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General Overview of the MSDD
The Manufacturing System Design Decomposition
(MSDD)
The MSDD is a decomposition of general objectives and means
for repetitive manufacturing systems. The decomposition distinguishes
six general functions of manufacturing systems: quality, identifying
and resolving problems, predictable output, delay reduction,
operational costs, and investment. The decomposition is therefore
a functional decomposition as opposed to a physical
decomposition. A physical decomposition would decompose
physical entities such as departments, manufacturing cells.
Each physical element, however, must achieve each of the functions
stated above. Applying the MSDD to a system design process
forces to think differently about manufacturing systems than
in physical structures, which was found to be very helpful
in industrial applications.
The following paragraphs describe the overall structure of
the MSDD. A more detailed description of each branch is available
by clicking on the appropriate box in Figure 1 or using the
hyperlinks in the text.
The highest-level functional requirement was chosen to be
“Maximize long-term return on investment.” It is important
to emphasize here that the goal is to maximize return on investment
(ROI) over the life cycle of a given system, not just in the
immediate future. Although long-term ROI may be very difficult
to predict accurately, ROI is taken here as the highest-level
focus of the manufacturing function as it represents a general
objective that is applicable to a wide variety of manufacturing
environments and is not inherently contradictory to any accepted
improvement activities.
The design parameter chosen as the means to achieve FR-1
is DP-1, “manufacturing system design.” The MSDD focuses on
the shop floor aspects of manufacturing systems. Aspects such
as product design, marketing are not in the scope of the MSDD,
even though they certainly contribute to overall performance
and ROI. The second level of the MSDD was determined based
on the components of ROI as given by:
(1)
Thus, the components of ROI are revenue, cost, and investment
over the life cycle of the manufacturing system. The requirements
placed on these components are that life cycle cost and investment
should be minimized and revenue should be maximized in order
to maximize long-term ROI, as shown in Figure 1.
Maximizing customer satisfaction (DP-11) was selected as
the means to maximize revenues. This DP was then further decomposed
based on the key attributes of manufacturing system performance
that affect customer satisfaction: conformance quality
(FR-111), on-time delivery
(FR-112), and minimal lead-time
(FR-113). The prescribed means for achieving high quality
is to ensure that production processes have minimal variation
from the target (DP-111). DP-111 is focused on improving processes
rather than trying to use final inspection to prevent the
shipment of bad parts. The design matrix at this level (shown
graphically with arrows in Figure 1) shows that achieving
conformance quality (DP-111) is critical for improving customer
satisfaction. Quality variation and the production of defects
makes system output unpredictable, which adversely affects
FR-112, “Deliver products on time,” and means that more parts
will have to be produced to replace these defects, adversely
affecting FR-113, “Meet customer expected lead time.” High
conformance quality is a critical factor required to reduce
the affect of DP-111 on the predictable delivery and lead
time of a manufacturing system design.
The MSDD treats customer satisfaction as a prerequisite for
the rest of the decomposition, meaning that it is a goal that
must be achieved before costs and/or investment can be minimized.
The MSDD interrelationships show clearly that minimizing running
costs and investment at the expense of customer satisfaction
is not a valid means for achieving the highest-level goals
of the system design. This information is consistent with
related empirical and theoretical work in the literature.
Ferdows and De Meyer (1990) developed a “sand cone” model,
describing that manufacturing capabilities should be built
by starting with quality, then focusing on dependability,
then reaction speed and flexibility, and finally focusing
on cost efficiency.
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, and the
mean, 
, manufacturing
throughput time (described by DP-112 and DP-113, respectively,
as shown in Figure 1). Variation reduction requires the ability
to respond rapidly to production disruptions when disruptions
occur, which is designated by the branch R1, and the increase
of the reliability of production resources, designated by
the branch P1. Mean throughput time reduction is decomposed
based on the various causes of delays in manufacturing systems
(FR’s T1-T5). It is important to note the distinction made
here between causes of variation in throughput time (addressed
by DP-112) and causes of increases in mean throughput time
(addressed by DP-113). The decomposition of DP-112 focuses
on the elimination of factors that cause variation in the
predicted system output time; decomposition of DP-113 focuses
on factors that increase throughput time but that can be accurately
predicted. Likewise, the process quality branch isolates factors
that affect process variation in terms of the mean and variation.