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Author: King, Carolyn, L. Title: An Assessment of Automated Hotel Pan Line Efficiencies at Company V

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: Xuedong Ding, Ph.D.

Submission Term/Year: Spring, 2013

Number of Pages: 46

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 Carolyn L. King DATE: 5/15/2013

ADVISER: (Committee Chair if MS Plan A or EdS Thesis or Field Project/Problem):

NAME Xuedong Ding, Ph.D. DATE: 5/15/2013

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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:

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King, Carolyn, L. An Assessment of Automated Hotel Pan Line Efficiencies at Company V

Abstract

Company V currently has an automated manufacturing process in place to manufacture

its patented hotels pans. These high production large quantity sellers are a staple of Company

V’s business. Currently, the automated manufacturing process that is in place is producing pans

at a much lower than expected output efficiency. The automated manufacturing hotel pan line

process was originally put into place as a way to reduce the costs of producing their standard

sizes of high volume hotel pans.

This field problem was conducted for the purposes of identifying the factors used to

calculate department efficiencies, to use those factors to identify the specific cause(s) of the

current low efficiency output in the automated hotel pan line department process, and to produce

an improvement plan to increase the department efficiency. For this study, recordable measures

to calculate department efficiencies were studied and reviewed to determine what factors were

causing the low output efficiencies. The data analyzed came from operator downtime logs, parts

produced per day/per shift data, time study data, and efficiency charts and graphs created from

this data on the automated pan line. Once some specific cause results were identified a Kaizen

event was planned and executed to address the most common cause(s) of the low efficiency

output of the line. Before and after data would then be gathered and analyzed to determine the

effectiveness of the Kaizen event as well as identification of further improvement opportunities

to be analyzed and addressed.

The purpose of this Plan B Field Problem was to use established lean manufacturing

methodologies to determine root causes of low efficiencies in the automated hotel pan line

process, address those causes starting with the ones creating the highest amount of downtime,

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and show improvement in output efficiencies using a comparison of before and after data.

Ultimately, the goal was to make good sustainable improvements and continue to build on those

improvements to attain even greater future increases in the automated pan line process output

efficiencies.

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Table of Contents

............................................................................................................................................. Page

Abstract ...................................................................................................................................... 2

List of Figures ............................................................................................................................. 6

Chapter I: Introduction ............................................................................................................... 7

Statement of the Problem ................................................................................................. 7

Objective of the Study ..................................................................................................... 7

Assumptions of the Study ................................................................................................ 8

Chapter II: Literature Review ...................................................................................................... 9

Lean Manufacturing Basics ............................................................................................. 8

The 5S System ................................................................................................................. 9

The Kaizen Event .......................................................................................................... 11

Defining Lean Manufacturing Study Steps..................................................................... 12

Six Sigma and DMAIC .................................................................................................. 13

The Beginning of the End .............................................................................................. 17

Chapter III: Methodology .......................................................................................................... 18

Definition of Terms ... ..…………………………..……………………………………………………………………………………….18

Table 1. Standard Hotel Pan Sizes ................................................................................ 18

The Current Process....................................................................................................... 19

The Assessment Project Plan ......................................................................................... 20

The Pre-Kaizen Event .................................................................................................... 21

The Main Kaizen Event ................................................................................................. 22

Data Collection Procedures ............................................................................................ 25

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Data Analysis ................................................................................................................ 26

Limitations .................................................................................................................... 27

Summary ....................................................................................................................... 27

Chapter IV: Results ................................................................................................................... 29

Results of the Pre-Kaizen Event ..................................................................................... 29

Results of the Main Kaizen Event .................................................................................. 30

Results of the Define Phase ........................................................................................... 31

Results of the Measure Phase ......................................................................................... 35

Results of the Analyze Phase ......................................................................................... 37

Results of the Improve Phase ......................................................................................... 38

Results of the Control Phase .......................................................................................... 40

Chapter V: Discussion ............................................................................................................... 43

Limitations ................................................................................................................... 43

Conclusions ................................................................................................................... 43

Recommendations ......................................................................................................... 44

References ................................................................................................................................ 45

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List of Figures

Figure 1: DMAIC Model…………....…………………………………….…………………..…14 Figure 2: Automated Hotel Pan Line…………………………………….…………………...….19

Figure 3: Typical Project Plan…………………………………………….………………….….23

Figure 4: Typical SIPOC Diagram Analysis…………………………….………………………24 Figure 5: Plan Line Project Plan……..…………………………………….…………………….33 Figure 6: Pan Line SIPOC Analysis……..……………………………….……………..……….33 Figure 7: Weekly Uptime Average Percentage Chart…………………….………………….….34

Figure 8: Pan Line Downtime Pareto Chart……………………………….…………………….35 Figure 9: Current Average Setup Time…………………………………….…………………….36 Figure 10: Setup Hours After Kaizen Event…..………………………….……………..……….41

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Chapter I: Introduction

Company V currently has an automated manufacturing process in place to manufacture

its patented hotel pans. Hotel pans are drop-in pans of various sizes that are used in buffet lines

that people see every day in hotels, restaurants, schools cafeterias, etc. These pans are sold in

large quantities and are a principle part of Company V’s business. Currently, the automated

manufacturing process that is in place is producing pans at a much lower than expected output

efficiency. The automated pan line process was originally put into place as a way to reduce the

costs of producing the standard high volume hotel pans. Continuing to operate this process at the

current low efficiencies will result in a decrease in company profit and could lead to loss of

market share and competitiveness. With the current state of the economy it is especially

important that Company V ensure that it continues to remain competitive in the manufacturing

market, which can be accomplished through increased output production efficiencies.

Statement of the Problem

The Company V automated hotel pan manufacturing process currently has a lower than

expected production output efficiency. Based on recent cycle times taken of the machines and

processes of the pan line, the line is only producing at about 40 percent average output

efficiencies. Company V has set a goal of 80 percent output efficiencies to meet customer

demand. Continuing at this level will result in a lack of ability to increase profitability and could

lead to loss of market share.

Objective of the Study

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The objective of this study is to identify the key factors used to calculate department

efficiencies and product costs, to use those factors to identify the specific cause(s) of the current

low output efficiency in the automated hotel pan line department process, and to produce an

improvement plan to increase the department efficiency by at least 10 percent.

Assumptions of the Study

The assumption of this study is that Company V has used recordable measures to

calculate department efficiencies, labor costs, and product costs, so that by studying and

reviewing all the data it will be obvious where the problem with low output efficiencies lies.

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Chapter II: Literature Review

Creating an environment for greater manufacturing efficiencies is the goal of every

company competing for market share today. The question is how can companies effectively

create such an environment. There are many forms of lean production systems available for

companies to choose from, but choosing the one that suits the needs of a specific organization is

the key.

Lean Manufacturing Basics

Many of the different types of lean manufacturing systems available have some basic

concepts. From those, each company will need to develop their own lean production process by

customizing the basic concepts to suit their individual needs. The first step is for a company to

recognize what it is trying to accomplish. Things such as reducing production times, reducing

resources, reducing quality problems, increasing innovation, cutting overhead costs, etc., are

goals every company should be aiming for (Ward, 2007). Once a goal is established, a team of

people should be put together to accomplish that goal. It is important that the team includes the

correct people. In other words, all the key people from all the affected areas should be involved

in some way (Womack & Jones, 2003). Once the team is established, it is time to create a plan

of action.

The 5S System

One process used to increase production efficiencies is the 5S System of workplace

organization (Balle & Balle, 2005; Womack & Jones, 2003). Most often lean initiatives start out

with a 5S program as a way to get things organized and cleaned up as a first step toward

continuous improvement. This system uses the title 5S as an acronym for the five organizational

tools identified by the system, which are as follows:

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Sort. Removing all unnecessary items from the work process area. This first step of

organization is used to sort out the useful from the unnecessary. The only things that should

remain in the work area are the tools, parts, and instructions needed to do the job.

Set in Order. Items are arranged in an easy to find and labeled location. This step is

where visual controls can be put into place to ensure everything has a place and everything is in

place. Shadow boards for tools can be implemented; shelves and floors can be painted and

labeled, etc.

Shine. Keeping resources in top condition and ensuring that they are always available.

This step is where spring cleaning can be done. Floors can be swept and mopped, machines can

be wiped down and even washed and painted, and anything else considered necessary to make

the work area shine.

Standardize. Ensure the first three steps are being followed to prevent setbacks. By this

step routine cleaning should be a way of life. A routine maintenance and cleaning schedule

should be developed and posted so everyone in the work area knows what the expectations are

and understands their responsibilities within the department.

Sustain. Properly make a habit of the other steps to maintain correct procedures. Both

supervisors and workers ensure that the 5S system steps are being followed. Workers follow 5S

schedule checklists and supervisors perform audits to ensure the process is sustained.

There are several benefits of the implementation of the 5S system. One benefit is that the

work area is kept clean and potential problems are not hidden. For example, when the area is

clean it is easy to notice if a machine starts leaking oil. Another benefit of the 5S system is that

because everything is set in order, time is not wasted looking for misplaced tools, materials, and

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supplies. The key to realizing the benefits of the 5S system is sustaining the system over time

(Systems 2 Win, 2013).

The Kaizen Event

In many cases the best way to create an effective plan of action is to have what is called a

Kaizen Event, which is one of many established lean manufacturing tools. It is important to note

the there are two different kinds of Kaizen to consider. One type is the flow Kaizen which

involves value-stream improvement and focuses on material and information flow. The other

type of Kaizen is the process-level Kaizen which involves the elimination of waste at the shop

floor level and focuses on people and process flow (Rother & Shook, 2003). Both kinds of

Kaizen are important to a company, but for the purposes of this project I am going to concentrate

on the process-level Kaizen focusing on elimination of waste in our process to improve output

efficiencies. Waste is defined as any activity that consumes resources but creates no value for

the customer. Eliminating a large number of wasteful activities is one of the greatest potential

sources of improvement in process performance (Marchwinski, Shook, & Schroeder, 2008).

The process-level Kaizen event is typically conducted over a five day period of time and

breaks each step up into its daily schedule. Day one is the planning part of the event. This

includes such things as training the team on lean manufacturing principles, concepts, and

techniques, and looks at all the tools that will be needed to resolve the problem at hand. Day one

is also when all the data that has been collected up to that point will be reviewed to further

analyze the underlying cause of the problem. Observations of the actual process are also made to

identify issues contributing to the problem. Day two is used to begin the experimental

implementing of changes to the process in an effort to address the problems found on day one.

Day three is used to review the changes made on day two to see if they are valid. If they were

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not valid, then new changes are made and the cycle repeats itself until a correct solution is found.

Day four is when standard work practices are developed based on the successful solutions found

and verified on day three. Once these standard work practices are in place and followed, the

original problems should not resurface. Day five is the day for sharing all the team findings and

celebrating the success of a job well done. This is also a good opportunity for teams to identify

other areas where implementation of their findings may be useful.

Defining Lean Manufacturing Study Steps

Once a Kaizen event has taken place and 5S processes have been put into action, what

does a company do next when it still does not see the production output efficiencies it expects?

It is time now to get into specific time study data and figure out what is slowing the process

down. This digs deeper into the process than our Kaizen event did and takes much more time.

According to Rother & Harris (2001), each work element of the process needs to be identified.

Takt times for each work element will have to be taken. Cycle times will need to be established

for each part of the process, both machine and human. Material management and flow needs to

be analyzed to ensure that each movement in the process is a value-added one. The direct

efficiencies of the work cell are not the only factors that affect production output. Factors such

as incoming raw material availability and quality affect the work cell production efficiency

(Smalley, 2004); the level of machine maintenance affects the work cell production efficiency;

the condition and maintenance of required tooling needed to do the job affects the work cell

efficiency; the skill level and quality of training of personnel affects work cell efficiency (Rother

& Harris, 2001), etc. All of these aspects need to be thoroughly analyzed to determine current

and potential problems in the work cell process. Data collection needs to be done and

maintained so that accurate comparisons can be made to old and new methods of production

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techniques. This data will tell you whether or not the improvements made were truly

“improvements” or just a way of redirecting the real efficiency issues.

Six Sigma and DMAIC

Six sigma is defined as a quality standard of just 3.4 defects per one million

opportunities. Six Sigma methodologies emphasize statistical tools to improve the quality of

established processes. The application of Six Sigma methodologies follows a five step process

often referred to as DMAIC, which is the acronym for the terms define, measure, analyze,

improve, and control (Marchwinski et al., 2008). See Figure 1.

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Figure 1. DMAIC Model

The define phase of DMAIC is the first phase of the lean Six Sigma improvement

process. In this phase the team makes an outline of the current process and determines what the

problem is that needs to be fixed. Once the team defines the problem, they determine what

sources of data will be used, what impact improving the process will have on the business, and

what departments are involved. The team will then confirm what resources they have available

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to them for the improvement project and then set a measureable goal that will determine whether

the project was successful (Go Lean Six Sigma, 2013). A few of the most common tools used

during the define phase are a project plan and a Suppliers, Inputs, Processes, Outputs, and

Customers (SIPOC) analysis. The development of a project plan is usually the first step of the

define phase. In the project plan a problem is defined by developing a problem statement. The

problem statement confirms that the process is causing problems, and that those problems are of

a high priority and have an impact on the process. The project plan then defines the project goal

by developing a goal statement. This statement defines a measureable goal for the project team.

The project plan also identifies the scope and boundaries of the project, lists the project team

members, and sets a general timeline for the phases of the DMAIC process (Go Lean Six Sigma,

2013). A SIPOC diagram is a tool used to identify all the relevant elements of the process

improvement project. It identifies the suppliers of the process, the inputs to the process, the

actual process steps, the outputs of the process, and the customers of the process. The SIPOC

diagram gives an overall roadmap of the process which enables the project team to get a clear

understanding of all the process elements for analysis (I Six Sigma, 2013).

The measure phase of DMAIC is the second phase of the lean Six Sigma improvement

process. In this phase the team uses data collection to determine the state of the current process.

Using this data, the team can set a baseline and try to figure out where there may be root causes

to waste in the current process. Setting a baseline and determining the root causes of problems

gives the team areas to focus on to achieve their improvement goal (Go Lean Six Sigma, 2013).

The analyze phase of DMAIC is the third phase of the lean Six Sigma improvement

process. This phase is often tied in with the measure phase. As new data is collected in this

phase, the data collection methods may need to be adjusted depending on the results when

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comparing the baseline data to the new data. Data may also need to be collected from additional

sources to get a better analysis of the situation. When doing a process analysis, a time analysis is

critical in determining the actual amount of time work is being done in the process (Go Lean Six

Sigma, 2013). A time analysis should consist of: machine cycle time, which is the time a

machine requires to complete all of its operations; operator cycle time, which is the time it takes

an operator to complete all the work elements before repeating them; and total product cycle

time, which is the time it takes for a product to move all the way through the process from start

to finish (Marchwinski et al., 2008). Data collection for the machine cycle time and operator

cycle time analysis is usually done by direct observation and timed with a stopwatch. Operator

cycle time is also sometimes analyzed by creating what is call a spaghetti diagram. This is done

by actually following the operator step by step and drawing out a path of all the steps the

operator takes during the process and timing them (Liker, 2004). An important element of this

phase is determining what time is value-added time and what time is non-value-added. Non-

value-added time is time that is spent on activities that add costs but add no value to the item

being produced. During analysis, this non-value-added time can be identified as waste and

targeted as a place to implement improvements. Another aspect of time analysis is to determine

the time lost during setup or changeovers, and downtime. Changeover or setup time is defined as

the measured time that elapsed between the last piece in the run just completed and the first good

piece from the process after the changeover. Downtime is defined as any production time lost

due to planned or unplanned line stoppages. Planned downtime is scheduled for such things as

shift changes and scheduled maintenance. An example of unplanned downtime would be

machine breakdown (Marchwinski et al., 2008). When analyzing the process, these are all areas

that can be targeted for the potential improvement of output efficiencies.

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The improve phase of DMAIC is the fourth phase of the lean Six Sigma improvement

process. In this phase the team determines how to improve the process to fix the problem. The

improvement solution is based on the analysis of the data collected in the previous phases. The

team usually will develop a list of possible improvements and then narrow down the list based on

priority and the ability of the improvement to achieve the previously set project goal. This phase

takes careful planning and multiple improvement attempts may be necessary. Once the team is

able to show that the solution resulted in measureable improvement, they can move on to the

fifth and final phase of the process (Go Lean Six Sigma, 2013).

The control phase of DMAIC is the fifth and final phase of the lean Six Sigma

improvement process. In this phase the team determines how to sustain the newly achieved

improvement. The team narrows down what important data of the ongoing process performance

they want to measure and monitor to ensure sustainability. The team also determines what to do

if the process performance data does not meet expectations. This may lead the team to address

further process performance improvements (Go Lean Six Sigma, 2013). The key to the success

of the DMAIC improvement process is to keep accurate records and to keep all documentation

updated.

The Beginning of the End

The most important thing to remember when implementing new and different lean

manufacturing production methods is that the improvement process is never complete. There

needs to always be a continual improvement and sustain schedule built into the process. There

also always needs to be follow-up studies and adjustments made to every process. This is a

never ending process, hence the name “continual improvement”.

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Chapter III: Methodology

This study was conducted to determine the cause(s) of the low production output

efficiencies of Company V’s automated hotel pan line department process. By determining the

problems causing the efficiency issues, the project team was able to implement changes in the

process to improve material flow, reduce labor costs, and reduce downtimes.

Definition of Terms

Hotel Pan. A Hotel Pan is a rectangular shaped pan used as a drop-in part in standard

buffet line units. They are made from stainless steel material in thicknesses of 0.024 inches (24

gauge), 0.036 inches (20 gauge), and 0.048 inches (18 gauge). The hotel pans are made in

various standard sizes ranging from full size to sixth size and are available in different depths.

See Table 1.

Table 1. Standard Hotel Pan Sizes

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Automated Hotel Pan Line. The Automated Hotel Pan Line is a production line set up

with hydraulic and mechanical presses, automated pan transfer arms, conveyors, and robots, so

that the hotel pans are produced from a steel coil at the start of the process and a finished product

at the end of the process with only one operator needed to complete the task. See Figure 2.

Figure 2. Automated Hotel Pan Line

The Current Process

The automated hotel line process is designed to take raw material and produce a finished

product in one location. As shown in Figure 2, the pan line process consists of the following

steps:

1. At the start of the line coils of steel are put onto a coil feeder, which uncoils the steel

coils.

2. The steel is then fed through a straightener, lubricator, and shear, which cuts the steel

to the proper blank size.

3. Robot number one picks up the steel blank and places it into the draw one hydraulic

press for the first draw.

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4. Once the draw one press makes the first draw on the part, robot number one removes

and part and places it onto a conveyor which brings it to robot number two.

5. Robot number two picks up the part and places it into the draw two hydraulic press

which draws the part to its full depth.

6. After the second draw is made on the part, robot number two removes the part from

the draw two press and places it onto a conveyor that feeds the part into the transfer beam.

7. The transfer beam is a machine that has four sets of arms to pick up the parts. The

arms move in and out, and up and down simultaneously. Once a part reaches the end of the

conveyor feeding the transfer beam, the arms simultaneously move in to pick the part off of the

infeed conveyor, out of the bead press, out of the stamper, and out of the trim press. It then shifts

over and places those parts into the bead press, stamper, trim press, and outfeed conveyor. The

transfer beam is always handling four parts at a time at different stages through the transfer

section. The part placed on the transfer beam outfeed conveyor is fed down to the deburr cell.

8. The deburr cell consists of two robots that take the parts and runs the edges of them

along a deburring/grinding wheel to remove the sharp edges before stacking the parts down onto

a pallet.

The Assessment Project Plan

Based on the scope of the project at Company V, the project team decided to approach

the assessment of the automated hotel pan line output efficiencies in two separate staged events.

The first event scheduled was what the team called the pre-Kaizen event during which the team

implemented the 5S system steps. The second event scheduled was what the team called the

main Kaizen event during which the team used the DMAIC model to determine what they

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wanted to accomplish, set a goal, and implement a process improvement plan to improve

production output efficiencies.

The Pre-Kaizen Event

The pre-Kaizen event was scheduled for February 2011. The primary focus of the pre- Kaizen event was to implement the 5S system, while at the same time gathering information in preparation for the main Kaizen event. The first step was to create a project team of key

personnel to participate in the event. The key personnel chosen were a lean manufacturing

engineer, a production supervisor in charge of the automated pan line department, four

production operators from various shifts, and two maintenance personnel. Once the project team

was created, meetings were scheduled every day at the start of the day and again at the end of the

day to follow the progress of the event. On day one of the five day event, the project team

focused on the sort component of the 5S system. The sort component required identifying what

items needed to be located directly in the work process area. On day two of the event, the

project team focused on the set in order component of the 5S system. This required all necessary

items located directly in the work process area to be not only identified but labeled with locations

as well. On both day three and day four of the event, the entire area was cleaned to meet the

requirements of the 5S system component of shine. On day five of the event, the 5S system

components of both standardize and sustain were implemented. The project team decided on a

cleaning and maintenance schedule that was to be written and posted with a list of operator

responsibilities and a check off sheet. During the entire pre-Kaizen event observations of issues

for the main Kaizen event to address were being documented.

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The Main Kaizen Event

The main Kaizen event was scheduled for March 2011. The same project team that was

created for the pre-Kaizen event participated in the main Kaizen event. It was decided by the

project team that the event format was to follow the traditional five day procedure of the standard

Kaizen event while utilizing the lean Six Sigma improvement process of DMAIC as the primary

assessment tool.

On day one of the event, both the define phase and the measurement phase was

implemented by the project team. For the define phase the project team set a measureable goal

to improve the automated pan line output efficiency by 10 percent. This goal was set based on

both project team member input and company expectations. A project plan was created to

develop both a problem statement and a project goal. The project plan also allowed the project

team to set the scope and boundaries of the project. The project plan listed the project team

members and let the team map out each phase of the DMAIC process and estimate how long

each phase would take. Figure 3 is an example of a typical project plan used in this type of

process methodology.

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Project Name and Location:

Problem/Opportunity Statement:

Financial/Business Impact:

Current State Measurables/Metrics (Process Performance, Efficiency, etc…):

Project Goals and Objectives:

Scope/Boundaries of Project:

Potential Safety Concerns/Hazards:

Champion-Facility Manager

Project Facilitator

Project Leader

Project Team

Preliminary Project Plan Target Date Actual Date

Define

Measure

Analyze

Improve

Control

Prepared by:

Date Prepared :

Figure 3. Typical Project Plan

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During the define phase, once a project plan was developed with a clearly stated project

goal, the team completed a Suppliers, Inputs, Processes, Outputs, and Customers (SIPOC)

analysis. The team was able to clearly define who the suppliers to the process are, what the

inputs to the process are, the actual process steps, the outputs of the process, and who the

customers of the process outputs are. This classic DMAIC tool allowed the project team to get

an overall view of all the relevant elements of the current process to be analyzed. Figure 4 is an

example of a typical SIPOC Diagram used in this type of process methodology.

Figure 4. Typical SIPOC Diagram Analysis

For the measure phase the project team reviewed all past documented data and

determined that downtime due to changeovers or setup was the leading cause of lost production

output time on the line.

On day two of the event the analyze phase was implemented by the project team.

Numerous trial setups were done by project team members. The setups were videotaped and

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elements of the process were timed to determine where there was waste in the process. Machine

cycle times and operator cycle times were taken through direct observation and measured with a

stopwatch. The videotaped trial setups were reviewed by the project team and spaghetti

diagrams of the setup process were created.

On day three and day four, the improve phase was implemented by the project team.

Based on the information attained during the analyze phase, selected actions were planned to

improve the current setup procedures. Some of these actions were addressed immediately, while

a number of the selected actions would require time to change. The selected actions that were

addressed and implemented immediately allowed the project team to do additional trial setups,

re-analyze the new data collected, and see some immediate improvement results. But some of

the selected actions would take more time to implement. All of the improvement actions

selected by the project team that could not be addressed immediately were documented and

given future deadlines for completion.

On day five the project team implemented the control phase. The goal of the control

phase is to maintain all the achievements attained in the improve phase. The project team

designed an improvement plan that would maintain the improvements already made, and they

included in the plan the steps needed to maintain the future improvements that would be made

based on the selected actions and timeline established in the previous phase.

Data Collection Procedures

Data collection of the pan line process consisted of the following steps:

1. Downtime sheets were used as an integral part of this study. These downtime sheets

are filled out by each operator every day during his/her shift. The sheet lists the job/part number

being run, the amount of pieces per hour expected and actually produced, and any downtime that

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occurred. The downtime sheet has columns listed with downtime reasons such as set-up time,

tooling issues, different maintenance and machine issues, etc., so the operator can log

everything. Scrap tally sheets are used to keep track of lost material. These sheets are filled out

by the operator for each job/part number and have a list of codes to identify the reasons for any

lost time and for the scrap. For example, bad raw material, tooling defects, set-up problems,

machine problems, etc.

2. The operator downtime sheets were collected by the department supervisors after each

shift.

3. The data from the operator downtime sheets was compiled and entered into an excel

spreadsheet from which production output efficiency and downtime charts and graphs were

created for analysis.

4. Time study data was collected and recorded through direct visual observation and the

actual timing of machine, process, and operator cycle times with a stopwatch.

5. Setup data was collected by videotaping actual setups.

6. Setup data was then further analyzed with the creation of spaghetti diagrams based on

the setup videos.

Data Analysis.

The data collected was analyzed very closely. Most of what was done was through the

simple plotting of charts and graphs and comparing the information from the year 2009 to 2011.

The downtime data from the operator downtime sheets was entered into an excel spreadsheet and

then plotted in charts and graphs. Data from the past two years was used to get the most accurate

historical accounting of downtime reasons, such as tooling and maintenance issues, so that

proper comparisons could be made using statistical analysis. The collection of work element

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cycle time data was difficult to analyze since there are apparently no consistent standard work

practices currently in place. This part of the study made the project team realize that standard

work practices would need to be established and enforced before any definitive results of this

project assessment could be realized.

Limitations

A limitation of this study is that all the results of this study are limited to Company V.

All the data collected and analyzed for this study was taken only from the Company V automated

hotel pan line process operation. The information used was gathered from data collected by

operators, management, and lean manufacturing engineers directly involved in the Company V

manufacturing process.

Summary

This study used both Kaizen and Lean Manufacturing principles to create greater output

efficiencies for the Company V automated hotel pan line process. Specifically, the DMAIC

method, including the five phases of Define, Measure, Analyze, Improve, and Control, was

established as the primary project methodology using the main practices from this approach to

improve production output efficiencies.

With the goal of increasing the automated pan line output efficiency at Company V, the

project team utilized various tools from lean Six Sigma improvement methodologies to provide

suggestions for improvement. The project team implemented the 5S system in the pan line

department. The project team used a five day Kaizen event to assess the department production

output efficiencies using the DMAIC methodology. In the define phase the project team set a

measureable goal of increasing the automated pan line output efficiency by 10 percent, created a

project plan, and completed a SIPOC analysis. In the measure phase the project team reviewed

28

past data to determine a primary root cause of reduced output efficiency. In the analyze phase

the project team gathered further data through trial setup tasks to determine where improvements

could be made to the process. In the improve phase the project team the team reviewed all the

data collected in the previous phases to determine which improvements needed to be

implemented. In the control phase the project team designed an improvement plan that would

sustain the implemented improvements.

Data from Company V was used to review the automated pan line output efficiencies.

This field problem analyzed past and present calculated output efficiencies, downtime data, set-

up time data, and labor cost data to determine what was causing the greatest negative impact on

output efficiencies. Based on this study, an improvement plan was developed to increase

efficiency by at least 10 percent in this department. The plan will be presented to Company V as

a recommendation on best how to improve their current automated hotel pan line manufacturing

process.

29

Chapter IV: Results

This study took a lean Six Sigma approach in order to create greater production output

efficiencies for the Company V automated pan line department. Kaizen, the 5S system, and

DMAIC methodologies were used. It was decided that the study would take place as two

separate five day project events. The first event was called the Pre-Kaizen event during which

the 5S system was implemented in the automated pan line department. The second event was

called the Main Kaizen event during which DMAIC methodologies were used to assess the

automated pan line production output efficiencies. Below are the results of the study.

Results of the Pre-Kaizen Event

The pre-Kaizen event was scheduled in February 2011. A project team of eight people

was created for the purpose of implementing the 5S system in the automated pan line

department. The project team was also tasked with making notes on potential issues that could

be addressed as part of the main Kaizen event planned for the following month.

The first step for the project team was to define what the 5S system was and use that

information as a tool for implementation of the steps. The project team started with step one –

sort. The project team members took all the items in the department area that were not clearly

identified or needed and placed them in a designated area. Once that was done the project team

members sorted through those items to determine what they were and if they were not needed

they were removed from the area.

The project team then moved on to step two – set in order. All of the items identified as

needed items were placed in the locations where they were needed and organized. Shadow

boards for hand tools were made and installed at their points of use. Parts and other machine

tooling, such as robot arms and tooling push-outs, were placed on shelves and the shelves were

30

labeled accordingly. Designated locations on the floor for raw materials, tool staging, scrap bins,

etc., were painted and labeled.

The project team then addressed step three of the 5S system – shine. The Project team

members wiped down all the machines, scraped the oil and grease from the floors under the

machines, swept, mopped, and used a floor scrubber on the floors in the entire department, etc.

During this step the project team members who were part of the company maintenance

department did repairs, such as fixing oil leaks.

The project team then began work on step four of the 5S system – standardize. For this

step the project team members created a standardized cleaning schedule with operator assigned

responsibilities. The tasks on the schedule were divided up based on whether the specific task

needed to be done each shift, daily, or weekly. The written schedule was then posted in the

department with an operator check off list to indicate when a task was completed.

Once step four was completed, the project team then addressed step five of the 5S system

– sustain. The project team decided that to ensure sustainability of the 5S system now

implemented, the supervisor of the automated pan line department would need to follow up each

day to make sure the operator assigned cleaning tasks were completed and checked off. It was

also decided that the supervisor would do a 5S audit of the department at least once a week to

verify the system was being sustained.

Results of the Main Kaizen Event

The main Kaizen event was scheduled in March 2011. The same project team that was

created for the pre-Kaizen event participated in the main Kaizen event. The purpose of the main

Kaizen event was to address the business problem of low production output efficiencies in the

automated pan line department at Company V. The strategy of this project was to conduct a

31

study of the department using the DMAIC methodology of lean Six Sigma. Below are the

results of each phase of the DMAIC methodology.

Results of the Define Phase

The business problem was defined at Company V as a lower than expected automated

pan line department production output efficiency. Once all the project team members had a clear

understanding of the DMAIC methodology and what each phase entailed, the project team

started on the define phase. First, the project team created a project plan based off the typical

DMAIC sequence which with they were able to set a clear project goal and timeline of the

DMAIC phases. This is shown in Figure 5.

32

Project Name and Location: Old Pan Line Project at Company V Problem/Opportunity Statement: Problem: Low pan line output efficiencies. Opportunity: By analyzing current data from operator downtime logs, time studies, and efficiency data created from those sources, a root cause of low efficiencies can be determined and addressed to increase pan line output efficiencies. By creating more consistency in the line, downtime can be reduced and outputs increased.

Financial/Business Impact: Increased output efficiencies. Labor and set-up reduction.

Current State Measurables/Metrics (Process Performance, Efficiency, etc…): Set-up times, Cycle times, Downtime data, Efficiencies, Outputs.

Project Goals and Objectives:

Increase line efficiencies. Increase fill rates/output rates. Reduce downtime and labor costs.

Scope/Boundaries of Project: Increase output efficiencies by improving the current pan line process. Costs of the project must remain minimal.

Potential Safety Concerns/Hazards:

Currently there are no standardized LOTO procedures developed for set-up or operation of the line.

Champion-Facility Manager Manufacturing Operations Manager

Project Facilitator Lean Manufacturing Engineer

Project Leader Lean Manufacturing Engineer

Project Team Operations Supervisor, Set-up Personnel, Operators, and Maintenance Personnel

Preliminary Project Plan Target Date Actual Date

Define 3/7/2011 3/7/2011

Measure 3/8/2011 3/8/2011

Analyze 3/9/2011 3/9/2011

Improve 3/10/2011 3/30/2011

Control 3/11/2011 6/8/2011

Prepared by: Project Facilitator

Date Prepared : 3/7/2011

Figure 5. Pan Line Project Plan

33

Next, the team used a SIPOC analysis which detailed the suppliers, inputs, processes, outputs,

and customers, as well as the resources within the process in order for the team to get a better

grasp on these elements of the process. This analysis gave the team a complete outline of the

current automated pan line process. The results of the SIPOC analysis are shown in Figure 6.

Figure 6. Pan Line SIPOC Analysis

After both the project plan and SIPOC analysis were completed, the project team then

determined the sources of data that would be used for the project. Operator downtime sheets

were determined to be a vital source of information because they list the job and part numbers

that were run, the amount of parts actually produced compared to the expected parts per hour

based on current time study data, and any downtime that occurred. Given this information it was

easy for the project team to determine that the amount of downtime incurred in the department

was the primary issue. The weekly uptime average percentage falls far below the expected

weekly uptime average goal of 80 percent as shown in Figure 7. It was determined that

34

increasing the weekly uptime average percentage would have a significant impact on the

business and a large cost savings could be realized if improvements to the process were made.

Figure 7. Weekly Uptime Average Percentage Chart

The project team noted that in order to increase the automated pan line weekly average

uptime percentage the reasons for the downtime would have to be analyzed. Due to the fact that

some of the reasons for the downtime involved supporting departments to the pan line

department, for example the maintenance department and the machine tooling department, key

personnel in those departments were notified that the confirmed availability of resources from

their departments would be necessary for the success of the project. Once resources for the

project were confirmed, the project team established a project goal. The team members all

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

8/2

1/1

0

8/2

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/10

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/2/1

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/9/1

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/6/1

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/13/1

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/27/1

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/4/1

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/11/1

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/18/1

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/25/1

0

1/1

/11

1/8

/11

1/1

5/1

1

1/2

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/11

2/1

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/11

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6/1

1

Upt

ime

% A

vera

ge

Week Ending

Old Pan Line - Weekly Uptime % Average

Uptime % Average Goal Free Pizza

35

agreed to set a measurable project goal of increasing the automated pan line production output

efficiency by 10 percent.

Results of the Measure Phase

During the define phase the project team had determined that the weekly average uptime

percentage needed to be increased. Based on that fact, the project team reviewed all the most

recent documented downtime data to determine the primary reasons for the automated pan line

process downtime. By doing this the project team was able to determine that while there were a

number of reasons for the pan line process downtime, the primary root cause was the amount of

hours logged as setup time. This is shown in Figure 8.

Figure 8. Pan Line Downtime Pareto Chart

0

50

100

150

200

250

300

350

400

Set U

p

Not S

taffed

Toolin

g

Robot -

C7

PM

/6S

Mate

rial/w

aitin

g for

matl

R&

D

Robot -

C6

Mechanic

al -

Feeder

Lube

Deburr

Cells

Lunch/B

reaks

TP

(T

rim

Pre

ss)

Tra

nsfe

r/conveyor

Tendin

g/C

6

Mechanic

al -

3371

Scra

p F

aults

Tra

inin

g

Sta

mper

(M/E

)

Mechanic

al -

3370

Bead P

ress M

ain

tenance

Sta

rt u

p

Ele

ctr

ical -

3370

Shear

Hou

rs

Root Cause

Old Pan Line Downtime Pareto Cumulative Hours - (last 60 days)

36

After determining that the primary root cause for the automated pan line process

downtime was setup time, the project team focused on reviewing all documented data on current

setup hours. By taking the current setup hours data and plotting it graphically, the project team

was able to determine that the current average setup time was 4.25 hours as shown in Figure 9.

Figure 9. Current Average Setup Time

Using the current setup time data that indicates an average of 4.25 hours per setup, the project

team was able to establish a baseline for setup time. Based on the fact that it has already been

determined by the project team that to achieve the project goal of increasing pan line output

efficiencies downtime needs to be reduced and the fact that it has already been determined by the

project team that the primary root cause of downtime is setup time, the team decided to set a

secondary goal to achieve the primary project goal. The secondary goal set by the project team

was to decrease pan line setup time from an average of 4.25 hours per setup to one hour per

0

2

4

6

8

10

12

14

16

18

1 8

15 22 29 36 43 50 57 64 71 78 85 92 99

106

113

120

127

134

141

Setup Hours/Setup #1 8/17/10 - 02/25/11

Setup Hours/Setup #1

Linear (Setup Hours/Setup #1)

37

setup. By decreasing the setup time, the primary root cause of downtime would be decreased,

and the project goal of increased output efficiency would increase due to the increase in the

automated pan line process uptime.

Results of the Analyze Phase

The project team allotted the majority of time during the main Kaizen event to the

analyze and improve phases based on the facts determined in the previous phases and the goals

that were set. Once it was determined that the pan line process setup times needed to be reduced,

the project team decided to do a number of trial setups and videotape them. While the trial

setups were being done, time study analysis was also done. Machine cycle times and operator

cycle times were measured through direct visual observation with the use of a stopwatch, and

then recorded.

After completing several trial setup runs, the project team reviewed the videotaped

footage and recorded cycle times. While watching the videotape the project team created a

spaghetti diagram to allow for even further analysis of the setup. These tools gave the project

team an enormous amount of insight into some of the obvious problems. The project team saw

that the setup personnel spent several hours lining up and centering the tooling in the presses

because there are no line-up pins in the press bed to indicate where center is. They also spent a

lot of time installing strikers on the tooling and assembling the tooling push-outs. Another thing

that took a lot of time was actually locating the tooling for the presses. The tooling is located in

various tooling racks throughout the department and in the tooling storage area which is in

another section of the building. It also took a lot of time to locate the steel coils allocated for the

jobs, which are located some distance away in the steel room department storage area. For all of

these issues, a lot of travel time was documented. The project team also found that the setup

38

packets/paperwork needs to be updated and that some of the part prints are not accurate. During

the setup a robot programmer had to be called out to adjust the robot programs for proper pick up

and placement of the parts, and according to the operators on the project team, this is an ongoing

issue. The project team discovered that there is no standard choreography as to the order of how

things should happen during the setup, and there are no standard lock-out/tag-out (LOTO)

procedures in place. Based on all this information, the project team made a list of some “quick

hits” that could be addressed immediately. Some of the items on the list are:

1. The setup paperwork needs to be updated.

2. The tooling and coils of steel need to be pre-staged for the next jobs to be setup.

3. A standardized setup choreography with LOTO procedures needs to be developed.

4. The tooling for the presses needs to be standardized (line-up pins, etc.) for easy

removal and installation.

5. The robot programs need to be verified and updated for each size of pan.

Based on the new data that the project team attained during the trial setup runs done

to this point, the team members decided to do additional trial setups with some proposed

improvements made immediately and then analyze the improvements. The project team then

went back out to the pan line department and pre-staged all the raw materials and tooling before

beginning the trial setup. After completing several additional trial setups and videotaping them,

the project team analyzed the new data. It was obvious to the project team that by even making

only some of the proposed improvements that the setup times were greatly improved.

Results of the Improve Phase

39

Based on what the project team determined in the analyze phase, a task list of

improvement items was compiled for the project team to complete. The task list contained the

following items:

1. A white board was placed in the area with a staging checklist so that as things were

pre-staged before the actual setup they could be visually checked off the list.

2. A standardized setup choreography procedure was developed. It was then printed

(pictures included), placed in a three-ring binder, and hung on the pre-stage white board to be

used as a standardized instruction manual for setups.

3. Line-up pins were installed in the press beds for centering the press tooling, and the

tooling services department is scheduled to install grooves in all of the tooling for centering

purposes.

4. The quality and drafting/engineering departments are scheduled to make the necessary

updates to the setup packets/paperwork and part prints.

5. The robot programs are scheduled to be reviewed, updated, and standardized for each

size of pan.

Some additional important issues that the project team noted and addressed immediately

during the improve phase of the main Kaizen event created even more setup time savings. Some

tooling racking was modified/relocated to allow for an easier and shorter walking path around

the enclosed cells for the setup personnel. The lubrication tanks for the steel lubricator were

moved to the outside of the enclosed cell with extended hoses through the cell wall. This allows

for the tanks to be checked and refilled without entering the enclosed cell which stops the line.

Rotary interlocks were installed on the six access doors to the enclosed cells. These interlocks

replaced the manual ones that the setup personnel had to stop and remove and/or insert a key into

40

each time a cell was entered to make an adjustment. The belt on the exit scrap conveyor of the

trim press was replaced with a cogged belt to minimize scrap faults/jam-ups. Castors were

installed on the scrap hoppers so that operators can easily change out the scrap hoppers without

the need of a forklift. With all these improvements in place, measureable improvements could

be seen immediately with the potential of even greater measureable improvements in the

upcoming weeks following the project event.

Results of the Control Phase

During the control phase, the project team discussed methods of measuring, monitoring,

and sustaining what the team accomplished during the improve phase. The first item discussed

was the fact that the full measure of improvement shown would not actually be seen for about six

weeks following the project event. This was due to the fact that some of the tasks on the project

improvement list were scheduled to be done by supporting departments and would take time to

be completed. Based on that fact, the project team felt that it was vital for the pan line

department operators to continue filling out downtime sheets to monitor the same data as

previously collected for comparison purposes. By continuing to document downtime data, any

changes could quickly be observed and any issues could be addressed immediately to sustain the

improvements already made.

In June 2011, three months after the main Kaizen event took place; updated pan line data

was assessed. The updated data showed that the goals that the project team had set were met.

Specifically, the goal of reducing the pan line average setup time from 4.25 hours per setup to

one hour per setup was achieved. As shown in Figure 10, the new average setup time was

reduced to 0.94 hours.

41

Figure 10. Setup Hours After Kaizen Event

Ultimately, all the goals set by the project team were met based on current data. With the

reduced setup times, the pan line process increased its average weekly uptime percentage. With

the reduction in downtime, the pan line is producing more product and has increased its output

efficiencies. The following is a list of the time and cost savings that resulted from the Kaizen

event.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

1 7

13 19 25 31 37 43 49 55 61 67 73 79 85 91 97

103

109

115

121

127

Setup Hours/Setup 3/01/11 - 6/8/11 After Kaizen

Setup hr/setup

Linear (Setup hr/setup)

Linear (Setup hr/setup)

42

Cost Calculations

Cost of Project Materials $1200 Cost of rotary interlock switches for six cell access doors

$400 Cost of cogged conveyor belt for scrap conveyor

$100 Cost of casters for two scrap hoppers

______All other materials for the project are used from existing in-house supplies

$1700 Total out-of-pocket expense

Time Invested in Project

One week Kaizen event with a project team of eight people.

Two weeks of additional time to train all operators on all shifts in new standard work procedures.

Total time before significant results were realized = three weeks

Cost Savings Three Weeks after Project Completion

Average two setups per day at one and one-half hours per set-up = three hours per day saved

Average two hours lost due to scrap faults per day = two hours per day saved

Average five hours saved per day = 25 hours saved per week = 1300 hours saved per year

Average two pan line operators at $30 per hour = $60 per hour

1300 hours per year x $60 per hour = $78,000 Total Savings

Please note that the $78,000 in total savings is the minimum amount that will be achieved

since calculations were based on 40 hour work weeks (no overtime hours) three weeks after the

Kaizen event. Future additional uncalculated savings will be realized due to some efficiency

increases that will be seen because of the various scheduled improvements still being made by

supporting departments.

43

Chapter V: Discussion

The purpose of this study was to improve the automated pan line production output

efficiencies at Company V through a lean Six Sigma approach using several lean methodologies.

Chapter I provided an overview of the company and stated the purpose of the study. Chapter II

provided a background of the lean Six Sigma methodologies of Kaizen, the 5S system, and the

DMAIC process, that were tools used in this study. Chapter III described the steps used in the

Kaizen, 5S system, and DMAIC processes specific to this study and Chapter IV discussed the

results of these implemented processes.

Limitations

This study and the results were limited in scope because of the uniqueness of the

automated pan line production process at Company V. Another limitation was the fact that there

have been a number of undocumented changes made to the automated pan line process since the

last work element cycle times were conducted, making past and present comparisons difficult.

Since these changes have been made to the process gradually over the course of time, there were

no longer any valid established standard work processes to follow, creating production output

inconsistencies from operator to operator and from shift to shift. Also, the study was limited by

time due to the fact that some of the recommended improvements could not be accomplished

immediately and needed to be scheduled with future deadlines by supporting departments.

Conclusions

This assessment project focused on the low efficiency production output of the automated

pan line process at Company V. A lean manufacturing project team was created to implement

lean Six Sigma methodologies into the pan line production process. The project team reviewed

data that was collected from actual output efficiency charts and downtime data collected from

44

operator log sheets. Based on all the data that was collected and analyzed by the project team, it

was determined that the automated pan line setup times was the primary cause of lost production

time on the line. After this determination was made by the project team, the team utilized the

lean methodologies of Kaizen, the 5S system, and the DMAIC processes, to make improvements

to the current process. After the project was completed, and before and after data compared, the

end result showed a definite and significant improvement to the process with the changes that

were made. The automated pan line production process setup times were reduced, average

weekly uptime percentages were increased, and overall production output efficiencies were

increased. These achievements also resulted in a production process cost savings for Company

V.

Recommendations

This project focused on pan line setup efficiencies once that was determined to be the

leading cause of production downtime. The recommendation of the project team is that another

Kaizen event take place in six months time to ensure that the improvements that were made are

being sustained. It is also recommended that additional events be done to address other noted

downtime causes, such as tooling problems and robot programming problems, to further improve

upon the overall production output efficiency of the automated pan line process.

45

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