author: carlson, curtis m applying lean manufacturing
TRANSCRIPT
1
Author: Carlson, Curtis M Title: Applying Lean Manufacturing Techniques to Streamline the Transportation
of Work in Process within Company X The accompanying research report is submitted to the University of Wisconsin-Stout, Graduate School in partial
completion of the requirements for the
Graduate Degree/ Major: MS Manufacturing Engineering
Research Adviser: Dr. Xuedong Ding
Submission Term/Year: Spring, 2013
Number of Pages: 38
Style Manual Used: American Psychological Association, 6th edition
I understand that this research report must be officially approved by the Graduate School and that an electronic copy of the approved version will be made available through the University Library website
I attest that the research report is my original work (that any copyrightable materials have been used with the permission of the original authors), and as such, it is automatically protected by the laws, rules, and regulations of the U.S. Copyright Office.
My research adviser has approved the content and quality of this paper. STUDENT:
NAME Curtis Carlson DATE: 4/29/2013
ADVISER: (Committee Chair if MS Plan A or EdS Thesis or Field Project/Problem):
NAME Xuedong Ding DATE: 5/15/2013
----------------------------------------------------------------------------------------------------------------------------- ----
This section for MS Plan A Thesis or EdS Thesis/Field Project papers only Committee members (other than your adviser who is listed in the section above) 1. CMTE MEMBER’S NAME: DATE:
2. CMTE MEMBER’S NAME: DATE:
3. CMTE MEMBER’S NAME: DATE:
----------------------------------------------------------------------------------------------------------------------------- ---- This section to be completed by the Graduate School This final research report has been approved by the Graduate School.
Director, Office of Graduate Studies: DATE:
2
Carlson, Curtis M. Applying Lean Manufacturing Techniques to Streamline the
Transportation of Work in Process within Company X
Abstract
Moving material and parts within a factory is inherently wasteful; it contributes nothing
to the bottom line and takes up valuable time and effort that could otherwise be better used
elsewhere.
This paper takes an in-depth look at part handling within Company X. The current
situation is such that all machine operators currently handle their own parts throughout the
facility. This practice is wasteful and inefficient.
This paper analyzes the current situation using simulation techniques. Data regarding the
current environment was collected and a simulation of a single work center was developed. This
simulation was used to draw conclusions regarding the current state of the entire facility.
Based on the analysis and simulation, this paper recommends that a part handler be hired
to work at Company X. This person would be more than justified in the increased capacity that
could be realized within the factory.
Company X has reached a size where keeping highly trained workers at their machines is
a priority. This paper demonstrates quantitatively that a part handler is justified for a company
the size of Company X and should be hired as soon as possible.
3
Table of Contents
.................................................................................................................................................... Page
Abstract ............................................................................................................................................2
List of Figures ..................................................................................................................................5
Chapter I: Introduction .....................................................................................................................6
Statement of the Problem .....................................................................................................6
Purpose of the Study ............................................................................................................7
Assumptions of the Study ....................................................................................................7
Definition of Terms..............................................................................................................8
Limitations of the Study.......................................................................................................9
Methodology ........................................................................................................................9
Chapter II: Literature Review ........................................................................................................10
Lean Manufacturing ...........................................................................................................10
Material Handling Equipment............................................................................................13
Table 1: A Comparison of Material Handling Equipment..........................................14
Facility Layout ...................................................................................................................15
Costs of Material Handling ................................................................................................16
Labor Costs .................................................................................................................16
Other Costs..................................................................................................................17
Conclusion .........................................................................................................................17
Chapter III: Methodology ..............................................................................................................18
Instrumentation ..................................................................................................................18
Data Collection Procedures ................................................................................................19
Data Analysis .....................................................................................................................20
4
Limitations .........................................................................................................................26
Chapter IV: Results ........................................................................................................................27
Simulation Analysis ..........................................................................................................27
Create ................................................................................................................................27
Assign ...............................................................................................................................28
Process ..............................................................................................................................29
Dispose ..............................................................................................................................31
Overview of Simulation ....................................................................................................31
Results ...............................................................................................................................32
Chapter V: Discussion ...................................................................................................................34
Limitations ........................................................................................................................34
Conclusions ........................................................................................................................34
Recommendations ..............................................................................................................35
References ......................................................................................................................................36
Appendix A: A Sample Time Entry Form .....................................................................................38
5
List of Figures
Figure 1: Diagram of the Model…..……………………………………….…………………….20 Figure 2: Input box for the “CREATE” module…………………………………………………21 Figure 3: Input box for the “ASSIGN” module…………………………………………..……...22
Figure 4: Input box for the “VMC WORK CENTER PROCESS” module……………….…….23
Figure 5: Input box for the “RELEASE PROCESS FOR MACHINE” module………….……..24
Figure 6: Input box for the “TRANSFER PROCESS” module…………………….…………....25
6
Chapter I: Introduction
Company X is job shop where the product mix varies and capacity is always a concern.
It specializes in custom fabrication of a wide variety of metal parts, from sheet metal cabinets to
large mining equipment. In a job shop environment, custom orders are taken from customers on
an ongoing basis and fabrication is completed to meet their time-frame. There are hourly
changes in the production schedule and there is seldom a long range forecast. This causes stress
levels to be very high throughout the facility.
The production floor is set up in five “bays” each with a general purpose, e.g. welding,
machining or laser cutting. The process flow changes for each order and is determined by the
routings for that product and by the current capacity of the facility. Each bay is connected by a
20 foot wide opening located on one end of the facility which is the only practical mean of
access between the bays.
There is a strong resistance within the company to adding indirect labor in the form of
material handlers. Therefore, product transport is currently handled by the operators themselves.
When the operators complete a project, they will move it to the next work center specified on the
product routing. This can involve finding a forklift, waiting for someone else to be done with the
forklift, driving back to their work center, and finally moving the product to the next routing
which might be all of the way across the shop. Advancing product when an operation is
complete is mandatory, with discipline given if product is not advanced immediately.
Statement of the Problem
The lack of a designated material handler is creating a need for operators to move their
own product around the facility. Machinery is not being utilized to its full capacity and the
company is losing potential profit.
7
Purpose of the Study
The goal of this study was to evaluate the need for a full time material handler whom
would be responsible for moving product from work center to work center within Company X.
This study evaluated potential costs and benefits of the introduction of this position and gave
recommendations as to the best implementation of the new process.
Assumptions of the Study
The assumptions for this study focused around taking a snapshot of the company and then
interpreting the data in a way that will allow generalizations to be made for the company in
general.
1. Production levels will continue at levels consistent with the levels occurring when
this study was completed.
2. Labor expenses for employees can be generalized to a base rate plus a modifier
which reflects additional company incurred expenses (health insurance, workers
compensation, etc).
3. The general arrangement of the factory will remain the same and nothing
significant will be done to streamline the product flow.
4. Analysis will be done on the Vertical Machining Center (VMC) work center.
Generalized conclusions will be applicable to other areas of the facility
5. When operators are performing the transportation of product, no work can be
done on the machine for safety reasons.
6. Only first shift will be analyzed
7. There will always be adequate product in the work center queue such that no
machine is idle due to lack of product. The VMC work center was chosen because it
is a bottleneck in this regard, and work is always present.
8
8. If sufficient capacity is available on a machine due to the proposed addition of the
material handler, the shop will be able to add additional sales to fill the capacity.
9. The machines are running eight hour work days, five days a week
10. The machines analyzed are 100% interchangeable, all product can flow across any
machine.
Definition of Terms
Job shop. A job shop is a type of business which takes orders from many different
customers and uses a specialized set of machinery to add value to product. The opposite of a job
shop is a continuous flow manufacturer such as a oil refinery or a grain mill.
Job router/traveler. A traveler is a piece of paper which indicates the order of work
centers which are used to produce a product and the type of material which is to be used to make
a product. A traveler will also indicate important information such as scheduled start date,
customer, quantity required, and final delivery date .
Value. Value is anything that is done to a product that a customer will pay for.
Work center. A work center is a specific machine or location which performs a specific
function to product. For example, a drilling work center would drill holes in parts, or a cutting
work center would cut parts out of a raw piece of material.
OEM. Original Equipment Manufacturer is a factory which produces its own product
and only its own product.
9
Limitations of the Study
This study will only be considering the effect of adding a material handler given
production at 2013 levels. Should production increase or decrease, the need for a part handler
may change.
This study analyzes only the Vertical Machining Center work center. Further analysis
would need to be done on other work centers.
Only day shift will be analyzed in this study. Night shift will not be considered in the
data.
A representative sample of three week’s worth of production was analyzed to develop
statistical distributions used in the simulation. This data was taken from February 2013.
Methodology
The methodology for this study will consist of collecting data regarding the amount of
time that operators currently spend moving material to and from their work centers. This
information will be used to develop simulation model parameters which will be input into Arena
simulation software. The output data from this simulation will be used to do a cost – benefit
analysis to determine if a dedicated material handler is justified.
10
Chapter II: Literature Review
A large amount of literature has been written regarding the problem of material handling
and logistics as it relates to creating a Lean factory. The transfer of material, supplies, tooling,
equipment and personnel from one location to another provides a visible target for companies to
easily increase efficiencies and provide proof that lean concepts work.
Lean Manufacturing
One of the main predecessors to Lean Manufacturing in the Unites States was the Toyota
Production System developed by Taiichi Ohno at Toyota Motor Company in the early 1950’s
(Ohno, 1988; Womack, Jones, & Roos, 1990). After the end of World War II, Japanese
manufacturing was stuck in a backwards tradition of intense manual labor. There was little to no
thought about improving efficiencies and moving into the manufacturing techniques which were
common in the United States at the same time. One estimate given by Ohno (1988), is that
efficiencies in Japan were so bad that it would take 10 Japaneese to produce the same output as
one American.
The president of Toyota Motor Company at the time was Kiichiro Toyoda (Ohno, 1988).
He instilled the vision to Japanese manufacturers that they were going to catch up to American
automobile manufacturing within three years. With this statement, he set a clear goal and Toyota
set upon the path of developing a manufacturing system unlike anything that had been seen in the
world before.
The Toyota Production System (TPS) revolved around a very simple concept: eliminate
waste (Ohno, 1988). As Taiichi Ohno looked around his factories, he realized that there was an
incredible amount of waste. He came up with seven categories which are still used extensively
today: the waste of overproduction, the waste of waiting, the waste of transportation, the waste of
overprocessing, the waste of inventory, the waste of movement, and the waste of making
11
defective products. Using these categories, Taiichi Ohno began the elimination of waste which
became the Toyota Production System. Since Taiichi Ohno developed the seven wastes, another
waste is typically referred to. This waste is the waste of underutilization of employees’ minds
and ideas (Dolcemascolo, 2006).
The elimination of waste lead to the development of Just In Time manufacturing (JIT).
The theory behind JIT is that the greatest waste of all is the waste of excess inventory (Standard
& Davis, 1999). Dolcemascolo (2006) estimates that inventory holding costs are at least 20% of
the value of the inventory per year. There are several reasons why this is true. First, any excess
inventory represents cash that is sitting around. This is money that could have been used in more
profitable ways. Second, any inventory allows the possiblility that that specific inventory was
produced incorrectly and is therefore defective or obsolete. Finally, inventory takes up valuable
space. Therefore JIT manufacturing stipulates that throughout each process, the proceeding
operation should only take place immediately before operation which requires the result of that
process. The way that the operation is signaled to begin production on the required product is
referred to as Kanban (Ohno, 1988; Dolcemascolo, 2006; Baudin, 2004).
Kanban typically involves a signal which is given from a down stream (closer to the
customer) operation to an upstream operation. This signal tells the proceeding operation that the
downstream operation is getting low on product and the upstream operation should produce more
(Dolcemascolo, 2006; Wang, 2011, Standard & Davis, 1999; Baudin, 2004). This way, the
waste of excess inventory is reduced since no product is produced other than what the
downstream operations are demanding.
One very powerful way to eliminate waste is to map out the value stream for an operation
(Dolcemascolo, 2006; Flinchbaugh & Carlino, 2006; Wang, 2011; Standard & Davis, 1999). A
value stream includes every process in the life cycle of a product laid out in a flow chart.
12
Starting with the vendor on the left hand side and the customer on the right hand side, each
process is given a physical location on the chart. In between each process, wait times are
recorded. Under each process value added times are recorded along with other pertanent
information regarding the process. This allows the process to be analized according to what is
adding value and what is not adding value in the process. Along the bottom of a value stream
map a time line of the process cycle is recorded, this timeline shows value added and non value
added portions of the process time. At the end of the map, a summary showing a ratio of value
added/non value added time is posted. Typically it is very clear that there is extreme waste in the
process, as the value added time is usually measured in minutes and the non value added time is
typically measured in day or months.
Another tool that is very commonly used in Lean Manufacturing is the 5S system
(Dolcemascolo, 2006; Wang, 2011; Santos, Wysk, & Torres, 2006). This system is intended to
produce a workplace that has everything needed to do the job at hand and nothing more. The
5Ss are: sort, set in order, shine, standardize, and sustain. Sort is the process where everything
that is located in a work area is removed. Then the 5S team will evaluate every single tool and
determine the how often the tool is being used. Tools that are used very often are kept near the
operator, tools that are not used very often are placed near by, tools that are used seldom are
stored elseware in the plant, and tools that are not needed are discarded. Discarded tools are
placed in a well marked “red tag area” which allows anyone to make a determination if that tool
has use in their area. “Set in order” is the process where everything that is remaining in the work
area is organized and has a place. Everything should be visual and anyone coming up to the
workcenter should know at a glance if a tool is missing and where a tool belongs. Typically
shadow boards are used, with outlines for each tool well marked. Labling is critical to setting a
work center in order. “Shine” is the process where everything is placed in order at the end of
13
every day (and also initially cleaned). This means that every part of the workcenter is cleaned.
Often, machines are repainted, floors are painted, desks are washed and cleaned, and every tool
is cleaned, greased, and put back. “Standardize” refers to the method that the organization
maintains the other three S’s. Typically every company will have a slightly different method of
5S standardization but in general companies will specify tape colors for certain areas, they will
have signs which easily designate areas, they will have a standardized way of maintaining the
shadowboards and everything will look similar from one 5S area to another. “Sustain” is a
culture of continuous improvement where the first four S’s are monitored, recorded, and
improved upon. The challenge with sustaining is that once an area has been through the first 4
S’s, most people think that the job is done. A culture of sustaining will continually go back
through an area and make sure that the process and procedure that was put into place is being
followed. “Sustain” is often the most difficult of the 5S’s to implement into a manufacturing
culture.
Material Handling Equipment
There are many different forms of material handling equipment which can be used alone
or in conjunction with one another to transfer material in the most efficient manner. Sule (1994)
classifies all material handling equipment into three types: conveyors, cranes, and trucks.
14
Table 1
A Comparison of Material Handling Equipment
Equipment Advantages Disadvantages
Conveyor o High Capacity o Path is difficult to change
o Can inspect product as it passes on conveyor
o A breakdown stops the entire production line
o Routing can be flexible (overhead, underground, etc.)
o They can get in the way of other equipment
o Automatic transfer of material, no operator required
Cranes and Hoists o Can lift and transport material o Are usually expensive to install and maintain
o Do not take up floor space o Most are limited in the areas that they are capable of servicing
o Can handle heavy loads o An operator must be present to operate the crane
o Can be used to load/unload material from work centers
Trucks o Are not fixed, therefore they can transport material anywhere in a shop
o They typically cannot haul heavy loads
o They can load machinery and lift material into position
o They have limited capacity per trip
o Trucks move in aisles, taking up production space
o Most are driven by an operator
Any of these systems can be automated to one degree or another (Sule, 1994; Baudin,
2004). Sensors, computers, guidance systems, and programs can make any system more or less
automated. Typically any automation comes with a high initial cost, and any effort to automate
transportation processes should be looked at from a cost-benefit standpoint. The upside of
15
automation is removing some of the “human factors” from the system. This includes decreasing
the risk of safety accidents, decreasing fatigue, and increasing the speed of material transfer.
Facility Layout
The second major way of improving material handling efficiencies is to actually change
the layout of the facility to decrease the physical distance that a part needs to travel as it is
processed. Using group technology (grouping theory) (Sule, 1994) the organization can
calculate how machines should be arranged in a complicated factory so that the distance parts
have to travel is minimized. The optimum solution will reduce material handling to the point
that each operator can transfer material directly to the next work center without causing a delay
in production.
Santos, Wysk, and Torres (2006), state that there are many different reasons that a shop
layout may need to be modified. What usually happens is that when machinery is purchased it is
placed in to the first available corner of a factory. This results in lower initial costs but causes
problems later. Thought and effort should be put into locating machinery so that it works
smoothly with the existing and future material flow.
Flinchbaugh and Carlino (2006) stress that no material movement system is complete if
there are bottlenecks in the process. They give the example of a streamlined logistics system
which effectively moves material across the country, but then hits a stumbling block when it
reaches the loading dock at the company; there is confusion and delay as the receiving personnel
try to organize the shipment for distribution within the company. Thus the material handling
system is only as efficient as the weakest link.
16
Costs of Material Handling
Many businesses go to great lengths to reduce the costs of material handling. Before
implementing a material handling cost reduction project, it is important to classify and quantify
the costs which are present in a material handling system.
Labor costs. In most businesses, labor costs are the largest single cost that a business
has. Therefore they are constantly the target of cost reduction initiatives. Berk (2010) suggests
that the easiest way to identify the labor costs associated with material handling is to produce a
flow chart. Once a flow chart has been produced it will usually be apparent where labor is being
unnecessarily used. Some of the things that need to be analyzed are the logical flow of work, the
bottlenecks in the process, the product travel distance, and the ability to get inventory closer to
where it is going to be processed.
Berk (2010) also suggests some other techniques to reduce labor costs, including
removing storage locations, minimizing distances between work centers, and keeping smaller,
local inventories of required tools and material. Removing storage locations involves trying to
keep all like finished goods combined in one inventory location. Minimizing the distance
between work centers refers to the idea that a shop should be laid out in a logical fashion such
that the majority of the work can progress easily from one work center to the next. Keeping
smaller, local inventories is a key idea in any lean manufacturing environment where only
enough product is kept on hand to supply the immediate requirements of the work centers.
One consideration that should be acknowledged is that a common practice in a lean
manufacturing environment is to decrease batch sizes and increase the frequency of delivery of
product to a work center. Low, Hsu, and Huang (2004) found that in a job shop, splitting an
order into 2-4 lots created great improvement in the total cost of producing a product. Due to the
17
fact that more material handling will be required in this scenario, an even greater importance
should be placed on the elimination of waste from material handling.
Other costs. When looking at a material handling system, some of the other costs
include: the initial purchasing of the equipment, fuel and maintenance on the machinery, pallets,
bins, or boxes used to actually hold the product, and the risk of damaging the product (Sule,
1994).
Another cost which is pointed out by Sheldon (2008) is space. Any material
transportation and handling system requires space to operate. A common manufacturing facility
will dedicate at least 25% of its floor space to material storage. Consideration must be given to
the space which is taken up by the material transport equipment. If forklifts are used, they need
larger paths than handcarts, long material “trains” can take up a large amount of space even
when parked. When space is at a premium within a facility, it is important to focus on getting
the most out of the existing equipment before committing to purchasing more.
Conclusion
Over the course of the last 30 years, lean manufacturing has developed as a standard way
for almost any facility to increase efficiencies. By looking closely at waste and the various
processes that create waste, the lean manager can create a factory that produces goods in the
most efficient manner. There are many solutions which can be implemented based on the
structure of the factory, but the key to the full realization of a lean manufacturing system is
realizing where the value-added work is coming from and focusing on improving efficiencies in
those areas. One key to achieving this is to potentially create extra work and inefficiencies in
other areas of the factory by increasing the amount of material handling that must occur.
Through single piece flow and kanban communication, extremely high efficiencies will be
achieved in the areas that are adding the most value to the organization.
18
Chapter III: Methodology
In business, cutting costs is the key to a profitable company and one of the most visible
costs is the cost associated with material handling. Most companies spend large amounts of time
and money on improving the efficiency of material handling. In this paper I analyzed the current
material handling situation within the Vertical Machining department at Company X and made
recommendations on improvements specifically with regards to whether or not operators would
transfer their own product between work centers or if a full time material handler would be
justified to perform this function. This chapter looks at the methodology used to determine if the
material handler position would be justified.
Instrumentation
The first way that information was collected for this project was through a self-
administered work center evaluation (see Appendix A). This simple time-entry form allowed
operators to quickly and easily tally time spent moving product from work center to work center.
The key in the design of this form was to make it easy to use, intuitive, and accurate. This
helped ensure that the information collected would be as complete and accurate as possible.
The second way that data was collected was through the electronic shop data collection
system. Every time an employee begins a job they are responsible for logging their start time
into the computer system. They then process the “setup” portion of the job. Then they make a
transaction which indicates that they have moved onto the “run” portion of their job. When the
job is completed, they will make a final transaction which indicates the quantity that they have
completed, weather the product was scrap or rework, and the total time which was spent working
on the product. At this time, they will log into the next job. This keeps an accurate record of the
number and type of jobs which were run through the work center.
19
Data Collection Procedures
The purpose of the data collection for this project was to enable an accurate simulation
model of the work center to be developed. This model would then be used to predict how much
time operators spend moving material during a given day and thus how much productivity could
be gained by adding a material handler.
There were three types of information which were required to generate the simulation.
First was the distribution of product. This is important because each type of product will have
different characteristics as is passes through the system, for example, processing time and
transportation time. When product arrived at the VMC work center, it could be categorized into
five different categories: Complex Weldments, Extra Large Plates, Fixtured Parts, Medium and
Large Plates, and Simple Vice Parts. Complex Weldments are large, complex parts which often
have extremely difficult machining operations that need to be performed. These typically take
many hours to process. Extra Large Plates also take many hours to process and they are typically
very difficult to handle. Fixtured Parts can be large quantity runs, and the setup time will usually
be very high relative to the running time. Medium and Large plates are a typical part with
medium run times and medium handling requirements. Simple Vice parts are the easiest and
most simple product and they constitute the majority of jobs. The shop operating software was
used to determine a total job load for a week’s worth of production. This job load was then
categorized by type to develop a distribution for each type of product.
The second type of information that was required to develop the simulation was the
processing time for each of the different types of product. This information was also taken from
the data collection system. All of the processing times for each category of product were
gathered. This data was input into the Arena Input Analyzer to develop distributions for the
process time of each operation.
20
The last type of data which was required was how long was required to transfer each type
of product to the next area. This information was gathered in two ways. First a form was
distributed to each operator in the VMC department and they recorded the amount of time it took
to transfer product to the following work center and enter any notes regarding the problems that
they had with this, see Appendix A. In addition, all jobs run during the trial period were
analyzed by the work center supervisor and his results on how long each job had taken to move
to the next work center were tabulated.
Data analysis. Once the data was gathered, it was analyzed using a simple Arena
simulation. This simulation modeled the existing situation on the shop floor within the VMC
work center. The key parameters and outputs were determined to be the processing times, which
would determine the total amount of jobs that went through each of the machines and the
transportation time required by operators to transport product from their work center to its next
destination .
Figure 1. Diagram of the model used to simulate the product flow through the Vertical Machining Center work center.
The different modules are directly associated with actual processes within the work
center. The Create module represents the product incoming into the work center. It provides a
constant flow of parts which are acted on by the following processes. Since, for the purposes of
this study, the work center is considered to have unlimited amounts of incoming work, the
21
purpose of this process is to input work at a rate which is greater than the rate that work is being
processed through the system. This supports the assumption that the work center has as much
work as it can handle.
Figure 2. Input box for the “CREATE” module
The Assign module is a “book keeping” module which represents the different variations
on product that can enter the system. The Assign module generates distributions and assigns
various attributes to parts. These attributes represent the type of part that would be entering the
work center. The main attribute is the type of part. Once a part type is assigned, each entity that
enters the system will be treated differently based on this assignment. This will effectively
simulate the differences in the various categories of parts that are present in the real world
system.
22
Figure 3. Input box for the “ASSIGN” module
The VMC process module represents several things that are actually happening in the real
world. Within this module, two different types of resources are utilized to process the entity:
Operator resources and Machine resources. These represent the actual operator that needs to
work on the product and the actual machine that is going to be utilized to process the product.
Within the simulation, there are four operators and four machines which represent the four
operators and four machines which are present in Company X. Once a machine and operator is
assigned to an entity (part), it can no longer be used to process any other entities entering the
system. The amount of time that each of these resources is utilized is determined by the
distribution “Process Time”. This distribution changes based on the part type entering into the
system, and is based on real life data representing the distribution on process times for each of
the five major part types.
23
Figure 4. Input box for the “VMC WORK CENTER PROCESS” module
The “Release Process for Machine” process represents the fact that in the current facility,
the machine will be available but will be sitting idle while the operator is spending time moving
parts to the next work center. The only purpose of this process is to independently free up the
Machine while the Operator is still being used to move the parts to the next work center. This
allows for a final output of how long the machine will sit idle and that will correspond to the
amount of time that could potentially be saved if a part handler was hired to move parts.
24
Figure 5. Input box for the “RELEASE PROCESS FOR MACHINE” module
The next process is the Transfer Process. In the real world work center, this process is
the actual act of moving parts from one work center to the next. This is simulated in Arena by
separate distributions for each part type. When each part enters into this process the operator is
delayed by a time equal to a distribution. This Distribution is based on actual data regarding how
long it takes to move parts of each type to the next operation. In reality, each part type can take
more or less time to transport to the next work center because some of the parts are transported
using a forklift, some are transported using a pallet jack, and some are transported by hand.
25
Figure 6. Input box for the “Transfer Process” module
The final module in the simulation is the Dispose module. This is simply an end to the
simulation. In reality it represents that the operator and machine have completed one cycle, the
parts have exited the system and the process is reset to the beginning.
After the simulation was run a final report which presented the total utilization of each
machine over the course of the simulation week was used to make the final recommendations.
This report presented the total utilization of each of the four machines which made up the
system. Any lack in utilization was due to the operators not being present because they were
moving parts through the system. The total of all of the unutilized time would be the total time
that could be saved by implementing a part handler.
A daily average of time spent on material handling for each work center was computed
based on the data. This average time per work center was then multiplied by the shop rate for
each work center to establish an average cost per day per work center. These were then added up
and multiplied by 260 working days in a year to establish a cost per year.
26
Limitations
The main limitations with this methodology are that it relies on a snapshot of the state of
the company to infer a year’s worth of data. Since Company X is a job shop, the product mix
from month to month can differ greatly. Therefore, the conclusions which are drawn from the
data should be used with caution if product mix is predicted to change drastically.
The other limitation is that it only analyzes the VMC work center. In order to fully
justify an additional person, the entire shop situation should be looked at since a parts handler
would undoubtedly affect the entire facility.
27
Chapter IV: Results
A simulation of the current state of the Vertical Machining work center within Company
X was conducted to analyze the feasibility of adding an additional employee for the purpose of
moving parts between work centers. The software program “Arena” was used to simulate the
steady state situation and provide simulation data to support the conclusions.
Simulation Analysis
Create. The create module within the simulation is typically used to determine the
frequency that entities are introduced into the system. Depending on the simulation, entities can
enter the system on a regular time interval. For example, a truck could come once a day and
drop off product, or it could arrive at a more complicated schedule. The quantity of entities that
arrive at a given time also can be constant or based on a complex probability distribution.
The analysis of how product enters into the actual work center was begun by visually
observing the work center for several months. What was observed is that within Company X, the
VMC work center is almost always the bottleneck and, over the course of the observation, there
was never a time that a machine was sitting idle waiting for product to arrive from another work
center. In fact, machine maintenance was routinely delayed because there was never time in the
schedule to perform maintenance. The operators of the machines were typically on five to ten
hours of mandatory overtime every week and there was a need for second shift to run at higher
capacity to take some of the workload off of first shift.
In addition to visual observations, the area supervisor was consulted about the amount of
time that the machines were idle and he stated that this seldom happens and that if it does it is not
for extended periods of time.
After these observations, it was determined that the best way to model the incoming
material would to be have a constant flow of material at a rate greater than the machines could
28
possibly use up. Thirty entities every eight hours was determined to be sufficient such that there
never was a lack of entities in the system.
Assign. The assign module within Arena has many uses. In general, the assign module
is capable of taking the entities which enter the system and turning them into an accurate
depiction of reality. This is done by assigning important attributes; the frequency of which are
typically based on probability distributions. Part identification attributes such as part type, part
color, which routing a part will take, even the picture which will represent the part within Arena
are all designated within the Assign module. The Assign module is one of the most important
modules within a simulation because it lays the foundation for the rest of the simulation to use.
The attributes assigned in this module can be quite complex to develop and analyze.
Based on observations of the VMC work center, it was clear that there were many
different types of parts that enter into the system. Analysis of several weeks worth of product
was performed. The lead machining supervisor was consulted to group similar products into
several categories. After discussion, groups were developed based on how the parts were
processed, with a focus on parts that would have a significantly different process time and/or
transportation time distribution. The categories that were developed were: Complex Weldments,
Medium and Large Plate, Simple Vice Parts, Extra Large Plates, and Fixtured Parts.
Complex Weldments is a category which encompasses all parts which are processed by
the VMC work center which are typically larger, cumbersome, and difficult to process with
many operations. Complex Weldments typically take large amounts of time to set-up in the
machine and require a large amount of work and thought to process. Medium and Large Plates is
a category which takes into account a large proportion of product which consists of flat plates
most commonly used in the mining industry which are sized such that they fit within the
operating envelope of the machine, do not need to be flipped or moved after being positioned,
29
and the quantities are typically in the one to ten piece range. Simple Vice Parts is a group that is
by far the most common category of parts. These parts are miscellaneous small parts which can
easily be inserted into a machining vice and have simple mill, drill, tap, or other features that can
easily be processed. Extra Large Plates is a category which is similar to Medium and Large
Plate, except that these are plates which will extend outside of the operating envelope of the
machine. These parts are difficult to process because they typically require a major repositioning
of the part after a first operation is performed. This will require the operator to stop the machine,
unbolt the part from the bed of the machine, get a crane to move the part, reposition the part
inside the machine, and then re-orientate the machine so that it can continue with the operation.
These parts typically have low run quantities but they take a long time to set up and a long time
to run. The last category, Fixtured Parts, consists of parts for which we have developed internal
fixutures to accommodate the parts. These fixtures typically make the initial orientation of the
parts easier and faster. The fixtures can also make inserting a new part easier and less prone to
human error. Fixtured parts can have quantities of several up to a hundred.
After the different categories were developed, a distribution of each part type was
developed. Product mix was analyzed for two weeks and each part was categorized into one of
the five types. It was determined that 6.5% of parts entering the system were Complex
Weldments, 22% were Medium and Large Plates, 56% were Simple Vice Parts, 13% were Extra
Large Plates, and 2.5% were Fixtured Parts. Using this distribution of part type, each entity was
assigned to one of the five categories based on a number from one to five. Then each category
was assigned a part type and a part picture. This allowed for a differentiation to be made further
along in the simulation between the different part types.
Process. The process module is used to assign process delays, which simulate an
operation being performed on the entity. This module also simulates a queue wait time for a
30
particular process, and assigns resources which allow for simulation of finite resource allocation
within a facility. Typically a process will seize a resource, perform some sort of operation on an
entity which will delay the entity and utilize the resource, and then release the resource and the
entity. The entity will then proceed to the next module and the resource will become available to
perform another operation on a different entity.
Within the simulation of the VMC work center there were two main objectives which
needed to be achieved during the “process” stage. First, each entity had to be delayed by a
certain amount of time which corresponds to the anticipated processing time of that particular
part type. The second objective was to simulate how much time a machine was idle due to the
operator being used to transport product. Therefore, two different resource sets were developed
to show which machine was being used and also which operator was being used.
The machine resource set consisted of four machines, which had the same attributes
based on the assumption that all parts could be processed on any machine. The operator set
consisted of four operators which also had the same attributes. When an entity entered the VMC
work center process, it would seize both a machine resource and an operator resource. These
resources would be locked together until they were both released in a future process. The VMC
work center was set up as a “seize, delay” process so it was not capable of releasing the
resources.
The delay time of the VMC process was based on probability distributions which were
assigned based on the part type. This is due to each part type having a different distribution for
process time. The process time distribution for each part type was analyzed based on the actual
time recorded values for each part. Over a course of two weeks, the total process time for each
part type was recorded in real time when it was processed using the facilities electronic time
recording system. Each process time was entered into Arena’s input analyzer. Arena’s input
31
analyzer is an application which will take a series of data points and develop a probability
distribution which most closely fits the given data. For each set of process times, a distribution
was determined which most closely represented the data. This distribution was assigned to the
delay time associated with the given part type.
The next process in the system was a simple process which immediately released the
actual machine. There is no delay associated to this process therefore the machine is
immediately released. Since the machine cannot be run without an operator, at this time the
machine is idle until the operator is released.
The next process simulates the transportation required when an operator is required to
move their parts to the next station. Each part type has a slightly different distribution for
transportation times since some part types are typically smaller and easier to handle than others.
The distributions for these part types were acquired by asking the work center supervisor to
assign a transport time to certain parts based off of actual times. Also the Time Tracking Form
(Appendix 1) indicated the time required to move parts if they required a forklift and how often
issues arose when attempting to find a forklift or other transportation equipment. Based on the
different part types, transportation delays were assigned. After these delays were completed, the
operator was released to be utilized back at the VMC work center and the entity proceeded to the
next module.
Dispose. The final module of the simulation is the Dispose module. This module is a
simple counter which counts the number of entities that exit the system. For the purposes of this
simulation, the number of entities exiting the system was not an important piece of data.
Overview of simulation. When an entity enters into the simulation, it follows a specific
path. It will begin as a generic entity in the create module at the beginning of the system. This
entity will enter the system in batches of thirty every eight hours. Every entity goes directly into
32
a queue. The first stop that the entity makes is at the assign module. In this module a continuous
probability distribution determines what type of entity will be assigned. The categories are:
Complex Weldments, Medium and Large Plate, Simple Vice Parts, Extra Large Plates, and
Fixtured Parts. Based on the collected data about the actual distribution of these part types, one
of these parts will be assigned to the previously undefined entity. At the same time, for
reference, the part will be assigned a part picture.
At this point the part is transferred into the VMC process queue. The system is designed
so that a queue always exists at the process. After the entity begins the process, the simulation
selects any available machine at random along with any available operator. At this point, the
process begins. The delay to the entity is determined by a distribution called Process Time. This
delay probability is dependent on the entity type which was assigned in the assign module. Each
entity type has its own Process Time based on experimental data.
Once the delay has expired, the part is transferred to the next process. This process
immediately released the machine which was assigned to the part, but maintains the operator
resource associated with the part.
The next process simulates the delay caused to production by the need to transport the
part to the next work center. Each part type has its own distribution of delay based on
experimental data. Depending on the part type, this distribution delays the operator from going
back to the machine, and thus causing the machine to become underutilized. This is the key
statistic that we are interested in: the amount of time that the machines are not being utilized due
to no operator being available.
Results. The simulation was run for 2000 replications each with duration of 40 hours
and the machines being utilized for eight hours a day to simulate a typical work week. As stated
previously, the main statistic that was of interest was the total utilization of the machines. The
33
result of the simulation was a total utilization of each machine at 95%. Combining all four
machines, this results in 20% of a part handler’s day being utilized on the VMC work center
alone.
The weekly rate for this work center was multiplied by a 20% increase in output from the
work center. This results in an additional yearly sales for the company of $39,000. Based on
this result, I would recommend that a part handler would be a justified investment if an
additional 80% of a workday can dedicated to moving parts for additional work centers. There
are around ten other major work centers within Company X. With approximately 20% of a part
handler’s time being used by each work center, a full time part handler would be justified by this
study, with the potential of two full time part handlers being necessary to fully accommodate the
part handling within the facility. The company could expect an addition of approximately
$429,000 in annual sales capacity.
In addition, a full time part handler would have the benefit of being more familiar with
how downstream work centers would like their parts staged. This would increase efficiency in
the downstream work centers since all parts would be presented in a standardized and uniform
way. Another side benefit would be the reduction of forklifts necessary to support the facility.
With fewer people responsible for moving parts, the existing forklifts could be more efficiently
used.
34
Chapter V: Discussion
Material handling in a manufacturing operation is a vital link between the different value
added operations. Deciding when and how parts should be moved can have a great effect on
productivity and profitability in a company. This study investigated the particular case of the
part handling out of a vertical machine work center within Company X. Data regarding the
current state of operations was gathered and a simulation which recreated the critical aspects of
the production flow was generated.
Limitations
This study will only be considering the effect of adding a material handler given
production at 2013 levels. Should production increase or decrease the need for a part handler
may change.
This study analyzes only the Vertical Machining Center work center. Further analysis
would need to be done on other work centers.
Only day shift will be analyzed in this study. Night shift will not be considered in the
data.
A representative sample of three week’s worth of production was analyzed to develop
statistical distributions used in the simulation. This data was taken from February 2013.
Conclusions
Based on the results presented in chapter four, a part handler is justified at Company X.
A part handler will be utilized approximately 20% of the day at the Vertical Machining Center
work center, and there are plenty of other opportunities within the rest of the facility. If the
change to using a part handler is implemented, capacity could increase to accommodate an
additional $430,000 in sales per year.
35
As the company grows, the problems arising from having the operators continue to move
their own parts around is going to increase. In order to prepare for the future, a solid system
which allows operators to stay at their machines where they add the most value is strongly
recommended.
Within Lean Manufacturing, the flow of product within a factory is critical to the
profitability of the company. Using part handlers to transport product is the first step to
implementing a system of material handling which achieves a lean and efficient flow throughout
the facility.
Recommendations
Based on this study, it is recommended that Company X implements a factory wide
change to utilizing part handlers to transfer parts in between work centers. This will free up
operators to continue to work at their machines, eliminate bottle necks due to insufficient
forklifts, and provide a standard means of part staging at future work centers. It will allow the
company to prepare for future expansion, and provide a visible, and accountable means to
transport parts within the factory.
36
References
Baudin, M. (2004). Lean logistics: The nuts and bolts of delivering materials and goods. New
York: Productivity Press.
Berk, J. (2010). Cost reduction and optimization for manufacturing and industrial companies.
Hoboken, NJ: Wiley - Scrivener. Retrieved from http://ezproxy.lib.uwstout.edu:2089/
web/portal/browse/display?_EXT_KNOVEL_DISPLAY_bookid=4082&VerticalID=0
Dolcemascolo, D. (2006). Improving the extended value stream: Lean for the entire supply
chain. New York: Productivity Press.
Flinchbaugh, J., & Carlino, A. (2006). The hitchhiker's guide to lean. Dearborn, MI: Society of
Manufacturing Engineers.
Low, C. H. (2004). Benefits of lot splitting in job-shop scheduling. International Journal of
Advanced Manufacturing Technology, 24(9/10), 773-780. doi: 10.1007/s00170-003-
1785-9
Ohno, T. (1988). Toyota production system: Beyond large-scale production. Cambridge:
Productivity Press.
Santos, J., Wysk, R., & Torres, J. (2006). Improving production with lean thinking. Hoboken,
NJ: John Wiley & Sons.
Sheldon, D. H. (2008). Lean materials planning and execution. Fort Lauderdale, FL: J. Ross
Publishing.
Standard, C., & Davis, D. (1999). Running today's factory: A proven strategy for lean
manufacturing. Dearborn, MI: Society of Manufacturing Engineers.
Sule, D. (1994). Manufacturing facilities: Location, planning and design Boston, MA: PWS
Publishing Company.
37
Wang, J. X. (2011). Lean manufacturing: Business bottom-line based. Boca Raton, FL: CRC
Press.
Womack, J. P., Jones, D. T., & Roos, D. (1990). The machine that changed the world. New
York, NY: Harper Perennial.
38
Appendix A: Sample Time Entry Form.
PART HANDLING - TIME TRACKING FORM FILL OUT THIS FORM WHEN MOVING PARTS FROM YOUR WORK CENTER TO THE NEXT ROUTING WORK CENTER_______________________
RETURN FILLED FORMS TO CURT CARLSON
DATE SHIFT TIME OUT
TIME IN NOTES INITIALS