APPLICATION OF LEAN MANAGEMENT TOOLS IN
INDUSTRY 4.0: A SYSTEMATIC REVIEW
Ingrid Teixeira
do Nascimento
Instituto
Federal do Rio de Janeiro, Brazil
E-mail: ingridteixeira22@gmail.com
Maria Eduarda
Alves da Silva
Instituto Federal
do Rio de Janeiro, Brazil
E-mail: malvesdasilva192@gmail.com
Gabriel Rodrigo
de Souza Gama
CBPF, Brazil
E-mail: grsgama@gmail.com
Ana Carla de
Souza Gomes dos Santos
Instituto
Federal do Rio de Janeiro and CEFET, Brazil
E-mail: anacarla.engenharia@gmail.com
Genildo Nonato
Santos
Instituto
Federal de Educação, Ciência e Tecnologia do Rio de Janeiro, Brazil
E-mail: genildo.santos@ifrj.edu.br
Marcelle Caruzo Xavier
Instituto
Federal de Educação, Ciência e Tecnologia do Rio de Janeiro, Brazil
E-mail:
xaviercmarcelle@hotmail.com
Submission: 3/29/2021
Accept: 3/31/2021
ABSTRACT
The
concept of Industry 4.0 is very recent and has not been fully consolidated,
and, for this reason, comprehensive
implementations by the industrial sector may not be prudent. Studies show that only fundamentals of
Industry 4.0 do not guarantee characteristics such as quality, for example,
in production processes. Thus, lean production concepts are probably
being used together to cover deficiencies in Industry 4.0. In this work,
a literature review is proposed that points out where lean production tools are being used in the production processes of Industry
4.0. Using the results of this search,
an analysis of the most important lean production tools, which appear in the works, has been made. The analysis
has shown what is
being used, in terms of the lean tools, in the production
processes of Industry
4.0, and what improvements are provided from these tools.
Keywords: lean; industry
4.0; review of bibliography;
PRISMA
1.
INTRODUCTION
The industry's interest in the
search for tools to improve the production performance of consumer goods is
constant. Within this context, two concepts stand out: Lean and Industry 4.0.
After World War II, the world saw
rises the Toyota Production System (STP) or Lean Management (LM) in Japan. The
Lean philosophy, also known as lean production or STP, is a multidimensional
approach that includes a wide variety of management practices in an integrated
system. The Lean Management is considered "slim" because it uses
fewer resources for mass production. The basis of STP is the complete waste
elimination, supported by two pillars: just-in-time and autonomation[1].
Just-in-time means ensuring that each process receives the necessary item, when
necessary and in the required quantity. Autonomation involves giving
intelligence to the machine, in order to detect abnormal conditions and stop
the process automatically, avoiding the generation of defective products
(Bento, Gomes & Tontini, 2019).
On the other hand, the Industry 4.0
(I4.0) concept emerged at a congress held in Hannover, Germany, in 2011,
bringing a wave of development to the industry. Countries that have been
investing in other industrial production technologies had even more government
investments for collaborations between industry and academia for Industry 4.0
projects, generating a new revolution (Souza et al., 2020). For the
implementation of Industry 4.0 to be viable, there must be an entire structured
base on some pillars, such as the Cyber-Physical systems, the Internet of
Things and Digitization (Ustundag & Cevikcan, 2017).
Lean and Industries 4.0 are from
different moments in the industry history, however both aim at the search for
improvement and constant efficiency of the means of production. Nevertheless,
I4.0 is a very recent concept, which has not yet been fully consolidated, and
the idea of a comprehensive implementation through the industrial sector
frightens businessmen (Tortorella et al., 2019).
In addition, some authors believe
that only fundamentals of I4.0 cannot guarantee some desired characteristics,
such as quality in production processes (Pagliosa, Tortorella &
Ferreira, 2019) and
that Lean Production concept should probably be used together to cover certain
deficiencies of I4.0 (Tortorella et al., 2019). For these reasons, it is
understood in this work that the LM tools are being associated with the
production processes of I4.0. Thus, the following question arises:
"What lean tools are being applied to the I4.0 production
processes?"
Therefore, the objective of this
article is to carry out a systematic literature review on scientific articles
available in CAPES Journals, and thus to identify which LM tools are used in
I4.0 and where they are applied. Thus, it will be possible to draw the current
scenario of what has already been done in the scope of research and guide
future steps.
In addition to the introductory
part, a review of the literature is presented in this article in the second
part, the methodological steps in the third part, in the fourth part the
results obtained in this analysis are presented and, finally, in part 5 the
conclusions are highlighted.
2.
THEORETICAL REFERENCE
LM seeks to
eliminate waste, absorbent resources activities that do not add value (Oliveira
et al., 2017) and is based on tools that seek continuous improvements such as
Lean Six Sigma (LSS), Lean Construction, Overall Equipment Effectiveness (OEE),
Value Stream Management (VSM), Glenday Sieve and
others. LSS is a methodology that aims to integrate Lean and Six Sigma
philosophies, which is a set of practices to systematically improve processes
by eliminating defects (Sony, 2020). Lean Construction is a current practice
that aims to better reconcile the needs of customers using the least number of
resources possible and is also based on the principles of production management
(Amaral, Oka & Camargo Filho, 2018).
One of the main performance
indicators in Lean is OEE, which is based on the multiplication of three
parameters associated with the equipment: availability, performance, and
quality. Used as a tool in total productive maintenance (TPM), OEE is the key
to indicate the performance of all organizations committed to eliminating waste
(Besutti, Machado & Cecconello,
2019). VSM is an important LM tool to evaluate criteria related to the process
flow. The VSM analysis is based on roadmaps of the manufacturing processes,
showing each step of value or non-value added.
These steps can cost, process time,
and other factors mapped from the orders received. VSM creates a link between
material, information, and process flow (Lugert, Völker & Winkler, 2018). The Glenday
sieve is a methodology for identifying a high volume of the production process,
which focuses on implementing process improvements based on introducing
color-coding or subtitles for the output volume in each part of the process.
With this methodology, it is possible to identify small portions of the
business that are responsible for a large part of sales (Rosienkiewicz
et al., 2018).
LM concepts can be applied to
advanced manufacturing processes, such as I4.0, leading to several improvements
such as quality, waste, and others. I4.0 allows more production autonomy as the
technology becomes more interconnected and the machines can influence each
other (Villalba-Díez et al., 2020). The basis
of I4.0 is composed of some pillars such as: Artificial Intelligence;
Cyber-Physical Systems; Big data; the Internet of Things (Besutti,
Machado & Cecconello, 2019). Artificial
Intelligence is a branch of computer science that using algorithms defined by
specialists can recognize a problem, or a task to be performed, analyze data
and make decisions, simulating human capacity (Causa, 2018). Cyber-Physical
Systems, in the context of I4.0, refers to the strong conjunction and
coordination between computational and physical resources. The impact on the
development of such systems is a new paradigm of technical systems based on
collaborative embedded software systems (Villalba-Díez
et al., 2020).
The amount of data generated by
humanity is climbing sharply, the so-called Big Data, and traditional
production processes will not be able to handle dealing with this gigantic
amount of data, whether to allow production forecasts or mere information
processing (Villalba-Díez et al., 2020). In I4.0
artificial intelligence algorithms can be used to mine this data and separate
the essential information that will be used to support management decisions
(USTUNDAG; CEVIKCAN, 2018).
3.
METHODOLOGY
For the selection of the articles to
be analyzed, it was necessary to choose a method for this purpose. It must be
study, understand and evaluate the various methods available for conducting
academic research, in order to determine its effectiveness in the search (Filser, Silva & Oliveira, 2017). The Preferred Reporting Items for Systematic
Reviews and Meta-Analyzes (PRISMA) is presented in the literature as one of the
most effective methods (Moher et al., 2009). Once the method was
determined, the search terms were defined within the platform of the Portal Periódico Capes (the only one we have institutional
access), Cafe.
They are “Industry 4.0”, “Lean
Manufacturing” and “Lean Management”. At first, the term “Industry 4.0” AND
“Lean Manufacturing” was used, which resulted in a total of 180 publications.
After, “Industry 4.0” AND “Lean Management” returning a total of 71. Figure 2
shows the filtering procedure used. Filtering parameters were used, such as
ENGLISH, document type ARTICLES, published between 2014 and 2020. After
defining these criteria, it was possible to verify a total of 166 articles with
the search for terms “Industry 4.0” and “Lean Manufacturing” and 62 articles in
the search for “Industry 4.0” and “Lean Management”, among these 29 were
repeated. Then, 199 were defined for verification in the next analysis phase
and 228 articles were removed.
The next step was to analyze the
titles and abstracts of each article to find out if those publications fit the
proposal presented. Thus, 39 articles were selected for a full reading. With
the full reading, 2 articles that were not related to the proposal's theme were
discarded.
Figure 1: Prisma Protocol
Source:
Own elaboration (2020)
An analysis of LM tools used in I4.0
was made on the 37 articles, but we only identified concrete applications of LM
in I4.0 in 8 of these works and the result of this analysis is presented in
Chapter 4.
4.
RESULTS AND DISCUSSION
Analyzing the data obtained, it was
possible to identify 8 examples of the application of the SC in I4.0, as shown
in Table 1. Dallasega et al. (2020) argue that lean
construction allowed improvements in the quality and sustainability of
production that were reflected by key indicators that measure production
progression in general, production time, and waiting time. Lauria
and Azzalin, (2019) find similar results applying
lean construction and pointed out a 15% cost reduction. Sony and Michael (2020)
state that the strategic connection project using the LSS methodology saves the
cost of unnecessary data collection and is more effective because it is linked
to the customer's needs.
Table 1:
Examples of LM application in I4.0
|
Author |
Year |
Journall |
Tools |
|
Dallasega et al. |
2020 |
ScienceDirect Journals
(Elsevier) - Procedia Manufacturing, 2020, 45, 49-54 |
Lean Construction |
|
Sony |
2020 |
Taylor &
Francis (Taylor &
Francis Group) - Production
& manufacturing research, 2020, 8(1), 158-181 |
LSS |
|
Huang et al. |
2019 |
ScienceDirect - Journal of Manufacturing Systems, 2019, 52, 1-12 |
VSM |
|
Besutti, Machado
and Cecconello |
2019 |
Directory of Open Access
Journals (DOAJ) - Scientia
cum Industria, 2019, 7(2), 52-67 |
OEE |
|
Lauria and
Azzalin |
2019 |
© ProQuest LLC All rights
reserved - Techne, 2019, 18, 184-190 |
Lean Construction |
|
Lugert, Völker and Winkler |
2018 |
ScienceDirect Journals
(Elsevier) - Procedia CIRP, 2018, 72, 701-706 |
VSM |
|
Rosienkiewicz et al. |
2018 |
Portal
de Revistas Científicas e Profissionais Croatas
- Hrčak - Drvna Industrija, 2018, 69(2), 163(11) |
Peneira Glenday |
|
Rafiq et al. |
2018 |
ScienceDirect Journals
(Elsevier) - Procedia Manufacturing, 2018, 23,
237-242 |
VSM |
Source: Own elaboration (2020)
The design of the parts of the I4.0
systems carried out with the support of the 5 LSS principles helped to bring a
structured and strategic analysis of the total, minimizing the waste of
resources (Sony, 2020). Huang et al. (2019) state that VSM can be used to
improve the multiple flows of processes in I4.0, providing valuable information
for decision making. Lugert, Völker
and Winkler (2018) also point out that the VSM-based methodology was successful
in providing increased productivity and flexibility in the process.
On the other hand, Rafiq et al.
(2018) use VSM in I4.0 to make the whole process more efficient and effective.
Highlighting as a result that the execution time of the whole process went from
210 minutes (before VSM) to 137 minutes (after VSM). Besutti,
Machado and Cecconello. (2019) argue that OEE can be
used to assist in quality control in I4.0. The design of 4.0 component
replenishment systems that use Glenday sieve combined
with AI systems capable of making effective predictions that can significantly
increase the speed and productivity of processes (Rosienkiewicz
et al., 2018).
The results show that several LM
tools are used in I4.0 such as LSS, OEE, and VSM, the latter being the most
cited. Of the articles analyzed, two articles say that the LM tool used has
allowed for an improvement in the quality and sustainability of production
processes. In these two articles, Lean Construction and OEE were used. There
was a reduction in the costs of the production process and the tools Lean
Construction and LSS are used. In one article there was an improvement in the
multiple flows of processes using VSM.
In two articles, the authors report
that the VSM allowed an increase in productivity, but another author also
achieved an increase in productivity using the Glenday
sieve. Thus, strong evidence was presented that there is a use of LM tools in
I4.0 applied to improve the production process, however, they are limited to
the areas of simulation software. It is possible to see that in all the
examples raised, LM tools are applied in virtualization layers (cyber-layers)
to assist in optimization processes or even as restrictions in operational
research problems related to complex computational calculation processes.
5.
CONCLUSION
In this article, a systematic
literature review of the application of LM tools in I4.0 was carried out. This
mapping was carried out on the Capes Periodic Platform through the PRISMA
protocol from 2014 to 2020. For the search, the terms “Industry 4.0”, “Lean
Manufacturing” and “Lean Management” were identified. 228 articles were
initially found, but after a detailed analysis and application of the protocol,
only 8 articles remained.
The analysis revealed that there are
several LM tools applied to improve I4.0 production processes, such as Lean Construction,
Value Stream Management, Lean Six Sigma, Overall Equipment Effectiveness, and Glenday Sieve. Several forms of improvement were
identified, such as, improving the quality and sustainability of production
processes, reducing costs in the production process, improving the multiple
flows of processes, and increasing productivity, and it has demonstrated the
applicability of LM tools in I4.0. However, the only area of industry 4.0 that
receives the LM tools is the virtualization layer (cyber-layers). It is
believed that this is due to a more computational nature of the LM tools that
are used in the optimization processes, for example in constraints variables in
operational research problems.
The next steps in this research
include understanding the reason why LM tools are found in applications only
assisting the computational process in the virtualization layers in I4.0.
6.
ACKNOWLEDGMENT
This work was carried out with the
support of IFRJ and CNPq. The authors of the article
are grateful to IFRJ and CNPq for the scholarship
granted and for their contribution to the development of Brazilian scientific
research.
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