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Foreword

− Introduction of SME Development Fund (SDF) − Introduction of project : Hong Kong foundation

industry towards “Industry 4.0” Editorial Board and Disclaimer Organizer and support organization

Table of contents

Short-Mid-Term Strategic Upgrade Mapping Section One: Upgrade mappings by Smart Dimensions

− Smart Products − Smart Processes − Smart Networks and supply chains − Smart Production − Digital Business Models

Section Two: Recommendations

− Solutions for common applications

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− Innovation readiness − Research for Hong Kong-specific advanced

applications

− Fundamentals for higher maturities − Promoting industry as a career − Infrastructure for leveraging Hong Kong's

unique position − From demonstrator to use-case: Learning in real

settings

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Foreword

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Introduction of SME Development Fund (SDF)

The Hong Kong Special Administrative Region Government established the SME Development Support Fund in 2001 to subsidize projects that will enhance the competitiveness of Hong Kong SMEs as a whole or in particular industries. The SME Development Support Fund aims to support non-distributed profit support organizations, business organizations, professional bodies and research institutes to implement projects which will enhance the competitiveness of SMEs in Hong Kong as a whole or their respective industries. SMEs in Hong Kong can apply and be suitable for the following institutions: A) Supporting organizations, business organizations, professional bodies and research institutions that do not distribute profits*; B) The applicant institution shall be a statutory body or an institution registered under the laws of the Hong Kong Special Administrative Region; * "Non-distributed profits" institutions/organizations are organizations/organizations that do not distribute

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bonuses to their directors, shareholders, employees or any person. Applicants may receive up to $5 million in funding or 90% of the project's funding for each approved project (whichever is lower). The balance must be borne by the applicant in cash, in kind, or by other sponsors. The SME Development Fund (SDF) and the Organization Support Programme under the Dedicated Fund on Branding, Upgrading and Domestic Sales (BUD(OSP)) have been merged to form the TSF with effect from 1 October 2018. TSF provides financial support to projects which aim at enhancing the competitiveness of non-listed Hong Kong enterprises in general or in specific sectors, including assisting them in developing any markets. For inquiries, please contact the Trade and Industry Department ("TID") for the Application Form and Guide to Application. Hong Kong Federation of Innovative Technologies and Manufacturing Industries (“FITMI”) has been funded by the "SME Development Support Fund" of the Trade and Industry Department of the Government of the Hong Kong Special Administrative Region. The Hong Kong Productivity Council has implemented the

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project to promote the implementation of Industry 4.0 for SMEs in Hong Kong. In this project, “Short-Mid-Term Strategic Upgrade Mapping,” developing a “Sector-specific Industry 4.0 Benchmarking Model” and a “Sector-specific practical implementation guideline” will be developed to assist HKSMEs of four Industries sectors to migrate their legacy manufacturing operation and production into Industry 4.0 gradually. In order to provide a robust reference protocol to assist them in riding on this new management and manufacturing concept, the information and standard are important to assist them in mastering the know-how of step-by-step realization towards Industry 4.0. Introduction of project: Hong Kong foundation industry towards “Industry 4.0” In the face of the increasing number of overseas customers who are implementing "Industry 4.0", Hong Kong companies as suppliers must also upgrade to "Industry 4.0" in order to remain competitive in the international market. To help Hong Kong SMEs move forward and implement "Industry 4.0", the Hong Kong

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Federation of Creative Technology and Manufacturing Industries (FITMI) has partnered with the HKPC to launch a three-year "Hong Kong Basic Industry into Industry 4.0". "Deployment Plan" to promote the upgrading and transformation of Hong Kong's industrial sector and enhance its competitive edge. The "Plan" is funded by the Industry and Trade Administration's "SME Development Support Fund." The "Industry 4.0" team of the HKPC will work with international experts to conduct an in-depth analysis of the current situation of the Hong Kong industry and deploy new services. The model develops a blueprint for the short- and medium-term strategy upgrade and prepares an industry implementation guide for Industry 4.0 to provide a step-by-step and feasible upgrade for local infrastructure industries. The "Plan" is supported by more than 20 chambers of commerce and will implement "Industry 4.0" through the three significant trilogy industries, plastics, electronics, metals, and machinery. The "Plan" trilogy: Enterprise on-site assessment, preparation of three industry guides of different natures, the publication of research results in various seminars and workshops, and sharing of experience with the industry.

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Three industry guides provide a multi-angle "Industry 4.0" upgrade reference: "Industry 4.0 Benchmarking Guidelines" for objective and systematic assessment criteria and models for Hong Kong companies, covering product development, sales, procurement, production, quality management , logistics and services, and other important operational areas; "Industry 4.0 deployment medium and short-term strategic upgrade blueprint" introduces the analysis of the overall maturity of Hong Kong enterprises; and "Industry 4.0 implementation of industry design and implementation of industry guidelines and case studies" is detailed Introduce the "Industry 4.0 Implementation Plan", including technology, hardware, software, management concepts, procurement solutions, cost budgeting, and business benefits. For HKSMEs, it is necessary to have knowledge and technique to implement industry 4.0 at different levels of adoption and company status. While the proposed upfront knowledge and know-how transfer programmes for four sectors will be the trump card to maintain their qualified suppliers status and act as the catalysis to boost the overall technological and unique

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position of HKSMEs in the global industrial arena, and hence, Hong Kong industry as a whole.

"Hong Kong foundation industry towards "Industry 4.0" deployment project" was officially launched. The guests included (from left): Dr. Lawrence Cheung, Director of Technology Development, HKPC, Li Yuen Fat, Chairman of FITMI, and Toni Drescher, Head of Fraunhofer IPT, Germany. The process of Hong Kong enterprises moving towards "Industry 4.0" has just started. Most of the enterprises are still in the stage of industrial 2.0 to 3.0, that is, labor-intensive production and application of automation equipment for mass production. There is no single method or technology for the implementation of "Industry 4.0".

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The industry must develop appropriate routes and strategies in accordance with the nature of its business and the degree of development. "Industry 4.0". Companies are advised to "listen and see more", understand their capabilities and customer needs firstly, and then develop an "Industry 4.0" development blueprint. The Hong Kong industry is now in need of absorbing more "Industry 4.0" information to tie in with the assistance of the Government, experts and partners, and to formulate an overall development blueprint based on its actual situation.

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Editorial Board and Disclaimer Publication: Hong Kong Productivity Council Productivity Building, 78 Tat Chee Avenue, Kowloon, Hong Kong Copyright: Hong Kong Federation of Innovation, Technology and Manufacturing Federation Hong Kong Productivity Council The project is organized by the Hong Kong Federation of Innovation, Technology and Manufacturing Industries. The Hong Kong Productivity Council is responsible for implementation and is funded by the SME Development Support Fund of the Trade and Industry Department of the Government of the Hong Kong Special Administrative Region. Any opinions, research findings, conclusions or recommendations expressed in this publication / in the event (or members of the project team) do not represent the Hong Kong Special Administrative Region Government, the Trade and Industry Department or the SME Development Support Fund and the development of brands, upgrading and expansion The

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opinion of the special fund (institutional support plan) review committee of the domestic market. The information in this report is for reference only. Although the content has been tried to be precise, neither the publisher nor the organization involved in the project is responsible for the negligence of the information provided or any loss caused thereby. Copyright may not be reproduced All rights reserved. No person may use any electronic or mechanical technology without the consent of the publisher. And other methods of reprinting or using the information in this report, including photocopying, recording, and placing the information into any form of information storage or reading system.

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Organizer and supporting organization

Organizer:

Implementation organization:

Funding for the SME Development Fund:

Any opinions, findings, conclusions or recommendations

expressed in this material/event (or by members of the Project

team) do not reflect the views of the Government of the Hong

Kong Special Administrative Region, Trade and Industry

Department or the Vetting Committee of the SME

Development Fund and the Dedicated Fund on Branding,

Upgrading and Domestic Sales (Organisation Support

Programme).

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Supporting organizations (in no particular order):

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Supporting organizations (in no particular order):

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“Short-Mid-Term Strategic Upgrade Mapping”

Section ONE:

Insights from

survey

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The survey analyzes current status of the manufacturing industry

in HK. Over 20 SME’s have been consulted and helped to migrate

towards in I 4.0 within the project. Industries from the area of

metal, electronics, plastics and machinery equipment have been

contemplated, the maturity level of each company, and on

average of the HK Industry. On basis of the maturity level,

recommendations have been derived and formulated for

support the upgrade of the HK Industry. Following insights have

been derived:

The strength, weaknesses opportunities and threats,

SWOT Analysis, of current manufacturers from HK and

Outline the current Industrie 4.0 Maturity and thereby

explain shortcomings of the industry and gaps-to-be-

closed

SWOT ANALYSIS

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Figure 1: SWOT of HK Industry

The strength of the HK Manufacturing Industry lies in

the willingness and mindset in adopting I 4.0 methods

and technologies. These are best practices from

international lighthouses that are adapted to the

specifics of the HK Industry. Most of the management

of the SME’s from HK understand the concept of I 4.0

and see the need to transform the company. Foremost,

the digitization is understood as a tool to optimize

current production operation. However, a holistic

understanding of I 4.0 such as the value of

supplementing traditional businesses by digital

business and service models is yet a new concept for

most top-levels.

§ HK Industries show mindset for

improvement of operations by methods and

technologies from Industry 4.0

§ Early adopters understand Industry 4.0 and

and see the need for transformation in

strategy and organization departments

Strength Weakness

Opportunity Threat

§ Processes are not digitalized by software

tools, thus, limiting vertical and/or

horizontal integration

§ Missing data transparency and reliability

(availability, status, utilization) of the

production resources of machines and tools

§ Transparency in operation by making

process steps and machine status visible

§ Improvements of operations by

standardization/digitalisation of processes

and application of data analytics

§ Insufficient capabilities and talent shortage

to develop smart machines/equipment and

Industry 4.0 Infrastructure

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Major opportunities for manufacturers lie in facilitating

transparency in operations and establishing an

environment of continuous learning and improvement.

Particularly in logistics and manufacturing, classic KPI’s

help to improve operations. In combiniation with

Industry 4.0 these KPI’s can be generated in real-time

by IIoT sensor and IT infrastructures. Logistics and

production processes can become transparent and

improved continuously. Furthermore, manufacturing

processes can be standardized and optimized by lean

principles. The streamlining of processes can be

supported by real-time data originating from a vertical

and horizontal integrated tool chain.

Today, operations of manufacturing companies are not

fully digitalized and lack the application of standard

digital tools. Software tools for a vertical integration

such as Manufacturing Executing Systems (MES),

Advanced Planning and Scheduling Tools (APS) as well

as the integration by a corresponding IT infrastructure

for handling a vast amount of data are not established

yet. The horizontal integration with IT Systems of

customers and/or vendors does not exist yet. Due to

the limited digitization of processes, transparency of

production has not been reached and improvements

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cannot be driven based on real-time data analytics. This

also means machine and shop floor status (i. e.

availability or failure states of machines) are not

digitally recorded and/or analyzed by production

personnel. Historic data are not analyzed and used to

improve operations in SMEs.

In addition, manufacturing companies lack human resources and capabilities in I 4.0. Digital talents are difficult to acquire especially due to talent shortage in HK. Among others, following capabilities need to be developed and/or acquired by HK manufacturers:

Hands-on experience and knowledge about digital tools and application in operations, especially production and logistics

IT-Knowledge of dealing with vast amount of data and setting up and integrating a vertical and horizontal IT Infrastructure

Capabilities in data analytics for analyzing production data, both on planning as well as machine level

Combining operation/process knowledge with analytics methods and models for continuous improvement

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INDUSTRIE 4.0 MATURITY The I 4.0 Maturity of the HK Industry has been determined based

on the maturity model and methodology outlined in Book 1

„Sector-Specific Industry 4.0 Benchmarking Models“. For each

smart dimensions, the maturity of the HK industry in average is

derived and the best/worst case limits are outlined (figure 2).

Following insights are deduced and detailed in the upcoming

paragraphs:

Figure 2: Maturity Scoring

Smart Products and Services (former: Smart Solutions)

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The HK Industry produces a portfolio of products for its national and internal customers. Most products are of physical nature, predominantly from a mechanical or electrical discipline. Service models are hardly offered to customers. Beyond singular parts/technologies, some products integrate mechanical and electrical components. There are first steps to a mechatronic product integrating mechanical, electrical and software components. However, fully CPS-based or Industry 4.0 Product with a high component of IT and data analytics capabilities do not exist yet. Some of the HK products, especially for the machinery industry offer services on-top. These are mainly after-sales services, maintenance or updates of the software. Nevertheless, digital business models are not used or applied or common yet. For the machinery industry it can be stated that sensor systems are used for data gathering, process improvements and additional information for the user. Also, human-machine-interfaces are used to interact with the user. However, none of the surveyed companies use data for processing, analyzing user interaction with the products and/or monitoring the conditions and performance along the life cycle. Data-based analytics

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and decision-making is not used for improving customer experience or offer additional services. Smart Processes (former: Smart Innovation) HK Industries follow a classic project management approach in engineering and/or production. Processes are planned before-hand, are separated in stages while each stage is controlled by quality gates. Industrial or applied research with cooperation partners such as applied research centers is hardly conducted. The development capabilities of manufacturers both in product knowledge as well as in production equipment are limited. If development departments exist, then these have standardized and discipline-specific software tools with limited exchange formats. The product life cycle in not digitized and often omits proper digital tools for project management, cost estimation and variance management. Lean principles are hardly applied in development and production leading to inefficiency, waste and limited learning capabilities. Whilst first approaches of lean manufacturing exist, the lean principle is not extended to development yet. Since most of the manufacturers follow an OEM business model, customer driven innovation processes are yet missing. None of the SME apply state-of-the-art

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development methodologies such as agile development. Furthermore, processes are not fully digitized (i. e. ideation, prototyping, development, launch) leading to mostly island solutions. Data-driven innovation based on analytics of internal and external data are yet missing (such as usage profile/information about the customer). Smart Networks (former: Smart Supply Chain) Most of the Hong Kong Industry track and trace the material flow. Most of the manufacturers base the material flow on best practices or experience, some use Auto-ID Technologies such as QR Codes. Warehouses are often supported by computer systems and inventory is registered digitally. However, these processes are often conducted by manual input (Scanning of QR-Codes). Lean principles are not fully applied such as value stream mapping or material pull. This leads to overstocks and chaotic material storages as well as inefficient in-production stocks. None of the manufacturers uses advanced data analytics technologies for predicting good consumption or supplier categorization or lead-time optimization. Data are either not sufficiently gathered, or when

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acquired, are inconsistent or not reliable due to manual inputs. Material flow simulations for optimization of the supply chain are not used leading to inefficiency in the shop floor. There is no digital interface to supplier and/or customers for an instant exchange of logistics data. Thus, a digital horizontal integration is missing for optimizing supply chain networks. Smart Production Most manufacturers divide tasks according to skill set/level of worker. Parallel lines are standardized and partially automated (reasonable automation of simple logistic/assembly steps). More than half of the manufacturers partially implemented lean principle (5S, Pull Principle, etc.). Key Performance Indicators are often defined on paper but lack support by real-time digital sensor data. Some of the KPI’s are not based on international standards, but are rather individually defined by the company’s operation management. Often production machines are not connected and overall processes are not visualized by usage of sensor or IIoT technologies. HK Manufacturers are not digitized vertically or horizontally. Real-Time data are

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not acquired and not centrally stored and/or processed for manufacturing optimization/ improvement. Product orders and configurations are not automatically processed, planned or executed on production floors. Mostly manual labor and input/conversion of information is necessary. The production is not yet autonomous and cannot be optimized by real-time data analytics technologies or methods. Digital Business Models The business model of the HK Manufacturer is well defined and communicated across the company and organisation. Owners, management and employees are aware of the current business processes and model. Customers have the possibility to individualize the product they order. Most of the manufacturers are contract-based OEMs. They are challenged by an increasing low volume order and high variance mix. Despite the growing importance, current operations are not transparent due to missing data acquisition strategies and technologies. The operations are not measured in real-time omitting major improvements in operation efficiency as well in revenue gains based on digital business models.

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Most of the manufacturers do not collect data about the customer and/or use data for monetization purposes (i. e. sales or profitability improvement). Furthermore, opportunities of business model innovation is unknown for the manufacturing industry. In addition, workflows are hardly automated and decision making activities are based on experience and do not use algorithms or data analytics techniques. Strategy and Organization Most of Hong Kong’s producing companies are contract-based manufacturers with an OEM Business Model. Some manufacturers have started Industry 4.0 pilot projects, thus, acquiring first hands-on experience with state-of-the-art methods and technologies. However, a holistic digitalization strategy from top-management to the shop floor workers does not exist yet. The computerization of processes are often seen by management as of lower importance than the actual physical production. Industry 4.0 is mostly often not included in the strategic planning of SMEs. Culture/ Mindset, Information Systems and Resources Manufacturers from Hong Kong are aware of the opportunities of Industry 4.0. The SME top-

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management have a willingness to drive Industry 4.0 – with main focus on practical and prompt return-on-invests projects. However, strategic and project implications unique with Industry 4.0 are not yet fully understood by SMEs. Agile and iterative I 4.0 implementation projects with a measuring, modelling and analyzing the sensor-based process data cycle are needed. Despite the high interest in Industry 4.0, its application is generally accepted for logistics and production department but not fully understood as a means for improving the entire company holistically in all departments.

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SMART PRODUCTS Smart Products refers to products that incorporate the

technical principles of Industry 4.0 such as sensor integration,

connectivity, data analytics for predictability, and context-

sensitive adaptability. Smart products have the ability to

connect with other smart products and/or their environment.

The upgrade options relevant to a company depend strongly on

the value the company wants to realize with the digitalization.

The use of Smart Innovation principles is vital for making the

success of a smart product possible. Smart, connected products

(like smartphones, smart watches, modern massively

connected cars, …) have massively disrupted traditional

products and brought about some of the most valuable

corporations and start-ups in the market. On the other hand, it

is all too easy to drive up the price of a product by adding smart

technology where it is not needed. As a result, the trend to

smart products has been misinterpreted to “add sensors and

connectivity to everything”, and a large number of smart

connected products exist without real benefits. Furthermore,

User experience is a key factor for product acceptance and

determines success. This can be seen in failed products in the

market due to high complexity in usage despite clear functional

benefits for customers.

As a result, to choose the right upgrade options for making

smart products, companies should first clearly outline the

strategy they want to implement by making smart products

(Why?). Main benefits of smart products are:

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They can be individualized to customer requests via

software or remotely, reducing the need to change

hardware for individualization requests

They feedback relevant data to development processes

in order to improve the next generation of the product

based on actual usage data instead of simulations and

surveys, therefore making it more likely to hit market

demand and finding technical optimizations which are

not easy to find with simulations.

They integrate into smart ecosystems such as Smart

Home or Smart City infrastructures to connect and

interact with other physical smart products and virtual

smart services around them, therefore being more

valuable to the customer than stand-alone products

They bring the possibility to offer value-added smart

services around the product thereby generating

revenue not only from physical product sales but from

aftermarket services in a digital and scalable form

Smart innovation can be used to find out which customer pains

should be addressed by adding what functionalities (What?)

and the user experience necessary to ensure that the product is

usable and liked by the target customers (How?). These steps

should be done repeatedly (some of the most successful

products on the market have been developed in hundreds of

such iterations), and in as small steps as possible, while getting

continuous market feedback.

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While of the considered industries electronics and machinery

components lend themselves best to integration of smart

technologies, special plastics and metal applications such as

toys and certain household goods can also directly benefit from

these approaches. In these cases, for plastics and metal

applications, an electronics unit providing the functionality

needs to be placed in the product, ranging from a small “tag”-

like device to a full Input/Output module with sensor and actor

connections in the product.

The following upgrade options are patterns for common

functionalities realized – after careful customer use-case

development – for smart products:

Figure 3: Roadmap for Smart Products

1i - Visibility Product state

Goal Roadmap

Product state

Product usage analytics

Predictive maintenance

Enhance product function by adding smart technology

0 1i 2i 3i

Adapting to changing situation

4i

Perceive environment

Access external data

Distinguish and authorize users

Condition monitoring

Provide interfaces

Integrate with systems/ persons/ platforms

Predicting user needs

Enable new services and marketing channels around products

For any services, products

usually need to be offered with an own

brand

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By integrating communications devices, it is possible to

communicate product state back to the vendor. This enables

new business models such as pay-per-hour, but also enables

generating statistics. This upgrade option is very common in

electronics, where anyway power and connectivity are

provided, but can also be used for machinery or household

devices. This option needs communications interfaces to the

Internet (e.g., WIFI or a mobile network adapter) and

connection to the product’s own electronics. Furthermore, a

(possibly cloud-based) back-end system to register the state

information is needed.

Perceive environment

Adding sensors to perceive environmental conditions (Is a user

present? Is there danger?) is a common way to improve safety

and energy efficiency in smart devices. If the specific conditions

to perceive are known in advance, it can usually be done

simpler than the default option of using cameras and image

recognition. Often, simple proximity sensors or other stock

sensors can fulfil most functions as well. This is very common in

machinery, and common in electronics. It could also add value

in toys. This option needs suitable sensors and control logics, as

well as a means to output required information either via

connectivity to a network, or by integration of actors or signals.

Access external data

Some products benefit from having a link to outside data where

they can get information for their operation. This can range

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from checking the weather or online databases to getting

updates and daily greetings, and is applicable for electronics

and machinery. It may also be applicable to toys and household

devices. A connectivity module to the Internet is needed, and a

link to an API containing the relevant data. However, it is not

necessarily needed to have an own back-end if the required

data is publicly available (like weather or traffic information).

Distinguish and authorize users

Products with complex user preferences or with safety- or

security-critical components benefit from user identification.

This is common in machinery and electronics. Users can be

identified using anything from selection from a list,

username/password or PIN entry, or biometric features. This

needs an input/output module of some form or biometric

sensors, as well as a processing unit storing user profiles and

reacting to use by different users. Internet connection can help

to reuse user profiles or information from cloud services, which

is often more user friendly.

2i - Transparency Product usage analytics

Analyzing how people use a product can help identify sales

potentials and deliver better and more individualized service to

customers. This applies to electronics, but can also apply to

machinery and toys or household devices. Very basic analytics

can be done within a product (for instance when having text

entry, learning the writing style of a user to make text entry

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faster, or learning the most used functions of a user to optimize

menu screens for them) but more sophisticated analytics

require a back-end platform for devices to connect to. Next to

input/output capability, for some applications like voice or

image recognition, sufficient computing power in the product is

needed.

Condition monitoring

Monitoring the condition of a product allows for better

maintenance or replacement scheduling and allows to offer

services around the product. It is common in machinery, more

expensive household electronics and cars, as well as

consumables. Sensor integration to measure the condition of

the product is needed, although in some instances simple usage

counters or timers suffice for basic functionality. A

maintenance model for the product needs to be made before,

and for best results should be continuously updated based on

real data, for which the product needs internet connection and

a back-end service.

Provide interfaces

Many products provide data or functionality which can be used

to realize things the product manufacturer did not think of, but

which adds to their value. The prime example are smartphones,

which are only as valuable as they are due to sophisticated app

stores bringing the innovation of millions of developers to

every device. However, any product can provide an API, either

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through direct communication or via a cloud back-end, and let

other developers leverage the functions of the product.

Integrate with systems/persons/platforms

The value of connected products rises above proportion to the

number of other devices they connect to in a simple way.

Integration within product ecosystems such as Smart Home or

Smart City systems is most prevalent in infrastructure goods,

but developing in home electronics and machinery. Support of

multiple standards and protocols is usually key for being able to

address large enough markets. The product can also function as

an adapter between different systems, in which case often

multiple communications interfaces are needed.

3i - Predictability Predictive Maintenance

Taking condition monitoring one step further by not only

reacting to maintenance or replacement need but predicting it

based on condition and usage patterns can offer interesting

service business models such as pay-by-use. This is now

common in machinery and possible for electronics and

consumables. Next to functioning condition monitoring, it

requires usage analysis and extrapolation of trends.

Predicting user needs

Similarly, identification of user needs can be taken one step

further by predicting user needs. For instance, very targeted

advertisement or recommendation (e.g. of movies or music) is

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possible in this case. This is possible in electronics. It requires

usage data analysis and a back-end system to correlate needs

of many users to analyze and predict suitable

recommendations.

4i - Adaptability Adapting to changing situation

This level is currently only seen in smartphones which e.g. are

able to react to traffic changes and change schedules semi-

automatically given the current position of the user. To realize

this, extensive connection to other devices, data sources and

ecosystems is needed as well as a strong back-end with strong

analytics functionalities.

SMART PROCESSES

Smart processes encompass both classic business

processes

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SMART NETWORKS AND SUPPLY CHAINS

Smart networks and supply chains refer to the use of

“horizontal integration”, the integration of data and digital

services along the whole value chain, including to suppliers,

customers, and other value partners. Given that Hong Kong

Manufacturers operate on very short lead times to their

customers, but particular products (including critical electronics

components) have high lead times and possibly allocation

markets, high capabilities of forecasting demand and supply as

well as tracking and tracing capabilities are needed to avoid

high inventory costs through too high safety stocks.

The main roadmapping activity needed is increasing transparency over the supply chain

Figure 4: Roadmap for Smart Networks

0i – Connectivity

SRM deployment

Using computer systems to track supplier performance directly

connected to EPR and manufacturing systems.

Goal Roadmap

SRM introduction

Supplier reliability

measurement

Demand forecasting

Predictive procurement

Reducing inventory levels by increasing transparency over the supply chain

0 1i 2i 3i 4i

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1i – Visibility

Supplier reliability measurement

Using quality and delivery performance data not only in

periodic supplier evaluations, but in real-time for assessing

current delivery and capacity situations. This is relevant for

companies with unreliable or high lead-time supplier systems

when needing to commit to delivery dates towards a customer

2i – Transparency

Demand forecasting

Using customer-provided demand forecasts fusioned with data such as macroeconomic trends or market size estimation to forecast overall demand for product groups more accurately than is possible for a single customer. This is relevant for all manufacturers in OEM business who need to ensure low lead times and have to maintain (and finance) safety stocks.

3i – Predictability

Predictive procurement / supply chain for C-parts and long-

lead-time parts

By integrating data throughout the supply chain (demand forecast, supplier risks, production capacities, other orders),

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SMART PRODUCTION

Smart production refers to the use of Industry 4.0 principles

directly in production units. In Hong Kong industry, it is evident

that there are still many manual tasks which can reasonably be

automated (e.g., feeding of materials and retrieval of products

from machines

0i – Connectivity Digitalization of remaining paper-based processes

ERP-MES integration

Warehouse-production integration

1i – Visibility KPI dashboards

OEE measurement in real-time

Machine IoT connection

2i – Transparency Condition monitoring

Quality root-cause analysis

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Data-driven continuous improvement

Collaboration platforms

Dynamic production planning optimization

3i – Predictability Predictive Quality control

Predictive maintenance

Individual worker support and training

4i – Adaptability Collaborative systems

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DIGITAL BUSINESS MODELS In order to benefit from digital business models, a company

needs to have end-customer touchpoints. (Here, end-

customers can be in the B2B and B2C sectors, but need to be

the actual users of the product) Such touchpoints can be

established by the vendor of the product as well as by

component manufacturers in specific industry sectors

(automotive, high-end computing, machinery) if they have a

very well-known brand.

Customer touchpoints can be before the product is sold

(websites etc.) or during the use of the product (user profiles,

configuration sites, accessory shops, …).

As most smart services operate as a “winner takes it all” model,

in order to offer additional services to consumers via a

customer touchpoint it helps strongly to have a lever of data or

access which cannot be replicated. Otherwise many services

will simply be replaced by more general-purpose apps or even

free derivatives. These levers include access to large amounts

of data from all products in the field (such as data from all

devices of a type) which can be used to derive preferences and

optimize use through data analytics, leveraging knowledge and

data of many users to provide better experience (usually via an

online platform), or integrating heterogeneous systems too

complex to master otherwise. Finally, exposing an API to allow

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others to innovate on top of a product or even component

(such as an operating system or chip) can also provide a major

lever for offering non-replaceable smart services (Figure 5)

Figure 5: Leverages enabling to build meaningful platforms for smart services

Next to end-consumer oriented digital business models, there are also attractive digital business models in the B2B sector. Such business models either componentize special knowledge of the supplier (e.g., offering ready design modules to be put together in an online configurator) or orchestrate a supply chain in the form of a platform like Alibaba. The latter case either needs massive scale or a niche market with very specialized requirements as otherwise major platforms can use their advantage of offering broader services to out-compete smaller niche platforms. Markets like construction, specialized electronics but also specialized injection molding (with more

Possible exploitation of

many data points?like e.g. Rolls Royce Engine

Health Management

Possible leverage

due to many users?like e.g. Amazon

Possible leverage by using many

suppliers and innovators?like e.g. Google PlayStore

New service levers

enabled through the use of

smart technologies?

Possible exploitation of

heterogeneous systems?like e.g. IFTTT

Possible reduction of initial

customer investment? (e.g. Software as a Service)

Service levers known from

cloud service models

Possible reduction

of utilization barriers? (e.g. Knowledge as a Service)

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than simple geometries) could be suitable for special-purpose industry platforms.

0i - Connectivity

Customer touchpoint establishment

Hong Kong industry in the considered sectors is currently mostly lacking end-customer touchpoints. Thus, there is no direct channel to contact the customer for using digital business models or for direct collection of customer data which can be marketed in two-sided platform business models. For any company which wants to benefit from end-consumer oriented digital business models, the first general recommendation needs to be to build up own end-customer touchpoints through establishing own brands and digital sales channels around it. This will be most relevant for consumer goods industries such as electronics or toys.

Specialty B2B online sales services

For companies operating as process experts (e.g., form and die making, injection molding, EMS, …) offering online sales can be a basis to interact in an efficient way with new types of customers such as start-ups, individual “makers”, R&D units of companies not used to these processes, etc. While these customers offer higher price per component. However, these customers require additional information and support to

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successfully use such services, which can in turn be monetized in more advanced business models.

1i – Visibility

Supply chain optimization based on demand visibility

Based on data observed from products, needs can be identified. This can include when replacement parts will be needed in certain areas for given products , or when products are likely to be sold. Based on this information, value chains can be optimized and targeted advertisements made.

Integration of value-added services into B2B digital sales

channel

On the B2B side, monitored online platforms with integrated support of inexperienced customers can be implemented. This includes the tool and die making industries and injection molding industry as well as EMS. Integrated services can include libraries of ready-made design components, integration of value-added services (such as design optimization) through the digital channel etc.

2i – Transparency Understanding latent customer needs

By analyzing data from products, manufacturers can learn about shortcomings of products (such as when “back” buttons are pressed very often it indicates that functions are not

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properly understood by users) or latent needs (if functions are emulated in crude ways by users with available functionality). This creates the potential for building further USPs in the next product generation.

Supplier orchestration / specialty platform In certain niche sectors online marketplaces are not yet strongly developed. B2B customers unfamiliar with a field have problems finding the right suppliers and ordering products for small volumes, even in traditional OEM business. For such products (such as specialized electronics/IoT devices), online platforms linking together suppliers in the same way as Alibaba or Amazon do for simple products, but with added domain know-how and service orchestration, can prove very profitable.

3i – Predictability Demand prediction

Customers get a notice if it is expected they need supplies of e.g., a consumable based on historic demand and analytics. They may also have a service level agreement so that the manufacturer agrees to keep them stocked with relevant goods, but unlike the 4i business model anticipatory shipping, no separate but automatically initiated billing takes place.

“Power-by-the-hour”

Advanced monitoring functionalities, predictive analytics and a well-developed logistics network allow to switch business

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models from selling the product to selling its availability (a common business model e.g. for jet engines, which are in many cases paid by unit of thrust instead of a lump payment). This makes sense for maintenance-intensive products in tightly packed customer areas. In Hong Kong, this can very well be imagined for commercial appliances, mobility, and construction services.

4i – Adaptability Anticipatory shipping

This still rarely-seen business model uses prediction not only for making internal arrangements in supply chains or sending reminders to customers, but to actually ship the goods for which a need is anticipated. Billing is either done if the customer does not send the good back to the manufacturer (which has a higher threshold of convincing customers for this model) or by digitally registering when the shipped product is first used.

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Section TWO:

Recommend-

ations

By observing the industry landscape in manufacturing SMEs in

Hong Kong, we have developed the following eight overall

recommendations for ensuring a highly productive pick-up of

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Industry 4.0 concepts by Hong Kong industry, and for ensuring

the re-industrialization initiative of Hong Kong leads to make

Hong Kong a very attractive venue for headquarters and

innovation functions of manufacturing enterprises in an

Industry 4.0 world.

SOLUTIONS FOR COMMON APPLICATIONS Across the evaluated industries several common applications

bringing strong benefits have been identified. These include

tracking and tracing of materials and WIP, OEE measurement,

and basic IoT intstrumentation of machine PLCs. Solutions for

these applications do exist on the market, but are mostly too

advanced and costly for the purposes of Hong Kong SMEs. The

development of simpler solutions focusing more on inventory

and lead time optimization rather than maintenance and quality

issues can strongly help Hong Kong SMEs.

INNOVATION READINESS Many Hong Kong SMEs are traditionally used to receiving full

specifications of a product and responsible mostly for efficient

scaling in manufacturing. One of the key elements to sustain the

competitive edge of Hong Kong SMEs in an Industry 4.0 world is

the development of OEMs to first ODMs and then OBMs.

However, the development of own products with commercial

responsibility for market success requires a very different

mindset, as many more levels of uncertainty (“VUCA” –

Volatility, Uncertainty, Complexity, Ambiguity) need to be

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handled in an efficient and effective way to accept, but minimize

inherent risks. This includes using established management

methodologies for dealing with innovations (Innovation and

Technology managements) as well as creating the right mindset

for innovation. This does not happen in one step, so a Hong Kong

model for transforming management methods and mindsets

from OEM business to world-class innovator needs to be

developed and suitable professional services offered.

RESEARCH FOR HONG KONG-SPECIFIC ADVANCED

APPLICATIONS The very low lead times and high flexibility of Hong Kong SMEs

are part of their core USPs in international markets. Rising wages

and a resulting higher need for automation, as well as more

unstable supply chains threaten these USPs. The development of

solutions for enabling collaborative automation while retaining

flexibility (using advanced collaborative robotics) and handling

of unstable supply chains (through AI) can help sustain and even

extend these USPs. This includes flexible assembly cells,

prediction models for supply chains, and similar industrial AI

applications.

FUNDAMENTALS FOR HIGHER MATURITIES Above visibility (1i) level, the use of data in day-to-day workings

by a large number of staff is integral to leveraging the benefits

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of Industry 4.0. Otherwise expensive technology to be aware of

the current state of operations will have been put in place

without the capability to use it to optimize operations on a daily

basis. This requires new levels of personal responsibility from

each employee to maximize the benefits for the company, and

training in capabilities including cross-departmental

collaboration, continuous improvement, data handling and

understanding, and problem-solving; on all different hierarchy

levels from supervisors to executive level.

PROMOTING INDUSTRY AS A CAREER In an Industry 4.0 world, industrial companies including SMEs

thrive on talent. Employees on very different levels (managerial,

professional, technical) need to be trained in understanding data

and information, and reacting to it in the most efficient way for

the company, as well as trained to generate, evaluate and

implement own innovative ideas from small improvements to

product ideas. In Hong Kong, Industry does not have an image of

a career one can aspire to. Curricula need to show the advanced

technologies, creative way of work, and career potentials

possible in manufacturing industry in an Industry 4.0 world to

attract the best talent to industry.

INFRASTRUCTURE FOR LEVERAGING HONG KONG'S

UNIQUE POSITION

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To sustain and attract manufacturing companies to have their

(regional) headquarters in Hong Kong, it is necessary to provide

infrastructure beyond the international appeal of Hong Kong

and its legal system. This infrastructure needs to facilitate

orchestrating supply chains from Hong Kong and to foster

product innovation in Hong Kong. Protoyping facilities for

building production-quality prototypes of new products at very

high speeds, and data infrastructures for orchestrating supply

chains with an ecosystem of professional services around

supply chains (e.g., a “Hong Kong Manufacturing cloud”

seamlessly connected to supplier and consumer IT

infrastructure, together with professional services for tracing

supply chains and certifying quality) can strengthen the USPs

leading headquarters and innovation functions to stay or return

to Hong Kong.

FROM DEMONSTRATOR TO USE-CASE: LEARNING IN REAL

SETTINGS To understand Industry 4.0 not only the technical perspective,

but also the mindset aspects relevant to achieving productivity

gains through data need to be understood. Both of these

aspects are best taught along real-life use cases showing the

difference between a classical production and Industry 4.0

approaches. Demonstrators highlighting Industry 4.0 showcases

help illustrate the concept, but do not suffice to teach the

interactions and processes needed to fully utilities a full

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Industry 4.0 implementation in a complex, real production

setting. To this extent, it is necessary to develop real use-cases

in factories and logistics shopfloors in Hong Kong – or

designating a specific “learning shopfloor” and fitting it with

suitable use-cases. Collaboration with the appropriate

educational institutions to train the Industry 4.0 concept along

these real use-cases ensures quicker pick-up of the relevant

skills.