Cloud Manufacturing: An Approach to Strengthen
Global Competitiveness of the Indonesian Small and Medium
Manufacturing Enterprises
Khamdi Mubarok and Mahrus Khoirul Umami
Department of Mechanical Engineering, University of Trunojoyo Madura, Bangkalan, Indonesia
Keywords: Industry 4.0, Making Indonesia 4.0, Small and Medium Manufacturing Enterprises, E-Smart IKM, Cloud
Manufacturing
Abstract: The World is moving into a new industrial revolution era and new industrial competition. Driven by the
advanced development of computer science and information and communication technologies (ICT), the
German strategic initiative Industry 4.0 has triggered many countries to establish their national strategies.
Responding to this trend, the Indonesian government launched “Making Indonesia 4.0” as a roadmap to
strengthen industrial competitiveness. Focusing on small and medium manufacturing enterprises (SMMEs)
or IKM, the Ministry of Industry released E-Smart IKM to help them improve their productivity and expand
their market. However, these initiatives paid less attention to the collaboration worth among companies. In
order to build a close relationship and strong collaboration among SMMEs, cloud manufacturing concept is
adopted in this research. By utilizing the Internet of things (IoT), service-oriented architecture (SOA)
technologies and cloud computing technologies, a cloud manufacturing platform for the Indonesian SMMEs
is developed. First, Making Indonesia 4.0 initiative and E-Smart program as the background of this research
are observed. Second, cloud manufacturing definition and basic concept are discussed. Finally, three
supporting conditions for the adoption of cloud manufacturing and nine implementation strategies for the
Indonesian context are proposed. The initial work of this implementation is also presented.
1 INTRODUCTION
Industry 4.0 (or Industrie 4.0) refers to the fourth
industrial revolution in which manufacturing
industries will be occupied by intelligent machines
and products to create intelligent systems and
networks which can communicate each other
autonomously (Oztemel and Gursev, 2020). This
concept was first introduced by National Academy
of Science and Engineering (Acatech) Germany at
Hannover Messe trade fair in 2011 as the strategic
initiative to secure Germany position as the world
leader in manufacturing industries (Kagermann et.
al., 2013). Industry 4.0 can be seen as a collection of
emerging information and communication
technologies (ICT) that drive future manufacturing.
Those technologies include Internet of Things (IoT),
cloud computing (CC), big data and analytics
(BDA), system integration, advanced robotics,
additive manufacturing or 3D printing, augmented
reality (including virtual reality and mixed reality),
advanced simulation, knowledge graph, blockchain,
digital twin, and cyber secrity (Mubarok, 2020).
Initiated from the manufacturing domain, the
application of Industry 4.0 technologies gain more
and more attention from both industry experts and
academic researchers. Those technologies have to
improve manufacturing life cycle processes in the
most suitable areas of application (Zheng et al.,
2020). Additive manufacturing is one of the newly
technologies taking fast advantages in this new era
enabling rapid product development by utilizing IoT
technologies (Wang et al., 2019).
Similar to Industry 4.0, General Electric and
other leading industries in the United States also
introduced the concept of Industrial Internet, putting
intelligent machines, advanced analytics and
connected people as the key elements of future
manufacturing (Evans and Annunziata, 2012). Other
countries also develop their unique strategies for
future manufacturing competition. Made in Sweden
2030 (Ersson and Sagström, 2013), Smart Industry
Dutch Industry fit for the future (FME, 2014) and
Mubarok, K. and Umami, M.
Cloud Manufacturing: An Approach to Strengthen Global Competitiveness of the Indonesian Small and Medium Manufacturing Enterprises.
DOI: 10.5220/0010305900003051
In Proceedings of the International Conference on Culture Heritage, Education, Sustainable Tourism, and Innovation Technologies (CESIT 2020), pages 185-192
ISBN: 978-989-758-501-2
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
185
Made in China 2025 (Liu, 2016) are some of the
examples.
Following this trend, on April 4th, 2018, the
government of Indonesia launched “Making
Indonesia 4.0” (Kemenperin, 2018a) as a roadmap
for guiding the reinforcement programs to boost
national industries globally. This is the way how
Indonesia revitalize the manufacturing sector to
achieve the vision to be among the tenth largest
world economy in 2030. Another initiative, focusing
on IKM or small and medium manufacturing
industries (SMMEs), the Indonesian Ministry of
Industry also created a digital technology project
called “E-Smart IKM” (Kemenperin, 2017). E-Smart
IKM is a government exertion to SMMEs to enter
online marketplace so that their product can reach
global markets.
Both initiatives, however, still lack focus on
strengthening the relationship and collaboration
between industries or among similar industries. Even
though those similar industries have been placed in
certain location forming an industrial cluster, the
collaboration between those industries is still very
low. As a result, they only able to undertake a small
project individually. They are incapable of
accomplishing big projects. Close collaboration
between those industries will allow them to
overcome this challenge. Based on this conditions, a
close collaboration network program applying a new
manufacturing paradigm called cloud manufacturing
(CMfg) is proposed. Cloud manufacturing platform
enable diverse industries to access and use
manufacturing resources from a pool of resources
provided by other companies (Ghami et al., 2019).
This approach will enable SMMEs to build a close
collaboration with other companies to carry big
projects together and enhance their global
competitiveness.
To enable on-demand access, manufacturing
equipment need to be connected to the Internet and
provide required data analytics tools as to assess
their capabilities and availabilities (Lu and Xu,
2019). These technologies will benefit Small and
Medium Sized Enterprises (SMEs) in term of
competitive advantage, flexibility, efficiency, and
quality. However, most of the SMEs have financial
and knowledge constaints to adopt those typical
Industry 4.0 technologies (Masood and Sonntag,
2020). Therefore, before integrate modern and smart
manufacturing equipment, SMEs are required to
analyze technological, organizational, and
environmental determinants of digital technology
adoption and implementation (Ghobakhloo and
Ching, 2019). In addition, other critical factors
comprised in this implementation are the support
and involvement of SME managers, training support
from expertise and academic researchers, also the
collaboration among SMEs in the industrial network
(Moeuf et al., 2020).
The main objective of this paper is to develop a
cloud manufacturing platform for Indonesian
SMMEs based on their typical characteristics. The
rest of this paper is organized as follow. Section II
highlights the new Indonesian government initiative
“Making Indonesia 4.0” and “E-Smart IKM”
program scheme as the background of this research.
Section III discusses the basic concept of cloud
manufacturing and its suitability for Indonesian
context. Section IV describes the adoption process
and the implementation strategy. Finally, Section V
concludes the paper and define future work.
2 MAKING INDONESIA 4.0 AND
E-SMART IKM
This section describes Making Indonesia 4.0, the
Indonesian national strategy to compete in today’s
global market, andE-Smart IKM project.
Following that, we identify some beneficial factors
as well as some drawbacks of government programs.
2.1 Making Indonesia 4.0
The main contents of Making Indonesia 4.0 roadmap
are five industrial sectors as the pillars and ten
national development priorities (Kemenperin,
2018a). Based on the real condition of the
Indonesian manufacturing environment, the Ministry
of Industry has selected five leading industries that
have enormous potential to be expanded globally.
Those leading industries are the main strength of
future Indonesian manufacturing. Those five sectors
are food and beverage, textile and apparel,
automotive, electronics and chemical. Figure 1
shows the five industry pillars and the main enabling
technologies such as artificial intelligence (AI), IoT,
wearables, advanced robotics and 3D printing.
However, other Industry 4.0 technologies as
mentioned on the first section will also be utilized.
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Figure 1: Five main industrial sectors (Kemenperin,
2018a)
Based on the study of the obstacle factors to the
development of manufacturing industries in
Indonesia, the government has placed ten national
priorities that urgently required to faster industrial
growth. Those ten priorities are fixing material
supply chain, redesigning industrial zone,
accommodating sustainability standards,
empowering SMEs, building national digital
infrastructure, attracting foreign investments,
improving human resource skills, forming
innovation-based ecosystems, offering incentives for
technological investments, and harmonization of
rules and policies (Kemenperin, 2018a). In this
research, the empowering SMEs (SMMEs) and
redesigning industrial zone or industrial cluster are
highlighted. Re-design industrial cluster can be
referred to re-managing industries within a cluster
for close collaboration.
2.2 E-Smart IKM Project
E-Smart IKM is a Ministry of Industry project to
improve the productivity of small and medium-sized
enterprises by introducing digital technology. The
government encourages SMMEs to trade their
products through the online marketplace on the
Internet that the government has created or
collaborated. Within this project, the government
also offer help and support on capital investment,
process and product standardization, intellectual
property right, raw material access, human resource
development, etc. This Internet-based project is a
good start. To this end, many SMMEs have joined
and experienced the benefits. To further improve
their global competitiveness, this project can be
improved further by building cloud manufacturing
platform to support collaboration.
Another government scheme to support SMMEs
is the industrial machinery restructuration project
that has been run since 2009. In this project, the
Ministry of Industry reimburses 25-30% of the total
money a company spent on purchasing new
machines or equipment (Kemenperin, 2018b).
Although this project can augment SMMEs
production capability, enlarge their production
capacity, and improve their competitiveness, this
project is less effective. This is because only the
companies which receive the grant can take benefits.
Other industries still suffer from their restricted
capability. Therefore, it is necessary for the
government to review this scheme as to have more
companies take benefits. Cloud manufacturing
approach holds this potential to share the use of
machines or equipment in a community or public-
based. On the other way, the Ministry of Industry
can manage under cloud manufacturing platform in
which machinery and equipment in one company
can be accessed by other companies. As a result,
many companies will benefit from access to that
machinery and equipment. This will be more
effective and efficient to improve global
competitiveness for many SMMEs.
3 CLOUD MANUFACTURING
Cloud manufacturing is a collaborative
manufacturing concept based on cloud computing
technology and service-oriented architecure (Li et
al., 2010). Hundreds of papers have been published
on this topic. In addition, several research projects in
Europe and China have also toughened the
foundation of this concept. However, the real
implementation of this concept still scarce.
3.1 Definition and Basic Concept
Cloud manufacturing is a cloud computing
application in manufacturing. Before cloud
computing technology introduced, software installer
was provided on compact disc (CD). Also, files were
stored on PC hard disk which holds a certain
capacity. Since cloud computing is introduced,
software installer, storage, and other services are
available in the cloud which can be accessed from
everywhere as long as internet connection are
available. Similarly, in cloud manufacturing,
machines, robots, and other manufacturing facilities
Cloud Manufacturing: An Approach to Strengthen Global Competitiveness of the Indonesian Small and Medium Manufacturing Enterprises
187
are virtualized and offered as a service that can be
accessed or used by anyone (cloud users).
One of the formal definition of cloud
manufacturing is mirroring the definition of cloud
computing. Cloud manufacturing is ‘‘a model for
enabling ubiquitous, convenient, on-demand
network access to a shared pool of configurable
manufacturing resources (e.g., manufacturing
software tools, manufacturing equipment, and
manufacturing capabilities) that can be rapidly
provisioned and released with minimal management
effort or service provider interaction.’’(Xu, 2012).
In cloud manufacturing, companies that have idle
resources, such as machines, equipment, and other
manufacturing facilities register their virtualized
resources in the cloud via cloud operator and offer
them as services. This means other companies can
access and use their resources on “pay as you go”
bases. The benefit of this concept, among other
benefits, is the users do not need to purchase
resources. They can use other companies’ resources
(cloud providers) and pay based on how long they
use those resources.
The other benefit of cloud manufacturing is
shortened time to market. A company which receive
high demand but its facilities incapable of doing so,
then this company must find other companies which
have similar facilities. Traditionally, an industry
catalogue or normal online search engine will be
used as a reference to discover dedicated companies.
However, this way is time-consuming, and it is
difficult to find the exact machines or equipment
needed. Cloud manufacturing platform will
eliminate this process and directly provide options
on lower facility level such as machines and
equipment. It can search available resources on its
system. To illustrate the cloud manufacturing
process, Figure 2 shows how cloud manufacturing
principle work. In general, a customer or cloud user
has the design of a product in CAD file. By
submitting this CAD file into cloud manufacturing
platform, which in this case illustrated as Google
search, the system will pop up different machines
that can process their product can be found. For
simplicity, this process is similar to Google search
engine when searching for a specific sentence. In
cloud manufacturing, a typical search engine is
developed. So, by inserting a CAD file into a cloud
manufacturing platform, a cloud user can find a
number of machines that capable to process the
product as required on CAD file. Then, this cloud
user can select the best machine based on machine
specification, price per hour, geographical location,
availability status (scheduling), etc.
Figure 2: Cloud manufacturing process illustration
There are different topics to realize this concept,
such as manufacturing resource virtualization,
service selection, service composition, scheduling,
pricing strategies, and so on. Despite the limited
implementation of cloud manufacturing concept, the
development of cloud manufacturing
implementation for the Indonesian SMMEs will be a
good example for other countries. The complexity of
the system, the technology enablers, and industrial
awareness are some of the challenges. Other factors
influence this implementation also include the
typical manufacturing companies, geographical
conditions, government policy, etc. Based on the
conditions of the Indonesian SMMEs, we propose
Industry 4.0 implementation for small and medium
manufacturing enterprises for Indonesia context,
which focuses on cloud manufacturing technologies.
3.2 Business Process
Figure 3 below shows the cloud manufacturing
participants and business process. Ideally, machines
and equipment are connected to the internet and
available to be accessed for real-time monitoring and
responsiveness. Data are gathered through intelligent
devices (sensors, cameras, RFIDs, smartphones,
wearable) and stored in the cloud. The cloud can be
accessed privately for internal purposes or open to
public for data sharing with other business partners.
Big data analytic helps smart factories to analyse the
data and to derive useful information for certain
decision-making purposes.
In cloud manufacturing, there are three main
participants, i.e. service providers, a cloud operator,
and cloud users/consumers, either individual entity
or business organization.
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188
Figure 3: Cloud manufacturing business process
First, companies which have manufacturing
resources will participate as service providers.
Machines, equipment and other devices on physical
resources are virtualized. In advanced version, these
virtual machines produce data. To keep internal data
safe and secure, data are saved in the factory private
cloud. Only data related to resources for sharing are
uploaded via factory public cloud. Service providers
virtualize resources and provide manufacturing
resources information database to be uploaded to the
cloud. This database consists of physical
manufacturing resources, such as machine tools,
cutting tools, materials, etc., and their manufacturing
capabilities. Then, those data are virtualized and
connected to the internet for ubiquitous access. IoT
sensing provides real-time resource monitoring
showing availability status of each resource.
Second, the cloud operator. Cloud operator is
responsible for taking control of the whole service
activities, such as service registration, orchestration,
and composition. The main role of the cloud
operator is to find matching user requests with
suitable resources. Then, offer the list of matching
resources for users to select based on their
requirements. The operator also manages to provide
the best service to users and providers. In addition,
the operator also concerns with cybersecurity issue
in a cloud environment to protect intellectual
property (IP) of the requests (products) and other
private data. Dealing with faulty in some extent also
need operator attention.
Third, cloud users or cloud consumers. Users
submit their request, such as product data, and select
the best resources from the list of matching
resources provided by the operator. They will be
given access to track and monitor the request status
in real-time based. Any feedback for both operator
and provider are submitted to measure the quality of
service.
The overall processes is developed based on a
knowledge-based system to determine
manufacturing related decision making as well as to
optimize the systems. All data and events, in the
overall processes are captured to building the basis
of this knowledge. Rules then created to drive the
systems.
4 IMPLEMENTATION
STRATEGY
This research focuses on finding the way for cloud
manufacturing implementation in the Indonesian
context. Therefore, some characteristic of SMMEs
and typical government organization is described
first. Then, step by step implementation procedure is
proposed. Following that, an initial development
process in our laboratory is also presented.
4.1 Business Process
Indonesia as a developing country has a large
number of SMMEs. Therefore, the government
through the Ministry of Industry pay attention more
to this industrial sector. Based on our investigation,
we define three supporting conditions for the
adoption and implementation of cloud
manufacturing concept in Indonesia. First, the
establishment of industrial clusters or industrial
zones in many cities. Those industrial clusters are
developed mainly based on similar products. For
example, central for foundry industry which located
in Klaten, furniture industries in Jepara, leather
industries in Sidoarjo, and so on. These industrial
clusters simplify the collaboration format that needs
to be established as the beginning step.
Second, support from local government.
Indonesia has local representatives for the ministry
of industries, called “Dinas UMKM” or “Dinas
IKM” that focus on developing local SMMEs. They
have data and information regarding the type of
industries, the size of the industries, etc. in their
local area. The local government also has a good
relationship and communication with the industries.
Within this good circumstances, the local
government can play the role as cloud operator
which facilitate the industries to provide their
manufacturing resource capabilities information.
Third, the new infrastructure development such
as highway and transportation systems. Since cloud
manufacturing concept is overlooked geographical
location, which means the manufacturing resources
Cloud Manufacturing: An Approach to Strengthen Global Competitiveness of the Indonesian Small and Medium Manufacturing Enterprises
189
can be located anywhere as well as cloud users also
can have access from anywhere, the role of transport
systems must be influenced. This new huge
improvement on the infrastructure facilities enables
the cloud manufacturing implementation in
Indonesia.
4.2 Step-by-Step Implementation
To implement the cloud manufacturing concept, we
define nine steps based on the cloud manufacturing
service management proposed by Tao et al. (2015).
Figure 4: Cloud manufacturing implementation procedure
The implementation procedure is divided into
nine steps as below:
1. Resource description and virtualization.
Manufacturing resources such as machines
and equipment are virtualized using cloud
computing technologies and agent-based
technologies. Beside those hard manufacturing
resources, soft manufacturing resources such
as a person (smart talents), software, and other
computational resources also can be offered as
s service.
2. Service encapsulation and publication.
Resource capabilities are translated into
service modelling language (using ontology
modelling) and published on public cloud
pool.
3. Task/request description. Tasks and other
specific requirements are represented as
product data in semantic description language.
4. Service searching and matching. Similarity
algorithms are commonly used for service
discovery to search and match user tasks with
suitable cloud services.
5. Service selection and composition.
Knowledge-based systems or other approach
and methodology can be used for optimal
selection and service composition.
6. Service scheduling. Selected resources are
scheduled using scheduling algorithms based
on resources real-time availability
7. Service execution. Production processes are
executed based on the scheduling.
8. Service monitoring. Users can access the real-
time status of their request.
9. Product delivery. Finished tasks/requests are
delivered to users.
4.3 Application Development
We have initiated this work in our lab, the
Laboratory of Robotics and Automation Laboratory,
University of Trunojoyo Madura. We have 2 CNC
milling machines, 2 CNC turning machines, and one
robot welding, also one robot assembly. The initial
project currently performed is how to virtualize the
CNC and robots in the machine (computer) readable
format. Ontology modelling is the best option so far
to virtualize the manufacturing resources. Figure 5
shows CNC milling machine characteristics that
need to be virtualized.
Figure 5: CNC milling data and characteristics
In compliance with cloud manufacturing
environment, these characteristics are required to be
transformed into ontology modelling (Talhi et al.,
2019). Figure 6 shows an example of the
development of machine tools ontology using
Protégé software.
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Figure 6: CNC Milling ontology
5 CONCLUSION
This research proposed a strategy for cloud
manufacturing implementation in the Indonesian
context to strengthen SMMEs global
competitiveness by building close collaboration
among SMMEs. The concept of cloud
manufacturing is described and the suitability with
the Indonesian context is discussed. As a result,
three supporting conditions are defined and nine
implement strategies for the cloud manufacturing
adoption are developed. However, following the step
by step procedure proposed, the real implementation
of this project is still in the initial stage. Therefore,
for future research, the efforts will be focused on the
next steps as presented in this paper. Furthermore,
by utilizing cyber-physical systems (CPS) and big
data analytics, the opportunity to gather data from
machines and process the data for prediction process
purpose and process simulation needs to be
investigates. So that, the cloud users will be able to
simulate the overall process before placing a request
on the cloud manufacturing platform. In addition,
cybersecurity issues also will be our concern.
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