2 pages on management


anyone who can complete this in three hours?2pgs, APA format, 5 references.For Assignment-2, you are required to read the below article attached, and complete the LLB template.

LLB template is attached, My parts are highlighted on Yellow

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1. Summary (100 – 200 words)
Provide a summary in your own words on the article you requested to read and analyze in the following space.
read the article in pdf file for this part

While you reading, identify the relevant statements to the session and
insert them in order in the following space. // Materials are attached,
try to mention the six sigma type, DMADV, DCOV which already mentioned
in the article. // 300 words maximum




Unformatted Attachment Preview

III. SUMMARY (100-200 words)
Provide a summary in your own words on the article you requested to read
and analyze in the following space.
Identify the key learning points in the read and analyze assigned activity.
While you reading, identify the relevant statements to the session and
insert them in order in the following space.
This is the most important section in your analysis. To complete it
sucessfully, learner is to consider the following guiding steps:

Present arguments coherently, supported by evidence and facts to
substantiate on why you may take a particular stance and/ or
position towards a particular approach whether against or in support
of it;

Capable of bridging the gap between the theory and conceptual work
with the application under consideration.
How could you apply the subject matter from the article in a real business case?
What have you learnt? Critical thinking is about lessons learnt to be drawn
from the analysis.
Copyright 2015 HBMSU All Rights Reserved
Design for Six Sigma at Ford
esign for Six Sigma (DFSS) has been publicized as a product development approach that complements the Six Sigma problem solving
methodology. Promoted as “Six Sigma goes upstream,”1 DFSS encourages systematic anticipation of customer needs and disciplined application of
scientific and statistical methods to meet those needs. Many organizations,
enthusiastic to build on Six Sigma momentum, generated their own DFSS
processes before a standard template emerged.
While Six Sigma is widely recognized by the DMAIC acronym that represents its five standard phases (define, measure, analyze, improve, control),
DFSS has no standard acronym. Therefore, organizations have adopted a variety of approaches that resulted in acronyms such as IIDOV, CDOV, IDOV,
DMADV, DCOV and IDEAS.2 Despite these naming differences, all versions of
DFSS share fundamental strategies and tools that promote a common goal: to
create a data driven product development culture that efficiently produces
winning products.
Initial Assumptions
By Nathan R.
Ford Motor Co.
Ford decided to launch “consumer driven Six Sigma” in 1999, with an initial focus on two things:
1. Training Black Belts (BBs).
2. Completing DMAIC projects.
Management set targets for the percentage of each division trained and dollar savings resulting from projects. It created a central, prioritized list of all
corporate quality issues to aid the coordination of improvement efforts with
available resources.
The implementation strategy assumed people throughout the organization
DFSS enhanced Ford’s existing
product development system.
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Design for Six Sigma at Ford
would be more likely to buy into Six Sigma if results
were quickly realized from the company’s short-term
(four to six month) “find and fix” DMAIC projects.
That buy-in was considered necessary to start a culture
change. And while significant energy was focused on
achieving the short-term targets, the importance of
developing DFSS for the long term was also recognized.
A small development team with representatives
from various divisions embarked on a plan to develop
DFSS for Ford. The team held benchmarking discussions with early DFSS adopting companies and listened to consultants familiar with those efforts. Much
of what was learned paralleled quality and reliability
initiatives already under way at Ford.
The team settled on a four-phase process: define,
characterize, optimize and verify (DCOV). The DCOV
framework aligned with Ford’s existing product development (PD) system and built on the disciplines of
systems, robust and simultaneous engineering, all of
which had been in use at the company for more than
10 years. Introductory training in related tools was
already available through the Ford technical education program (FTEP), an online curriculum all engineers are expected to pass (see Table 1).
Implementation began with Ford’s Powertrain
Division, which wanted to apply DFSS to the development of new engines and transmissions. Work was
divided into a large number of subprojects with an
active BB assigned to each. Growth in the number of
projects was driven by a senior vice president, who
demanded regular status reports.
Key to progress was the strategic placement of a
DFSS Master Black Belt (MBB) as manager of the
department responsible for the computer modeling of
Table 1. Ford Technical Education Program
Ford technical education program subjects
Web based, self-paced training with tests
Process fundamentals: DMAIC, DCOV*
System engineering fundamentals
Statistical engineering
Applied consumer focus
Experimental design
Design verification and production
Parameter design
Failure mode and effects analysis
Tolerance design
Eight discipline (8D) problem solving
Process control methods
* Added in 2004; all other subjects were available prior to
DFSS deployment.
DMAIC = define, measure, analyze, improve, control.
DCOV = define, characterize, optimize, verify.
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W W W . A S Q . O R G
new engine designs. This manager teamed up with an
engine program manager to act as working level champions for DFSS. Soon other divisions were launching
DFSS by identifying beta projects and training teams to
carry them out. Issues with the training and execution
of these early projects highlighted implicit assumptions that needed reevaluation. For example:
• The rationale for DFSS would be clear to midlevel management, and DFSS would be embraced as
a natural extension of Six Sigma.
• Projects would easily integrate into the company’s
standard PD process because the DFSS steps had
been carefully aligned to that process.
• Similar to DMAIC, steps to project completion
could be detailed in a prescriptive set of procedures using a standard toolset.
• The DFSS training should follow the BB model,
in which all participants receive extensive training in Six Sigma tools.
The following sections address these assumptions
one at a time, explaining why they were flawed and
outlining implementation changes required to maintain momentum of the DFSS rollout.
DFSS Rationale
DFSS proponents argue the benefits reaped from
DMAIC defect reduction multiply when Six Sigma
rigor is applied to defect prevention. But even when an
organization has achieved significant DMAIC success,
management may be legitimately skeptical of DFSS.
At Ford it became clear early on that DFSS acceptance could not be achieved riding on the coattails of
Six Sigma. Basic questions such as “Isn’t DFSS just good
engineering with a fancy brand name?” and “The tools
are not new—so what is new?” needed to be clearly
answered up front. To answer these questions, the team
concluded Six Sigma culture, which establishes statistically verifiable facts as an underpinning of all product
decisions, could be a lever to increase the influence of
Ford’s ongoing quality engineering initiatives.
DFSS packages methods and tools in a framework
that promotes cultural change under a recognized
brand name that helps overcome an initial resistance
to change. It is most useful if it generates permanent
behavior changes that outlast its own life as a brand.
Given the DFSS toolset is not substantially new, the
rationale for DFSS should not focus on tools. Over
time, DFSS at Ford has emerged as a scientific
approach to PD that leverages Six Sigma culture. It
has become a means to reinstill rigorous deductive
The Powertrain Division was the first to implement DFSS.
and inductive reasoning in PD processes. It requires:
• Identifying customer desires.
• Developing validated transfer functions (mathematical models) that describe product performance through objective measures.
• Correlating these objective measures to customer
desires and effectively assessing the capability to
meet those desires well before product launch.
• Applying transfer function knowledge to optimize
designs to satisfy customer desires and avoid failure modes.
Six Sigma culture aids implementation of these
steps by providing:
• A cross company common language for problem
resolution and prevention.
• A mind-set that demands the use of valid data in
decision making.
• An expectation across the organization that
results should be measurable.
• A disciplined project management system to help
achieve timely results.
None of the elements of this approach are revolutionary, but together they provide a template for success.
Based on experience applying DFSS, Frank McDonald,
a VP of Cummins Inc., observed: “[DFSS] may sound
like the latest new way if not for the fact that it really is
more like the development of the old way to a higher
standard that feels a lot like the right way.”3
Recently, some DFSS proponents have contended
that organizations should begin Six Sigma deployment
with DFSS instead of DMAIC. Ford’s experience indicates otherwise. Short-term DMAIC projects led to rapid
elimination of a significant number of issues and resulted in measurable financial benefits. This success boosted confidence in Six Sigma, and continued institutionalization helped build a culture receptive to DFSS.
Furthermore, once BBs had successfully completed a
few DMAIC projects, they were better equipped to support the longer and more complex DFSS projects.
Project Integration Within Existing Processes
Even when the rationale for DFSS is clear, practical
reservations about its alignment with existing processes
may remain. Ford had been evolving its PD system for
years when DFSS was introduced. Natural fears arose
that DFSS was intended to replace this system, potentially causing disruption and confusion. To counter
those fears, senior management made it clear DFSS
would not replace, but would augment, the existing PD
process in specifically designated areas.
DFSS projects would demand a deeper dive into the
establishment of customer connected performance targets (Y’s) and transfer functions that link those targets to
critical design characteristics (X’s). This approach is consistent with the experience of other DFSS implementers:
“We shouldn’t tell our engineers we’re discontinuing the
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Design for Six Sigma at Ford
process they’ve been working with for 10 years and
replacing it with DFSS. We should integrate DFSS deliverables into the current development process and ask
project managers to commit to providing them,” said
Doug Mader, president of SigmaPro.4
Integrating DFSS deliverables into the current PD
process sounds simple, but it involves real challenges.
For example, PD entails at least three different categories of scope: the creation of a new product or technology, the evolution of a next generation product
from a current design or the enhancement of an existing product. The rhythm and timing of DFSS projects
associated with these efforts will vary depending on
the category (see Table 2).
Boundaries are not always well defined, but the cat-
egories provide initial guidance for establishing project expectations and timing. Breakthrough projects
have the most design latitude and typically require the
most time to complete. Evolutionary projects have less
design latitude, and their timing is tied to standard PD
milestones. Adjustment projects have the least design
latitude, and they are generally expected to be completed as soon as possible.
In addition to delivering an optimized design, each
DFSS project at Ford is required to institutionalize
learning and transfer functions by developing design
guidelines and training that can be reused in the
future. This effort to reduce waste in the PD factory is
what distinguishes an adjustment DFSS project from a
DMAIC project.
To reduce waste in the product development factory, each DFSS project develops reusable guidelines and training.
Ford uses the four-phase define, characterize, optimize, verify (DCOV) abbreviation for all categories of DFSS projects.
Some practitioners use different process phases for
different categories of projects. For example, the
authors of Design for Six Sigma in Technology and Product
Development use invent, innovate, develop, optimize and
verify (IIDOV) to describe DFSS for technology development and concept, design, optimization and verify
(CDOV) to describe product commercialization
(design).5 To reduce confusion, Ford uses the DCOV
abbreviation for all categories of DFSS projects.
A second challenge in integrating DFSS deliverables
into the current development process is determining
the manager to which they should be assigned. DFSS
projects typically deal with the most challenging
designs, such as new concepts or technologies linked
to a compelling business case or complex systems that
have exhibited problems in the past. In the first case,
no natural project owner may have yet evolved in the
organization. In the second case, the natural owner
may not be clear or may be disputable because product attributes and system interface issues often cut
across system boundaries.
Even if the organization dictates a clear owner, the
fact existing designs are underperforming indicates a
need for a new approach. In each of these cases, it is
critical to apply basic project definition and management techniques. These include:
• Ensuring the team is led by someone who has
responsibility for the design and can engage the
appropriate technical expertise.
• Providing mentoring in statistical and PD tools—
Table 2. DFSS Project Categories
Project category
Design latitude
I. New product or product breakthrough:
• Introduce new product, concept or technology.
• Add a new feature to next generation product.
Open — exploration of alternative
concepts allowed.
Driven by market opportunities
and technology feasibility; linked
to technology development plans.
II. Evolutionary change in next generation product:
• Upgrade performance.
• Maintain performance while lowering cost.
• Prevent problems.
Moderately constrained —
concepts often already selected,
assumptions for component
reuse limit design space.
Driven by market trends and
competitive pressures; linked
to existing product program
III. Adjustment to existing product design:
• Optimize performance within existing production constraints.
• Reduce current costs.
• Fix problems.
Heavily constrained — limited to
“running changes” to existing
Driven by waste reduction goals;
linked to yearly budget targets,
similar to DMAIC projects.
DMAIC = define, measure, analyze, improve, control.
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DFSS project numbers grew rapidly during the first three years of implementation.
for example, assigning BBs and MBBs or their
• Securing an executive Champion to actively support and review the project.
• Committing the team and Champion to a project
charter that outlines goals aligned with organizational objectives, scope matched to team resources, roles and responsibilities, and key project milestones with delivery dates.
The importance of active senior management leadership cannot be overestimated at the project or organizational level. In a division whose senior leader
actively drove DFSS from the start, project numbers
grew exponentially over the first three years of implementation. In a similar sized division, in which DFSS
deployment leaders solicited projects from mid-level
management, project numbers remained in the low
teens for the same time period.
Process Flexibility
The variety of scope addressed by DFSS projects
means DFSS needs to be more comprehensive and
flexible than DMAIC. In DMAIC, BBs identify and
reduce the frequency of defects generated by existing
processes. The majority of work is analysis. In DFSS,
teams must not only anticipate and prevent defects,
they must anticipate and meet explicit and latent customer needs.
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W W W . A S Q . O R G
DFSS must address all three types of quality represented in Noriaki Kano’s model: basic, performance
and excitement.6 DFSS requires a balance of analysis
and synthesis—the synthesis of new designs and design
standards from a combination of deductive and inductive reasoning based on experience, observation and
theory. While analysis often proceeds linearly or is at
least guided by procedure, synthesis proceeds iteratively and sometimes unpredictably as connections are
made between disparate ideas. Such iteration is an
inherent part of the PD progression from the conceptual to the concrete. Elements of each DCOV phase
are repeated as designs proceed from concept to computer model to prototype to production.
Compounding the challenge of DFSS is the added
uncertainty about future customer desires and future
sources and levels of production and usage variability
that will affect product performance. Assessing these
types of uncertainty is often not possible by collecting
frequency data from existing processes and making
statistical inferences. Such phenomena are either not
random or their random nature is not discernible.
So in addition to being equipped with statistical
tools, DFSS teams must have knowledge about nonstatistical methods outside the typical BB curriculum,
including methods for obtaining consumer insight,
cascading customer desires down to component specifications, designing for robustness, mistake proofing
and verifying designs with small sample sizes for testing. This methodology expertise, typically provided by
Design for Six Sigma at Ford
BBs and MBBs, must be combined with deep technical expertise in the product functionality in question.
An ideal situation occurs when a BB from a functional area finishes certification and returns to the area to
support related DFSS work.
The Ford team initially devoted time to devising a
single DFSS flowchart. Attempts to capture any substantial detail were finally abandoned because they
ended up being redundant to existing PD flowcharts
and failed to adequately address different project categories and represent iteration in the process. It was
also difficult to clearly represent the proper relationship between tools and outcomes in a single chart.
The team, therefore, decided to produce two documents:
1. A tool matrix to outline which tools might be
applied at each project phase (see Table 3).
redundant to FTEP.
2. Not all the specialized tools presented would
apply to a particular project. For those that
would—due to the extended length of DFSS projects—the team members worried they would forget much of the training by the time they needed
to apply it. They concluded it was inefficient to
train all team members in all tools.
As a result of the feedback, DFSS training was
restructured. To enhance continued adherence to the
process, teams now meet periodically in workshops
corresponding to each project phase (D, C, O and V).
Instead of teaching tools, the workshop teaches the
process and describes the results expected from the
team. The bulk of the time is devoted to helping the
team make progress on its specific project by interpreting data and formulating strategies for the technical work ahead. By the end of each workshop, the team
has a written work plan for the project’s next steps.
A team process leader, typically a trained BB, guides
the application of Six Sigma tools. An MBB facilitates
the workshops, collaborates with team leaders
throughout the project and provides additional training in advanced DFSS tools as required.
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