1 Author: Higgins, Patrick, A Title: Raw Material Utilization in Food Manufacturing The accompanying research report is submitted to the University of Wisconsin-Stout, Graduate School in partial completion of the requirements for the Graduate Degree/ Major: MS Manufacturing Engineering Research Adviser: Thomas Lacksonen Submission Term/Year: Spring, 2013 Number of Pages: 30 Style Manual Used: American Psychological Association, 6 th edition I understand that this research report must be officially approved by the Graduate School and that an electronic copy of the approved version will be made available through the University Library website I attest that the research report is my original work (that any copyrightable materials have been used with the permission of the original authors), and as such, it is automatically protected by the laws, rules, and regulations of the U.S. Copyright Office. My research adviser has approved the content and quality of this paper. STUDENT: NAME Patrick Higgins DATE: 12/07/2012 ADVISER: (Committee Chair if MS Plan A or EdS Thesis or Field Project/Problem): NAME Thomas Lacksonen DATE: 12/08/2012 --------------------------------------------------------------------------------------------------------------------------------- This section for MS Plan A Thesis or EdS Thesis/Field Project papers only Committee members (other than your adviser who is listed in the section above) 1. CMTE MEMBER’S NAME: DATE: 2. CMTE MEMBER’S NAME: DATE: 3. CMTE MEMBER’S NAME: DATE: --------------------------------------------------------------------------------------------------------------------------------- This section to be completed by the Graduate School This final research report has been approved by the Graduate School. Director, Office of Graduate Studies: DATE:
Transcript
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Author: Higgins, Patrick, A Title: Raw Material Utilization in Food Manufacturing The accompanying research report is submitted to the University of Wisconsin-Stout, Graduate School in partial
completion of the requirements for the
Graduate Degree/ Major: MS Manufacturing Engineering
Research Adviser: Thomas Lacksonen
Submission Term/Year: Spring, 2013
Number of Pages: 30
Style Manual Used: American Psychological Association, 6th edition
I understand that this research report must be officially approved by the Graduate School and that an electronic copy of the approved version will be made available through the University Library website
I attest that the research report is my original work (that any copyrightable materials have been used with the permission of the original authors), and as such, it is automatically protected by the laws, rules, and regulations of the U.S. Copyright Office.
My research adviser has approved the content and quality of this paper. STUDENT:
NAME Patrick Higgins DATE: 12/07/2012
ADVISER: (Committee Chair if MS Plan A or EdS Thesis or Field Project/Problem):
This section for MS Plan A Thesis or EdS Thesis/Field Project papers only Committee members (other than your adviser who is listed in the section above) 1. CMTE MEMBER’S NAME: DATE:
2. CMTE MEMBER’S NAME: DATE:
3. CMTE MEMBER’S NAME: DATE:
----------------------------------------------------------------------------------------------------------------------------- ---- This section to be completed by the Graduate School This final research report has been approved by the Graduate School.
Director, Office of Graduate Studies: DATE:
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Higgins, Patrick, A. Raw Material Utilization in Food Manufacturing
Abstract
This project discusses raw material utilization for food manufacturing regarding certain
initial processing steps and the relationship with the initial size of the raw material. In food
manufacturing a certain amount of the initial raw material can not be used in the final product
because of being inedible or failing to meet customer specifications. Customer specifications
can usually not be adjusted. It is up to the strategic decisions of the company and the equipment
or processes to maximize the utilization of the raw materials. Analysis of company XYZ
provides a baseline at three years ago, current state and recommendations for the future.
This is a gap analysis to highlight the areas of improvement and to justify the resources in
pursuing similar opportunities further. The three areas discussed are: raw material sizing,
processing equipment capability and finish product specifications. The work so far has proved a
4% increase in yield with a 10.5% realistic current gap assessed by performing bench top testing
by hand instead of geometric calculations or line testing. A predicted increase of 5% was
determined if the current sizing system was improved to incorporate a variable that was not
assessed with the initial sizing project.
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Acknowledgments
I would like to thank my family, especially my Grandfather. Without them, I would not
have had the opportunities in my life to advance my education and obtain this M.S. degree.
List of Tables Table 4.1: Raw Material Size Categories Before and After Sizing Revision……………………22 Table 4.2: Comparison of Bench Top, Geometric and Actual Yields...…………………………26
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List of Figures Figure 4.1: Piece Count and Raw Material Diameter Comparison...……………………………22 Figure 4.2: Minitab Analysis Showing Fitted Line Plot for Raw Material Diameter
and Weight………..………………………………..…………………..………………..23
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Chapter I: Introduction
The company XYZ is a food manufacturing company. Most of their products are
battered and breaded vegetables that require frying before they are ready to eat. Consumers
enjoy this product by purchasing over 50 million pounds annually from this one factory. The
primary customers of these products are restaurant chains.
Only one certain vegetable will be studied; however many of the discussed ideas could be
applied to others. The challenge facing this company is to continually strive to increase the
utilization of the certain raw material. The vegetables are the input; all utilization directly affects
the over head costs and profits.
The raw material comes in large one ton bags on slip sheets. They are raised by a crane
and the bag is cut at the bottom to dispense the vegetables into a large hopper. From the hopper
they are conveyed to a worker who orientates each vegetable a certain way on a pocket of
another conveyor. This feeds to a piece of equipment that performs the end cutting and peeling
processes. The end cutters are vertical circular saws controlled by a vision measuring system
and programmed set points. This camera calculates measurements based on the SKU
specifications, operator input and the size of the each individual raw material. The root and stem
are cut off and the vegetable travels past spring loaded razor blades. These razor blades are
called slitter blades and they score across the peel or skin. The vegetable is conveyed to a tunnel
with air nozzles and rubber coated rollers which help remove the outer peel. After this process
the vegetable is end-cut and peeled which makes it ready for slicing. A worker sets the vegetable
on one of the end cut sides, onto a conveyor. This conveyor feeds the vegetable into the slicing
equipment. The slicer has large horizontally opposed circular knives staggered above a platform
with pockets that hold the vegetable while the vegetable is cut. The height from these knifes to
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the platform can be adjusted to achieve the proper cut thickness, depending on the SKU
specifications.
In cross cut slices of uniform thickness, the vegetable slices are conveyed through a hot
water blancher for approximately five minutes. The vegetable slices get poured on to a vibrating
table that helps separate the slices into rings. These rings get conveyed past an optical vision
sorter that removes most defects. Defects are considered peel, discolored skins, bruised spots,
misshaped pieces and broken rings. Workers are stationed after the optical sorter to finish
removing the defects, separate the remaining slabs into individual pieces and orientate them on
the belt with proper spacing in between each slice.
From here the processed material are conveyed through batter and breading machines
with multiple passes of each depending on product formula. Then they are either frozen, or par
fried and then frozen all with a continuous flow. These are conveyed to packaging where they
are sorted and weighed electronically, then placed into cartons or plastic bags. The packaging is
either heat sealed for bags or hot glued for cartons. Packaging or pick and place robots place the
cartons into boxes while the bags are hand packed into the larger boxes for shipping. Palletizing
robots prepare the slip sheets and stack the boxes per the most economical cube stack and layout.
These pallets are plastic wrapped and taken immediately to the holding freezer. These are sent to
the distribution center or the consumer business depending on order requirements.
These vegetables have some material that can not produce saleable product such as: the
peel, skin, discolored or rotten flesh, root and stem. Then there is other material waste that is
compromised when processing the vegetables to the customer specifications. The customer
specifications could include pieces per pound, size, shape, and coating percent to name some
critical ones. The waste goes one of two different paths depending on what waste stream it was
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in. On average, 58% of the initial incoming raw weight is not saleable in current form and is
waste. Out of this 58% waste, 38% of this material can be used for animal feed, land spreading,
or energy production. The remaining 62% of the 58% that is waste, can be separated by color to
sort out any remaining peel, root and stem. This will be shipped to another facility that grinds
down this vegetable and forms the finished product. The variability of grown raw materials,
equipment capability, and product specifications are the three approaches to increase raw
material yield. This Thesis focuses on the variation in the raw material sizing and the equipment
capabilities.
The original raw material sizing is as follows. There are four different size groups, with a
minimum and maximum diameter. The four ranges in inches are: 3 to 3.75, 3 to 4, 3 to 4.5, and
3.75 to 4.75.
The portion of this system that was concentrated on for testing purposes was between
initial end cutting of the raw material where the stem and root ends are removed and the
blanching process. Analysis concentrates on only one SKU and therefore has certain
specifications. This product was chosen because of the high demand volume. The
measurements taken were weight of the raw material before and after certain processes to
calculate the percent loss and percent utilization or yield.
Statement of the Problem
This paper will help answer the following questions. To what extent does a raw material
need to be changed for the end product? In other words, waste of the raw material is necessary
to form it into the finished product. How much is necessary? The first step is to optimize the
raw material with the end product by sizing the incoming raw material. There is a large gap
between theoretical raw material yield and the actual results. A 1% increase in yield on average
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for all 50 million raw material pounds equates to approximately $190,000 in raw material
savings annually. There is also the benefit of labor efficiency and profit from the saleable
product.
Purpose of the Study
The goal was to increase yield of the raw material. Produce more saleable product with
the same incoming raw material amount or produce the same saleable product while using less
incoming raw. With all of the SKUs and three plants producing similar products, a small
percentage increase across the board would mean a significant annual savings. The study looked
at two of the three main approaches to this opportunity. The sizing of the raw material and the
process that it goes through both play very large roles with utilization. This research highlighted
the largest areas of opportunity and suggests how to obtain these increases in yield.
Assumptions of the Study
The data assessed was collected from one SKU, in one factory, and during a certain raw
material season. It is assumed that the results could be applied to other SKUs, seasons, and at
the other factories with similar products. During certain times of the year there is a drastic shift
in raw material quality. Fresh crop is during June through August and storage season is the
remaining months out of the year. If samples were taken during separate seasons, the samples
would skew the data. This is why the study will concentrate data collection in October during
the storage raw material season. The consistency of quality is also another benefit in performing
the study during this time.
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Definition of terms
BOPs. Best Operating Practices established by quantitative analysis.
End Cutter. These are vertical circular saws that cut off the ends of the vegetables.
Piece Count. Customer driven product specification for how many pieces per pound.
Placing more than the required pieces per pound in a container is considered waste.
Puck or Slab. This is a cross section cut or slice of the vegetable and is the desired
thickness that can be different depending on specifications.
Raw Material Diameter. Distance perpendicular to the height.
Raw Material Height. Distance between the root and stem ends of the vegetable.
Raw Material Shape. The relationship of height and diameter. Elongated means height
is taller than the diameter, while short references the opposite scenario.
Raw Material Utilization. RMU abbreviation and acronym. Another term for Yield.
Saleable Product. Finished goods that meet all the specifications for that product. This
could include piece count, diameter sizing, percent coating pick up, limited defects.
SKU. Abbreviation and acronym for stockkeeping unit. (APICS 2011)
Slicer. This circular blade is mounted horizontally and slices the vegetables in to slabs.
Slitter Arm. This holds the slitter blade in place during operation.
Slitter Blade. This blade slices the peel so the first couple layers can be removed.
Stockkeeping Unit. An inventory item. For example, a shirt in six colors and five sizes
would represent 30 different SKUs. 2) In a distribution system, an item at a particular
geographic location. (APICS 2011)
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Yield. The amount of good or acceptable material available after the completion of a
process. Usually computed as the final amount divided by the initial amount converted to a
decimal or percentage. (APICS 2011)
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Chapter II: Literature Review
In this section a number of factors are looked at. They include: food processing
utilization, food processing equipment, grown food variability, food manufacturing: current
trends and future technology.
Food Processing Utilization
Food processing utilization is dependent on three main aspects: raw material, processing
equipment, and the customer specifications required for the finished product. Utilization is
calculated by finished good weight, subtracted by the coating pickup and then the difference is
divided by the initial weight of the raw material to express as a percent. Using the most of your
product is one of the largest impacts that can be made to your revenue. Since this material is
already paid for, utilization is essential for maximizing profit from the product.
Besides directly using the product it could possibly be reused for something else.
Looking at this raw material there are certain parts that are not edible. This material that is
organic, yet inedible in its current state can be processed and used for various applications.
Organic material can be ground down for feed, fertilizers, bedding, and possibly digested to
make energy (Earth Engineering, n.d.). This waste in some areas is looked at as a commodity
and can be bought/sold and leveraged as so. The remainder of the material that is edible but
cannot be used for the main product at this factory is shipped to another processing facility to get
formed in to similar end product. Waste materials handling and disposal should also be analyzed
to minimize costs that are constantly increasing (Fellows, 2000).
Similar to furniture making, trees (raw material), the customer (specifications), and the
processing equipment, there would be some material you could not use and would need to
recycle elsewhere. Bromhead (2003) stated that solid timber yield averages 64% with a range
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from 27 to 90%. Similarly, in processed foods, very commonly there is a certain amount that is
“lost” because of the transformation to the material. Depending on the vegetable the yield could
vary drastically. There were no current benchmarks.
Food Processing Equipment
Food processing equipment plays a large role in food manufacturing. The impacts on
business include overhead or capital project, maintenance, processing, and possibly logistic
related costs (Gulati, 2009). The equipment settings, material’s capability, and the relationship
of both are deciding factors in utilization. Not all processing equipment and technologies are the
same. Most of the time there are positive and negative attributes and outcomes associated with
these different methods.
The equipment usually involves physical or chemical reactions for the processes. Blades
used for cutting would be an example of a physical change that is used to shape or prepare the
raw material for the desired product. The thickness of the blade and how the raw material is
measured plays a significant role in that utilization. An example of a chemical change would be
blanching, cooking, or freezing. Here you are permanently changing the chemical compound of
the material for the desired end product specifications. This paper will look at changing the food
processing equipment procedures to increase product utilization.
Grown Raw Material Variability.
Can we engineer an ideal raw materials size, shape, and internal characteristics? To a
certain extent we can help the raw material grow in to an ideal quality product (Martin et al.,
2005). There have been great advances in agriculture sciences that help maximize these ideal
characteristics. Countless amounts of capital have been put into understanding the company’s
raw materials to help reduce processing costs, improve efficiency and utilization.
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The spacing of the vegetation in rows in the field plays a direct role in the size and
possibly the shape of the material. Bonsai trees are “tortured” into taking shapes and directions
with their limbs that are intricate and otherwise would not have happened. As far as the size and
shape we have moderate control. The environment plays a large role in the quality of the raw
material. Humidity, temperature, water and air quality sometimes cannot be controlled without a
large monetary investment (Martin et al, 2005). Controlling nature in that respect is difficult.
When the raw material is growing then becomes dormant, it creates a negative feature inside that
drastically limits the utilization. This negative feature is difficult to detect from the outside
without a physical cut through the material. This thesis will look at raw material sizing to
improve product utilization. How to grow the desired sizing is worked through the Agriculture
Department.
Food Manufacturing
Current trends. Transportation of the material has always been an area of opportunity
with potentially great cost savings. Conveyors and augers are not the only conveyance options
out there. Water can be used to move product around the factory. Transportation plays the role
of moving the material while not incurring any damage. Conveyors and augers use relatively
low power to operate (Fellows, 2000).
Many trends in food manufacturing utilization involve energy reduction. This includes
all forms of energy from water to heat that escapes through various processes. The energy used
to heat or cool air and water would decrease with the reduction of the amount of this material
being processed. Refrigeration systems can be huge sources of financial opportunity (Klemeš, Et
al., 2008).
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Other trends lately have been around continuous improvement of just getting better at
what a company does. Being experts at your own game is the only way companies can survive
in a weak economy. About half of U.S. food goes to waste, similar to the yield when
manufacturing this product (Food Production Daily 2004).
Future technology. Future technology will only further help raw material utilization.
With advancements in agriculture, an engineered raw material might not be too far off.
Equipment will advance with technology, possibly changing how we cut, shape, or size
the material. Lasers, high pressure air or water can be used to cut instead of traditional blades or
knives of metal.
One technology that is used for detection of harmful materials before food is packaged is
x-ray technology. Harnessing this technology to detect defects in the raw material could be
beneficial. Processing equipment could be set up differently to utilize the defects better rather
then it being a surprise when it is processing through the facility. Being able to check the
internal quality of a supplier’s products before purchase and delivery could control what
suppliers this company works with, also even rejecting shipments based on contract
specifications. This would be a huge advantage and a savings of resources would be apparent
(Fusaro 2012).
This XYZ factory has looked into other technology greater than ten years in the past.
Since that time there have been advances that are worth investigating once again for this specific
application.
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Chapter III: Methodology
This paper will help answer the following questions. To what extent does a raw material
need to be changed for the end product? In other words, waste of the raw material is necessary
to manufacture the finished product. How much is necessary? There is a gap between
theoretical raw material yield and the actual results. A small increase in yield results in
substantial increases financially.
Data Required
Data collection procedure, raw material diameter and weight. The data collection
procedure was developed in house, by the senior leadership for this initiative. Over 6 months
time, encompassing both raw material seasons, the vegetables diameter in inches and weight in
grams were recorded.
Data collection procedure, equipment with two processes. The data collection
procedure was developed in house, by a Manager and the researcher. A random sample was
collected by taking ten vegetables each from the bottom, middle, and top of the same bag to
collect thirty samples total. These samples were controlled through the processes while the
weight was measured separately to see the direct impact of the process to that specific raw
material.
Data collection procedure, bench top yield. The data collection procedure was
developed in house, by the researcher. Specific raw material was chosen by diameter. The root,
stem, and peel were removed using knives. The inner diameter specification was achieved by
using a vegetable corer with a .75” diameter. The flesh of the raw material was sorted into three
categories: saleable product, inedible, and defects. Inedible material would be the root, stem,
peel, and any rotten flesh. Defects were considered deformed, too small, too large or otherwise
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not acceptable shape for the finished goods. The weight by category was recorded and the
usable material was divided by the overall material weight to equal percent yield.
Data collection procedure, geometric calculated yield. The shape of the raw material
was assumed to be a sphere, although it can vary in height. The center diameter customer
specification was subtracted out by using the volume of a cylinder calculation. The raw material
peel was subtracted from the overall diameter in the initial sphere calculation. All other material
was assumed to be saleable, measured against the initial weight for each sample, and yield
percent recorded. Yield was calculated by using the volume of a vegetable subtracted by the
shapes representing the processes physically changes. The formulas used were volumes of a
sphere and cylinder as found in the Machinery’s Handbook 28th Edition (Oberg et al, 2008).
Data collection procedure, actual yield. The data collection procedure was developed
in house, by the corporate Accounting group. These numbers are calculated that were retrieved
from the online tracking system for RMU.
Methods
Raw material diameter and weight. A fitted line plot was performed to assess the
relationship between the raw material diameter and the weight in grams. Due to the
confidentiality of this next step, specifics will not be mentioned in results. Certain size ranges
were ordered to test for adherence to the expected diameter and weights along with the results
from processes to insure customer specification of piece count is achieved. The size ranges were
adjusted slightly to result in the raw material weight corresponding with required piece count.
The weight is how the raw material sorting equipment organizes the individual vegetables in the
proper size ranges.
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Equipment. These samples where weighed before and after this equipment using a
digital scale. The data was analyzed by the difference of the before and after. A percent loss or
inversely, a percent utilization was calculated.
All data was analyzed using Microsoft Excel or Minitab statistical software.
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Chapter IV: Results
There are three main approaches to improving yield in a food manufacturing
environment: the raw material sizing, processing equipment capabilities, and the finished product
specifications.
Material Sizing
The first step was an analysis of the raw material to ensure it is consistent in regards to
processing performance and quality. Good quality in this case is proper size, shape, and quantity
with no rotting or decay. Generally, the customer and marketing groups agree on the required
finished good specifications and these have limited flexibility to increase the raw material yield.
The first approach worked on sizing the raw material into groups by diameter that
correlate with the customer specification of piece count or the number of pieces per pound in the
packaged containers, reference Figure 4.1. Regressions were calculated between the raw
material diameter and the finished product’s piece count to re-size these categories to fit more
consistently with piece count specifications. It was established that more consistent results were
achieved by using five size groups with a smaller range of sizes. The four existing size groups
were adjusted with the addition of another size group to make five total, as shown in Table 4.1.
The raw material diameter does correlate with the raw material weight as shown with the
regression below and fitted line formula with R-Sq of 92.7% as seen in Figure 4.2.
Diameter = 2.351 + 0.003279 * Weight
Therefore, since the piece count specification ultimately correlates with the weight of the
raw material mechanical size sorting can be effectively achieved. New equipment was
purchased to perform this sizing accordingly to the study results and what the order requirements
from the factories are each week.
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Figure 4.1 Piece Count and Raw Material Diameter Comparison
Table 4.1 Raw Material Size Categories Before and After Sizing Revision
Group Old Sizing Range (inches) New Sizing Range (inches)
A 3 – 3.75 3 – 3.5
B 3 – 4 3 – 3.75
C 3 – 4.5 3.5 – 4
D 4 – 4.5
E 3.75 – 4.75 4 – 4.75
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21
22
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24
25
26
27
28
29
30
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Pie
ce
Co
un
t Piece Count and Diameter Analysis
Baseline
3.50-3.75"
3.75-4.00"
4.00-4.25"
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Figure 4.2 Minitab Analysis Showing Fitted Line Plot for Raw Material Diameter and Weight
Prior raw material sizing had wide ranges in diameter within each group that were not
scientifically paired with the end product’s piece count. They were initially driven from the
availability of the different sizes specific to that growing season. This is not to state that the
finish product was out of specification because equipment adjustments would compensate for the
large range in raw material diameter at a financial loss of decreased yield. Average yield across
all products was 42% of the initial whole vegetable. The new sizing average yield across all
products in one year was 45%, an increase of 3% or approximately $540,000 annual benefit.
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Equipment Capability
The second approach concentrated on the equipment capabilities with two processes.
The first process is the end cutter or removal of the root and stem ends. The second process is
the removal of the raw material peel. Two processes were assessed together for this study
because of the difficulty in obtaining data off the line separately without further analysis.
The two processes removed an average of 7% of the diameter and 25% of the weight
compared to the initial raw material aspects. There was a range from 9% to 46% loss by weight
of the initial raw material within the fifteen separate sample runs of thirty vegetables. A portion
of this variance is attributed to the raw material shapes and this does impact yield or utilization.
Raw material shape is considered the height and diameter. This shape can influence the
equipment’s effectiveness to only trim off what is needed. Sometimes this will trim off more,
hence the variability in yield loss. Generally, if the height is less than the diameter the yield
would be larger. If the height is more than the diameter than the yield would be lower. This is
assuming that the finished product is paired properly with the raw material size group.
There are other variables not mentioned that impact the ability to achieve more consistent
results at this process because the constraints are raw material shape, customer specifications,
and equipment condition or settings. By improving the control and consistency of this
equipment we can focus efforts to improve the yield at this location.
The second process cuts the peel off the vegetables. A prior study noted that the actual
loss was approximately twice as much as intended for the removal of peel. This was verified
with a more recent study that, by weight, the slitter blade should remove between five and eight
percent of the initial raw material. Actual line performance of this process removed between
eight and fourteen percent of the initial raw material.
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The shape of the slitter arm, slitter blade and angle at which the blade contacts the
vegetables had an effect on how much raw material was actually removed. The ideal setting is
just enough to get the peel off the vegetable which is about 2 millimeters (.09375 inches) deep.
An extension was added on one side of the slitter arm that prevented the vegetables from being
scored on the wrong side by the blade. Due to the shape of the raw material, the slitter blade
would continue to cut the prior end cut sides of the vegetable. This was the solution for the
problem of cutting more than the intended amount off of the raw material during the peeling
process. The process change accounted for a 1% increase in overall raw material yield. This
was not the whole opportunity at this process due to the variability of the end cutter and the
impacts of settings.
Geometric Yield
Theoretical yield can be quantified by using geometry calculations and bench top studies
by means of cutting the raw material by hand. The raw material diameters that were used in the
calculations were: 3, 3.25, 3.5, 3.75, 4, 4.25, 4.5, and 4.75 inches. The shape was assumed to be
a sphere for the geometric yield but for the bench top yield shape was categorized as shown in
Tale 4.2 below. The three categories for the bench top yield testing were: spherical, elongated,
and short.
The bench top total average yield was 56.5% which is a very good goal for obtainable
yield. Considering the current actual performance of 46%, the gap or the opportunity to improve
RMU is by 10.5%. While the geometric yield resulted in 80%, this would not be a good
obtainable goal because the assumption of unknown saleable material is too great. It assumed all
material on the inside of the vegetable is saleable but in reality there are some inedible parts that
the geometric calculations could not quantify because of how this vegetable grows. The more
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realistic goal is the bench top yield result and not the geometric calculations that assume too
much. There are no known metrics for how much the internal quality of the vegetable affects
overall process ability and therefore yield.
The bench top testing highlighted one type that resulted in lower average yield.
Elongated raw materials yield lower because of the extra needed to get cut off. These only
represent about 4% of the total raw material and currently cannot be sorted out or otherwise
eliminated from the source.
Table 4.2 Comparison of Bench Top, Geometric and Actual Yields
Group Average Yield Range of Yield
Bench top - Spherical 57% 50.5 – 63%
Bench top - Elongated 54.5% 51 – 57%
Bench top - Short 58% 51 – 66.5%
Bench top Total 56.5% 50.5 – 66.5%
Geometric Calculations 80% 71 – 86%
Initial Actual 42% 32 – 48%
Current Actual 46% 34 – 52%
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Chapter V: Discussion
There are three main approaches to improving yield in a food manufacturing
environment: the raw material sizing, processing equipment capabilities, and the finished product
specifications. This research focused efforts into raw material sizing and process equipment
capabilities to improve the gap between theoretical and actual raw material yield. There will
always be room for improvement as capabilities improve and technology to achieve new ideas
advances. To achieve theoretical yield the company would need an extreme amount of manual
labor. The costs of the manual labor would far outweigh the benefit of maximized yield for this
raw material. Due to the lack of specific raw material research, no information was found out to
be new or contradictory to prior studies. It was found out however that other industries
regarding grown raw material have the same needs and concerns about maximizing yield.
Conclusions
Raw material sizing was adjusted to better fit the customer driven specification of piece
count with a 3% average increase in yield. The slitter arm part adjustment increased yield by
1%. A total improvement of 4% was realized for the system. There is a realistic yield gap
between bench top yield and current actual yield of 10.5%.
Recommendations
First, sustain the slitter arm modification cost savings and reassess the current sizing
adherence to what is ordered. Then, advance sizing by reducing the limitations of the current
sizing system. Currently the sizing is only correlated to the raw material diameter. The future
sizing needs to consider the height as well as the diameter to allow the equipment to maximize
its efficiency. This overall size will also be the key to maximizing the raw material sizing to its
current form’s extent without breaching into genetics. Same procedure is recommended to start
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research to determine the yield improvements to justify the resource expenditure for additional
sizing equipment.
Then it is recommended to perform line testing by hand sizing for raw material height.
This new sizing will increase utilization while maintaining the current required customer
specifications. Predicted increase is 5% or half of what the gap is because the raw material
sizing is only a part of what needs to be focused on to achieve the full opportunity.
