Process Improvement Proposal for the Distribution Management to
Reduce Lead Time Using 5S, SMED and Autonomous Maintenance
in a Plastic Company
Maria Alejandra Alamo Matos
a
, Ximena Fernanda Espiritu Gonzales
b
and Alberto Flores-Perez
c
Keywords: SMED, 5S, Autonomous Maintenance, Plastic Indutry, Lead Time.
Abstract: The plastic industry in Peru has grown by 4.5% in recent years, causing great competition among the different
companies that exist. In this regard, the most common problem in the industry is low productivity, which
causes companies to be unable to meet the lead time agreed with customers. Faced with these difficulties, this
study proposes the implementation of Lean Manufacturing tools, specifically Autonomous Maintenance,
SMED and 5S, seeking to eliminate waste and mainly reduce lead time. The results demonstrate the feasibility
of using these methodologies. An improvement of 88% was obtained in comparison with the current situation
that represents 70% of order fulfillment. This happens due to the increase in productivity to 86.83%, waste
reduction to 6.74% and increased equipment efficiency to 86.33%.
1 INTRODUCTION
In Peru, the plastic industry is considered to belong to
the non-primary manufacturing industry by “Banco
Central de Reserva del Perú.” In this country, the
industry has significantly grown by 4.5% in recent
years (Instituto de Estudios Económicos y Sociales,
2019), generating more than 650 thousand jobs
(Población Ocupada, Según Ramas de Actividad,
Tamaño de Empresa y Categoría de Ocupación,
2007-2020, n.d.). The article emphasizes the need to
accelerate production systems and the proper use of
resources in emphasized, since these produce
negative economic impacts (Fernández Marca et al.,
2020). Therefore, the results show that it is necessary
to increase productivity to guarantee order fulfillment
(Ames et al., 2019).
The problem, according to the literature, can
occur due to several factors such as low productivity,
high amount of waste, equipment downtime, among
others (Flores Barbarán et al., 2020), which leads to
the need to improve processes in companies in the
industry due to increased customer requirements
(Ribeiro et al., 2019). This problem has been noticed
a
https://orcid.org/0000-0002-6629-3331
b
https://orcid.org/0000-0002-2953-1783
c
https://orcid.org/0000-0003-0813-0662
in different studies worldwide. For example, a
company in the same industry in Portugal presented a
high number of complaints from customers due to
low performance, availability of equipment, low
productivity and employee autonomy (Ribeiro et al.,
2019). Another article from India found that orders
were not being met on time due to misuse of
resources, poor staff involvement, and inadequate
maintenance (Shukla, 2018). Therefore, it is shown
that companies that produce plastic products need
solutions for the different exposed problems.
On this basis, it is essential that these companies
seek to be more efficient in order to achieve the
planned results. For this purpose, a case was chosen
to demonstrate the problems of the plastic industry
regarding the delay in lead time orders due to low
productivity, poor equipment maintenance and high
percentage of waste, waste that generates monetary
losses of 7% of the utility from the study company.
Therefore, in order to provide a solution to the above,
an improvement model was proposed using Lean
Manufacturing tools specifically Autonomous
Maintenance, SMED and 5S. This improvement was
carried out with the support of projects that have been
Alamo Alamo, M., Espiritu Gonzales, X. and Flores-Perez, A.
Process Improvement Proposal for the Distribution Management to Reduce Lead Time Using 5S, SMED and Autonomous Maintenance in a Plastic Company.
DOI: 10.5220/0012055700003612
In Proceedings of the 3rd International Symposium on Automation, Information and Computing (ISAIC 2022), pages 807-811
ISBN: 978-989-758-622-4; ISSN: 2975-9463
Copyright
c
2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
807
successful with similar difficulties as the case study
of Diana Fernandez and Karla Mostacero (2021),
which seeks to increase the capacity in their
production process, using 5S to standardize the order
and cleanliness, SMED to reduce their times, and
TPM to gradually obtain a system with zero
breakdowns (Fernández Marca et al., 2020). Finally,
there are very few scientific articles with relevant
information about the mentioned problem in the
industry, being the main motivation to carry out the
corresponding study.
This scientific article is divided into five parts,
which are Introduction, State of the Art, Contribution,
Validation and Conclusions.
2 STATE OF THE ART
2.1 Autonomous Maintenance
Autonomous Maintenance is one of the six pillars of
Total Productive Maintenance (TPM), which aims to
teach workers to keep equipment safe through
activities established in a schedule (Ames et al.,
2019). Likewise, this tool seeks that production does
not stop even when the machine faces serious
problems (Acharya et al., n.d.). On the other hand,
with the application of this pillar, the operators will
have the possibility of being in charge of the
maintenance so the maintenance technicians will be
able to use their time in more serious activities
(Fernández Marca et al., 2020).
2.2 Single Minute Exchange Die
(SMED)
The Single-Minute Exchange Die or better known by
its acronym SMED was developed by Shigeo Shingo,
who sought to reduce changeover times on machines
(San Antonio Ignoto et al., 2018). SMED is effectively
used to improve quality and accelerate lead time to
meet customer needs (Haddad et al., 2021). For its
implementation in an industrial company there are
seven steps, starting with the observation of the
current situation, followed by staff training, creation
of an equipment programming schedule, data review
on mold changeover times, data collection on
improvement times for later comparison, application
of the proposed improvements and finally, in the last
step the collection of information on the implemented
improvements, including the staff training (Cervantes
Esparza & Zorilla Briones, 2018). In addition, the
methodology is defined by four phases. In phase zero
there is no difference between the internal and external
operation of the setup. Phase one separates the internal
and external operation. Phase two convert internal
operations to external. Phase three apply the
improvement of all the setup operations (Antosz &
Pacana, 2018).
2.3 5S
The 5S tool was created by the Japanese engineer
Shigeo Shingo. This methodology combines five
steps which ensure that the environment is kept clean,
safe, and efficient (Ribeiro et al., 2019). The five
phases are called Seiri, Seiton, Seiso, Seiketsu and
Shitsuke, which in English mean Sorting (separate
what is not used), Organizing (assign a place for each
element), Cleaning (leave the environment in optimal
conditions), Standardization (standardize operations)
and Discipline (ability to do things while respecting
established guidelines) (Shahriar et al., 2022). The
application of this Lean Manufacturing tool is crucial
as it helps to achieve productivity improvements in
the work environment with less human effort,
equipment, space and time (Fernández Marca et al.,
2020).
3 CONTRIBUTION
3.1 Basis
For the proposal development to improve the lead
times of orders in the company of the plastic industry,
references of several scientific articles related to Lean
Manufacturing tools, mainly 5S, Single Minute
Exchange of Die (SMED and Autonomous
Maintenance, were considered. Compared to other
studies, this one focuses on the development of the
worker regarding the use and solution of machinery
failures. In addition, waste management proposal was
added. Next, the comparative matrix between the
causes of the proposed model and the state of the art
is shown below.
ISAIC 2022 - International Symposium on Automation, Information and Computing
808
Table 1: Comparative matrix of causes of the proposal vs.
State of the art.
3.2 Proposed Model
The proposed model is based on the implementation
of three tools, 5S, SMED and Autonomous
Maintenance in the production process to improve the
order fulfillment on time. At the same time, the
impact of the application of these will be positive on
productivity, equipment efficiency and the output of
defective products. Likewise, the model was
developed in three phases: diagnosis, proposal, and
implementation.
Figure 1: Proposed model.
3.3 Model Components
3.3.1
Component 1: Diagnosis
The first phase, called Diagnosis, was based on the
collection of the company’s historical data. Limits
were established with the help of the SIPOC tool,
Pareto and Ishikawa diagrams were applied to
determine, the main problem and its root causes, and
more precise causes were obtained with the 5 whys
tool. In addition, with the objectives tree it was
possible to have a broader view and thus, a better
analysis of the information.
3.3.2 Component 2: Proposal
The second phase, called Proposal, was based on the
tools chosen to be implemented. With the literature
review, it was possible to decide which tools were the
most appropriate for the case of study. It was
determined the use of 5S to reduce the number of
defective products, Autonomous Maintenance to
reduce failures in the company’s machines and
SMED to reduce downtime.
3.3.3
Component 3: Implementation
- 5S implementation
For the 5S application, it was divided into the stages
the Seiri (Sorting), Seiton (Organizing), Seiso
(Cleaning), Seiketsu (Standardize) and Shitsuke
(Discipline) to reduce the number of defective
products.
- Autonomous Maintenance implementation
The autonomous maintenance application was used to
reduce failures in the blow molding machine,
establishing schedules and training plans so that
operators act with knowledge in case of problems and
avoid unnecessary downtime.
- SMED implementation
To reduce the downtime due to low productivity,
SMED was applied. By following the seven steps of
this methodology, times could be reduced, as well as
increasing the process efficiency and reducing lead
times.
Finally with the use of the Arena software the
simulation of the implementation was carried out.
The results were evaluated by indicators.
3.4 Indicators
To measure the impact caused by the improvement
tools, four indicators were used to analyze the results.
They are detailed below.
3.4.1
Order Fulfillment
This is used to measure the number of orders
delivered in relation with the agreed date.
∗ 100 (1)
Process Improvement Proposal for the Distribution Management to Reduce Lead Time Using 5S, SMED and Autonomous Maintenance in a
Plastic Company
809
3.4.2
Overall Equipment Effectiveness
Provides insight of the machine efficiency
𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦 ∗ 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 ∗ 𝑄𝑢𝑎𝑙𝑖𝑡𝑦
(2)
3.4.3
Productivity
It allows to measure how productive a process is in
accordance with time.
∗ 100 (3)
3.4.4
Rework Level
It allows to know the number of reprocessed units
produced.
∗ 100 (4)
4 VALIDATION
4.1 Initial Diagnosis
It was determined in the initial diagnosis that there is
a technical gap in the order fulfillment. Currently, the
company under study complies with 70% of its
orders, compared to the general index of the industry
that represents 85% compliance. Therefore, in order
to increase productivity and the percentage of order
fulfillment, the main causes of the problem were
addressed: (a) insufficient maintenance, (b) output of
defective products, (c) inefficient employee. The
following are the results of the data obtained from the
current model and what we wanted to achieve with
the application of the proposed model.
Table 2: Average values of the indicators.
Indicators Current Objective
Order Fulfillment 70 % 85%
Overall Equipment
Effectiveness
(
OEE
)
68.24 % 85%
Productivit
y
69.05% 85%
Rework Level 9.81 % 6%
4.2 Validation Design and Comparison
with the Initial Diagnosis
For the validation design and comparison with the
initial diagnosis, two schemes were made. One of the
current model that represented the output process of
the bottles from the blow molding machine and its
output from the process as packages containing 300
bottles ready to continue to the next process. And
another off the proposed model containing the
implementation of 5S tools to reduce the number of
defective products, SMED to reduce downtime and
Autonomous Maintenance to reduce machine
failures. With the application of these tools, it was
also possible to reduce the number of processes and
resources compared to the current model.
4.3 Simulation of the Proposal
The model simulation was developed in Arena
software to validate the results and corroborate the
performance. The number of replicates was
determined in 330 times with the Input Analyzer
software wand the collected data. The proposed
model simulation is presented in Figure 2 below.
Figure 2: Diagram of the proposed model.
The simulation diagram shows the elimination of
activities that did not add value. At the same time, the
production work is only centered on the operator due
to Autonomous Maintenance and SMED.
Table 3: Actual indicators vs Improved situation.
Indicators Current Improvement
Order Fulfillment 70 % 88%
Overall Equipment
Effectiveness (OEE)
68.24 % 86.33%
Productivity 69.05% 86.83%
Rework Level 9.81 % 6.74%
The results obtained showed an 88% in the order
fulfillment percentage, verifying the effectiveness of
the 5S tools, Autonomous Maintenance and Single
Minute Exchange of Die implementation and
demonstrating the improvement of all the indicators
when applying them.
ISAIC 2022 - International Symposium on Automation, Information and Computing
810
5 CONCLUSION
The implementation of the model that applies the
Lean Manufacturing methodology allowed to
improve the productivity index by 17.78% and thus
an 18% increase in the order fulfillment on time.
Therefore, demonstrating the viability of the
improvement proposal and its possible application in
companies of the same industry.
In turn, it was found that the application of these
tools managed to exclude activities that did not
generate value, eliminate waste, and reduce time.
In the future, it is recommended to carry out a
good diagnosis and data collection to be able to
determine more easily the problem and its main
causes, and thus obtain more accurate results.
Likewise, to validate the improvement of process
optimization with the use of Lean Manufacturing
tools in different scenarios using other equipment
such as the injection molding machine.
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Process Improvement Proposal for the Distribution Management to Reduce Lead Time Using 5S, SMED and Autonomous Maintenance in a
Plastic Company
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