transferred to your local

service company.


Predictive Analytics continues with well connected components

SIMOTICS IQ

Digital link through SIMOTICS Connect,

a plug & play sensor box with communication via

WLAN and integrated power supply.

• Motor operating data

• Power and speed

• Operating status and operating hours

• Fleet management

• Electronic rating plate


Predictive Analytics continues with well connected components


Robotics &

Automation

Predictive

Analytics

Internet of

Things (IoT)




Adoption Rate

61%

57%

55%

37%

17%

24%

89%

89%

92%

2024+

Adoption Rate



9%

9%

17%

25%

26%

28%

31%

Cold Chain Temperature& Humidity Integrity

Artificial Intelligence &Machine Learning

Streamlined Production

Quality Control

Customer / Market Insight

Customer and/orSupplier Collaboration

Real-Time Analytics

80% believe

customer demands

for more

customized

products and

services represents

a significant

company challenge

How are companies using / planning to use the Internet of Things?



System Engineering Approach

Mechatronic

Concept Designer

Machines

components

Production

Cells Process Simulate

Plant Simulation

Machines

Production

Plants

Simcenter Amesim


Machine concept

Design and

simulate

the machine

concept

NX Mechatronics

Concept Designer


Mechatronic Concept Designer

How will the machine work ?

Machine sequence 3D basic geometry

Control signals Force/load profiles

Cam plates

Kinematic description

Sensor-actuator lists

Reference designation


Integrated engineering reduces the time from the first idea

to the machine realization

Software

Electrical / Fluid To

day

Fu

ture

Mechanical design

Detailed Engineering

Mechanical concept

Concept Design

Requirements

Planning

Real

Machine

Real commissioning

Commissioning

Electrical / Fluid

Mechanical design

Software

Interdisciplinary Engineering

Mechanical concept

Concept Design

Requirements

Systems

Engineering

Digital Twin

Virtual

commissioning

Real Machine

Real

commissioning

Commissioning

Time

saved


Kinematic validation Virtual commissioning with Mechatronic Concept Designer

Capabilities

• Define mechatronic model including kinematic, sensors, actuators,

logic and signals

• Connect directly with PLC Hardware or PLC Simulation (PLCSIM Adv.)

• Share data between mechanical, electrical and automation departments

• Reuse standardized mechatronic components for a faster machine

design

Key Points

• Define and validate the mechatronic concept of the machine directly

with the CAD model in the early phases of development

• Optimize machine design before the first prototype (sequence, traveling

path, speed of motors, position of sensors…)


System Engineering Approach

Mechatronic

Concept Designer

Machines

components

Production

Cells Process Simulate

Plant Simulation

Machines

Production

Plants

Amesim


Production engineering

Optimize

material flow

Tecnomatix

Plant Simulation


Material flow optimization Simulation – typical objectives

Optimized lot size Reduced stock

size Less work in

progress

Increased

flexibility on

customer demands

Reduced number

of “gut decisions”

Detection of

interdependencies

Optimized control

strategies

Investment

savings

“What if

scenarios”

Reduced over

dimensioning

Reduced

throughput time


Cell validation Virtual commissioning with Plant Simulation

Capabilities

• Validate material flow and control logic

• Verify PLC code and HMI

• Verify conveying unit and head unit level

• Perform system diagnostic testing

Key Points

• Perform “what-if” scenarios (Failure Modes)

• Validation prior to conveying system construction

• Operator training


Material Handling faces speed and efficiency risks not only in

operations but in design and implementation as well

• Full simulation of complex

production systems and control

strategies

• Object oriented models of

handling equipment

• Bottleneck analysis tools

• 3D visualization

• Automated optimization of system

parameters

Plant Simulate w/ Warehousing and Logistics Library


How did we do? Share your thoughts to win!

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Seminar Slides

After MiA, seminar slides will be available at:

http://www.usa.siemens.com/mia-seminars





Questions?

Bhaskar Chopra

Strategic Business Developer – Material Handing

Phone: 770-549-0249

E-mail: [email protected]

mailto:[email protected]

Best-In-Class Solutions for Material Handling · Source: MHI 2017 Annual Report: https: ... •...

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Transcript of Best-In-Class Solutions for Material Handling · Source: MHI 2017 Annual Report: https: ... •...