OPTIMUM EQUIPMENT START-UPS:
Conquering the
Commissioning Blues
Steven
Michael Ouellette Dr.
Althea D’Souza
President, The ROI Alliance,
LLC Staff
Associate
Senior
Associate, Luftig & Warren
International ASQ
Member
ASQ CQE, CQA
Luftig
& Warren International
2025
Red Cloud Road 2000
Town Center,
Suite 2000
Longmont,
CO 80501 Southfield,
MI 48075
www.ROI-Ally.com
Summary
The reader will attain a fundamental understanding of how
advanced quality planning and a statistics-based start-up strategy have been
used successfully in industry to commission over $750 million worth of new and
existing equipment over the last 15 years with vast reductions in the real
costs of specifying, commissioning, and operating equipment.
Key Words
Equipment Installation Set-up
Introduction
The “traditional” equipment start-up method and its frequent
results are shown in Figure 1. Engineers
involved in these start-ups have the goals of purchasing new equipment,
installing it in a timely manner under projected cost and turning it over to
production as quickly as possible for full shipping runs. Although these are desirable goals, a closer
examination will reveal that there are real costs if these are your only goals.
Terminology:
Product refers to the output of the purchaser’s process, and can be
an object or service. Product
characteristics can be either in-process (may be modified in subsequent process
steps) or end-of-line (as the customer sees it).
Commissioning refers to the activities leading up to turning over
new equipment for normal production.
Functional Testing refers to testing the safety and mechanical
functionality of equipment.
Qualification or Acceptance
Testing are the tests that must be passed by the
new equipment prior to releasing the process for normal production.
Project engineers are frequently rewarded, explicitly or
implicitly, on the amount of equipment they install. Rarely are they rewarded for avoiding new
equipment capital expenditures through process improvement on existing
lines. Since capital project engineers
do not typically perform that function this is not an important consideration
for their success. However, the business
as a whole would benefit from an examination of production’s needs and if these
needs can be met with existing equipment through process improvement or smaller
capital outlays.
Rewarding project engineers for on-time installation when an
outside vendor is responsible for much of the timing is also a frequent occurrence. Typically, this is an attempt to ensure that
the equipment is fully installed by a certain date when penalties for the
vendor have not been written into the contract.
This situation can encourage the engineer or vendor to cut some corners
to meet the required date, particularly if there are no process and product
performance guarantees written into the vendor’s contract. Rewarding engineers for coming in under
projected cost may have the effect of driving them to submit a slightly padded
project cost or to bypass an unexpected but needed cost at some point in the
project.
The goal of quickly turning the new process over to
production drives the project engineer to spend little time on commissioning
beyond functional testing. It is usually
left up to the production personnel to figure out how to run the new equipment
in the real world after the project engineer has moved onto the next project.
No hard-working project engineer wants any of these things
to happen, but the capital improvement system that most companies use can
pressure them into doing just that. Most
engineers end up doing the best job they can under those conditions, and
succeed in bringing their projects to conclusion. It is ironic to note that the managers they
are protecting through their actions will likely be the ones pressuring them to
control costs and provide a more rapid turnover to production.
We contend that a capital improvement project brought to
completion in the typical way is not complete, and will almost certainly cause
a net loss to your bottom-line. In the
traditional start-up, there is no mechanism for the start-up engineers to make
new production lines easy to run, or to make sure that the line meets
production’s needs beyond the trial run.
We will show how an “optimum” start-up, on the other hand,
will not only result in a lower cost in the short-term,
it will show an improvement to your bottom-line over the long-term. This strategy has been used effectively by
several of our clients. You will find
this strategy is unique in its practicality and efficacy in industry. By following the methodology summarized in
Figure 2, you could realize savings like those shown in Table 3. We use the
term “optimum” start-up not because it will be free of problems, but because
when the inevitable problems occur, you will have vital information and a plan
for overcoming them.
Terminology:
An Optimum Start-Up of new equipment refers to a process by which
advanced statistical methods are applied in a strategic and disciplined fashion
to critical product performance, quality, and defect requirements, as well as
critical equipment performance requirements.
The purpose of this effort is to achieve statistical qualification or
optimization for all of the critical elements prior to the initiation of
full-scale production. (Luftig, 1997 p.
4)
An Optimum Start-Up of existing equipment refers to a process by which
advanced statistical methods are applied in a strategic and disciplined fashion
to critical product performance, quality, and defect requirements, as well as
critical equipment performance requirements.
The purpose of this effort is to achieve statistical qualification or
optimization for all of the targeted elements during the partial or complete suspension
of the 100% dedication to production requirements. (Luftig, 1997 p. 5)
The Situation
At some point, your company will believe it has a gap, and
believe that they need new equipment to fill that gap. Usually, it will be a need for more capacity,
better product quality, and, less frequently, newer technology. The preliminary step is to fully explore and
document the need, not the equipment that is needed. It is important to try to describe the need
in terms of product and process results and quantify the impact of fulfilling
these needs in monetary terms. Technological upgrade should not by itself be a
justifiable reason for expenditures.
Many companies will require an estimated return on
investment, or payback time; consequently impact quantification is the first
step in justifying capital expenditures.
We suggest working with an accountant in this phase,
to make sure that the numbers are valid and that the full impact is
counted. For example, if you need more
production, you may be increasing speeds, decreasing maintenance downtime, or
running the machine longer, and all of these have effects beyond that machine
itself. If you increase speeds, you
should ask whether you would be able to transport and pack quickly enough. If you decrease maintenance downtime, will
you be freeing up mechanics for essential work elsewhere? If you are able to run the machine longer,
will you need more crewmembers? Once
management is provided with an accurate accounting of the need, they can in
turn support the decision to proceed with confidence that there will be a
bottom-line benefit realized as a result.
As soon as you have decided that there is a need and that it makes sense
for the business to fulfill that need, you are ready to begin the Optimum
Start-Up Methodology. The steps below
give the details behind the flowchart in Figure 2.
First Step – Do you really need new equipment
or can you get what you want from existing equipment?
Although this is not the primary thrust of this paper, we
need to emphasize how important this step is, and how frequently it is not
done. Project engineers have, at one time or another, become involved with
equipment that should never have been purchased. In one of many cases of this
in an author’s experience, the needed capacity improvement was achieved on
other similar equipment without any major capital investment. The tragedy was that new equipment had
already been purchased before the improvement efforts had begun since everyone
“knew” that process improvement alone could not close the gap. The start-up technique that we will outline
later can be applied to an existing line just as it can be to a new line
(except for advanced quality planning).
It does, however, require that you to be willing to devote line time and
personnel to its improvement. Listed
below are some common techniques in the literature that we have found useful in
improving existing processes, short of major capital improvements.
·
Improving maintenance metrics
·
Operator training
·
Mistake proofing
·
Autonomous control
·
Standard Operating Procedures (SOPs)
·
Supplier Quality Assurance (SQA)
·
Experimental design
·
Smaller equipment additions or changes such as:
-
Controllers
-
Measuring devices
-
Feedback and feedforward controls
-
Climate controls
·
Robust process design
·
Statistical and engineering process control
-
Improving stability (Shewhart SPC charts)
-
Adjustment charts to improve output (different
than Shewhart SPC charts)
Second Step – Advanced Quality Planning
1) Define vendor requirements in terms of
end-of-line product characteristics.
Consider what you are really purchasing when you buy new
equipment. For example, are you purchasing a machine that will deliver a
certain temperature, or are you really purchasing a machine that will make a
product with a given strength by controlling the temperature?
Too often, we define the process or equipment variables
without the involvement and commitment required from the equipment vendor to
meet the product requirements.
Specifying end-of-line product performance actually benefits your vendor
since it gives them more flexibility in design as well as clearly defining what
will make their customer happy. An
unhappy client who received exactly what they ordered often unfairly berates
the vendor when the vendor was not told their customer’s product needs.
In order to define vendor requirements in product
characteristics, you begin by defining
the process output in terms of customer-delivered characteristics. For many mature industries, these
characteristics can be written right into the vendor’s contract. For example, if you are purchasing a new mill
for rolling steel sheet, you will write into the contract the control you need
over thickness. The vendor has installed
enough mills to feel comfortable (based, hopefully, on data) guaranteeing
thickness control in the product.
If the equipment is not the last process that
affects any of these characteristics, you will need to cascade product
characteristics back through the process until you get to output of the new
line (in-process product characteristics).
For example, if your final characteristic is how many cookies fit in
your package, you will need to link size back through baking variables to
variables for the new dough extruder you are buying.
Compile a list of the
in-process and/or end-of-line product characteristic specifications and
capabilities. Define your needed
process averages and specifications or defect and defective rates and assign
desired capabilities to the characteristics defined in the previous step. Remember that you usually don’t sell
“averages” so define capability in terms of individuals.
In some industries where the purchaser is the expert, an
additional step of translating the
product characteristics to process parameters will need to be
performed. RESIST THIS IMPULSE unless absolutely necessary. This puts the burden of process engineering
on the purchaser and reduces the vendor’s responsibility for actual end-of-line
product output. If the vendor doesn’t
know what product output you want, she may provide you with something that
meets your process specifications but had she been asked would have known it
could not do what you wanted to the product.
If you do have to specify process parameters, make sure you clearly communicate
with the vendors what your design intents are, ideally through a design Failure
Mode Effects Analysis (FMEA) (Krausch et al., 1994 p. 14).
There are still some process parameters that you may have to
specify like sizes, weights, depths, and range of motions. The key is to leave as much of the process design that affects the product as possible to the
vendor.
Note that part of what you are actually buying is the
safety, productivity, maintainability, and quality output of the machine. These should also be defined with
specifications for the vendor to meet.
An efficient way to do this is by using safety and Total Asset
Utilization (TAU) metrics (Medlin 1992, p. 7–8).
2) Clearly
define your performance criteria and put them in the request for quote and in
the final contract.
Once you have defined the in-process and end-of-line product
characteristics, write them into your request for quote along with the
potential penalties if they are not attained.
A typical payment plan would be one-third before starting, one-third
after on-time equipment installation, and one-third after it has passed all of
the performance criteria. Some vendors
who promise that their equipment will do whatever you need become very
defensive when you tell them that part of their fee will be dependant on
product performance guarantees. It is
very reasonable that you ask that their faith in their equipment be backed up
with actual performance data at your location and enforced in the
contract. Be sure to define your
performance criteria as being of a given sample size, in statistical control,
and with a given capability. Be fair to
your vendor, though. Use the limits you
really need for your criteria, and pick what capability you really need for
each based on the risks. Clearly define
what penalties will be incurred if the equipment is installed late or does not
meet some or all of your criteria. There
is a real consequence to your end customer, and it is fair that the cost be
passed back to the vendor. Consider a
reward for exceeding performance criteria that affects the bottom-line. For example, just as a vendor should be
penalized if the equipment requires more maintenance downtime than planned, so
should they be rewarded if the maintenance needs are lower, since this improves
the purchaser’s bottom-line. Also give some thought to confidentiality
agreements. If it is a custom-designed
piece of equipment, do you want others to be able to see the design? If it is acceptable for competitors to see
it, and for the vendor to sell it to them, perhaps they can give you a price
reduction for your aid in design.
Another possibility is that you and the vendor learn how to get better
performance from off-the-shelf equipment during the start-up tuning activities. The vendor will want to use this information
with future customers, so perhaps you can license the settings or work out a
discount based on the performance improvement.
3) Pick a
vendor that will commit to working with your people in equipment, maintenance,
and process design (as appropriate).
Part of your request for quote should include the
requirement that vendor personnel will work with you to:
·
Design
the equipment (design FMEA) if the equipment is custom made. If it is “off the shelf”, you should require
that a copy of the vendor’s design FMEA accompany the quote so that you can
make sure that your product criteria were accounted for in the design. If the vendor did not design the equipment
with the aid of a tool such as a design FMEA, it is an invitation to you to propose
creating one together.
·
Design
the maintenance schedules (equipment FMEA).
If it is “off the shelf”, you should require that a copy of the vendor’s
equipment FMEA accompany the quote along with reliability data from actual
installations.
·
Design
the process (process FMEA). If it is
“off the shelf”, you should require that a copy of the vendor’s process FMEA
and SOP’s accompany the quote.
·
Resolve
any occurrence if the equipment fails to meet the acceptance criteria. The system for this point will be
outlined later in Acceptance Testing and Process Tuning.
If the vendor can supply you with data of any sort (from
bench tests to data gathered at other installation sites), use these data to
perform a potential capability study.
Vendors who can supply data should be ranked ahead of those that cannot,
even if they are not capable. At least
you know how close they are likely to be and the vendor can plan for any
required performance improvements in the quote.
Advanced Quality Planning Conclusion
Note that performing these steps may not lead to the lowest price vendor, but it will certainly lead
to the lowest total cost vendor. Oddly, people seem willing to “save” capital
purchase money (which is capitalized and depreciated) and end up losing money
from the bottom-line due to continual losses in safety, productivity,
maintainability, and quality (which is not depreciatable). Advanced quality planning
attempts to minimize these ongoing costs through initial preparation.
Third Step – Design of Day-to-Day Controls
This step establishes the daily controls on the process to
ensure that it will continue working after acceptance testing. Many of these activities can be done prior to
and during installation while some must be done after the equipment is running. During the traditional start-up, the day-to-day
running of the process is rarely given much consideration since the people who
are usually involved in the start-up are not the people who will be running it
once it is turned over to production.
The activities and information you need to design a daily control system
nicely overlap with what you need to be doing anyway for the start-up
itself. The scope of this activity is
beyond this paper, but a list of activities to help design a comprehensive
day-to-day process control system is below.
·
Gage capability studies
·
Process flow diagram
·
Supplier-Input-Process-Output-Customer (SIPOC)
diagram
·
Process FMEA
·
Process control plans
·
Quality Function Deployment (QFD) tables
·
Standard Operating Procedures (SOPs)
·
Defining and monitoring critical process metrics
·
Reaction and containment plans
·
Audit system
·
Operator training system and materials
These activities can be spread out and accomplished
before, during, and after installation.
They should be complete, however, before turning the process over to
production for unrestricted production.
Fourth Step – Equipment Installation and Check-out testing
There is a well-defined discipline to preparing the site,
installing equipment on time, making sure everything fits together and
functions safely, providing operator training, and more. An optimum start-up includes this planning as
well as contingency planning. Check-out
testing is frequently done by the vendor, but we suggest that you have operators
and engineers watch what they do very closely and take notes on anything that
is not already documented. This is one
area, though, that most businesses do quite well, so we will not dwell on
it. Prior to and during installation,
much pre-work can be done. This includes
the following.
·
Acceptance testing sample size (based on a
and b
risks)
·
Failure Mode Effects Analyses (FMEAs)
·
Some gauge capability studies
·
First-draft standard operating procedures
·
Equipment and process training
·
Product and Process Control Plans
Fifth Step – Acceptance Testing
A traditional start-up would require only enough units
produced to allow for customer testing.
The danger in this is that a non-statistically designed production run
may appear to be acceptable, but in reality provide unacceptable long-term
results. Below is an example (Luftig,
1996) of how this worked on a coil plating line. Table 1 shows the data and decisions made
based on traditional acceptance testing (sample size of 10), followed by the
production line data after the line had been in full-scale production for three
months.
Table 1 - Acceptance Testing Results and
Outcome After Three Months Production
|
Quality
Category
|
Requirements
/ Specifications
|
Observed
Outcomes (and Decision) after Acceptance Testing
|
Observed
Outcomes (and Decision) after Three Months of Production
|
|
Product Quality
|
0.1025 ± 0.0025
|
0.10211, 0.10492, 0.10371, 0.10416,
0.10156, 0.10370,
0.10400, 0.10272,
0.10244, 0.10325
(ACCEPTABLE)
|
4.73 % Defective
(UNACCEPTABLE)
|
|
Product Defects
|
No more than 2 Voids per Coil
|
1, 0, 2,
1, 1, 2, 2, 2, 1, 2
(ACCEPTABLE)
|
17 % of Coils with > 2 Voids
(UNACCEPTABLE)
|
|
Product Performance
|
2% Units per Coil Maximum
|
2, 0, 1,
0, 0, 2, 2, 1, 1, 2
(ACCEPTABLE)
|
9.86 % of all Coils > 2 % Defective Rate
(UNACCEPTABLE)
|
|
Equipment Performance
|
MTBF ³ 2 Hours
|
MTBF = 2.35 Hrs
(ACCEPTABLE)
|
MTBF = 1.75 Hrs
(UNACCEPTABLE)
|
The results are dramatically different after the Optimum
Start-Up strategy was used on the plating line as shown below in Table
2.
Table 2 - Results on Plating Line Three
Months After Optimum
Start-Up and Tuning
|
Quality
Category
|
Requirements
/ Specifications
|
Observed
Outcomes (and Decision) after Statistical Qualification
|
Observed
Outcomes (and Decision) after Optimization
|
|
Product Quality
|
0.1025 ± 0.0025
|
99.994 % In Specification with m
= 0.1025
(ACCEPTABLE)
|
» 100% In Specification with
m = 0.1025
(More than
Minimally ACCEPTABLE)
|
|
Product Defects
|
No more than 2 Voids per Coil
|
99.865 %
of Coils with £
2 Voids
(ACCEPTABLE)
|
» 100% of Coils
with 0 or 1 Void
(Lower Costs
due to Higher Yield, Lower Internal Rejection Rates and Low/No Customer
Returns and Complaints)
|
|
Product Performance
|
2% Units per Coil Maximum
|
99.997%
of all coils less than 2% defective rate
(ACCEPTABLE)
|
» 100% of All
Coils < 1 % Defective Rate
|
|
Equipment Performance
|
MTBF ³ 2 Hours
|
MTBF = 2.35 Hrs
(ACCEPTABLE)
|
MTBF In Control at 6.25 Hours
(More than
Minimally ACCEPTABLE; Lower Costs due to Higher Levels of Asset Utilization)
|
An optimum start-up should have two phases to the acceptance
testing. The first phase would be a
short-term capability study (Petrovich 1997, 84–93 and Luftig 1996, 6-1 to
6-45) to tentatively qualify the process for production. This would involve examining an appropriate
sample of the output over a relatively short time period to analyze whether the
process is potentially able to satisfy the performance criteria. This will likely not catch long term effects
like tool-wear, maintenance, and seasonality, among others. Depending on the industry and equipment, you
may make the decision to begin using the equipment for probationary production
after a successful short-term capability study if you were to very closely
monitor the output and process variables.
If the short-term capability study shows the process might
be capable, then you would move onto the second phase. This second phase is the long-term capability
study (Luftig 1996, 6-46 to 6-65) which tests to see if the output conforms to
your requirements after giving everything that can go wrong a reasonable chance
to occur. If, for example, your process
were likely to be affected by the low humidity and temperatures during winter,
you would not want to say with finality that the process is capable without
having to work under those conditions.
This also gives you a chance to observe the effect of maintenance
cycles, raw material fluctuations, operator differences, motor burn-in and
other time-dependent occurrences. When
the long-term study shows that the process is in control and capable of
producing the product characteristics you want, the start-up is officially
concluded and can be turned over to production and the vendor paid their last
installment. The intensive monitoring
that you have been doing of product and process variables can now be reduced to
a sampling frequency calculated from your data and the risks involved, and the
transfer to unrestricted production will go smoothly.
Sixth Step – Process Tuning
Unfortunately, it is has been our experience that the ideal
start-up you were aiming for with advanced quality planning rarely materializes. When it does, it is usually a mature industry
and an application of well-tested technology.
In either case, the advanced quality planning done at the beginning will
help you out either by preventing problems or by giving you the information to
find a path out of the crisis. It is
important to note that you probably only know you are in a crisis because you
are using the optimum start-up methodology.
The traditional start-up would already have turned the equipment over to
production with a full schedule planned for the next year, as in the example in
Table 1 and Table
2. The problem
would eventually be detected and still needs to be fixed, but you have to do it
without the equipment experts and while maintaining a full production schedule.
Start off by eliminating
known issues and special causes. If
common sense tells you to fix something, and it is easy and inexpensive to do,
take care of it. Since you are analyzing
the process statistically, you may be able to identify sources of special cause
variation with Shewhart charts and eliminate those as well.
It may be obvious what to do, but if the problem remains, or
if it is not obvious where to start, deploy
efforts to close performance gaps using the appropriate methodology.
·
Quality Function Deployment (QFD) (Cohen, 1995)
·
Quality improvement strategy (Luftig, 1989)
·
Problem solving
(Petrovich, 1996)
·
TAU improvement for equipment gaps (Medlin, 1992, sec. 9)
These efforts can be teams working in parallel, or even be
a single multi-tasking team, depending on the size of the project and the
nature of the gaps. Some or all of these
efforts may end up designing and running an experiment to investigate process
parameters. We have found fractional
factorial screening experiments followed by confirmations extremely effective
if there are many factors that might cause the performance gaps. Once the results have been experimentally
confirmed, any process changes should be systematized as part of the day-to-day
controls. This triggers reinitiating the
short-term acceptance testing. When the
performance gaps have apparently been closed in the short term, the
improvements are verified with the long-term study.
Bottom-line Gains using the optimum start-up
methodology
If you follow this methodology from start to finish on new
equipment installation, the following list tells you what you will get for your
investment.
·
The new equipment will be operating in a state
of statistical control and at the maximum level of capability possible (or at
high process performance capabilities) for those product and performance
variables you designated in the beginning.
·
The new equipment will be operating at the
minimum cost profile available given the parameters defined by the process and
management goals.
·
A complete quality operating system that is
related to the critical product and process variables including:
-
Master and process block QFD matrices
-
Design, process, and equipment FMEAs
-
Product control plans and appropriate control
systems
-
Process and measurement control plans and
control systems
-
Maintenance control plans and control systems
-
Reaction plans for all critical product and
process variables
-
SOPs and a workforce that has been trained to
use them
Depending on the size, complexity, and focus of the
start-up, the cost savings can be astounding.
In situations in which the equipment had already been ordered or changes
were made to existing equipment, none of the advanced quality planning benefits
were possible.
Yet in every instance, the cost savings due to the start-up methodology
saved in excess of the cost of the start-up activities. In most cases, the company saved more than
the capital cost of the entire project due to detecting and correcting issues
that affected product performance or liability before any product was
released. See Table 3 for a sample of savings from optimum start-ups. You will recall too that the costs of
starting up a new piece of equipment are capital costs, and are subject to
depreciation. The losses you would have
experienced with the traditional start-up and turnover to production are not
depreciable and directly impact your bottom-line.
Table 3 - A Sample of Optimum Start-Ups
and Savings
|
Line/Process
|
Existing
or New
|
Savings
Mainly From
|
Money
Saved
|
|
#3 Coating Line
|
Existing
|
Increased Throughput
|
$23.6 Million / year
|
|
Multi-Shearing
|
New
|
Improved Reliability
|
$1.7 Million / year
|
|
Y-Line
|
New
|
Increased Throughput
|
$16 Million / year
|
|
Product Defect
|
Existing
|
Decreased Returns
|
$750,000 / year
|
Frequently Asked Questions
Won’t it cost more
time/money/effort to do the methodology?
A Vice President of Operations once challenged us
about the presumably large amount of time, money and effort required to perform
an Optimum Start-up. When questioned
about his oldest plant, the Vice President admitted that although the plant had
been in operation for 12 years, none of the critical product and process
conditions were operating in a state of control or capability. Our reply to him was that after 12 years, he
was still “starting up” the plant.
Having got the point, the Vice President enlisted our aid for a start-up
on two new plants. The first of the two
came in at about $80,000 a month under budget, at a higher than projected level
of production. This was in a plant with
less than 100 hourly and salaried workers.
We are buying new
equipment off the shelf. Do we need to
use the methodology?
It is just as important to use the methodology in
this case, although the data from previous installations (if available) will
make your job somewhat easier. It is
particularly important that you give thought to a design FMEA to make sure that
the piece of equipment designed for general use is giving you what you need in
your particular application.
We have installed
equipment like this before. Do we need
to use the methodology?
We would still recommend using the methodology. If you have not followed the methodology on
the similar equipment, the rigor will help you with both the old and new
processes. If you have, it should be
easy to follow the discipline of the methodology and to be prepared in case
this equipment does not perform like its predecessor did.
We really like our
vendor, and we don’t want to imply that we don’t trust them.
As logical as the first few questions are, this one is
actually the most common real reason for not wanting to use the
methodology. As engineers, we know that
you work with the vendors, eat with them, talk with them, and form a
comfortable relationship with them – and there is nothing wrong with that. However, we can sometimes lose sight of the
fact that they are there to provide a service that will end up making us money
for a fair price. You are not asking
anything from them other than guarantees that what they promised will come
true. You may end up paying a bit more
for them to work with you in the design phase and the acceptance testing, but
you should not pay them more for a guarantee that the equipment will perform as
you request. This is in the vendor’s
best interest as well, both to keep their current customer satisfied and coming
back for more, and to generate data which can be used to improve their products
and bring in new customers.
Conclusion
The rigor and discipline of using the Optimum Start-Up
methodology provides a system for vendor and purchaser multi-disciplinary and
multi-departmental communication before, during, and after equipment installation. Its strong basis in statistical sampling and
experimentation along with the information exchange this method facilitates
between vendor and customer ensures that the customer’s needs are known, and
that the vendor provides a process to meet those needs. In the unfortunate event that the vendor does
not supply a process to produce the critical product parameters needed, the
customer will have options in the contract to offset (at least partially) the
cost they will bear as a result. Establishing maintenance and production
metrics as part of a day-to-day control system ensures that when the shine has
worn off of the new equipment, it will still be performing equal to or better
than what it did on the first day of production. These conclusions are supported by numerous
case studies we have compiled over the past 14 years in disparate industries
that show vast reductions in total start-up costs and/or improved profit
associated with the methodology.
References
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Luftig, J.T.
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