Available via license: CC BY
Content may be subject to copyright.
*
Corresponding author: nihlahz@gmail.com
Lean Manufacturing: Waste Reduction Using Value
Stream Mapping
Zahrotun Nihlah
1,*
, Taufiq Immawan
2
1
Department of Industrial Engineering, Faculty of Engineering, Diponegoro University, Semarang – Indonesia
2
Department of Industrial Engineering, Faculty of Industrial Engineering, Universitas Islam Indonesia, Yogyakarta –
Indonesia
Abstract. Cristal Sri Sujarwati is a small medium enterprise (SME) that produce keripik
salak in Sleman, Yogyakarta. To survive and win industrial competition, Cristal Sri
Sujarwati was required to improve its performance. But in reality there was a lot of waste
in order fulfillment processes marked by ineffective and inefficient work. In this research,
lean manufacturing aims to identify and eliminate waste so that the company could
improve its performance in winning the industry competition. Lean manufacturing is a
systematic approach used to identify and eliminate waste. This lean concept could improve
responsiveness through waste reduction, continuous improvement and cost reduction. In
order to identify and eliminating waste, a value stream mapping tools, waste weighting
questionnaire, value stream analysis tools, and fishbone diagram are used. From the results
of research, the dominant waste in the production process was waste defects, waiting, and
unnecessary inventory. To eliminate waste, process activity mapping (PAM), the one of
detailed mapping tools in VALSAT are used. From the results of the improvement
recommendations analysis, lead time decreased by 80 minutes. From the analysis using
PAM, there was a reduction of NVA activity from 3.10% to 1.01%.
Keywords: Lean Manufacturing; Process Activity Mapping; Value Stream Mapping;
VALSAT; Waste.
1 Introduction
Efficiency and competitiveness of a company are the two
most important challenges in the global market. This
makes many manufacturing companies are competing to
update its manufacturing strategy management. The
problems most commonly faced manufacturing
companies today is how to deliver a product or material
with fast, cheap, and with good quality. Some methods
or approaches such as computer simulation, statistical
analysis, and lean tools are used to improve efficiency
and productivity by determining the best combination on
the production line process of construction, energy,
services and supply chain. Increased efficiency and
productivity is done so that the company can survive and
win industry competition [1].
Cristal Sri Sujarwati is one of a Small and Medium
Enterprise (SME), that produces a variety of food from
salak in Sleman, Yogyakarta. In orders fulfillment,
companies often have difficulty because there is waste in
the production process that are not identified. Waste is
defined as all activities that consume time, space and
resources but does not contribute to satisfying the needs
of consumers [1]. Identification of waste needs to be
done in order to know what waste it is in the production
process, and to do improvements.
In that case, as an effort to solve the problem, lean
manufacturing concept is applied. This concept is one
approach that is widely used by manufacturing
companies to be able to win the competition and meet
the high demands of consumers. This concept is used to
improve business responsiveness through waste
reduction, continuous improvement and cost reduction
[1]. The aims of this study is to identify what kind of
waste in the order fulfillment; determine the precise
detailed mapping tools to reduce waste; propose the root
cause of waste and improvement planning; determine the
comparison of lead time before and after the production
process improvement.
2 Literature Review
2.1 Lean Manufacturing
Lean is a continuous improvement to eliminate waste
and increase the value-added (VA) products both goods
and services to provide value to customers [2]. Lean
https://doi.org/10.1051/e3sconf/2018730
,0(2018)
E3S Web of Conferences
73
ICENIS 2018
70 7010
10
© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0
(http://creativecommons.org/licenses/by/4.0/).
manufacturing can be defined as a systematic approach
to identify and eliminate waste or non-value added
(NVA) through continuous improvement by delivering
products (materials, WIP and output) and information
using pull or pull systems [3].
In lean manufacturing approach, there are three
activities that must be differentiated, namely:
a. Activities that do not provide added value (non value
added) and can reduced or eliminated.
b. Activities that do not add value but can not be
eliminated, or necessary (necessary non value added).
c. Activities that provide added value (value added).
2.2 Waste
The main principle of the lean concept is to reduce or
eliminate waste. Waste is an activity that does not
provide value added (value added) in the process along
the value stream [4]. According to Toyota's Production
System (TPS), there are seven things categorized as
waste [5], i.e:
a. Overproduction, producing more than needed and
excess stock is overproduction waste [5].
b. Defect, rejected/ defective finished products can
disrupt production and require expensive rework.
c. Waiting or idle time includes waste. This is because
it does not add value to the product.
d. Transportation, includes the transfer of goods/
materials are too frequent and delay the movement of
material. The main cause of excess transport is the
plant layout [2].
e. Inappropriate Processing, includes unnecessary
processes or procedures, goods production but does
not add value to the product itself.
f. Unnecessary Motion, poor organizing work stations,
resulting in poor ergonomics. The motion of someone
who is not directly related to the added value is
unproductive.
g. Unnecessary Inventory, finished products, semi-
finished goods, or components with inventory status
do not add value.
2.3 Value Stream Mapping (VSM)
Value Stream Mapping (VSM) is a visual method for
mapping the production line of a product that includes
material and information from each work station. Using
VSM means getting started with a big picture in solving
problems not just on single processes and improving
thoroughly and not just on certain processes [3].
According to [6], VSM consists of two types that can
help to make real improvements, namely:
a. Current State Map (CSM), is the current product
value stream configuration, uses specific icons and
terminologies to identify wastes and areas for
improvement.
b. Future State Map (FSM) is a blueprint for the desired
lean transformation in the future after the waste
identification and elimination.
2.4 Value Stream Analysis Tools (VALSAT)
Value stream analysis tools (VALSAT) are used to
analyze the identified waste. The VALSAT concept is
used in the selection of detailed mapping tools by
multiplying the waste weights from WAQ (Waste
Assessment Questionnaire) with the scale shown in the
VALSAT table [8].
The following are the most commonly used detailed
mapping tools for waste analysis:
a. Process Activity Mapping (PAM) is a tool for
mapping the production process in detail that is used
to determine the proportion of activities grouped in
value added (VA), necessary non-value added
(NNVA), and non-value added (NVA).
b. Supply Chain Response Matrix (SCRM), is a graph
that connects between cumulative inventory with
cumulative lead time on the distribution channel used
to determine the increase or decrease inventory levels
and lead time lengths at the time of distribution of
each supply chain area [9].
c. Production Variety Funnel (PVF), is a visual
mapping technique where in a sequence of processes
there is an increase in product variation.
d. Quality Filter Mapping (QFM), is a tool used to map
where quality problems arise in an existing supply
chain [10].
e. Demand Amplification Mapping (DAM), a tool used
to map patterns or demand changes in each supply
chain [10].
f.
Decision Point Analysis (DPA) is the point where
there is a change in the trigger of production
activities that initially based on the forecast to be
based on orders [10].
g. Physical Structure (PS), is a tool that used to
understand the condition of the supply chain on the
production floor [5].
2.5 Fishbone Diagram
Fishbone diagrams are used to identify and show
possible causes of problems and especially when a team
tends to fall into thinking on a routine [7]. Figure 1
below is a picture of fishbone diagram with 5M and 1E
factors that are often used:
Fig. 1. Fishbone Diagram [11]
3 Methodology
In this study the research methodology conducted by
stages as follows:
https://doi.org/10.1051/e3sconf/2018730
,0(2018)
E3S Web of Conferences
73
ICENIS 2018
70 7010
10
2
Stage of data collection and processing is done by
interview, observation with a direct view on the field and
questionnaires. Data collected include: 1. Information
products; 2. Data flow infromation and material; 3.
Details of the production process; 4. The cycle time; 5.
Identify waste. Stages of data processing are divided into
several steps, among others:
3.1 Value Stream Mapping (Current State)
Current state mapping used to determine the initial
conditions of the production processes prior to repair,
and used to identify other types of waste, which is used
as a reference for improvement.
3.2 Waste Identification - Weighting
Questionnaire
At this stage the author makes a waste-weighting
questionnaire, which is used to identify the most
dominant waste in the system. Weighting is done by
assigning value to each waste, using Likert scale
according to the frequency level that occurs during the
production process.
3.3 Value Stream Analysis Tools (VALSAT)
VALSAT (Value Stream Analysis Tools) helps in
determining the detailed mapping tools that will be used
to reduce the dominant waste during the production
process. With the percentage of the most dominant waste
weight as VALSAT input, the stages are:
a. Changing the scale of linguistic H, M and L on
VALSAT into a numerical scale on the columns
value stream map.
b. Input the weight of each type of waste based on the
waste identification output on the VALSAT.
c. Multiply the weight of waste at waste weighting with
a numerical scale for each column value stream
mapping tools with numeric scale multiplier.
d. Summary the result of the multiplication of each
column value stream mapping to determine what the
greatest.
e. Select the greatest value for the detailed mapping
using the right tools.
f. Waste identification using selected tools for the
analysis and conclusion.
3.4 Fishbone Diagram
Fishbone diagrams can identify and show possible
causes of problems, especially when a team tends to fall
into thinking on a routine. The stages are as follows:
a. Selecting or collecting potential waste problems
experienced.
b. Identifying the cause categories.
c. Finding the cause of a potential by way of
brainstorming.
d. Review and agree on the causes most likely.
3.5 Improvements Recommendation
Provide recommendations for improvement to eliminate
the most dominant waste. Recommendations for
improvements should be implemented in actual
conditions and should also be effective in eliminating the
dominant waste
3.6 Comparison of Actual Condition and
Recommendations Condition
This phase is intended to determine the extent of repairs
carried out successfully. Comparisons the lead time
before and after improvements intended to see the
potential of the company if the waste is eliminated. The
stages are:
a. Calculating lead time of the actual conditions by
using cycle time before the repair.
b. Calculating the cycle time and lead time after
repairs on the future state map by eliminating non-
value adding.
c. Doing a comparison of cycle time and lead time
before and after repair.
4 Result And Discussion
4.1 Current State Mapping
Current state mapping (CSM) is a description of the
operating conditions that occur in the production process
at this time. CSM describe the production process from
beginning to end, so the issues that involved can be
know, and do analyze their waste in the process. Figure 2
shows the current state map of keripik salak.
Fig. 2. Current State Mapping
4.2 Waste Identification
Waste identification is done by distributing
questionnaires to the employees who understand the
impact and keripik salak production process regarding
the level of frequency of waste that occurred. The waste
weighting results can be seen in Figure 2.
https://doi.org/10.1051/e3sconf/2018730
,0(2018)
E3S Web of Conferences
73
ICENIS 2018
70 7010
10
3
Fig. 3. Percentage of Waste Weight
4.3 Value Stream Analysis Tools (VALSAT)
After obtained a score of each waste, then converted into
a matrix VALSAT to get the detailed mapping tools that
will be used. Furthermore, the results VALSAT
conversion matrix can be seen in Figure 4.
Fig. 4. Detailed Mapping Tools Score
4.4 Process Activity Mapping (PAM)
Process Activity Mapping (PAM), is a tool used to map
the detail of production process and then used to
determine the proportion of activities grouped in value
added (VA), Necessary non value added (NNVA), and
non-value added (NVA). By grouping their production
line activities, PAM is used to identify the waste that
occurs in every process. In this tools, the existing
activity at each work station are grouped into five types
of activity, namely O (Operation), T (Transportation), I
(Inspection), S (Storage), D (Delay).
Based on PAM production process of keripik salak,
Table 2 below is the recapitulation time and percentage
of each activity category:
Tabel 2. Recapitulation of Process Activity Mapping
Activities Total Time Percentage
Operation 12 624 80,72%
Transportation 14 49 6.34%
Inspection 1 12 1,55%
Storage 1 10 1.29%
Delay 12 78 10.09%
Total 40 773 100%
Classification Total Time Percentage
VA 13 641 82.92%
NNVA 14 108 14.62%
NVA 13 24 2.46%
Total 40 773 100.00%
4.5 Fishbone Diagram
According to the waste identification in the previous
section, the most dominant waste in this company is
defect, waiting and unnecessary waste inventory. The
causes of each waste can be seen in the next section,
namely Improvement Recommendation.
4.6 Improvement Recommendation
The following recommendations for improvements are
made by identifying the causes of waste using fishbone
diagrams and eliminating NVA activities based on
established PAMs. Recommendations for improvements
made to eliminate the dominant waste and NVA
activities in order fulfillment processes. Here are
recommendations for proposed improvements:
4.6.1 Eliminating Waste
Based on the problems described in the previous section,
the elimination of waste from waste identification can be
seen in Table 3 below:
Tabel 3. Improvement Recommendation
Sub
Waste Causes Secondar
y Causes
Recommendations
for Improvements
Defect Raw materials
not suitable
Passed
sorting
Reselection of
suppliers and
tightening up on
sorting raw
materials
Final product
passes
inspection
limitation
s visual
Tightening final
product inspection
and making quality
control card
Power outages
from center
No
notificati
on
Request
notification
blackout or buy
diesel
Waitin
g
The production
process depend
on the arrival of
raw materials
- -
Available
supplier
- Selection of
suppliers
The raw
materials can
not be predicted
From
nature
and
seasonalit
y
-
Unnece
ssary
Invento
ry
System order to
stock
Resource
utilization
Making another
type product
Lack of
machine
- Making a job
descriptions and
SOP for each work
stations and
https://doi.org/10.1051/e3sconf/2018730
,0(2018)
E3S Web of Conferences
73
ICENIS 2018
70 7010
10
4
Sub
Waste Causes Secondar
y Causes
Recommendations
for Improvements
operators
The raw
material is not
within
specifications
Order to
stock
Making another
type product
4.6.2 Eliminating NVA Activities
This stage is done by eliminating activities that are
categorized as non value adding, so that production time
can be reduced. In addition, efforts to shorten production
lead time is also done by changing the sequence of
activities that are not efisien and increase the number of
operators in activities which require more work load.
4.6.3 Future State Mapping
FSM (Future state mapping) conditions are ideal targets
to be achieved. According to the improvement
recommendations in the previous section, the following
is a comparison of cycle time between the current state
and the future state by eliminating the NVA activity.
Tabel 4. Comparison of Total Cycle Time
Process
Average
Cycle Time
CSM FSM
Sorting, weighing and
entry
20 18
Stripping the bark 48 30
Peeling of Ari Skin and
Cleavage
107 70
Washing 14 10
Water seeping 8 5
Frying 358 343
Oil seeping 10 10
Storage 16 16
Packaging 192 191
Based on the average cycle time in the Tabel 4, then
created the future state map in figure 8:
Fig. 5. Future State Mapping
4.7 Comparison of Actual Condition and
Conditions Recommendations
According to the elimination of waste and NVA
activities using PAM, obtained comparison a lead time
between actual conditions (CSM) and the
recommendation condition (FSM). Figure 9 shows a
comparison of lead time on the CSM and FSM:
Fig. 6. Comparison of Current State Mapping and Future State
Mapping
5 Conclusion
Based on the result, dominant waste in the keripik salaks
production process is defect, waiting and unnecessary
inventory. PAM is the chosen VALSAT mapping tools
with total score 558.1 and there is a VA activities
amounted to 82.92%, NNVA amounted to 14.62%, and
the NVA amounted to 2.46%. The improvement
recommendations can be seen in Tabel 3. In future state
mapping, the lead time was reduced from 773 minutes to
NVA 3.10% to 693 minutes with NVA 1.01%. This
research has contribution to develop low carbon society.
Waste reduction, especially overproduction and
transportation give direct impact to reduce carbon
emissions. Further research, a study about waste
reduction can be done with lean and green supply chain
approaches.
References
1. M. L. Singgih, M. V. Permata, P. Sem. Nas. Man.
Tek, VII, 1-11, (2008).
2. V. Gaspersz, Lean Six Sigma For Manufacture and
Service Industri, (Jakarta: Gramedia Pustaka Utama,
2007).
3. S. Batubara, F. Kudsiah, J Tek. Ind, 147-159,
(2015).
4. H. Soenaryo, Rispianda, Y. Yuniati, J. Onl. Inst.
Tek. Nas, 03, 92-103, (2015).
5. P. Hines, N. Rich, Inter. J. of Oper. & Prod. Man,
46-64, (1997).
6. T. M. Aken, Val. Strm. Mapp: A Rev. and Comprtv.
Anlyss. of Rcnt. App, (2010).
7. N. R. Tague, The Quality ToolBox, Milwaukee,
Wiconsin: ASQ Quality Press, 2005).
8. M.R.F. Rochman, Sugiono, R.Y. Efranto, J. Rkys.
dan Man. Sist. Ind, 02 (04), 907-918, (2014).
https://doi.org/10.1051/e3sconf/2018730
,0(2018)
E3S Web of Conferences
73
ICENIS 2018
70 7010
10
5
9. A.W. Nuruddin, Surachman, N.W. Setyanto, R.
Soenoko, J. Rkys. Msn, 4 (2), 147-156, (2013).
10. I.N. Pujawan, Supply. Chain. Managament.
(Surabaya: Penerbit Guna Widya, 2005).
11. W.D. Ariani, Penendalian Kualitas Statistik, (Andi,
2004).
12. R.A. Saputra, M.L. Singgih, P. Sem. Nas. Man. Tek,
XV, 1-8, (2012)
https://doi.org/10.1051/e3sconf/2018730
,0(2018)
E3S Web of Conferences
73
ICENIS 2018
70 7010
10
6
