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NWA Quality Analyst
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Achieving Customer Specifications Through Process Improvement
by
John G. Surak, Ph.D.
Syed A. Hussain Ph.D.
Jeffery L. Cawley
Achieving customer specifications is an important job of the quality assurance
professional. Specifications define the difference between acceptable and
unacceptable products and are at the heart of customer satisfaction. The
ability to consistently deliver product within specifications often determines
whether the supplier will continue to do business with the customer.The
most certain way for the supplier to achieve the goal of delivering product
within specification is to adopt Statistical Process Control (SPC) methods.
SPC provides the means to achieve and maintain stable production processes
that are capable of meeting specifications.An improved process is achieved
by better coordinating the design of the process with the specifications
of the product. A fundamental aspect of this improvement process is to recognize
that processes, no matter how closely monitored, will have variation. This
variation is well defined when a process is in a state of statistical control
(i.e., is varying randomly without large, assignable variations).The second
component is to measure how well the process can meet specifications. This
is called process capability. Figure 1 illustrates the defect rates
associated with different levels of process capability. By reducing process
variation, the supplier increases his capability to meet specifications
and thereby reduce the amount of out-of-specification product.
| Cpk |
Sigma Level |
Calculated
Number of
Out-of-Spec Products |
| 1.00 |
3 |
2700 ppm |
| 1.33 |
4 |
63 ppm |
| 1.67 |
5 |
0.57 ppm |
| 2.00 |
6 |
2 ppb |
|
Figure 1
Relation of Process Capability (Cpk) with a Theoretical Amount of Out-of-Specification
Product Figure 2 shows the formula for Cpk, an index commonly used
to describe process capability. Cpk takes into account the target level,
acceptable amount of risk and product variation, and provides a convenient
snapshot of process performance.
| Cpk = Minimum[(USL-Mean)/3S
or (Mean - LSL)/3S] For example, given:
| Mean = |
12.5 LSL = 11.5 |
| Std. Deviation, S
= |
0.2 USL = 13.5 |
| Cpk = |
Minimum[(13.5-12.5)/3(0.2) or (12.5
- 11.5)/3(0.2)] |
| = |
Minimum[1/0.6 or 1/0.6] |
| = |
Minimum[1.67 or 1.67] |
| = |
1.67 |
Referring to Figure 1, this yields a 0.57 parts per
million defective,
commonly called a 5 sigma process. |
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Figure 2
Calculation of Cpk - Process Capability Index In order to achieve high quality,
the supplier must keep the process in a state of statistical control. This
means that the process must not be affected by special causes or unpredictable
variation. The supplier can be assured that the process is in statistical
control, if they properly develop a process control plan and monitor the
process using techniques such as control charts.The final step is that the
supplier should continually reduce the level of process variation using
continuous improvement techniques. This in turn improves product quality
and further reduces the risk that out-of-specification product will be made.
As a result, the supplier can set meaningful specifications and the processor
will worry less about product failure caused by an out-of-specification
ingredient.Since food processing often uses natural products which are frequently
non-homogeneous, process capabilities tend to be lower than in industries
which use homogeneous starting materials. We have found that usable guidelines
are Cpk > 2.0 for sanitation, Cpk > 1.33 for pilot plant, and Cpk
> 1.0 for natural product processing. By using continuous process improvement
methods to push capability as much as possible, the food processor will
both reduce costs and the chance of shipping out-of-specification products.Process
Improvement and Capability Studies at Con Agra (Case Study) Changing
tastes of consumers and marketing trends of restaurants, particularly fast-food
restaurants have increased the use of fully cooked and sliced muscle meat
products in prepared food. An example is the popularity of add-on meats
to sandwiches.The portion control of the slices enhances our market position
by fulfilling customer's desire to deliver a consistent product to the consumer
. Reducing variation in product slice weight has a large impact on our bottom
line. The customer demands and the government agency requires that the amount
of product in the package, on average should be at least as much as the
label on the package states. This is especially critical for packaged consumer
products which must meet governmental labeling requirements. However, to
remain profitable and to be cost effective to shareholder and customer alike,
we avoid overfilling. Using SPC, ConAgra has achieved a fair and effective
balance between under- and overweight products. This results in significant
savings and gives ConAgra an advantage over others suppliers who have less
control of their processes.ConAgra Refrigerated Prepared Foods uses SPC
along with a structured program of continuous monitoring and improvement
to optimize product weights. We routinely analyze portion weight data to
identify out of control situations and capability to meet the product specifications.
If there is an incompatibility between the specifications and process, the
normal procedure is to improve the process.Manufacturing ProcessPre-cooked
muscle meat in the form of circular sheets are provided by an improved method
developed at ConAgra Refrigerated Prepared Foods. Grinding the muscle meat
to break down the connective tissue also increases the surface area to allow
better penetration of the seasoning. The meat blend is de-aerated by vacuum
which minimizes voids while increasing the development of the protein exudates
for binding of the muscle meat pieces.The stuffing of the final blend yields
consistent, unitary logs of circular cross section and a diameter of 4.18".
The logs are cooked to an internal temperature of 160oF, then
chilled in a blast chiller to a temperature of 26-28oF for 2-3
hours prior to slicing to insure a smooth slicing process. The casing is
removed prior to slicing and slice thickness can be adjusted using conventional
meat slicers. The slice surface is essentially free of separable seams between
abutting surfaces of the original muscle meats from which it was formed.
Therefore, restaurants and fast-food purveyors are provided with ready-to-serve
or microwave heatable round slices with consistent diameters.Slice weight
for each product and product line is measured at least once per hour, the
results entered into the computer, and corrective action taken as needed.
If more than two consecutive weight checks are below the declared net weight
then all products are retained to the last acceptable check. By controlling
the running average for each product, all products are within specs and
as a group their weight equals or exceeds the total declared weight.Technical
services examines the "capability" of all processes to determine
if the processes are producing within specifications. Figure 3 illustrates
this analysis using X-Bar and Range control charts and a histogram. During
initial process startup, statistical analysis revealed that the process
was stable but the variability made it incapable of meeting specifications.
As shown in Figure 3, the process frequently exceeded the upper specification
level (USL) but never fell below the lower specification level (LSL). The
customer on average received more than the declared weight of a product
but never less. Thus, Con Agra was over-filling product while not exceeding
the Maximum Allowed Variation (MAV) as mandated by National Conference of
Weights and Measures.This excess overweight was unnecessarily expensive.
The problem was identified, and a corrective action team formed. This team
included Corporate Technical services, plant operations, quality assurance,
engineering personnel, and line operators. The investigation revealed that
the slicing machinery needed improvement.The charts in Figure 4 show
the resulting reduction in process variation. The team determined that tighter
control on slicing temperature and regular maintenance of the blade of the
slicing machine would improve slice-weight control. The team worked closely
with line operators to implement these improvements.
As a result of the team's efforts, we greatly improved the process capability.
The original Cpk was 0.8288 with a calculated 0.64% of the production overweight.
After the process adjustments, the Cpk increased to 1.324, and our calculated
overweights were reduced to only 63 per million portions.High capability
production gives us more than the confidence that we will routinely deliver
product within specifications. When we are highly capable, we can tolerate
a shift in the process without losing our production. An example of this
is the large safety margin we maintain in sanitation (Food Quality Magazine,
May 1998). When line conditions were altered, our process capability changed
from Cpk = 12.2 to Cpk = 1.495. Since CpK = 1.495 is still highly capable,
we had the opportunity to correct the process shift with the confidence
that we were still shipping safe food products.In the above case of meat
slice portions, a shift from the original Cpk = 0.8288 to Cpk = .67 (2 sigma
process) would increase our calculated overweights from 0.64% to 4.54%.
Such a shift substantially increases the amount of product given away for
no compensation.ConclusionConAgra successfully monitors control points
using SPC to push continuous quality improvement. This permits us to develop
highly capable processes that both meet our customer needs and minimize
our production costs. As a result we establish ourselves as both a more
dependable and more profitable vendor.John G. Surak, Jeffery L. Cawley,
Syed Ajaz Hussain, "Integrating HACCP and SPC," Food Quality
Magazine, May 1998. |
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