June 2007 Vol. 138 No. 6
Continuous Processes Can Be Lean
http://www.sme.org/cgi-bin/findarticles.pl?&ME07ART42&ME&20070610&&SME&#article
Although developed for use in producing discrete parts,
lean manufacturing and six sigma can also be applied to
continuous-process manufacturing
SiewMun Ha
Consultant
Implementation Services LLC
Highlands Ranch, CO
E-mail:
siewmunha@yahoo.com
To order a hardcopy reproduction of this article, click here. To purchase digital reprints
or reproduction licenses, please contact the resource center at service@sme.org or call
(800) 733-4763.
Process manufacturing is fundamentally different from discrete manufacturing: material
flows in a continuous stream in the former, while parts move in discrete batches in the
latter. The breadth of work on process improvement in discrete manufacturing is vast.
And it seems very logical to apply popular existing methodologies tailored to discrete
manufacturing, unaltered, to the process-manufacturing industries. This approach,
however, is akin to fitting square pegs into round holes. A better approach is to adapt lean
techniques developed for use in discrete production within a new processimprovement
framework for process manufacturing. The new framework identifies the various forms
of waste in the process-manufacturing value stream, and manages the wastes with the
appropriate concepts and tools.
The two most popular process-improvement methodologies in use today—lean
manufacturing and six sigma—originated at Toyota and Motorola, respectively. These
pioneering companies were discrete manufacturers, and the subsequent evolution and
development of the two methodologies has focused mostly on improvements in discrete
manufacturing. Much less development work has been carried out on
applications of lean and six sigma to process manufacturing.
How is process manufacturing critically different from discrete
manufacturing, and why do the differences matter to the processimprovement approach?
The key characteristic of process manufacturing that distinguishes it from discrete
manufacturing is material movement. In this type of manufacturing, material is processed
continuously through a series of machines from raw material to final product. It flows in
a continuous stream from one machine to the next, without periods of stopping and
waiting in between. Some examples would be iron-ore processing, petrochemical
refining, paper manufacturing, and sugar refining. In contrast, the fundamental
characteristic of discrete manufacturing is that material and parts move in discrete
batches between machines, with the very real possibility of work-in-process (WIP)
buildup between processing steps.
Lean manufacturing and six sigma each has a central focus that has been the basis for
its structure and tools. For lean manufacturing, it's the delivery of value to the customer
through the elimination of waste, where waste is defined as anything that is non-valueadded from the customer's perspective. In the case of six sigma, the central focus is the
elimination of defects, where a defect is defined as a part or service that does not conform
to the customer's specifications. How do these concepts apply to process manufacturing,
when you consider its differences with discrete manufacturing?
Lean manufacturing defines seven types of waste that make a production system "unlean" and inefficient at delivering value to the customer. These are:







Over-production: Producing too many parts, too soon.
Inventory: Extra parts required to buffer process variability.
Transportation: Movement of parts without adding value.
Waiting: Increasing lead time without adding value.
Movement: Movement of operators without adding value.
Defects: Parts that do not conform to customer specifications.
Over-processing: Processing a part more than is necessary to meet customer
specifications.
The first four types of wastes relate to a lack of material flow in the lean sense, a major
problem at many discrete manufacturers. Here, parts and material are processed,
transported, and wait in large batches, instead of moving smoothly in a one-piece flow
from raw material to finished product. In process manufacturing, however, the very
nature of the process dictates that the material already flows (literally!) from one machine
to the next. Hence, the lean ideal of flow occurs by default. Also, there is typically little
or no WIP between machines in process manufacturing. What WIP that exists tends to be
of the order of hours of production rather than days or weeks of production, as is usually
the case with discrete manufacturing. As a result, over-production, inventory, and waiting
are either nonissues or only minor issues in process manufacturing.
If the plant is suboptimally laid out, transportation is potentially an issue in process
manufacturing, as material must be moved over greater distances than absolutely
necessary. Suboptimal transportation increases the extent and complexity of the
conveyance system (e.g. pipes, conveyors), which then requires increased investment and
maintenance—waste. In reality, however, the nature of the machinery in process plants is
such that any movement of machines to optimize material flow is usually difficult and
expensive, and is consequently a nonstarter in most process-improvement efforts.
Movement waste is also less relevant to process manufacturing. Operators in these plants
typically monitor automated machinery, and even if they have to move from one piece of
equipment to the next, that movement usually does not have an adverse impact on the
ability of the equipment to continue processing the material. In discrete manufacturing,
on the other hand, operator involvement is required to process a part on a machine.
The last two types of waste—defects and over-processing—exist in process
manufacturing just as they do in discrete manufacturing. Defects in process
manufacturing result in the production of material that does not meet the specifications of
the downstream internal/external customer. In iron-ore processing, for example, the ironcontaining rock must be crushed to a certain size before further processing can begin to
separate the iron from impurities. If the rock is not crushed to the specified size, then the
downstream separation process suffers from degraded performance. Over-processing
occurs when the material is processed to a greater extent than is required by the
downstream customer. In the iron-ore processing example, over-processing occurs if the
ore is crushed more finely than required, with no commensurate benefit to the
downstream separation process. This over-processing unnecessarily consumes crushing
capacity and energy, and thus constitutes waste.
Six sigma's focus on defect reduction/elimination aligns well with certain types of waste
that exist in process manufacturing. It is, however, not the complete solution. While the
six-sigma tool set is very powerful and works well to optimize process performance with
respect to quality, throughput, and efficiency, the methodology fails to address other root
causes of waste in process manufacturing. The fully successful process-improvement
effort thus takes advantage of a complete armament of techniques, and applies the ones
best-suited to achieving the desired results.
What might some of these root causes be? To answer that question, it's instructive to
analyze the process-improvement opportunities in process-manufacturing from first
principles, rather than trying to force-fit the opportunities into the structure of lean
manufacturing and/or six sigma. We do so by visualizing a perfect process-manufacturing
value stream, and then identify improvement opportunities by mapping the gaps between
this perfect value stream and its real-world counterpart. What would such a perfect value
stream look like? The perfect process value stream is one where all the machines are:




Capable: Able to produce product within the quality specifications of the
downstream internal/ external customer.
Available for production with no unplanned downtime.
Efficient: Consumes no more energy and raw material than absolutely necessary.
Adequate: Possess sufficient capacity to meet demand.
With these characteristics, the perfect value stream produces good-quality product
reliably, efficiently, and in sufficient quantity, at the individual machine level as well as
for the value stream as a whole. A suboptimal condition with respect to each of these four
ideal characteristics constitutes a type of waste. Because the perfect value stream is an
idealization, all real-world process-manufacturing value streams will contain one or more
of these wastes, representing targets of opportunity for any process-improvement effort.
The root causes of these wastes may be identified by means of fish-bone (Ishikawa)
diagrams. A putative first-level fish bone for machine capability is shown in the
illustration on page 108. Ishikawa diagrams are not meant to be a complete and
exhaustive identification of all causes of waste, but rather a starting point for further
investigation. You can use such diagrams as "straw models" to identify the root causes of
wastes in your specific value stream. As befits a root-cause analysis, each of the firstlevel causes under Man, Machine, Environment, Method, and Material may be
deconstructed, as appropriate, into successively higher-level causes, until the root cause
has been found. At that point, the appropriate methodology/tool can be applied to address
it.
While the causes of process-manufacturing waste are many and varied, a few occur with
regularity across all or most of the four categories of waste tracked in Ishikawa diagrams.
First and foremost is mechanical condition.
This refers to machines that are at a suboptimal state of maintenance, a very common
condition at many process plants. Machines in poor mechanical condition have poor
availability, produce poor-quality product in inadequate quantities, and operate
inefficiently. In short, they operate wastefully! A maintenance kaizen event is the
appropriate process-improvement tool to return the machine to an optimum mechanical
condition. To sustain the improvement, a long-term maintenance program such as Total
Productive Maintenance (TPM) must be installed.
A second major cause of waste is suboptimal operation. Process manufacturing
typically involves a combination of physical parameters such as temperature, pressure,
density, flow rate, moisture level, and chemical concentration that are set at the machine
to process the material. If the settings of these physical parameters are suboptimal, then
the machine also operates suboptimally in terms of throughput, quality, and efficiency.
To fix this problem, we need to identify the optimum settings at which to run the
machine. Optimization problems of this nature are ideally solved using the six-sigma
methodology and tool set, employing designed experimentation to characterize the
behavior of the machine with respect to its settings.
Design and technology are another two major causes of waste. It's not uncommon to find
machines at brownfield process plants that have been in use for many years, if not
decades, that are obsolete with regard to both design and technology. Such obsolete
machines operate wastefully in terms of availability, quality, throughput, and efficiency,
much like a machine that is in poor mechanical condition. Improving machine
design/technology is an engineering problem requiring technical analysis and designed
experimentation.
In addition to the characteristic of material flow, another distinction between discrete and
process manufacturing is that changeovers are often not an issue in the latter, as most
production lines only produce one type of product. Availability can still be adversely
affected, however, by long setup times after a machine has been taken down for
maintenance. In this case, quick changeover techniques such as Single Minute Exchange
of Die (SMED) may be applied to reduce setup times and improve availability.
If the overall management objective is to increase throughput, then the Theory of
Constraints (TOC) can be a useful device to focus and guide the process-improvement
effort. Briefly put, TOC posits that in any production system, at any one time, there
usually exists only one constraint that limits the overall system throughput. We increase
overall throughput by improving the performance of the constraint. Improvements
elsewhere make no difference. As the existing constraint is lifted, a new constraint
appears at another location, and we repeat the process to achieve additional throughput
improvements. TOC enables us to focus our scarce resources on the critical part of the
value stream that will make a difference, instead of diluting our efforts where they will
not.
With regard to process improvement, process manufacturing differs from discrete
manufacturing in critical ways. Applying discrete-manufacturing process-improvement
methodologies without modification results in disconnects and gaps in the improvement
effort. Instead of blindly applying methodologies in ways that are more suited to discrete
manufacturing, a more rewarding approach is to realign them to a framework that
accounts for the unique nature of process manufacturing, identifies the specific wastes,
and applies the appropriate tools to tackle them.
To order a hardcopy reproduction of this article, click here. To purchase digital reprints
or reproduction licenses, please contact the resource center at service@sme.org or call
(800) 733-4763.