Teaching Lean Process Design using a Discovery Approach
Sharon A. Johnson, Arthur Gerstenfeld, Amy Z. Zeng, Boris Ramos, Saumitra
Department of Management
Worcester Polytechnic Institute
Worcester, MA 01609
Operations and industrial engineering practice have been transformed
over the past 20 years by the principles of lean thinking. Womack and
Jones  describe lean thinking as an antidote to muda, meaning waste.
Lean thinking helps to create a value stream throughout the supply chain
by eliminating waste. Lean design is guided by general principles, which
are translated into practice using tactics such as creating manufacturing
cells. The design process is complicated because in reality not all
waste can be eliminated, particularly in 'harder' processes that extend
across organizational boundaries. To be effective designers, students
need to understand how variability affects process dynamics and to combine
this knowledge with analysis of process data.
In this paper, we describe lean laboratory exercises that we developed
based on a physical simulation of a clock assembly called TIME WISE.
Students taking an introductory course in production system design are
required to take the laboratory, which meets weekly for 2.5 hours. Traditional
topics covered in the course are linked through the lean concepts of
value, flow, demand pull and perfection. The physical simulation that
serves as the basis of the lab was developed by MEP-MSI and is used
by Manufacturing Extension Partnership (MEP) programs in several states
to teach lean principles to employees at small- to medium-size manufacturers.
In adopting the simulation to an undergraduate course, we wanted to
provide students with more opportunity to 'discover' theory, by generating
and analyzing data that could be used to support decision-making. The
laboratory exercises specifically address: (1) 'traditional' manufacturing
processes and process variability, (2) problem-solving using a QI-story
format, (3) process flow, takt time, and balance, (4) demand pull and
visual management, (5) supply chain management, and (6) product customization.
We have offered the laboratory sessions once at Worcester Polytechnic
Institute (WPI), and report here on our initial analysis of the teaching
experience and student learning. Our objectives were: (1) to develop
students' ability to apply lean design principles, (2) to develop students'
ability to analyze data, and (3) to increase student understanding of
fundamental process dynamics and variability. We used student surveys
and an evaluation of student work to assess our success in meeting these
objectives. In this paper, we concentrate on the impact on our first
objective, the ability to apply lean principles.
Many organizations are focusing on streamlining their supply chains
to increase responsiveness, and there is a need for analysts and engineers
to improve such processes. Supply chains have many stages, often involving
different firms, which require coordination and synchronization .
To be effective designers, students need exposure to research and practice
in applying lean concepts in complex environments, where design is more
difficult. In developing our approach, we examined how lean principles
were taught in a number of settings and reviewed pedagogical approaches.
Teaching Process Design and Lean Principles. We reviewed courses
taught in IE programs at a number of universities and found that relatively
few had developed a separate course focusing on with lean topics at
the undergraduate level. Those that had lean courses typically geared
these courses to upper-level undergraduates or graduate students. More
typically, courses had been revised to address the individual tactics
associated with lean design, but typically as an add-on topic (for example,
in production planning and control, one might add a session on kanban).
We had traditionally taken this approach at WPI. As a consequence, we
observed in senior projects that students often could not articulate
the underlying principles of lean design (at least initially), and they
failed to understand the links between various tactics and the conditions
necessary for their success.
We also examined the Introduction to Industrial Engineering courses
at a number of schools. Many schools have created such introductory
courses in the engineering disciplines to reduce attrition rates by
linking traditional mathematics and science topics to applications .
While such courses in IE have provided an effective overview of the
discipline, course materials and textbooks do not focus on process design
or the impact of lean ideas (see, for example, ). As with lean topics,
project-based courses that focus on process design are generally aimed
at senior-level students (see, for example, ).
On the other hand, many universities have established partnerships
with industry to teach and apply lean ideas. For example, Kettering
University has established a lean manufacturing program in conjunction
with Ford Motor Company . Students focus on planning, analyzing
and implementing lean principles, gain professional experience and apply
lean principles by working on opportunities provided by Ford Motor Company
and its partners. Georgia Tech has established Georgia Teach Lean Enterprise
Services, which conducts day- or week-long programs to impart lean ideas
to industry . Rochester Institute of Technology (RIT) has a Center
for Excellence in Lean Enterprise (CELE) . Both of these Universities
use classroom training supplemented with hands-on applications, plant
floor exercises, and live simulations. The continued interest in and
success of such partnerships provides evidence that the ability to apply
lean topics is important to industry. We can also take advantage of
the methods and materials used in these settings for undergraduate teaching.
Discovery Learning. "What we have to learn to do, we learn
by doing." . Evidence suggests that students' design and problem-solving
abilities are improved in courses that use active and collaborative
learning . The lean laboratory exercises we describe in this paper
were designed to engage students in their learning, setting the high
expectations, cooperation and faculty/student interaction consistent
with good practice in undergraduate education . Discovery learning
seeks to connect students to knowledge. In this approach tools and information
may be provided by the faculty to solve the problem, but it is the responsibility
of students to "make sense" of them by drawing conclusions
based on his/her own experience and knowledge.
As described by Bicknell- Holmes and Hoffman , there are five basic
methods associated with discovery learning. Case-based learning is the
most common and easiest method to apply. In this active learning strategy,
students learn through stories that illustrate the effective application
of knowledge, skills or principles. Incidental learning is an active
learning strategy where course content is tied to game-like activities;
here, knowledge is gained indirectly. In learning by exploring methods,
students ask a faculty member or other students about a particular topic
or skill. The faculty member tries to direct the interaction in a particular
conversation or a topic. Learning by reflection is an approach that
seeks to have students apply higher level cognitive skills, focusing
on deeper levels of comprehension and analysis. In simulation-based
learning, an artificial environment that is close to the real environment
is created so that students have the advantage of developing and practicing
complex set of skills. Our approach to discovery-based learning primarily
combines two methods - learning by exploring and simulation-based learning.
Lean Design Laboratory Exercises
Because lean thinking plays a central role in process planning in most
organizations today, we believe that students should be given a holistic
view of lean principles early in their academic careers. The goal of
this project in our IE curriculum was to provide a process design foundation
early, embedded in the contemporary business context that includes lean
ideas. Project-based courses that build repeatedly on core ideas in
a 'spiral curriculum' have been successfully implemented in other engineering
disciplines at WPI (,). We thus established the lean laboratory
exercises as part of an introductory operations and industrial engineering
course, currently titled "Production System Design". Industrial
engineering majors take this course early in their program, and it serves
as a foundation for more advanced courses. The course is also taken
by management majors at WPI to fulfill their operations management requirement,
as well as students in related engineering disciplines such as manufacturing
and mechanical engineering. For these students, it may be the only operations
and industrial engineering course that they take.
Laboratory Format and Topics. We created laboratory exercises
using the TIME WISE simulation developed by MEP-MSI, which is used by
the Massachusetts Manufacturing Extension Partnership (MEP) to teach
lean principles and tactics. In this simulation, students assemble two
types of clocks, using a 4-stage process. In addition to assembly personnel,
the simulation requires production planners, material handlers, quality
inspectors, warehouse clerks, and inspectors. The simulation is carried
out in a large group, with each group member assigned a different role.
One simulation takes 15 minutes, and corresponds to a work shift. We
ran two sections of the lab with 15 and 18 students respectively.
The Massachusetts MEP uses TIME WISE as part of one-day seminars that
provide a foundation for understanding the principles of lean manufacturing.
Employees of small- to medium-size firms attend the seminars. There
are two major between our laboratory sessions and the seminars conducted
by MEP that required some adaptation of TIME WISE. First, participants
in MEP seminars typically have been working for several years, often
many years. They bring to the seminar an understanding of manufacturing
operations, and can tie what they learn to their own work context. Students
taking introductory course at WPI are usually sophomores and juniors,
who typically have little work experience in engineering or operations
(they are more likely to have worked service industries, including retail,
restaurants, and computer services). The TIME WISE simulation provides
them with a context for exploring lean principles, but we need to spend
more time understanding basic process dynamics and relating issues to
other examples. Second, we have significantly time more available (approximately
15 hours of lab time versus about 4 hours spent on TIME WISE in MEP
seminars). With this additional time, we ask students to collect data
on the process and use more structured methodologies (e.g., assembly
line balancing) to suggest solutions. We also explore problem-solving
approaches, and experiment with proposed solutions to see how well they
work. Finally, we explore additional scenarios to examine the impacts
of product customization and distant suppliers.
An overview of each laboratory session is provided in Table 1. Each
lab lasted approximately 2.5 hours and was focused on a particular topic.
The format of the labs was similar. Using data collected from previous
labs (e.g., lead time, work in progress, quality data), students were
asked to propose solutions for continuous improvement using tools introduced
in class. For example, in session 3, one focus of the lab is better
balance among the various assembly tasks. In the course lectures, students
have reviewed assembly line balancing and now have an opportunity to
apply it. After students present one or more solutions, we then set
up the lab to experiment and see what improvements can be made to the
solution. In our first delivery of the course, we explored supply chain
ideas in another simulation but will be switching to the TIME WISE activity
outlined in Table 1 for future courses. Because undergraduate courses
are delivered in a 7-week format at WPI, students completed an in-class
laboratory for session #6 that required no additional assignment outside
of class time. By the end of the term, students were focusing on an
exam and a project as part of the course.
An Example of Student Work. In Session #3, students examined
the issues of flow and balance, and the impact on process performance.
Using the 7-step problem-solving approach  introduced in Session
#2, students were asked to explore the root causes of the long lead
times experienced in the first laboratory session (with the original
layout). Given data on customer orders, students could calculate the
takt time needed to meet demand, i.e.,
Takt Time =
min per shift
= 0.83 min per batch or 10 sec per clock
orders/5 clocks per batch)
Given assembly times (captured by students playing industrial engineers
in earlier sessions), students could also estimate capacity to find
bottlenecks. Using assembly line balancing ideas, students could then
explore new ways to assemble clocks to achieve takt time. Students suggested
combining assembly operations in different ways and shifting labor resources
to improve capacity. In experimenting with the proposed solutions, students
learned why it is important to have good data and capacity cushions.
Although the solution we tested in the lab worked well on paper, variability
in the actual assembly times kept students from achieving the desired
production rate (although it was much improved from Session #1).
Table 1: Lean Laboratory Exercises
Session and Topic
Description Lab Assignment
- Traditional process includes large lot sizes, unbalanced and
insufficient capacity, poor layout
- Played for 3 shifts, switching roles so students could observe
the process from several viewpoints
- Calculate and summarize performance measures, including lead
time, capacity, quality
- Identify process problems
- Introduce 7 step problem solving method developed by Center
for Quality Management to examine TIME WISE process
- Examine process variability and capability
- Use the 7 step method to define a root cause and improvements
that can be made to TIME WISE
Balance and Flow
- Revise TIME WISE setup to reflect student suggestions
- Measure process performance and suggest additional improvements
- Calculate takt time
- Balance work and capacity to achieve takt time
- Simplify flow
Demand Pull and
- Introduce additional product to examine robustness
- Revise TIME WISE setup to reflect student suggestions, test
kanban and visual management
- Measure process performance and suggest additional improvements
- Develop a demand pull system
- Suggest visual controls and 5S activities
- Examine the impact of distance and variability in the supply
chain on system performance
- Introduce customized products
- Explore the advantages of a postponement strategy
In the 7-step problem-solving approach, students develop a QI story
to document the problem and solutions. Figure 1 shows a student representation
of the original scrambled flow in the TIME WISE process (as experienced
in Session #1), used to demonstrate pictorially the flow problem. One
of the student groups came up with the idea of separate lines for the
two different products, as shown in Figure 2. Focusing on specialization
worked quite well for the two product lines but as we moved into Session
#4, a new product was introduced. Students discovered (learning by exploring)
that the solution worked well for one problem but when the process complexity
and variability were increased, the solution required modification.
Figure 1: Process Flow in Lab Session #1
Figure 2: Specialized Lines in Lab Session #3
Our objectives in introducing the lean laboratory exercises were to
improve students' ability to apply lean concepts, to improve students'
ability to use data to support decision-making, and to improve student
understanding of process variability and dynamics. We are using student
surveys, course evaluations and reviews of student work to establish
our success in achieving these objectives. Data was collected from a
course section taught in Spring 2002 without the laboratory sessions
to compare to our first use of the sessions in Fall 2002. We have started
our data analysis, and report preliminary results for the first objective
in this paper.
Results from Student Surveys. We used student surveys to examine
student confidence in their learning in a variety of areas, including
their understanding of lean principles, supply chain activities, and
calculation and understanding of process measures. We gathered data
at the beginning and end of each course. In general, students expressed
greater confidence about their knowledge with the introduction of the
laboratory exercises, particularly in their ability to understand and
apply lean concepts. Figure 3 shows student responses regarding their
understanding of lean thinking and its application. In the Fall 2002
course with the lab sessions, 93% of students indicated that they understood
all lean thinking principles and their application at the end of the
course. Only 5% of students in the Spring 2002 course with no lab sessions
expressed this level of confidence.
Figure 3: Students' Confidence in their Ability to
Understand Lean Thinking and its Application
Students also evaluated their ability to understand a variety of process
measures and to calculate them. As shown in Figure 4, students taking
the course in either the Spring (without the lab exercises) and the
Fall (with the lab exercises) felt confident in their understanding
of process measures. Students in the Fall session, however, expressed
significantly more confidence in their ability to calculate process
measures relative to the Spring.
Figure 4: Students' Confidence in their Ability to
Understand and Calculate Process Measures
Results from the Evaluation of Student Work. In addition to
student surveys, we collected student responses to essay questions on
exams and have started evaluating them in relation to our objectives.
We broke each objective into smaller aspects, then created rubrics to
score student work relative to that aspect of the objective. Table 2
shows rubrics we have developed to evaluate students' ability to understand
and apply lean ideas. Currently, these rubrics have been applied to
a subset of final exams given in Spring term (without the lab) and in
Fall term (with the lab).
Our evaluation of students' ability to apply lean ideas based on their
work in final exams was virtually unchanged between the Spring and Fall
terms, based on these rubrics. We were surprised by these results, but
have several hypotheses that we are testing as we move forward. First,
the final exam in the Spring term was a take-home exam, where students
were expected to use outside sources to support their analysis of a
case problem. In the Fall term, we used a shorter case and students
completed the exam in class. For the in-class exam, students could use
course materials but no additional references. The fact that students
could produce similar results in the Fall in a shorter time frame might
suggest greater familiarity with the material. Second, we have not yet
completed the evaluation of our rubrics. For example, we will be examining
consistency to ensure that different reviewers assign similar scores.
Additionally, we may define additional dimensions or aspects to the
Table 2: Rubrics for Scoring Students' Ability to
Apply Lean Design Principles
Students understand lean thinking principles
and can apply them in specific settings.
Students can apply all principles of lean thinking:
giving clear definitions of their meaning and/or give examples
of their applications on specific cases.
|Students can apply three principles
of lean thinking giving definitions of their meaning and/or give
examples for the application of these three principles.
||Students can apply two principles of
lean thinking, giving definitions of their meaning and/or give examples
for the application of these two principles.
||Students can barely apply one principle
of lean thinking, giving definition of its meaning and/or give examples
for the application of this principle
||Students cannot apply any principles
of lean thinking in any case.
Students comprehend the links between various
|Students are able to fully identify
7 tactics in a given ordering scheme and/or explain the logic of
||Students can satisfactorily identify
a of given ordering schemes, identifying the correct order of five
tactics and/or explaining the logic of its sequence.
||Students can partially identify one
of the existing ordering schemes, identifying the correct order
of three tactics and/or explaining the logic of its sequence.
||Students can barely identify one of
the existing ordering schemes, identifying the correct order of
two tactics and/or explaining the logic of its sequence.
||Students cannot identify any ordering
scheme for lean tactics.
Students can apply lean tactics in the solution
of lean problems
|Students can completely solve specific
lean problems applying the seven tactics, through the definition
of their meaning and/or using examples as specific solution alternatives
for the seven tactics.
||Students can satisfactorily solve specific
lean problems applying five tactics, through the definition of their
meaning and/or using examples for these five tactics
||Students can partially solve specific
lean problems applying three tactics, through the definition of
their meaning and/or using examples for these three tactics
||Students can barely solve specific lean
problems applying two tactics, trough the definition of their meaning
and/or using examples for these two tactics.
||Students cannot apply and explain lean
This paper describes our implementation of lean laboratory exercises
in an introductory production systems design course at WPI. The six
laboratory exercises, based around a physical simulation of clock assembly
called TIME WISE, encouraged students to experiment with theoretical
concepts and critically examine process results. Students who took the
course with the added laboratory exercises expressed significantly more
confidence in their ability to understand and apply lean ideas, as well
as to calculate process measures. Our preliminary scoring of student
work showed little difference between those who took the course with
the lab and those who did not. These initial results may be explained
by differences in the format of the student work and/or the preliminary
nature of the evaluation.
We are teaching the laboratory section of the course again in Spring
2003, and are continuing our evaluation of the project impact. In addition
to lean design, project objectives include improving students' understanding
of process dynamics and variability and their ability to make data-based
decisions. We are testing rubrics to evaluate these objectives. Based
on the preliminary results, we are also interested in examining student
learning over a longer time span to see whether or not the context created
by the laboratory helps students to remember what they have learned.
We are also making several changes to the exercises, incorporating more
required calculations and exploring supply chain impacts. Students who
participated in the TIME WISE exercises in Fall 2002 were overwhelmingly
positive about the laboratory activities in student evaluations. We
also found the interaction and exploration required by the labs to be
a stimulating and satisfying teaching experience.
Acknowledgement. Partial support for this work was provided
by the National Science Foundation's Course, Curriculum, and Laboratory
Improvement Program under grant DUE-0126672.
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SHARON A. JOHNSON is an Associate Professor and Director of the Industrial
Engineering Program at WPI, where she teaches courses in facility layout,
production planning, and process management. She received her M.S. and
Ph.D. in Industrial Engineering from Cornell University. Her research
interests include process analysis and modeling, case study development,
capacity planning, and remanufacturing.
ARTHUR GERSTENFELD is Professor of Industrial Engineering and Management
at WPI and teaches courses in production system design and managing
technical innovation. He received his Masters and Ph.D. from MIT and
has published more than fifty articles in academic journals and edited
AMY Z. ZENG is an Assistant Professor and teaches in the areas of business
logistics, operations management, and supply chain management at WPI.
She received her M.S in Industrial Engineering from the University of
Washington, and her Ph.D. in Operations Management from Pennsylvania
State University. Professor Zeng has published numerous articles in
the area of supply chain management.
BORIS RAMOS is a PhD student and a research assistant at WPI. He also
teaches in the Electrical Engineering Department at ESPOL in Ecuador
and has been Undersecretary of Telecommunications of Ecuador. He received
his Masters in Computer Science from WPI and an MBA from ESPOL.
SAUMITRA MISHRA is pursuing a Master's in Operations and Information
Technology at WPI, with expected completion in May 2003. He received
Bachelor and Masters degrees in Commerce from Gujurat Univeristy, and
has worked as a software programmer.