Computer Integrated Manufacturing Architecture: A Literature Review

Abdelkarim Remli, Amal Khtira and Bouchra El Asri

IMS Team, ADMIR Laboratory, Rabat IT Center, ENSIAS, Mohammed V University, Rabat, Morocco

Keywords:

Manufacturing systems, Smart Manufacturing, Computer Integrated Manufacturing, Systems Architecture.

Abstract:

The exponential technological revolution has had a positive impact on industrial companies, providing them

with plenty of opportunities to improve their production ﬂows and optimize their costs. This revolution has led

to contemporary computer integrated manufacturing (CIM) that consists of linking the shop ﬂoor systems to

the high business layer. And in order to do that, there has been some research to deﬁne a reference architecture

to cover all the use cases. This paper presents a literature review of CIM architectures. The purpose of this

review is to enumerate the different aspects covered by the different architectures in the literature and the

approaches proposed to handle them.

1 INTRODUCTION

Competition and rapidly changing customer demands

are calling for continuous changes in manufactur-

ing environments. For that, the competitive com-

panies had to effectively handle the concurrent evo-

lution of products, processes and production sys-

tems (Farid Meziane, 2000). As a result, companies

started to integrate information technologies from

other ﬁelds in the manufacturing process. This change

has had several names such as Smart Manufacturing

(Li et al., 2019) and Computer integrated manufactur-

ing (Thomas Hedberg, 2016).

This trend consists of two major elements: Com-

puterizing the industrial processes, and facilitating the

exchange of data. This can be achieved through inte-

grating every system in the manufacturing process in

the same architecture in order to create a fully con-

nected plant, where every retrieved data is reusable to

optimize the various business processes. This is what

we call a smart factory (Li et al., 2017). To achieve

that, we should ensure the connection between the dif-

ferent levels of the plant, from the shop ﬂoor level

that contains the production machines, to the highest

level of the plant where the company’s strategies are

established. This connection is challenged by the in-

herent difﬁculty of aggregating and applying context

to data from heterogeneous systems across the pro-

duction life cycle (Tolio et al., 2013). Therefore, the

researches have been able to propose several solutions

that are able to encompass all of the company’s major

IT systems into one architecture while ensuring the

interchangeability among them.

In this paper, we present a literature review on the

contributions regarding Computer integrated Manu-

facturing Architectures. The main objective of this

review is to go over the literature in this ﬁeld between

2015 and 2019 and to identify the number and the na-

ture of contributions in the collected papers, as well

as the different aspects covered by them. We identi-

ﬁed six aspects that we deemed essential to handle in

a contribution: Data integration, Systems integration,

Security, Monitoring & Data analysis, Mobility and

ﬁnally Cloud computing.

This paper is sequenced as follows: Section 2 ex-

plains the literature review methodology we will fol-

low. In Section 3, we analyze and discuss the results

found against the predeﬁned research questions. Sec-

tion 4 presents some limitations of the study. Finally,

Section 5 concludes the paper.

2 RESEARCH STRATEGY

Through time, researchers have been able to propose

several architectures and models for computer inte-

grated manufacturing that can have the ability to han-

dle multi systems data. To analyse these solutions,

we decided to conduct a review of the different ap-

proaches proposed in the literature. For this pur-

pose, we followed the same stages and steps of a Sys-

tematic Literature Review (SLR) as recommended in

Kitchenham’s guidelines (Kitchenham, 2007).

The SLR protocol is composed of six main steps:

1) Identiﬁcation of research questions and Research

Strings, 2) Search in the Data Sources, 3) Deﬁnition

Remli, A., Khtira, A. and El Asri, B.

Computer Integrated Manufacturing Architecture: A Literature Review.

DOI: 10.5220/0010148002490256

In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 3: KMIS, pages 249-256

ISBN: 978-989-758-474-9

249

of Inclusion and Exclusion criteria, 4) Data Reﬁne-

ment, 5) Data Extraction, and 6) Data Analysis. The

ﬁrst ﬁve steps of the followed protocol are detailed in

the rest of this section, while the last step is detailed

in Section 3.

2.1 Search Questions and Strings

The main goal of this review is to analyse the existing

studies on CIM Architectures and to scrape the dif-

ferent aspects covered by each architecture. For this

reason, we formulated the three following questions:

• RQ1. What are the different architectures pro-

posed for CIM to handle production data integra-

tion in the literature?

• RQ2. What are the types of contributions regard-

ing the systems interoperability in a CIM environ-

ment?

• RQ3. What are the different aspects that have

been covered by the existing approaches in the lit-

erature?

Based on these questions, we constructed our

search string by using the main keywords of our re-

search as well as including the synonyms and related

terms. Then, we concatenated the alternative key-

words using Boolean ”OR” and linked the main terms

using Boolean ”AND”. As a result, we obtained the

following search string :

(Software OR Systems OR Manufacturing Execution

OR MES) AND (Architecture OR Framework OR Ap-

proach OR Model) AND (Computer Integrated Manu-

facturing OR Smart Manufacturing OR Industry 4.0)

2.2 Data Sources

In this step, we used the constructed String as a search

input in the most commonly used Digital libraries,

namely IEEE Explore, Science Direct, ACM Digital

Library and SpringerLink. Due to the multitude of

search features provided by these digital sources, we

did not use a single search string for all the Digital

libraries. Instead, we derived a speciﬁc search string

for each library and we carried out some additional

actions to get equivalent results from the different li-

braries.

2.3 Data Selection

The main idea of the systematic review is to collect

relevant papers regarding a speciﬁc subject. Accord-

ingly, we used a staged selection process that follows

a number of predeﬁned criteria. In the ﬁrst stage, a

paper was included only if:

• It was a full article, a book, a chapter or a thesis.

• The title or the abstract of the paper contained the

keywords related to the search.

After the ﬁrst stage, the number of papers found

was 4073, distributed as follows, 1737 from IEEE Ex-

plore, 1776 from Science Direct, 402 from Springer-

Link, 158 from ACM Digital Library. In the second

stage, we kept only the papers that introduced a solu-

tion for Computer integrated manufacturing architec-

ture. As a result, we had 1462 papers left at this stage.

During the third stage, we excluded papers that does

not meet the following criteria :

• The paper is written in a language other than En-

glish.

• The publication date is previous to 2015.

• The paper is a short article, a standard, a poster,

an editorial, a tutorial.

• The paper is duplicated.

After the third stage, we obtained 74 papers. To

reﬁne our study, we had to follow through a quality

based selection on the remaining papers. For that, we

deﬁned two additional criteria :

• Number of citations : We deﬁned a minimum

number of citations required that varies for each

year.

• Work continuity: If the work described in the pa-

per does not have a continuity in recent papers,

then the paper is excluded.

We investigated each of the 74 papers, and after ap-

plying the quality based selection, we kept the 29 pa-

pers presented in table 2.

2.4 Data Extraction and Synthesis

We fully read each of the 29 papers in order to extract

the required data. To help us answer the predeﬁned

questions, we had to formalize the extracted data,

hence we deﬁned a set of attributes to ﬁll for each

paper. These attributes are : 1) Paper title, 2) Authors

of the paper, 3) Publication year, 4) Paper type (i. e.

Journal paper, conference paper, thesis, book, chap-

ter, workshop paper), 5) Database (i. e. IEEE, ACM,

SpringerLink, Science Direct, Google Scholar), 6)

Source (e. g. Journal name, conference name), 7)

Research type (e. g. Review, Approach evaluation,

Solution proposal, Experiment, Case study), 8) Key-

words speciﬁed in the paper, 9) Short description of

the paper, 10) Contribution (e. g. Model, Framework,

Tool, Method, Algorithm), and 11) Domain of appli-

cation.

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3 RESULTS AND ANALYSIS

3.1 Demographic Data

Demographic data consists of the metadata of the

selected papers. In our review, we focused on

three types of metadata: the database, the year of

publication and the source.

Data Source

Figure 1: Papers distribution per Data source.

Figure 1 represents the percentage of papers

per database. Among the 29 papers selected using

the staged process, we identify 1 paper from ACM

digital Library, 4 papers from Google Scholar, 8 from

Springer, 6 from IEEE and ﬁnally 10 from Science

Direct. We can clearly notice that Science Direct is

the database with the largest number of relevant pa-

pers with a percentage of 34%. Springer comes next

with a percentage of 28%, which can be explained

by the number of papers initially retrieved from these

two databases (402 for SpringerLink and 1776 for

Science Direct). For the other databases, we can

notice that Google Scholar kept the same percentage

in the end, 14% compared to the ﬁrst selection,

and the same thing goes for ACM Digital Library

with 3% in the beginning. For SpringerLink, in the

beginning, the initially selected papers represented

only 9%, but in the end they represented 28% from

all the papers.

Two conclusions can be drawn from this ﬁrst

analysis. First, the quality of papers is not pro-

portional to the initially selected number. In fact,

a database may contain a huge number of papers

related to a speciﬁc area, but most of them cannot

be qualiﬁed as relevant. Second, the search engines

proposed by the selected databases are not perfect,

which is why the initially selected papers do not

correspond to our search String.

Year of publication

Figure 2: Papers distribution per publication year.

As mentioned before, the search was carried out for

the period 2015-2019. The diagram presented in Fig-

ure 2 shows the number of papers published per year.

We can clearly notice that the number of publications

has been changing from 3 to 4 publications per year

between the year 2015 and 2017. The peak year was

2018 with 12 publications.

Publication Source

After analysing the data sources of the selected

papers, their types and the number of papers for each

source, we have found that there are 25 sources;

13 conferences and 12 journals. The number of

papers published in all the conferences is 17, which

represents 58.62%. The Springer Confederated

International Conferences, ”On the Move to Mean-

ingful Internet Systems” alone has 3 papers. There

are 2 conferences for which we can ﬁnd 2 papers:

”Springer Business Modeling and Software Design”

and ”Science Direct International Federation of

Automatic Control”. For journals, we have 12 papers

selected; which represents 41.37%.

3.2 Contributions Analysis

After carefully reading each of the 29 papers, we fo-

cused our study on the papers content and the pro-

posed contributions. As a result, the ﬁrst remark we

have had is that 26 papers give a proposition; which

represents 89.66 % of the selected papers. The 3 re-

maining articles are reviews and analyses of existing

approaches.

Table 1 sums up all the types of contributions pro-

posed by the selected papers, in addition to the num-

ber of papers associated with them. For papers that

propose solutions, we can distinguish 4 types of con-

tributions: Tools/Prototypes, Frameworks, Architec-

tures and Models/Meta-models.

Computer Integrated Manufacturing Architecture: A Literature Review

251

Table 1: Papers per Contribution types.

Type of contribution Number of

Papers

Review and Analysis 3 (Li et al., 2019), (Li Da Xu, 2018), (Lia et al., 2018), (Wei Zhao,

2018)

Tools / Prototypes 4 (Ding et al., 2019), (Sherwin Menezes, 2018), (SangSu Choi, 2018),

(Mohammed et al., 2018)

Frameworks 5 (Li et al., 2017), (Zhang et al., 2019), (Tao et al., 2018), (Fei Tao,

2019), (Alessandra Caggiano, 2016)

Architecture 12 (Leit

ao et al., 2017), (Emanuel Trunzer1 · Ambra Cal

a2, 2019),

(Kavakli et al., 2018), (Thijs Franck, 2018), (Jiang, 2017),

(Tang et al., 2018), (Theorin et al., 2017), (Jeon et al., 2016),

(Lane Thames, 2016), (Michael P. Papazoglou, 2015), (Bousdekis

et al., 2015),(Li et al., 2019)

Models / Meta-

models

5 (Khakiﬁrooz et al., 2018), (M

uller et al., 2016), (Tae Hyun Kim,

2019), (Dennis Weihraucha, 2018), (Timothy Sprock, 2015)

3.2.1 Review and Analysis

Many researchers have attempted to sum up the cur-

rent state of research on a particular topic related to

CIM architectures. For instance, Xu and his col-

leagues presented a state of art on Industry 4.0, the

new technological trends and the architectures that are

related to it (Li Da Xu, 2018). Li and his colleagues

did an overview on the smart manufacturing stan-

dard frameworks and models, and they listed some

of the standardization roadmaps such as Integration

of Industrialization & Informatization (iI&I), Manu-

facturing 2025 and Industry 4.0 of Germany (Li et al.,

2017).

3.2.2 Tools / Prototypes

Many papers have provided tools and prototypes in

order to validate the solutions they proposed. These

tools can address a speciﬁc use case or several use

cases. For example, Menezes and his colleagues pre-

sented a Real Time RFID-enabled MES dedicated to

medium and small businesses. This tool provides

the capability to write and read manufacturing data

(Sherwin Menezes, 2018). Choi and his colleagues

came up with a Web-based Platform based on third

party technologies and services for smart manufac-

turing assessment in order to improve planning, with

the capability to learn and recommend improvements

(SangSu Choi, 2018).

3.2.3 Frameworks

Some studies propose a ’semi-complete’ or special

purpose architectures that can be specialized to pro-

duce custom systems, or what we call ”frameworks”.

In this sense, Caggiano and his colleagues’ Cloud

Based Framework enables smart monitoring of ma-

chining in order to offer real time diagnosis (Alessan-

dra Caggiano, 2016). Tao and his colleagues pre-

sented the Data-Driven Smart manufacturing Frame-

work which enables the usage of the data collected

through the manufacturing process in order to in-

crease its efﬁciency (Tao et al., 2018).

3.2.4 Architectures

A system architecture is the conceptual model that de-

ﬁnes the components, the structure and the behavior

of a system (Clements, 1996). Among the analyzed

papers, twelve have proposed architectures in relation

of our research. For example, Sprock and his col-

leagues proposed an architecture for smart manufac-

turing to bridge the gap between system data and anal-

ysis models (Timothy Sprock, 2015). Tang proposed

the Cloud-Assisted Self-Organized Architecture (CA-

SOA) to build a vertically enabled system for data

consolidation (Tang et al., 2018).

3.2.5 Models / Meta-models

Systems modeling is the interdisciplinary study of the

use of models to conceptualize and construct systems

in business and IT development (Wegmann, 2007).

An example of the models proposed in literature is

the one introduced by Khakiﬁrooz and his colleagues.

The objective of this system dynamic model is to

describe links between the components of “Industry

4.0” and how they inﬂuence each other (Khakiﬁrooz

et al., 2018). Kim and his colleagues also presented

a conceptual model; the Smart-MES (S-MES) dedi-

cated to rolling stock manufacturing (Tae Hyun Kim,

2019).

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3.3 Aspects Discussed

Based on the 29 analyzed papers, we extracted six as-

pects that were taken into consideration when propos-

ing a CIM architecture. These Aspects are: Systems

Integration, Data Integration, Security, Monitoring &

Data Analysis, Mobility and Cloud Friendly. Figure

3 shows the aggregation of papers per aspects.

Figure 3: The number of papers by artefact.

Table 2 presents a comparison between papers de-

pending on the aspects they cover.

3.3.1 Systems Integration

System Integration is the capability of a solution to

ensure the integration and the cooperation between

different IT systems in the same architecture. In

works dealing with systems integration, the systems

are sometimes limited to MES due to the crucial

role it plays (Wei Zhao, 2018),(Mohammed et al.,

2018),(Sherwin Menezes, 2018),(Tae Hyun Kim,

2019). The other contributions deal with IT systems

in a general overview. Among the solutions proposed

in this context is Service Oriented Smart Manufac-

turing (SOSM) Framework.It aims at facilitating the

integration of smart manufacturing systems based on

service-oriented technologies (Fei Tao, 2019). To val-

idate their approach, the authors provided a use case

on Milk industry. Thames and Schaefer proposed the

Software-Deﬁned Cloud Manufacturing (SDCM), a

networked model that exploits on-demand access to

a shared collection of diversiﬁed and distributed man-

ufacturing resources (Lane Thames, 2016).

3.3.2 Data Integration

Data integration consists of applying context to data

from heterogeneous systems across the production

life cycle. We can remark that this aspect has been

covered by all of the 29 articles. In this vein, the

PERFORM system architecture was proposed to es-

tablish an adequate middleware in order to connect

industrial ﬁeld devices with upper IT systems (Leit

et al., 2017). Theorin and his colleagues proposed

an event Driven Architecture called LISA (Line In-

formation System Architecture) for rapid integration

of smart services in the manufacturing environment

(Theorin et al., 2017).

3.3.3 Security

Security is the ability of the proposed solution to pro-

vide secured connection for systems’ integration and

data exchange. This aspect has been covered in 7

contributions, however, it has been just highlighted

as a prerequisite and there have been no propositions

on how to implement it (Lane Thames, 2016) (Mo-

hammed et al., 2018) (Lia et al., 2018).

3.3.4 Monitoring and Data Analysis

Monitoring and data analysis consists of utilizing col-

lected manufacturing data to improve productivity. In

this aspect, we can distinguish two types of data. The

ﬁrst one is Real-time Data used generally for monitor-

ing. This data type is covered in all MES-related con-

tributions due to the real-time monitoring functional-

ities the MES provides. The second type is Historic

Data used for Data analysis. Among the contributions

that cover this type is the architecture proposed by

Kavakli and his colleagues.It supports decision mak-

ing in the context of disruptive events in manufac-

turing (Kavakli et al., 2018). Bousdekis and his col-

leagues proposed a model to integrate real-time Data

and to store it, in order to be used as an historic data

for predictive maintenance (Bousdekis et al., 2015).

3.3.5 Mobility

Mobility is the ability to integrate IT systems on

phones and tablets, generally for data monitoring.

Among the papers that cover this aspect, the RFID-

enabled MES integrated to an android-Based interface

was proposed by Menezes and his colleagues to write

and read real time manufacturing Data. The tool they

proposed is dedicated especially to small and medium

sized manufacturing enterprises (Sherwin Menezes,

2018).

3.3.6 Cloud Computing

This aspect concerns the capability of the solution

to ensure the usage of cloud computing for some or

all the functionalities. For example, Weihraucha and

his colleagues propose a model to enhance agility

and productivity using a Cloud-Based Platform (Den-

nis Weihraucha, 2018). Caggiano and his colleagues

presented a Cloud Based Framework to enable smart

monitoring of machining in order to offer real time

diagnosis (Alessandra Caggiano, 2016).

Computer Integrated Manufacturing Architecture: A Literature Review

253

Table 2: Comparison between approaches according to Aspects.

Systems Data Security Data Mobility Cloud

integration integration Analysis Friendly

(Bousdekis et al., 2015) X X

(Timothy Sprock, 2015) X

(Michael P. Papazoglou, 2015) X X

(Lane Thames, 2016) X X X X X

(Alessandra Caggiano, 2016) X X

uller et al., 2016) X

(Jeon et al., 2016) X X X

(Theorin et al., 2017) X X X

(Tang et al., 2018) X

(Jiang, 2017) X X X

(Fei Tao, 2019) X X X X

(Mohammed et al., 2018) X X X

(Tao et al., 2018) X X X

(Wei Zhao, 2018) X

(SangSu Choi, 2018) X X

(Thijs Franck, 2018) X

(Lia et al., 2018) X X X

(Sherwin Menezes, 2018) X X X X

(Dennis Weihraucha, 2018) X X

(Khakiﬁrooz et al., 2018) X X X X X

(Kavakli et al., 2018) X X X

(Li Da Xu, 2018) X X X X X

(Li et al., 2019) X X

(Zhang et al., 2019) X X X

(Ding et al., 2019) X X X

(Tae Hyun Kim, 2019) X X X

(Emanuel Trunzer1 · Ambra Cal

a2, 2019) X X X X

(Li et al., 2017) X X X

(Leit

ao et al., 2017) X X

4 LIMITATIONS OF THE

REVIEW

In this review, the main idea was to select the maxi-

mum number of pertinent papers regarding Computer

integrated manufacturing architectures. Nevertheless,

the results of the review could have been affected by

some limitations. First, the search systems of the dif-

ferent databases are not fully accurate; a huge num-

ber of papers initially retrieved are not related to the

review scope. As for the data selection process, the

application of exclusion and quality assessment cri-

teria have caused us to ignore some interesting ap-

proaches, because they were not well cited, or be-

cause they were published in short papers.

5 CONCLUSIONS

Nowadays, it has become a must for industrial com-

panies to digitize their processes, in order to keep up

with the customers’ demands and to optimize their

costs. This digitization is done trough connecting the

real world to the virtual one, using cyber physical sys-

tems, data sensors and IT Systems. However, the us-

age of several systems and technologies in the same

environment is very challenging, due to the dissimi-

larities between them and particularities of each one

of them. For that, researchers have been able to pro-

pose architectures that are capable of encompassing

every system in the CIM context. In this paper, we

presented the results of a literature review whose main

objectives were to investigate the different approaches

proposed to handle computer integrated manufactur-

ing architecture between 2015 and 2019, to identify

the nature of contributions in this area and to deter-

mine the different aspects covered by them. At the

beginning, we identiﬁed 4073 papers retrieved from

four digital libraries. Based on a set of exclusion cri-

teria and quality assessment criteria, 29 relevant pa-

pers were selected.

Several ﬁndings have been drawn from this re-

view. First, we noticed that 58% of the contributions

propose a Design oriented solution such as architec-

tures or models. We believe that tools and frame-

KMIS 2020 - 12th International Conference on Knowledge Management and Information Systems

254

work must be given more attention, because without

proper tools, it is difﬁcult to validate the proposed

approaches. Concerning the aspects covered by the

selected papers, all studies have covered the data in-

tegration aspect. Data analysis and monitoring have

also been covered by 16 papers and Systems integra-

tion comes third, with 15 papers. We think it is nor-

mal that these two aspects are the most covered as-

pects, due to the fact that computer integrated man-

ufacturing is all about connected systems, data inter-

changeability and reusability. Cloud computing has

been covered as well by 9 contributions, which is less

than what we expected, in view of the opportunities

that are allowed by it. Thus, much work remains to

be done to cover other aspects of CIM. As for Secu-

rity, little attention has been given to this aspect in

research. Yet it is a crucial prerequisite to ensure the

sustainability of the business. Mobility has been cov-

ered the least, with only 3 contributions, despite it has

being an important aspect in the era of industry 4.0,

which makes it besides security potential research ar-

eas.

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