JIMTOF 2018 ifm efector co., ltd. IMPLEMENTATION OF KAIZEN ... · IMPLEMENTATION OF KAIZEN ACTIVITY...

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IMPLEMENTATION OF KAIZEN ACTIVITY

THROUGH IOT TO EXPLOIT VIBRATION DATA

IN MACHINE TOOL APPLICATION

JIMTOF 2018 – ifm efector co., ltd.

ifm diagnostic gbmh 114/12/2018

© ifm© ifm

Your speaker:

Mr. Edil Alvarez


ifm diagnostic (International Project Manager Vibration Systems)

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Let us introduce the Y Path approach

5 % of the data is

processed in the controller

– in bytes per millisecond

95 % of the data should be

processed in the IT world

– in megabytes per

second


Industry 4.0 – what does that mean for ifm customers?

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Y Path: from the sensor to SAP (Database)

Y Path provides 95 % of the process data without detour via the controller.

IT and automation technology are integrated in a simple and economical

manner for the first time – from the sensor to the SAP® database.


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From sensor to SAP (Database)

For the first time, sensor data can be directly transmitted to the business

software – and this on a factory-wide or even worldwide level.

Evaluation of the obtained data in real time enables an increase in

production efficiency and energy savings in the context of Industry 4.0.


© ifm© ifm ifm diagnostic gbmh 614/12/2018

SPSPC,

Server Modbus-

TCP

Smart Observer

VSE DLL

Proprietary protocol

ifm OPC server VOS00x

(classic OPC)

VSE15x

Parameter software VES004

Office

LAN

OPC

Industry 4.0 = Online Condition Monitoring + Connectivity & Y Path

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WCM (World Class Manufacturing): Kaizen Activity 10 technical pillars and 10 management tasks to be improved

Commitment Involvement Communication Understanding Measurement Deployment

Implementation Evaluation Standardization with visibility Documentation

Sa

fety

/ H

ygie

ne

& w

ork

ing

en

viro

nm

ent

Kaizen Activity (WCM)

Custo

me

r S

erv

ice

Cost D

ep

loym

ent

Fo

cu

se

d Im

pro

ve

me

nt

Qu

alit

y C

on

tro

l

Au

ton

om

ous A

ctivity

Pro

fessio

nal M

ain

ten

an

ce

Ea

rly P

rod

uct /

Equ

ipm

ent

Ma

na

ge

ment

Pe

op

le D

eve

lop

me

nt

En

viro

nm

ent

ifm

solutions

are available

for all pillars.

Roadmap

solution

packages.

NOW

1-2 years

1.5 -2.5

years


© ifm© ifm

Key Principles of WCM

WCM comprises 10 technical and

10 managerial pillars

In every pillar 5 points can be achieved

The status is checked by audit through

WCM Experts

Status for each pillar is structured

from Step1 – Step7

Example:

Professional Maintenance

WCM Status is the result

>50 points BRONZE

>60 points SILVER

>70 points GOLD

>80 points WORLD CLASS


Commitment Involvement Communication Understanding Measurement

Deployment Implementation Evaluation Standardization with visibility

Documentation

Safe

ty /

Hyg

iene &

work

ing e

nvironm

ent

Kaizen Activity

(WCM)

Custo

mer

Serv

ice

Cost

Deplo

yment

Focused I

mpro

vem

ent

Qualit

y C

ontr

ol

Auto

nom

ous A

ctivity

Pro

fessio

nal M

ain

tenance

Early

Pro

duct

/ E

quip

ment

Managem

ent

People

Develo

pm

ent

Environm

ent

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ifm application solutions – RTM Improvement in Maintenance


Autonomous Maintenance

Professional Maintenance

RTM ifm solutionfrom

Time-Based (STEP 5 )

to

Condition-Based

Maintenance (STEP 6)

RTM

Real

Time

Maintenance

Predictive

Maintenance

Commitment Involvement Communication Understanding

Measurement Deployment Implementation Evaluation Standardization

with visibility Documentation

Sa

fety

/ H

ygie

ne

&

wo

rkin

g e

nvir

on

me

nt

World class

manufactur

ing

Custo

me

r S

erv

ice

Cost

De

plo

ym

en

t

Fo

cu

se

d Im

pro

ve

me

nt

Qu

ality

Con

tro

l

Au

ton

om

ou

s A

ctivity

Pro

fessio

na

l

Ma

inte

na

nce

Earl

y P

roduct / equip

ment

Managem

ent

Pe

op

le D

eve

lop

me

nt

En

vir

on

me

nt


Steps of improvement

Step 1 Step 2 Step 3

Once the problem has emerged,

corrective measures are adoptedReactive

Step 4 Step 5

According to experience acquired,

appropriate corrective actions are

adopted to avoid repetition of an

already known problem

Preventive

Step 6

Improvement with

RTM ifm solution

from Time based (STEP 5 )

to Predictive

Maintenance

Proactive

enables for

Step 6

>> Preparation for

connection to SAP


Predictive Maintenance


Wear / Consumption WEAR INDICATORS INFLUENCE QUANTITIES

Rolling element bearing

1 - 4 months prior to failure:

Bearing frequencies,

vibrations, temperature and

abrasion

Before first measurable wear

indicator occurs (bearing noise):

Operating hours

Vibration- and impact-related

loads (dose)

Temperature load,

Bearing position (dose)

Play Unbalance, shaft vibrations Speed, operating hours, load

Milling toolAcceleration measurement

a_peak (cutting forces)

Processing time (use of the tool)

Tank content Filling level Consumption/km + history

Gearbox oilClouding, conductance, ph-

value

Temperature distribution during

operation

(Lithium-ion) battery Voltage drop Operating time, temperature

Tool clamp (HSC spindle)play; only towards end of

lifetime

Number of replacement cycles

Electronics Check sums, error logs Writing cycles (flash memories)

Ball screw drivepreload, overrolling noise

(vibrations)

12

Predictive MaintenanceDistinction of wear indicators and influence quantities


Information

Machine running / not running Operating hours

Machine running with different loads/

operating points => load collective of the

operating hours

Operating mode; if possible, conclusions as to

further areas, e.g. performance factor

Number of impacts above limit value =>

degree of impact load

Operating mode, impacts during start-up

Bearing temperature > permissible value Viscosity of lubrication

Temperature classes of gearbox oils

Alarms / unit of time Micro-interruptions

Distance covered in linear guidance systemsOperating time

Acceleration of robots Material strain

Predictive MaintenanceA closer look at the influence quantities

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Influence

quantity ->

Wear

indicator

< MTBF > MTBF

HIGH

“vibration”

LOW

“vibration”


Residual life: 1,200

operating hours

Influence Quantities

Runtime-counter

MTBF

Weak point

Corrective action

Longer service life

Money saved!

Preparation of

maintenance

measure

Planning and

implementing

maintenance

measures

Normal operation

No preventive

action necessary!

• No inspection

• No diagnosis

Predictive Maintenance

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Predictive Maintenance – a living system!


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ifm diagnostic gbmh14/12/2018

OEE =

Availabilty Productivity Quality

X X

OEE (Overall Equipment Effectiveness)

The formula: OEE = A x P x Q


Sources: IFW Hannover, WZL Aachen,

KIT Karlsruhe, VERSTAND research

project, Germany

OEE availability losses

Unplanned downtime classified by technical causes

Availabilty

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Wear 6 %

Lubrication 5 %

Leakage 4 %

Others 10 %

Crash, overload, wear, 75 %

1 2 3 4 5

Vibration monitoring can …

Make spindle load

transparent

Protect against overload

Avoid unplanned downtime

Reduce consequential

damage


Source: KIT / IWB / ifm, 2018



Availabilty

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Motor spindle monitoring: typical error messages

Error messages Activities, alarm schedule

Vibration value too highCounters document the load collective; depending on the time spent in a

high vibration range, a reaction is also possible, if appropriate

Impact value too highDocument the incident, intervene in the process, if appropriate. Control

bearing condition (e.g. stone has hit the windscreen).

Imbalance too high – during

operationCheck the tool; verify process parameters, if necessary

Imbalance too high during

reference runWear of bearing

Poor bearing condition (BPFs) Prepare replacement of bearing

Temperature too high Check for electrical faults, inspect ventilation and cooling system

Maximum operating hours

reached

If lead times are long, prepare replacement of bearing, but wait for

deterioration of bearing condition. If operation exceeds expected service

life, ROI calculation provides reliable profitability forecasts.

Load classes green/yellow/red to be considered when evaluating the

operating hours.


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Vibration severity (= effective vibration velocity or v_eff)

includes the sum of all amplitudes from 10 to 5,000 Hz (unit: mm/s).

The indicator v_eff is correlated with material fatigue.

Counters indicate the time spent working under a certain load.

Unbalance Cutting frequencies

Measurement of overall vibration (object v_eff)


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Monitoring of motor spindle fatigue


7000

5187

1154

659

0

1000

2000

3000

4000

5000

6000

7000

8000

Operating time o.k. yellow red

Ho

urs

Operating time

o.k.

yellow

red

During

process,

standard-type

spindle, 600

to 28,000 rpmin mm/s _rms

10-5000Hz

During

process,

HSC spindle,

28k to 40k

rpm

in mm/s _rms

10-5000Hz

A0 - 7 0 - 5

B

C 7 - 17 5 - 8

D 17- 23 8 - 12

E > 23 > 12

100 % lifetime when:

yellow < 10%

red < 1%

of total runtime

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Monitoring of shocks to the motor spindle


Example of integrated data logger (VSE100):

Differing proportions of unbalance- and process-related vibrations

included in the overall vibration of a milling machine during various

processing steps

=> Optimisation potential

Unbalance

v_eff

© ifm© ifm ifm diagnostic gbmh 23

Crash monitoring: g-monitor (a_peak)

Crash measurement via acceleration impacts

(a_peak).

Correlation of acceleration with effective force:

(F = m*a).

Force impacts propagate in the material along 3

space axes.

Measurement time: 1 ms; alarms issued directly

to the NC unit via fast outputs.

Each impact above the crash limit is counted.

A single impact can destroy a hybrid bearing!

Analogy: stone hitting a glass window.

Check bearing after crash!

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During

process,

standard-

type spindle,

600 to

28,000 rpm

in g _pk

10-1000 Hz

During

process,

HSC spindle,

28 k to 40 k

rpm

in g_pk

10-1000Hz

Spindle

without

turning

15 6 4

25 13 10

G-monitor (a_peak)


Impact beyond RED threshold:

potential destruction of bearings

To provide safety: subsequent bearing

check by reference run

Immediate reaction protects machine from

consequential damage

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Machine protection – why each millisecond saves money


1: Rapid movement without disruption

2: Process-relevant shutdown threshold

(depends on material, tool and cutting parameters)

3: Spindle-relevant shutdown threshold

(protection of bearings and tool)

4: Destruction of the tool and/or workpiece;

bearings likely to be damaged

5: Overloading of feed drive and shutdown

of motor currentt / ms

Picture:

wikimedia.org

© ifm© ifm

QualityProcess quality


Process-related limit values (g-monitor)

Tool-related limit values (g-monitor)

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Tool quality


Milling cutter with 5 cutting edges

Tool okay

Milling cutter with 5 cutting edges

One edge worn

The next cutting edge must double its performance

=> Increase of g–level by 37 %

Quality

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Tool quality


Raw acceleration signal

over one cycle

Edge #5 not cutting

broken

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Surface quality – chatter vibrations


Stable process

Instable processChatter marks

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Process quality – summary

Tool quality

Tool balancing

Avoiding tool damage

Chatter detection (quality)


OEE =

Availabilty Productivity Quality

X X


Sources: IFW Hannover, WZL Aachen,

KIT Karlsruhe, VERSTAND research

project, Germany



Availabilty

© ifm© ifm

References & Case Studies

ZF, Germany – gearbox manufacturer

ZF Friedrichshafen global locations marked blue

Cost saving calculations for machine tool applications

In production

In maintenance


Source of images: https://commons.wikimedia.org/wiki/Category:ZF_Friedrichshafen?uselang=de

© ifm© ifm

Cost savings in production – example 1


Potential Cost Saving due to Simplified Machine Diagnosis

Simplified Fault Detection 77,220.00 ¥*

Without CM there can be no machine diagnosis upon receipt of an alarm message,

unless production is stopped.

Messages / year 1,50

Diagnosis without CM 3,00 h

Online diagnosis with CM (without shut-down of machine) 0,00 h

Machine-hour rate 17,160.00 ¥

Prevention of wrong decisions 278,784.00 ¥

Incorrect diagnosis results in an increase of machine downtime.

Wrong decisions / year 0,25

Unscheduled maintenance 65,00 h


*Original calculation in EUR (€); basis of conversion: 1 Euro = 132 Yen

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Potential Cost Saving due to Scheduled Maintenance Activity

Forseeable Exchange 350,064.00 ¥*

Whereas unscheduled maintenance consists of response time, time for procurement

of replacement parts and time for repair, scheduled maintenance is limited to

the time needed for repair.

Unscheduled maintenance 65,00 h

Scheduled maintenance 14,00 h

Failures / year 0,40


*Original calculation in EUR (€); basis of

conversion: 1 Euro = 132 Yen

© ifm© ifm



Potential Cost Saving due to Preventive Maintenance Activity(Quality issues)

Prevention of reject production 704,880.00 ¥*

Without CM, disturbance in a spindle is only noticed upon deterioration of the quality of

the parts produced. CM, however, provides for replacement of the spindle without

producing rejects.

Failures + messages / year (for quality reasons) 2,67

Quality inspection, every X pieces 50,00

Piece costs per blank 5,280.00 ¥

*Original calculation in EUR (€); basis

of conversion: 1 Euro = 132 Yen

© ifm© ifm

Cost savings in maintenance – example 1


Potential Cost Saving due to Simplified Machine Diagnostics

Simplified Fault Detection 51,728.00 ¥*

Fault messages concerning spindles that are received via CMMS have to be verified on site

if there is no CM. CM provides for much faster and better diagnostics.

Messages / year 1,50

Diagnostics without CM 3,00 h

Diagnostics with CM 0,25 h

Master engineer's hourly wage rate 12,540.00 ¥

Prevention of Wrong Decisions 165,000.00 ¥

In case of a wrong decision regarding the spindle condition, the spindle is dismantled

and sent in for maintenance. With CM, no incorrect diagnosis can occur.

Wrong decisions / year 0,25

Maintenance of spindle (without damage) 660,000.00 ¥


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Potential Cost Saving due to Scheduled Maintenance Activity

Forseeable Exchange 76,745.00 ¥*

If maintenance is unscheduled, maintenance staff will be tied up with

repair of the damage.

Unscheduled maintenance without CM 65,00 h

Scheduled maintenance with CM 14,00 h

Failures / year 0,40

Master engineer's hourly wage rate (30%) 3,762.00 ¥


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Potential Cost Saving due to Preventive Maintenance Activity

Prevention of Consecutive Faults, Wear, Handling Errors 84,480.00 ¥*

Leaving faults undetected will provoke consequential

damage.

Consequential damage 10,00 %

Maintenance costs 2,112,000.00 ¥

Failures / year 0.40

Longer Lifetime of Components 132,000.00 ¥

With every case of prevented damage, the component lifecycle is extended.

Extension of lifecycle in per cent 5.00 %

Price of new spindle (motor spindle) 2,640,000.00 ¥



Cost saving Calculation per Spindle (24-7 operation) / year*

Potential cost saving in production / year 1,411,014.00 ¥

Potential cost saving in maintenance / year 425,436.00 ¥

Total cost saving potential / year 1,836,487.00 ¥


Summary: cost savings per machine (= 1 motor spindle per year !!)

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Carlo Di Nicola on FCA / CNH projects

Carlo Di Nicola (ifm System Sales Engineer from Italy) is the

global coordinator for RTM systems of the FCA Group regarding

the implementation of WCM strategy (Kaizen activity).

His experience:

With our system we are currently present in more than 30 FCA

and CNH plants worldwide.

This means we are successfully monitoring over 50 machine

tools online!


© ifm© ifm

References

Realised installations at Fiat Chrysler Automobiles:

FCA, Italy

CNH, Italy

FCA USA

CNH USA

FCA Brazil

CNH Brazil

FCA Serbia

CNH France


© ifm© ifm

FLASH ALERT at Renault plant informing about anomalies at a

machining centre due to excessive vibration during machining

20-09-2018

Error: V_RMS 10 – 5000hz in mm/s -> wear condition of spindle

1) Vibration level with Smartobserver

2) Details with Diziview

3) Link to Smartobserver

4) Information

Purposes of the alert:

• Increase life of spindle

• Check physical load

• Determine cause of vibration

• Reduce vibration

• Measure the result


Information + Action + Verification of results:

1) Identification of tool concerned -> P0114 machining of drill hole -> 25-09-2018

2) Anticipated action -> stiffen the mandrel of tool P0114 -> SM39 to 40

3) Anticipated action -> modify the milling cycle as in 4154?

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Renault: measurement of vibration level with SMARTOBSERVER


• Supervision by ifm

SMARTOBSERVER

shows: RMS values

are too high.

• A warning is issued:

electrospindle is

subjected to too

much stress.

• Machining

conditions are not

good!

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Renault: 2.2 details with Diziview


• Detailed analysis

shows that the

relevant vibrations

occur once per

cycle.

• Among all the

tools used, it is

always the same

tools that

generate these

vibrations.

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Renault: 4.1 – information relating to the tool


• This is the tool causing the fault.

• Intended tool lifespan: 32,000 pieces.

• Tool has been destroyed 4 times

since beginning of the month.

• Following this analysis, Renault will

proceed to take corrective action.

© ifm© ifm

VSE1xx in electrical cabinet of machine tools


ifm’s diagnostic

electronics

VSE1xx in the

electrical cabinet

of machine tools,

connected to the

Ethernet network.

Accelerometer is

mounted on the

spindle.

© ifm© ifm

JIMTOF 2018

Thank you very much for your attention!


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