Rui
M.F.Dias
A&I,
Portugal
rdias1263@hotmail.com
Luis
Diogo Silva
UNIDEMI,FCT,UNL, Portugal
ld.silva@campus.fct.unl.pt
Alexandra
Tenera
UNIDEMI,FCT,UNL, Portugal
abt@fct.unl.pt
Submission: 23/04/2018
Revision: 08/05/2018
Accept: 25/07/2018
ABSTRACT
The
current market, becoming more rigid, forces companies to search continuously
for innovation and improvement of their processes and products as a way to keep
competitive and gain strategic advantages. Due to the global economic crisis,
more and more companies try an approach through new management methodologies
that allow better performances in terms of earning, profit and cost reduction.
The present article proposes an integrated TOC (Theory of Constraints), Lean
and Six-Sigma (TLS) model, with the objective of improving continuously a
productive system, although it shows flexibility to be applied in other kinds
of systems. The model synergistically integrate the best practices found in existing
TOC, Lean and Six-Sigma models. The proposed model derivatives mainly from
Eliyahu Goldratt’s TOC model of the “5 focus steps” and TLS model “Ultimate
Improvement Cycle”, developed by Bob Sproull. The proposed TLS model was tested
on an important Portuguese Manufacture. The implementation of a first
continuous improvement cycle was completed and a second cycle began. The main
results obtained by the implementation of the TLS model were extremely
satisfactory.
Keywords: Continuous
Improvement; TOC; Lean; Six-Sigma; TLS
1. INTRODUCTION
The XX century was of extreme importance to the industrial world
where three big production paradigms
arised and which are still decisive in the way managers administer industrial
plants and their processes till nowadays (JACOBS; CHASE; AQUILANO, 2009).
From those new paradigms, came
some new methodologies that through continuous improvement cycles can create
satisfactory results on productive system’s performances. Current studies prove
that the most effective continuous improvement systems in terms of costs
reduction are gaining market share and improving quality currently are the
models that combines the Theory of Constraints, Lean and Six-Sigma
methodologies (PIRASTEH; FARAH, 2006; SPROULL, 2009).
Those models are known as TLS models.
On this paper, one TLS model is presented and the results of the
proposed model tested in a real Lean productive system are shown. The model was
built after reviewing each methodology by itself and the TLS existing models.
Then, the three main classic improvement methodologies were compared and the
converging characteristics were analysed, in order to make them merge
synergistically.
A brief exploitation was made of the existing integrative TLS models and
the best practises found on each model were resorted to be able to build a
logic model. The main objective of creating a continuous improvement model was
to improve an existing Lean productive system of an important Portuguese
manufacturer.
The best state of the art found during the review of the models, which
integrate the Theory of Constraint, Lean and Six Sigma, use TOC to focus and
identify system constraints and some Lean and Six Sigma (LSS) tools which are
mainly utilized to eliminate waste and reduce variability in the constraint
step.
2. BRIEF THEORETICAL REVIEW ON CONTINUOUS IMPROVEMENT
SYSTEMS
The biggest goal of continuous improvement systems is to concretize all
the objectives defined by an organization in a systematic, consistent and
gradual way (PEREIRA; REQUEIJO, 2012).
2.1.
Theory
of Constraints
TOC was developed firstly as an Optimized Production Timetables
scheduling software in 1979 and five years latter its model was conceptualized
on the bestseller “The Goal” by Goldratt and Cox (GOLDRATT; COX, 2004). The
basic concept of TOC is often introduced through the chain analogy, where the
chain is only as strong as its weakest link. So, any improvement that does not
improve the performance of the weakest link most likely will not improve the
system and can be considered waste (DAVIES; MABIN, 2009).
TOC is more than a system to find constraints; TOC is a continuous
improvement system to improve and manage the system constraint performance in
the global context, trying to achieve overall system improvement and not just
localized improvements. TOC is a system focus, first on the system’s leverage
points (constraints) and then on how all parts of the system that impact on the
operation of the leverage points.
Constraints could be physical if the issue is related to equipment,
materials or resources or politics if caused by the market, policy of
management, roles, standards or measures (LUCAS; TENERA, 2014).
The TOC evolved from the production planning technology to a system of
managing tools that integrates the areas of logistics, production, project
management, finances, accounting, performance measurement, distribution and
supply chain, marketing, sales and problem resolution (COX; SCHLEIER, 2010).
The TOC as a methodology of continuous improvement uses a set of tools
that aim to promote and elevate the performance of the systems, grouped in
Table 1 in four main quadrants:
Table 1:
Schematic Synthesis of TOC
Source: adapted from Tenera, (2006)
In
the model presented in this paper we use two different tools of TOC methodology
·
Five Focusing Steps – Figure 1
Figure 1: Goldratt’s
five focus steps model
The five steps can be briefly described as (TENERA, 2006; PRETORIUS, 2014).
a) Identify
the system’s constraint – It’s identified which process or processes limit all
system’s performance;
b) Decide
how to exploit the constraint – It should be answered to the question: “How to
make the constraint the most efficient possible? At this moment it’s not
resourced to financial investments and the constraint should be “squeezed” at
his full potential.
c) Subordinate
everything else to the above decision – This step insurances that all the other
as processes
work in order to support the constraint even if through losing some of its own
capacity. The recommended tool to be applied on this step is DBR.
d) Elevate
the system’s constraint – The constraint’s performance
is potentiated. One way to improve is by investing in new resources.
e) Evaluate
constraint – It’s verified in this step if the capacity of the constraint is
now superior to demand this means if the constrain has been broken. In that
case the improvement cycle closes and returns to step 1 but can’t allow inertia to become the
new system constraint. Otherwise returns to step 4 and elevates the capacity
until the process is no longer the constraint.
·
Drum – Buffer- Rope (DBR) – Figure 2
Figure 2: Drum-Buffer-Rope
Source: adapted from Tenera, (2006)
DBR promotes the
constitution of strategic reserves (Buffer) in order to protect the Constraint
(Drum) and the synchronization of the flow through logistic mechanisms of alert
(Rope).
DBR is a hybrid
method of programming production, where the materials and components are pushed
into the production system through a system of communication called rope, which
aims to guarantee the supply of the buffer that allows the fluctuations that
can occur in the productive flow do not affect the performance of the constraint,
drum. (Tenera, 2006)
2.2.
Lean
Production
Lean appeared in the middle of XX century in Toyota associated with the
bigger complexity of processes. It covers since the conception and develop of
products, supply of materials, tools and components, productive processes until
the commercialization of products.
The emphasis of this methodology is given to the optimization of
processes, seek or elimination of non-value activities and on generation of
value to stakeholders (PIRASTEH;
FOX, 2010).
According to Womack and Jones there are 5 principles that define Lean (WOMACK;
JONES, 1996):
a)
Define Value from the perspective of the final
costumer;
b)
Identify the completed chain of value for each product
or family of products and eliminate waste;
c)
Take actions that make flow the activities that
generate value;
d)
Pull production to clients demand, this mean provide
what the customer wants, when he wants;
e)
Pursue perfection.
Identification and elimination of waste is the most fundamental aspect
to an organization that implements Lean. In Toyota’s production system, Shigeo
Shingo identifies 7 Muda that
correspond to the biggest wastes that don’t add value to the costumer, as show
and described on Table 2 (PACHECO,
2014):
Table 2:
Identification and description of the 7 Muda
Muda |
Description |
Recommended Lean Tools |
Overproduction |
Producing something when it’s not needed. Results in
excess of inventory, resources, energy and materials utilization. Generates
loss of planning flexibility. |
- Takt Time - Kanban - SMED |
Defects |
Production that needs reprocessing or being
eliminated. It’s caused by lack of quality, low performance or human
failures. Causes productivity decrease. |
- Jidoka - Poka-Yoke - Standard Work |
Unnecessary inventory |
Having a quantity of inventory superior to the immediate
needs, causes the unnecessary costs of material possession and lower
costumer’s service rate. |
- Just-in-time - Heijunka - Pull system |
Inappropriate processing |
Results in incompatibilities between the necessary
processes and tools to make a product. |
- Kaizen |
Excessive transportation |
Can be reduced by layout changing, transportation
system or alteration to a production cell. |
- VSM - Continuous flow |
Waiting |
Inactivity for a long period due to operators and
material and lack of information can result in a poor flow and increasing of
Lead Time. |
- Standard Work - Heijunka -SMED |
Unnecessary motion |
Bad organization of workplaces due to weak
ergonomics, lack of formation or demotivation of operators and inappropriate
layout. |
- 5S -VSM |
2.3.
Six-Sigma
Six-Sigma was developed initial by Motorola executives in the late 1980s
then some years later, it was exploited and developed by General Electric,
Honeywell and others companies (TENNANT, 2001).
Six-Sigma
is defined as a “business strategy used to improve business profitability, to
improve the effectiveness and efficiency of all operations to meet or exceed
customer’s needs and expectations”.
Applied for the first time in
manufacturing operations, it rapidly expanded to different functional areas
such as marketing, engineering, procurement, services, and administrative
support, as organizations perceived its benefits, especially when they
associated financial returns and cost reduction with implementation of Six
Sigma (PACHECO, 2014).
The methodology statistic basis is to try to optimize processes until an
efficiency rate of 99, 99966%, where a
process must not produce more than 3.4 defects per million opportunities.
The Greek letter σ (Sigma) correspond to a standard deviation of process
variability so in Six-Sigma it is intended that all processes own a variability
inferior to six standard deviation compared to the average of the process.
The most common improvement cycle used to apply Six-Sigma is the DMAIC
cycle as shown at Figure 3. Each
phase of the cycle and the recommended tools to apply in every of the five
phases are shown at Table 3 (KHANDEKAR;
SULAKHE, 2014):
Figure 3: DMAIC
cycle
Table 3: DMAIC cycle
phases, description and tools used
Phase |
Description |
Recommended Six-Sigma Tools |
Define |
Define with
precision the project where are identified the objectives and the scope. It
is chosen a team and decided the timeline. It’s important to define the
priorities of the client in matters of what he considers to have most impact
on quality. |
- Project
Charter - VOC (Voice of
Client) -Run Chart and
Flowchart |
Measure |
Define the
baseline of the project, so the location or focus of the problem. It is
defined the metrics to evaluate and the criteria of rejection in the
inspection method. Data of the system is collected and analysed. |
- Pareto chart - Control chart - Gage R&R
study |
Analyse |
For the main
problems that cause variability in the processes, the critical factors and
the root causes that are the origin of the variability are identified. It is
searched the tools that are able to continuously improve the process more
easily. |
- Ishikawa
diagram - DOE (Design of
Experiences) - FMEA Matrix - ANOVA |
Improve |
It’s proposed,
evaluated and implemented solutions to each problem found in a way to
eliminate defects and improve the process respecting the needs of the client. |
- Brainstorming - Opportunities
Flowchart - 5 Whys |
Control |
Ensure that the
solutions are reached with success and maintain sustained at long term. The
improvements should but standardized and the statistic control of processes
must be implemented. |
- Control Charts - Hypothesis
Tests - Audits |
2.4.
Integration
of Theory of Constraints, Lean and Six Sigma
All continuous improvement methodology brings competitive advantages by
itself for any company’s system.
The importance of the three philosophies, up until now
described, the gains and successes obtained with them, created in the users and
researchers the necessity to evaluate if the complementarity between the
methodologies may fill the individual weaknesses of each one and improve the
system performance.
These investigations, more than evaluating
convergences and complementarities, have essentially sought to integrate the three
methodologies, and creating more consistent models that promote the continuous
improvement of organizations.
Controlled
experiences on real industrial plants demonstrate that is possible to obtain
more considerable improvements when combining TOC five focus step model with
Lean and Six-Sigma, compared with applying each methodology isolated (PIRASTEH; FARAH, 2006).
It’s
possibly to increase the market share and without spending money due to the
benefits that Lean and Six-Sigma can bring integrated with the Theory of
Constraints (SPROULL, 2009). In a study proposed by Piratesh & Farah during
two and half years in 21 industrial plants, the ones that applied TLS
methodology obtained 4 times more profit than the plants that applied Lean or
Six-Sigma alone and the people involved in the implementation of TLS projects
showed more proud of the results obtain by the implementation (PIRASTEH; FOX,
2010), Figure 4 shows the results in
terms of contribution for cost reduction in each methodology:
Figure 4: Contribution for cost reduction in each
methodology
Source: adapted from Pirasteh and
Fox (2010)
The three main methodologies of improving systems
continuously present different methods to improve the productive process of the
organizations. In Table 4 is compared
the main aspects encountered on each one:
Table 4: Six Sigma, Lean and TOC comparative results
((Sproull, 2010), (Stamm, Neitzert, Singh, 2009), (AGI, 2009), (Pirasteh,
Farah, 2006))
The complementarities found in each methodology can be
synthetized as (PACHECO, 2014; OKIMURA; SOUZA, 2012):
§ Lean
focus on flow aiming the waste losses and adding value to customer. The
application of value flow mapping and problem resolution tools, with the
involvement of every hierarchical level, facilitates the cultural change to the
continuous improvement of the production systems.
§ Six-Sigma
focus on the problem that aims the variability and defects reduction originating
more stable and predictable processes. Due to his structured and disciplinary
statistical tools, to solve complex problems it leads to big improvements in
the quality of processes and in the design of new products.
§ TOC
supports in the identification of system’s constraints which should be the
focus of all improvements actions made through Lean and Six-Sigma. Managing the
constraint allows reduction of inventory besides the systematic
improvements. Owning to an accounting
system of gains it is possible to have an appropriated way of measuring the
improvements through performance measures (Gain, Inventory and Operational
cost).
2.5.
Brief
exploration of the main existing TLS models
The existing models have proved to be generic regarding to the destiny
where they can be applied. Although the focus of some models being on
productive systems, they can be adapted to be implemented on project management
or on services.
The most relevant models found are: Bob Sproull’s Ultimate Improvement
Cycle (UCI) (SPROULL, 2010), iTLS model introduced by Pirasteh & Farah in
2006 and revised in 2010 book “Profitability with no boundaries” by Pirateh
& Fox (PIRASTEH; FOX, 2010); TOCLSS model introduced by AGI and later developed in the book VELOCITY (AGI, 2009) and “Excelência
360º” model developed by Eduardo Moura (MOURA, 2010).
The first two models previously presented were the most used as basis in
the construction of the proposed model in this paper and for that reason they
are presented with more detail.
The
iTLS model uses the characteristics of TOC, to identify the constraint and
focus the improvement there to the optimization of the global system, elevate
the constraint and increase gains using the tools of Lean and Six-Sigma in a way to
eliminate waste and variability. It’s a continuous improvement model because it
works like a cycle, so after applying the efforts to eliminate the first
constraint, return to the begin to identify a new constraint and continue a
cycle. Figure 5 shows the 7 steps
existing in the models and the recommended tools and logics to be applied on
each step.
Figure 5: 7 Steps of iTLS model
Source: adapted from Pirasteh and
Fox (2010)
a. Mobilize
and focus – The stakeholders should get involved and the communication needs to
be open from the beginning between key-people involved. Efforts are made to
find the constraint with TOC tools and the root-cause must be analysed. It’s
decided where and how the efforts and which should be the expected returns.
b. Exploit
the constraint – Value Stream Mapping Lean tools and new performance indicators
are applied at this step.
c. Eliminate
sources of waste – After being identified the value, Lean tools are implemented
to eliminate waste, increase gains, reduce inventory and operational costs.
d. Control
process variability – on this step Six-Sigma tools are applied to reduce the
variability in critical processes. It’s important to control process
variability through statistical tools.
e. Control
supporting activities – standards and mechanisms are established to keep
critical processes under control. The processes that feed the constraint must
be subordinated to avoid failures in supply the constraint process.
f. Remove
the constraint and stabilize – ensure the correct application of the tools to
remove the constraint and stabilize the process.
The key to keep the process stable and controlled must lie on the
formation of employees.
It’s necessary to ensure that performance indicators are fulfilled.
g. Revaluate
the system – checking if the objectives initially defined were performed and if
there is a new constraint. The final situation is compared with the initial one
in terms of the appropriate indicators of performance.
Ultimate Improvement cycle combines harmonically the best practices in
each of the three main continuous improvement cycles. This integration of TOC,
Lean and Six-Sigma generates a powerful and rentable strategy for improving any
system. On Figure 6, it’s presented
the model and although appearing complex, it’s easy to interpret and follow:
Figure
6: Ultimate Improvement Cycle model
Source:
Adapted from Sproull (2009)
The model is focused on Goldratt’s 5 focus step model, in the 5
principles of Lean and in the 5 steps of DMAIC cycle that conciliate together a
continuous improvement model. In Table 5
each step of UIC model is described and showed the recommended tools to apply
on every step:
Table
5: Steps and tools in UIC model
Step |
Description |
Recommended
tools and actions |
1a) Identity Value Steam, current & next
constraint & Performance Metrics |
At this phase is characterized the value flow and
the constraint identified. Waste, defects and variation are defined, measured
and analysed. |
- VSM, Flow & Inventory Analysis, Performance
Metrics Analysis |
1b) Define, Measure & Analyse waste in current
constraint |
- Run Charts, Spaghetti Diagrams, Time & Motion
Studies, C & E Diagram, Future State VS Map |
|
1c) Define, Measure & Analyse Variation in current constraint |
- Pareto Charts, Run Charts, C & E Diagram,
Causal Chains |
|
2a) Plan How to Exploit current constraint |
Constraint is improved and stabilized in
simultaneous. The process will became more trustful, predictable and
consistent. |
- Plan How to Exploit current constraint |
2b) Reduce waste and Cycle Time on current
constraint |
- 5S, Processing Time Reduction, Mfg Cells,
Standardized Work, Visual Aids |
|
2c) Reduce variation and defects in the current
constraint |
- Problem Solving Roadmap, DOE, Paths of Variation
Reduction |
|
3a) Plan How to Subordinate Non-Constraints to
current constraint |
The flow of materials and information is optimized.
It’s necessary to solve problems that affect the consistency of the flow. |
- Plan How to Subordinate Non-Constraints to current
constraint |
3b) Reduce processing Time and Establish Flow |
- Improve Flow & Partial Line Balance (Time
& Motion Study) |
|
3c) Implement DBR, constraint buffer and Pull System |
Optimize Buffer Size and Time & Non-Constraint
Pull Systems |
|
4a) Plan How to elevate constraint and define
protective controls |
At this phase is necessary to insurance that all
changes and improvements are to stay in the future and cannot be wasted. |
- Plan How to elevate constraint and define
protective controls |
4b) Elevate the constraint if required |
- Perform Capacity Analysis and Cost/Benefit
Analysis |
|
4c) Implement protective controls to sustain the
gains |
- Perform Process Audit & Policy Analysis |
Source:
adapted from Sproull (2009)
3. A TLS MODEL TO PRODUCTION SYSTEM IMPROVEMENT
According to Sproull, the key of success of integrated TLS models it’s
in the first place to identify the constraint, and then to decide how to
exploit the constraint applying the appropriate Lean and Six-Sigma tools and in the third place subordinating all the
rest to the constraint and finally, if necessary, breaking the constraint with
monetary investment (SPROULL, 2009) .
The
proposed new model ment to grant flexibility in a way that could be applied on
any productive system even if it was previously improved by a Lean and/or
Six-Sigma project before (SILVA, 2015). A simplified sketch of the proposed TLS
model is presented in Figure 7
Figure
7: Simplified Sketch of TLS proposed model
The model presented in the previous figure can suit as roadmap for the
implementation of a continuous improvement project. As each project is
different when applying the model, it could be necessary to adapt it depending
on the output obtained at the end of each step. The model is flexible and there
are points where it’s required to take decisions and in some systems, it’s
possible to skip any step if the tools and logics indicated to implement at
that phase are already correctly applied.
Next, on this chapter every step of the proposed TLS model is described
in detail with the tools and logics recommended to be used at each step.
3.1.
Analyse
System and Identify Constraint – Figure 8
Figure
8: Step 1 of TLS proposed model
After identifying the system and its frontiers, the leader responsible
for the implementation of TLS project should characterize it thoroughly in a
way to obtain full knowledge about its operation. To get to Constraint’s
identification it’s recommended to:
§ Design
process diagram and obtained all information necessary to build a VSM in order
to understand the value of the existing flow in current system and determine
the existing Lead Time.
§ Promote
a real system simulation, if possible, placing it at the maximum capacity to
evaluate the evolution of inventory before each step of the process. This
assumes that it`s operating only during normal working hours and every process
pushes WIP to the next process of the system and operators work at a normal
rhythm during all the simulation.
When comparing the results of the two previous tools it is identified
and validate with reliability system’s constraints. All the efforts and
improvement focus must stay, at this moment in the Constraint. This process
must be analysed with more detail and a team must be mobilized to decide the
approach and how to exploit the constraint.
3.2.
Exploit
Constraint – Figure 9
Figure
9: Step 2 of TLS proposed model
On this step of the proposed TLS model it is necessary to identify and
measure Waste (Muda). Some possibly
logical tools to which can be resorted are:
·
Study motion with Spaghetti Diagram;
·
Go to Gemba
to detect possible opportunities in 5S and if visual aid is appropriate;
·
Check the needs for Standardized work or losses in
tool exchanges (changeovers);
·
Check if performance metrics and OEE are being
correctly measured;
·
Compare VSM current State with pretended Future State
and plan and implement continuous improving Kaizen events;
Simultaneously to the identification of waste it’s necessary to
characterize and identify variability in the constraint. The recommended logics
and tools to apply are:
·
Apply Voice of Costumer, Run Charts, Check sheets and
MSA;
·
Create Pareto Charts to identify main causes of
variability;
·
Study causes and effects with Ishikawa Diagram and 5
Whys;
·
Make gage R&R studies;
·
Study potential impact of defects reduction.
Now it’s possibly to answer the question 2a: “If there is LSS
improvement opportunities?” In case of the system being already too exploited,
the solution is to go to next step of the model and subordinate the others
processes to the constraint. Otherwise depending on the opportunities found
before, it’s chosen where to act and that corresponds to question 2b. In case
of finding improvement opportunities that can help reducing waste, some
recommended tools are:
·
Apply 5S and improve section’s visual aid;
·
Implement SMED;
·
Allocate machines, organize work and reduce
unnecessary motions;
·
Standardize and normalize changes;
·
Implement continuous flow and reduce Lead Time;
·
Create needed indicators.
For the variability opportunities found, the Six-Sigma tools and logics
recommend to apply are:
·
Making opportunity flow diagram and Matrix FMEA;
·
Implementing Statistical Process Control resourcing to
DOE, Control Charts and
·
Process Capacity;
·
Studying equipment reliability;
·
Giving formation to operator about maintenance,
stoppages and variability and defects reduction;
·
Reducing DPMO (Defects per Million Opportunities) until
it gets close to level 6 of Sigma.
3.3.
Subordinate
System to the Constraint – Figure 10
Figure
10: Step 3 of TLS proposed model
After implementing Lean and/or Six-Sigma improvements the next step is
to check if DBR and Pull are already being correctly applied in the system. If
the correct tools are in use, than it’s necessary to make the whole system
using them properly. The Kanban and Buffer should get optimized before
constraint in a way that the bottleneck stays always fed with materials to
avoid unnecessary stoppages.
3.4.
Revaluate
Constraint and Elevate Constraint’s Performance – Figure 11
Figure
11: Step 4 & 5 of TLS proposed model
At this step, the Constraint needs to be revaluated. In case the process
now fulfils Takt Time, this means that its capacity is superior to the current
demand rate than it closes the first continuous improvement cycle.
In
this transaction between cycles, it’s important to keep the improvement active
and critical attitude to avoid deterioration of the good practices achieved.
To identify new constraint of the second improvement cycle it should be
made an actualization of the VSM or another simulation with the new parameters
of the current situation. Internal audits, with focus on the control of the
improvements applied are recommended, to avoid the process to become a
constraint again.
On the other hand, if the constraint still can’t keep up with Takt Time
it is required to go to step 5 of the model. To elevate constraint’s
performance at this moment, monetary investment can became the only solution.
These investments can be done through:
·
Buying new machines and equipment;
·
Hiring more operators;
·
Changing plant layout;
·
Solving external factors to the system;
·
Searching for better technology and innovation.
The
entire model is shown in figure 12:
Figure
12: TLS model to Production System Improvement
4. RESULTS OF TESTING THE TLS PROPOSED MODEL ON A LEAN
PRODUCTIVE SYSTEM
The proposed TLS model was tested in a Lean productive system of an
important Portuguese manufacturer where a three year old Lean Program was
implemented.
The organization wanted to maintain a Lean as a continuous improvement
methodology, but it showed total openness to experiment other continuous
improvement methodologies or integration of others like a TLS.
In the Table 6 it`s described
which were the tools and logics used in each one of the phases of the model and
what the expected impact in the system under study.
Table 6: Tools, Logics and impact expected impact in
each one of the phases of the proposed model
In the first step of the model two different techniques have been used
to identify the
constraint:
·
Real system simulation – Figure 13
Figure
13: WIP variation before process
Table 7: Trend line equation of variation of WIP
before process
After
analysing the Table 7 it is possible
to conclude that the constraint is located in process 5, because it`s in this
stage that the trend line of WIP has greater slope.
·
VSM – Cycle Time
Table 8: System Cycles time
In
process 5 the Cycle Time is longer – Table
8, so it`s possible to conclude that the constraint is located at this step
of the system.
The conclusions obtained about system’s constraints were equal in both
methods and it was possibly to define with reliability the existing first
improvement cycle’s constraint. That process was analysed with more detail and
a team was assigned with the task of focusing on process improvement.
After the constraint was exploited corresponding to the second step of
the proposed TLS model and several Lean Six-Sigma (LSS) opportunities were
identified. On those identified and characterized opportunities for waste and
variability reduction it was applied the most appropriate Lean and Six-Sigma
tools to solve them – Table 7.
After improving the constraint with LSS, it was verified if Pull logic
was implemented in the system and if DBR was applied properly before the
constraint. There was no need to make any changes in the study case system
because Pull and DBR were already well applied and the existing Kanban and
buffers were well optimized.
At this moment it was possibly to revaluate constraint found in the
first improvement cycle. Table 9 compares the
values encountered for Cycle Time in seconds to produce one piece on every
process at the initial conditions that the system was found (October 2014) with
the values obtained at the moment of constraint’s revaluation (April 2015):
Table 9: Comparison of system’s Cycle Time (seconds to
produce one piece)
|
Process 1 |
Process 2 |
Process 3 |
Process 4 |
Constraint |
Process 6 |
Initial Cycle Time (October 2014) |
31,19 |
33,67 |
33,89 |
32,53 |
39,09 |
35,08 |
Cycle Time (April 2015) |
29,80 |
29,84 |
29,66 |
31,72 |
26,48 |
29,09 |
From the table above, it is possible to conclude that
the constraint became one of the most efficient processes in the system
and it is also possible to notice that
all the other processes in the system improved due to the leverage created by
the reduction of constraint’s Cycle Time avoiding delays and waiting for
materials provision.
In the initial conditions that the study case was found the Cycle Time
calculated for the bottleneck was 39,09 seconds to produce one piece and when
revaluated after the LSS improvements it was only required 26,48 seconds/
piece. This corresponds to a reduction of over 32% in Cycle Time on the
constraint just by the application of the suitable LSS tools.
Calculated Takt Time corresponding to the rate of costumers demand was
establish at 33,88 seconds/ piece which means that the constraint fulfils successfully
the Takt Time demanded by system’s clients.
Table 10 shows some
performance indicators results in terms of Productivity and Quality in the two
months when LSS improvements occurred (January and February 2015) and on the
two following months after the first cycle improvements (March and April 2015)
on constraint:
Table 10: Performance indicators on constraint
Productivity |
Quality |
||
Average
of daily processed quantity (pieces/ day) |
OEE
average (%) |
Defects
average (%) |
Stoppage
time due to malfunctions (hours) |
January 2015 |
|||
2.894 |
62,17% |
9,7% |
198h |
February 2015 |
|||
3.130 |
68,13% |
10,8% |
91h30 |
March 2015 |
|||
3.217 |
76,88% |
9,2% |
29h30 |
April 2015 |
|||
3.175 |
77,07% |
8,5% |
14h15 |
With
this obtained results it was possible to close the first improvement cycle of
the proposed TLS model. It was not necessary to elevate constraint’s performance
with financial resourcing corresponding to the fifth step of the model.
In the transition between cycles the creation of a continuous
improvement attitude was defined with the Industrial Manager. For that reason
the former constraint was kept under control, a meeting between the improvement
team about constraint situation kept being realized once a week and it was
implemented internal audits in the whole system, with special attention on
Capacity-Constrained resources found at the first improvement cycle.
So a second improvement cycle was needed, starting by the updating of
the previous VSM with the new data collected. A new improvement cycle begins.
5. MAIN CONCLUSIONS
Reviewing of continuous improvement systems it’s possible to verify that
from the existing systems found at state of art, the reported to bring better
results for managers are the ones that integrate the methodologies Theory of
Constraints, Lean production and Six-Sigma in a single improvement project.
This paper proposed a TLS model that shows flexibility to be applied in
any system. To test the proposed hypothesis it was decided to implement it in
an important Portuguese manufacturer Lean productive system. The application of
a TLS model demonstrate to be not more difficult than the implementation of a
Lean or Six-Sigma project alone, because the focus of a TLS project only need
to stay on constraint’s sector instead of being on the whole system.
It’s possible to observe results, even in the first improvement cycle
which means that is highly recommend apply TLS projects for short-term results . The constraint found went from being the
most inefficient process to become one of the most efficient and also all the
others processes benefit from the improvements corresponding in a general
reduction of Cycle Time.
There is still a need to validate the proposed model with further
discussion and in new real systems to make the implementation. Continuous
improvement projects should be taken care with a pro-active attitude and need
to be maintained with protective measures to avoid a deterioration of the good
results obtained.
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