the Electronics Assembly industry Semiconductors, and vice ... · 20171115_SMT learning from...

Dr. Michael AlexanderPartner

Munich, 15th November 2017

Industry 4.0 – Can the Electronics Assembly industry learn from Semiconductors, and vice versa?

220171115_SMT learning from SEMI_Vfinalgraphics.pptx

Contents Page

This document shall be treated as confidential. It has been compiled for the exclusive, internal use by our client and is not complete without the underlying detail analyses and the oral presentation.

It may not be passed on and/or may not be made available to third parties without prior written consent from .

© Roland Berger

A. A quick introduction to Roland Berger 3

B. Electronics Assembly in a nutshell 5

C. Industry 4.0 in Electronics Assembly 8

D. Learning from Semiconductors 14

E. A one-way road? 25

F. Summary 27

A. A quick introduction to Roland Berger


Roland Berger is the only leading global consultancy of German heritage and European origin

Roland Berger at a glance

Founded in 1967 in Germany by Roland Berger

50 offices in 34 countries, with around 2,400 employees

Nearly 220 RB Partners currently serving

~1,000 international clients

Terra Numerata™ digital ecosystem joining forces with more than 30 leading digital firms

B. Electronics Assembly in a nutshell


Flat overall Electronics Assembly market of ~ EUR 430 bn – Players leverage Industry 4.0 to extend service offerings & service quality

Source: IMS, Roland Berger

Key take-away Electronics Assembly market

> Electronics Assembly market is ~EUR 430 bn with ~1.0% CAGR 2011-15> Market is dominated by Electronic Manufacturing Services (EMS) and Original

Device Manufacturers (ODM) 1> EMS take ~75% or ~EUR 333 bn with ~7% CAGR 2011-15> Expected further slowing down of growth to ~5-6 %> ODM moving to EMS business to load their production capacities2> Most end-market segments growing at the same pace> Medical, Industrial, Automotive and other niches are ~20% of overall market> These appear to be the most profitable1) end-market segments, only slightly above 3C2)3> Price remains an important Key Buying Factor> Leading EMS players move towards extended service offerings and better service quality> Industry 4.0 is seen as a key enabler4

1) Based on an analysis of EMS players with over USD 100 m revenue / year, representing ~85% of the total market 2) Computers, Consumers, Communication


Electronics Assembly mainly consists of Front-End (SMT) and Back-End manufacturing steps – FE more automated than BE

Simplified Electronics Assembly manufacturing process

Source: Interviews, desk research, Roland Berger

Assy Back-endAssy Front-end Modules

1) Surface Mount Technology; 2) Through Hole Technology

SMTassembly

Post-SMTassembly

Calibration/ Programming

Test Boxing/Assembly

> In-circuit testing (ICT) of the board

> Functional testing, i.e., testing that the board functions as designed

> Flashing of firmware

> Uploading of programs onto the microchips

> Mounting of THT2)

components> Gluing of

components, underfilling, coating of the PCB

> Mounting of electric SMT1) components that are placed on top of the copper pads of the Printed Circuit Board (PCB)

> Placing PCB intoa housing

> Assembly of the full mechatronic system

While the front-end production is highly automated, the back-end is often characterized by a significant larger share of manual work

Simplified

C. Industry 4.0 in Electronics Assembly


Mechanization, Electrification, and Computerization have already influenced our working world radically – Industry 4.0 is next

Development stages of industrial manufacturing

Source: Bitkom/Fraunhofer, DFKI, Roland Berger

1784Mechanical weaving loom

First industrial revolution

100 %

1923Introduction of a moving assembly line at Ford Motors to support Taylorism

Second industrial revolution

100 %

1969First programmable logic controller

Third industrial revolution

100 %

201XReal time, self optimizing connected systems

Fourth industrial revolution?

<10 %

Time


Major Industry 4.0 trends

Industry 4.0 is driven by technology, demand, and competitive trends with a strong impact on manufacturing

Source: Roland Berger, pictures: with courtesy of Grenzebach, Rethink Robotics, Google

Technology Demand Competition

Changes within the existing competitor landscape

Utilization of established/new SW technologies

Increasing degree of automation in the factory

Digitally connected factory

New players entering the market

Increasing flexibility of production systems

Advanced automation concepts


Industry 4.0 scope comprises the entire value chain and business functions and has a huge impact on industry conduct and structure

The Industry 4.0 generic framework – Scope and impact

ImpactFlexibility/Mass customization

Direct client relationship

De-laborization

Higher asset rotation

Decentralization/ Regionalization

Faster product launches

Operator

Customer

Product Development

SupplierSmart Factory

Industry 4.0 scope

I

II

III

IV

V

VI

Shift of skillsetsVII


SMTassembly

Control1)

In the Electronics Assembly industry we found ~ 20 potential SW and HW technology building blocks for Industry 4.0

Overview of main Industry 4.0 technology blocks in Electronics Assembly


Fully automated equipment Automated material handling

Flexible workshop-based production

Predictive maintenance

Machine/line perf. opt.

System integration

HW-centric

SW-centric

Process control

Supply chain management

Smart Factory

PCB manufactur-

ing2)

Final packaging

Test / rework

Calibration / programm-

ing

Post-SMTassembly

Customer

Warehouse Shipping

Procure-ment tools

CRM

Asset performance mgmt. Quality mgmt.

Control1) Control1) Control1) Control1) Control1)Control1) Control1)

Prod. planning & schedulingProcess flow control

Process master control

Production scheduling

System integration

Product-to-machine communication

Machine-to-machine communication

Feedback loops

1) Machine control and/or line control including software interfaces 2) Usually not part of the electronics manufacturing process

QM systems

Automatic quotation tools

Order tracking

Supplier integration Digital twin

Material handling systems

Supplier

Sales tools

Design for manufacturing tools (Dfx)

Human-machine interfaces

8

9

Test

Prototyping

Product development

Plant eng.tools

Simulation

EDA/ECAD

PDM/PLM

Material handling


20%

28%

31%

31%

41%

43%

44%

50%

31%

50%

52%

57%

Tier-1

Tier-1

Tier-3

Tier-1

Tier-2

Tier-3

Tier-2

Tier-4

Tier-4

Tier-4

Tier-2

Tier-2

The overall market for Industry 4.0 technology building blocks has huge potential – even leaders still have half the way to go

Relative Industry 4.0 maturity of selected EMS players

Even the leading players have about half the way to I4.0in front of them


Note: Assessment based on RB I4.0 in EA technology building block segmentation and rating. Tier-1 players: turnover > USD 5 bn; Tier-2 players: USD 500 m < turnover < USD 5 bn ; Tier-3 players: USD 50 m < turnover < USD 500 m ; Tier-4 players: turnover < USD 50 m

Best in class

100%

D. Learning from Semiconductors


Generalmfg. SW

Diversified EDA

Electronics Assembly can learn from Semiconductors especially in Software

Electronics software player landscape

Smart

Factory

Productdevelopment

SMT EDASemi EDALong-tail of small players Specific PCB EDA long-tail of players

Long-tail of generalists &niche players

Offering both Semi and PCB design, as well as modules for System in Package

Semi Design

Semi front-end

Semi back-end

Assembly front-end

Assembly back-end

Modules

Note: Siemens refers to Camstar, Dassault to Apriso, SAP to Visiprise

Source: Interviews, Roland Berger

Semi mfg. SW

SMT mfg. SWSome smaller niche players

Majority developed inhouse;Some smaller niche players

Common ground especially in Semi back-end and SMT mfg. SW

1620171115_SMT learning from SEMI_Vfinalgraphics.pptxSource: Interviews, desk research, Roland Berger

SECS/GEM1) OIC2)

Unlike Semiconductors, different machine interface standards are used in Electronics Assembly – SECS/GEM has no "godfather"

Machine interface communication standards

Initiator

Hermes

Functionality > Interface to equipment and plant management SW

> Exchange machine data with plant management software

> Data exchange between machines

> Passing data within the line> Not designed for interfacing to

plant mgmt. SW

Importance > Limited importance -Only supported by small SMT players

> Widely used in Semiconductors

> Driven and supported by major players

> Widely used in Electronics Assembly, esp. SMT

> Driven and supported by major players

> Only focused on line control

> Relatively wide-spread in Electronics Assembly

Partners(selected)

1) SEMI Equipment Communications Standard / Generic Equipment Model; 2) Overall Inline Communication


Material handling, QM systems & Dfx tools are the mostly explored I4.0 SW technology building blocks in Electronics Assembly today

Average and best-in-class market maturity I4.0 SW technology building blocks

Best-in-class AverageTrend2016-21SW Technology Building Block


Process master controlSystem assuring that products pass all processes in the right order; flexibly assigns operators to lines based on tasks

Machine/line perf. opt.Systems for visualization of machine KPIs, proposing recommendations, or even automate improving processes

Maturity

Production schedulingSystem generating an optimal production schedule taking capabilities, bottlenecks, changeover times, etc. into account

Predictive maintenanceSystems predicting machine defects to avoid unscheduled as well as scheduled maintenance

Material handling systemsSystem managing the overall material handling process including change overs and replenishments

QM systemsSystem responsible for tracing all consumables used in the production and capturing all testing data

Design for manufacturing (Dfx)Software supporting design for manufacturing and assembly tasks by analyzing schematics


Within the next years, accelerating I4.0 adoptions will foster Process Control and Asset Performance Management software solutions

Average and best-in-class market maturity I4.0 SW technology building blocks

Source: Interviews; desk research; Roland Berger

Best-in-class AverageTrend2016-21SW Technology Building Block

Process master controlSystem assuring that products pass all processes in the right order; flexibly assigns operators to lines based on tasks

Machine/line perf. opt.Systems for visualization of machine KPIs, proposing recommendations, or even automate improving processes

Maturity

Production schedulingSystem generating an optimal production schedule taking capabilities, bottlenecks, changeover times, etc. into account

Predictive maintenanceSystems predicting machine defects to avoid unscheduled as well as scheduled maintenance

Material handling systemsSystem managing the overall material handling process including change overs and replenishments

QM systemsSystem responsible for tracing all consumables used in the production and capturing all testing data

Design for manufacturing (Dfx)Software supporting design for manufacturing and assembly tasks by analyzing schematics


Illustration

According to market participants Process Master Control is one of the most important levers to increase labor and capex efficiency

Source: Interviews, desk research, picture on top: Mycronic – Photographer Magnus Elgquis, second from top: Bosch Rexroth, Roland Berger

Process master control system

SMT Line 1

Flying probe tester 2

Dispensing system 1

Assembly station 7

Process master control

"The process master control system assures that each product moves through all process steps in the right order. It thereby reduces the risk of errors and enables us to process different products at the same workstation simultaneously"

Tier-3 EMS player

"A process master control system enables us to handle the complexity of workshop-based production in the back-end and significantly increases the capex utilization in low volume environments"

I4.0 maturity leading Tier-2 EMS player

"The ability to pool operators across several SMT lines instead of assigning them to a certain line would enable us to further reduce the labor intensity of our production process – This requires a system that flexibly assigns tasks to operators according to their priority"

Tier-3 EMS player

Program provisioning

Step by step work instructions

Transportation routes

Machine operator tasks


Illustration

Future Production Scheduling Systems need to be cross-vendor compatible to achieve full impact

Production scheduling


Job 1

Production plan

A B C D

Job 1

AJob 2

B

Job 3

C

Job 4

D

A BJob 2

C D

Line 1

Job 2

Line 2

Job 1 Job 2

Line 1

Job 1

Line 2

Job 2

Equip. 1

A1 A2

Equip. 2

A3

Equip. 1

A1

Equip. 2

A2 A3

Grouping production orders with feeder setup

Optimal assignment of jobs to lines to maximize line performance

Optimal assignment of pick & place tasks to different machines

High-level planning of products

"Production scheduling in SMT is quite complex since production and changeover times are highly depended on the specific machine/feeder setup – Finding the optimum between production time and changeover time is key to increase equipment utilization"

Tier-3 EMS player

"Most market solutions currently focus on specific parts of the scheduling problem, while true multivariate optimization is difficult it would be a significant improvement"

Tier-2 EMS player

"There is a large potential in optimizing the production schedule across lines from different machine vendors, however, third-party solutions can only approximate the machine behavior and usually underperform the solutions from machine manufacturers"

Tier-2 EMS player


Illustration

Systems visualizing KPIs, proposing recommendations or auto-matically improving processes will penetrate the market quickly

Machine/line performance optimization

Source: Interviews, desk research, picture: Mikroelektronika, Roland Berger

Level 1 Visualization of process parameters

Level 2 Advances analytics and recommendations

Level 3 Process Feedback

Level 1 Level 2 Level 3

OK?

"Visualization of process parameters like the OEE is a simple method to increase transparency and improve the overall manufacturing efficiency – Therefore this is standard in our plants"

Tier-3 EMS player

"While analyzing data with basic statistical methods can significantly help operators in fine tuning machine parameters in the NPI process, new algorithms like machine learning will bring this to the next level"

Tier-2 EMS player

"In the future machine parameters will be automatically optimized based on data without the need of human experts – Feedback loops are already the first step into this direction"

Industry Expert


Nanotronics combines nanoscale imaging with artificial intelligence to create automated defect detecting microscopes

Machine/line performance optimization

Source: Nanotronics, desk research, Roland Berger

> Manual inspection times: 30 min to look at 50 chips

> Manual inspection often error prone> Learning via data sharing limited

Current process

> Nanotronics microscopes can analyze up to 100,000 chips/min

> Automatic error and defect detection with feedback loop

> Article Intelligence (AI) software to detect new error types and improve inspection algorithms

Nanotronics solution

AI to identify new error types

AI to improve detection algorithms

Automatic optical detection

Integration via SECS/GEM

Conventional error reporting

Product offering – Wafer quality inspection

Founded 2010

Headquarters New York, NY

Revenue[2016, USD m]

n/a

Funding [USD m]

30.0 Series D, Oct 2017

Board of directors containsPeter Thiel, Beth Comstock, Jaan Tallinn

Data repository

Manual inspection stations

Inspiration story


Prediction algorithms using big data

Database containing historic & future equipment data

The predictive maintenance offering is currently still limited – Many new players entering the field



Illustration"The predictive maintenance offering by machine manufacturers is currently quite limited – We had to develop our own solution for our electrical testing equipment"

Tier-3 EMS player

"Analyzing machine behavior and failures is not only providing value to operators, it is also key for future machine development and can provide a significant competitive advantage to machine suppliers"

Equipment manufacturers

"While machine manufacturers have a key advantage in predictive maintenance, many new players are still entering this field"

Industry Expert

Pick & place

Oven

Asset performance management

Dispenser

Robot Machine

Plant m – EMS 1

Plant n – EMS 1

Machine Machine Machine

Asset performance management

Machine Machine


Cassantec offers enhanced analytics solutions using basic sensors that are already included by the manufacturer at point of sales


Source: Cassantec, desk research, Roland Berger

Alert / Alarmfor immediate response

Monitoring

> Vibration, ultrasonic, infrared etc. sensors & devices

> Software for data illustration, mapping, projection, trending

> Lubricant, vanish and filter debris lab services

Insightfor work orders

Diagnostic

> Advanced software based on equipment-specific models

> Specialized consultants, field technicians interpreting results

> Experts making predictions ("predictive analytics")

Prognosis

> Objective, condition-based info on remaining life (RUL)

> Computed risk profiles over a significant, future time horizon

> Online solution utilizing data and functions already available

Foresightfor long-term planning

Founded 2007

Headquarters Zurich, Switzerland

Revenue[2016, USD m]

n/a

Funding [USD m]

n/a

Collaborations with leading international research institutions as Stanford, RWTH Aachen and EPFL Lausanne

Product offering – Predictive maintenance on long-term horizon

Inspiration story

E. A one-way road?


Not much can be seen vice versa – Electronics Assembly is still way back in Industry 4.0 maturity from Semiconductors and FPD

Industry 4.0 maturity in different industries

Source: Interviews, Roland Berger

Indicative

Scale of production

Batch size one production vs. mass production

Degree of customization

High levels of customization vs. standardization

Capital intensiveness

High capital intensiveness in production vs. low capital intensiveness

Production discreteness

Discrete production vs. process production

Drivers

Low maturity High maturity

Surface-mount

technology

Semi-conductor

manufacturingFlat panel manu-

facturing

Maturity level

F. Summary


Summary: Electronics Assembly on its way towards Industry 4.0 can learn a lot from Semiconductors – Especially in the SW domain

Industry 4.0 scope comprises entire businesses. I4.0 driven by technology, demand, and competitive trends will have strong impact on factory automation in Electronics Assembly

In the Electronics Assembly industry we found ~ 20 potential technology building blocks for Industry 4.0. Most of this market is yet immature. Even EMS leaders still have half the way to go towards Industry 4.0

Electronics Assembly can learn from Semiconductors especially in Software

> Unlike Semiconductors, different machine interface standards are used in Electronics Assembly – SECS/GEM has no "godfather"

> Material handling, QM systems, and Dfx tools are the mostly explored I4.0 SW technology building blocks today

> Within the next years, accelerating I4.0 adoptions will foster Process Control and Asset Performance Management SW

Not much learning can be seen vice versa

The overall ~EUR 430 bn Electronics Assembly market is flat – Industry 4.0 will help extending service offerings & service quality


Your contacts for further information regarding SMT 4.0

[email protected]

[email protected]

Dr. Michael

AlexanderJonas

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