final proyect'operations managment

8/18/2019 Final Proyect'operations managment

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QUALITY LEADERSHIP UNIVERSITYUNIVERSITY OF LOUISVILLE - PANAMA

MASTER IN ENGINEERING MANAGEMENT

EM 613OPERATIONS MANAGEMENT

GROUP PROYECT

“OPTIM I ZATION OF HAM PRODUCTION PROCESS

IN PROCESSED MEAT I NDUSTRY

ALIMENTOS CÁRNICOS DE PANAMÁ S.A.”

MEMBERS:CRUZ, ESTEFANÍA Id. 8-831-2043

CRUZ, JOSÉ Id. 8-785-79CHANIS, NICOLE Id. 8-837-172.

PALMA, MANUEL Id. 8-845-2054IBAÑEZ, ROBERTO Id. PE-11-1044

PROFESSOR:JOHN S. USHER, PhD, PE

JUNE 19, 2015.


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INDEX

INTRODUCTION ............................................................................................................................... 3

ALIMENTOS CÁRNICOS DE PANAMÁ S.A. ................................................................................ 3

Processed Meat Business within Grupo Nutresa ................................................................................. 3

Alimentos Cárnicos de Panamá S.A. .................................................................................................. 3

Goals: Process Optimization ............................................................................................................... 3

PROJECT OBJECTIVES ................................................................................................................... 4

General Objectives: ............................................................................................................................. 4

Specific Objectives: ............................................................................................................................ 4

PROJECT JUSTIFICATION .............................................................................................................. 5

PROCESS ANALYSIS ....................................................................................................................... 5

ACTUAL FLOWCHART OF COOKED HAM PRODUCTION PROCESS .................................... 6

ACTUAL LAYOUT AND FLOWLINES OF COOKED HAM PRODUCTION PROCESS ........... 9

PROBLEM#1: ICE MACHINE PRODUCTION PROBLEM ......................................................... 10

PROBLEM #2: EXISTING PROBLEM FROM THE COOLING CHAMBER #2 UNTIL THESLICING STAGE ............................................................................................................................. 14

HAM BARS SPECIFICATIONS: .................................................................................................... 14

HAM BARS ROTATION FROM COOLING CHAMBER #2 TO COOLING CHAMBER #3 ..... 15

BOTTLENECK PROBLEM IN COOLING CHAMBER #3 ........................................................... 15

STARVING PROBLEM IN THE SLICING PROCESS .................................................................. 18

MONITORING DATA TABLE OF COOKED HAM WEIGHT IN MAY ..................................... 20

FREQUENCY HISTORGRAM AND PROCESS OVERVIEW OF COOKED HAM WEIGHTSSAMPLING IN MAY ....................................................................................................................... 21

STAGES OF FLOWCHART WITH IMPROVEMENTS PROPOSALS AND STATISTICALCONTROL ANALYSIS ................................................................................................................... 25

IMPACTS OF THE IMPROVEMENTS PROPOSED IN THE PROCESS..................................... 27


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INTRODUCTION

ALIMENTOS CÁRNICOS DE PANAMÁ S.A.

Processed Meat Business within Grupo Nutresa

Alimentos Cárnicos de Panamá is part of the Nutresa group. Produces and commercialize processed meats such as: sausages, hams, hamburgers, mortadella, and some others. Wecount with nine production plants distributed like this: 7 in Colombia, 1 in Panama, 1 inVenezuela.

We are leaders in Colombia with 73.3 % market share, while in Panama reached 18%.

Alimentos Cárnicos de Panamá S.A.

Alimentos Cárnicos de Panamá is the merge from two businesses that already existed inPanama and group Nutresa decides to buy: Blue Ribbon and Berard. These production plantsare located in different parts in the country and have been running like this for three yearswith their own products and brands. But the meat business takes the decision to merge bothPanamanian production plants and change the name to Alimentos Cárnicos de Panamá S.A.about a year ago.

The production plant has suffered a series of changes such as:1. The Berard plant moved its equipment and products to the Blue Ribbon plant so there

was an operational merge.2. Products with low sale were eliminated from the production.3. The focus was given to high sale products in the Panamanian market.

The Panamanian processed meat plant have 4 lines of fixed production in the market and oneline of special products:1. Sausages2. Hams (cooked and smoked)3. Bars (mortadella and salami)4. Special Products (for Christmas and new years).

The leading brands are BLUE RIBBON and BERARD, but also Alimentos Cárnicos S.A.represents HORMEL and ARMOUR in Panama.

Goals: Process Optimization


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The processed meat plant from Panama give report to the lowest earnings in the processedmeat business, partly affected of all the changes it has suffered. In the meantime, there is process and equipment restructure in the plant to optimize the profitability of the business.

The product line with the most economic loss for the business in Panama is the cooked ham

because of the variability in the process.

PROJECT OBJECTIVES

General Objectives:

1. Optimize ham production using operations management techniques.

Specific Objectives:

2.

Identify the principal problems in ham production.

3.

Propose improvements in ham production that reduce variation and improve thequality of the end product.

4.

Evaluate the impact of the improvements proposed in ham production process.


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PROJECT JUSTIFICATION

With respect to the following graphic, we can visualize why the main interest is the product

line of sliced cooked hams, which represents the most reprocess. Inside of this line of slicedcooked hams we choose the one with the most production, which is Blue Ribbon cookedham.

Graphic #1:

Tendency

of reprocess per product line of production.

PROCESS ANALYSIS

The first step was to study the chosen production process. Then, after studying it, the principal causes that may cause variation in the several stages were determined. After this,the operational standard of the process in the production of a sliced ham was analyzed withthe objective of comparing what the parameters of the process versus the operational realityindicate us.

In the next pages we will start with the flow of the process and the explanation of the problems.

0

500

1000

1500

2000

2500

3000

3500

4000

jamon Chorizo Salchichas Barras

3508

1440

1132

294

Análisis de Kg Reprocesos por linea


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ACTUAL FLOWCHART OF COOKED HAM PRODUCTION PROCESS

DRY STORAGEINGREDIENTS

DOSAGE

COLD MEATSTORAGE

DOSAGE

BRINE

PREPARATION MILLING

MIXED

REST OF THE

MIXED

INLAY


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THERMAL

PROCESS:

COOLING #1

UNMOLDING

COOLING #2

COOLING #3


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SLICING

PACKING

FINISHED

PRODUCT

TRANSPORT TO

THE SALE PLACE


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ACTUAL LAYOUT AND FLOWLINES OF COOKED HAM PRODUCTION PROCESS

Figure #1: Plan view of areas of cooked ham process production


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PROBLEM#1: ICE MACHINE PRODUCTION PROBLEM

The ham production consists of a mixture of certain ingredients that have to be measured forthe product to have the correct consistency; these ingredients have to be available for the

process to go on smoothly. The studied ham is the BR Cooked ham it is produced daily andits mixture is composed of 2376 kg of several ingredients (1169 meats, 500 water, 400 of ice,318 dry ingredients) as seen in table n. Every day there are at least 3 different types of hamsthat have to be made and sometimes the ice machine can´t go on with the needed production,so the lack of ice introduce variation in the process.

Type of Ham Condiments (Kg) Water (L) Ice (kg) Total Mixture (kg)

A 60,25 283 157 500,25B 253,26 380 315 948,26C 13,31 22 39 74,31

D 135,3 200 157 492,3F 154,74 305 315 774,74G 31,39 55 50 136,39H 210,3 350 315 875,3

BR Cooked Ham 543,6 500 400 1443,6

J 182,81 229 200 611,81K 17,41 157 40,6 215,01L 73,56 599,4 235 907,96M 68,43 604,9 235 908,33 N 18,48 55 30 103,48

O 90 585 235 910P 90 585 235 910Q 206,3 350 315 871,3R 923,56 539 235 1757,56S 11,35 121,6 60 192,95T 31,39 65 40 136,39

Table #1 - Ingredients needed per ham type.

This is a problem that has to be solved because the lack of an ingredient so common like icecannot be the cause for stopping the ham production and this is what has been happening.The actual ice machine has an approximate capacity of 90 kg of ice per hour and the ordersof ice are made twice a week. Each order consists of 200 bags of ice that cost $2.75 if icecube-shaped and $3.75 if flake ice. If the bag bought is of cube ice, then the production lags because of the ice grinding. If the company buys an ice cube bag and has to use workers togrind ice, this is a capacity loss in the overall work; also there is $1100 per week to pay forordering the bags of ice. On the other side if the company buys flake ice bags they don’t have

to grind but will have to pay an extra $1.00 that turns into $400 per week in regard to the ice


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cube bag. There is no increase in the process efficiency as the company is paying $1500 forsomething that they could produce in the plant.The proposed solution is to increase the capacity and reliability of the ice producing systemadding another ice machine with more or the same capacity in parallel to add redundancy to

the system. As we know in reliability analysis if there is only one component in the systemand this component fails, then there is no backup for the system to continue working. In ourcase if the existing ice machine is out, the needed ice orders increase to approximately 5orders per week giving us a payment per week of $3750. So if we add another ice machineto the system, now it has a backup in case an ice machine is damaged, since the other onecan do the job and by doing these ice orders can be fixed at the current value. If we make asummary of the previous analysis we can study the requirement or not requirement of a newice machine in terms of reliability, we can divide the decision in two scenarios, one with thefailure of a unique ice machine (Scenario #1) and other with the failure of one of the two icemachines available (Scenario #2). This is shown in the following table:

Scenario Machines Bags to orderper week

Price of Ice BagsOrdering

Total Capacity of theSystem per hour

1 1 1000 $3750 90 kg / hour

2 2 400 $1500 180 kg / hour (at least)

Table #2 – Scenarios for the failure of an ice machine

With the previous analysis we can conclude that with two machines there is no increase inice orders because if a machine is out the other one does the job partially as the current system

(two orders of ice per week). Now if we analyze the system in terms of capacity it can bemodeled the following way:

=

=

If we calculate the actual ice requirements per week assuming the machine works 15 hoursfrom Monday to Friday and 6 hours on Saturdays there are:Current ice machine: 90kg/hour*[(5*15 h) + (6h)] = 7290 kg/weekBags of ice: 400 bags/week*(20kg) = 8000 kg/weekTotal ice required per week = 7290 + 8000 = 15290 kg /week

Then the machines needed to avoid ice bags ordering are:

=15290 /

7290 /= 2.10 ℎ


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We actually need 3 ice machines of the actual capacity or one of more capacity in additionthe existent to avoid ice bags ordering, so we have to look for a machine with a capacity toadd the 8000 kg/week needed to avoid ice bags ordering and for increasing the reliability ofthe system.

We investigated in the market how much a flake ice machine that can produce at least 90kg/hour can cost, and we found that there are no commercial machines that can produce 90kg/hour of flaked ice, so we searched for a bigger machine and found a machine that can produce 104 kg/hour which specs are shown in figure n.

Machine Specifications

Max. production/24hrs 2500 kg

Production/81hrs (week) 8437.5 kg

Weight 390 kg

Power Consumption 7.4 KWh/100 kg

Figure #2 – Proposed ice machine

The approximate cost of the machine is $23600.00, based on this we can study the

profitability of adding a new ice machine. We need two ice machines to produce 15290kg/week, but we need to know how profitable it is to add another ice machine instead ofordering 200 ice bags two times per week. If we assume that the cost of operation of themachine is given by its energy consumption, if it produces the needed 8000 kg/week, wehave then:

= 7.4 ℎ ∗8000 /

100 = 592 ℎ

By knowing the energy consumption per week we can formulate the “machine cost” as: = ∗ +

Where:MC: Machine costW: WeeksEC: Energy consumption (EC = 592 * cost per KWh)Ii: Initial investment ($23600.00)


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To start the calculation we can assume the cost of the energy is negligible and make MC= Ii, under this assumption the recovery of the initial investment is made in:

=

$1500/

=$23600

$1500

= 15.73

Where:RT: Investment recovery time in weeks

If we now assume a initial value of W = 15.73 weeks and use a cost per KWh of0.19217 cents/KWh we can find the investment recovery time by using a numerical solutionas shown in the next table:

Table #3 - Numerical solution for the investment recovery time

From the table above we see that the initial investment is recovered in almost 4 months and

from there on there is a saving of:

Weekly ice bag ordering price = $1500.00Machine Energy Consumption = $113.76Saving = $1386.24

RT1 15.73

W*EC 1789.90

MC 25389.90

RT2-RT1 1.19

RT2 16.93

W*EC 1925.65

MC 25525.65

RT3-RT2 0.090500884

RT3 17.0171

W*EC 1935.94

MC 25535.94

RT4-RT3 0.006863867

RT4 17.0240

W*EC 1936.72

MC 25536.72

RT5-RT4 0.000520577

RT5 17.0245

W*EC 1936.78

MC 25536.78

RT6-RT5 3.94822E-05

RT6 17.0245


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If we multiply the obtained value by 12 months, per year there will be a saving of$16634.88, then we can conclude that adding a new ice machine increase the reliability,capacity and saves the company $16634.88 per year.PROBLEM #2: EXISTING PROBLEM FROM THE COOLING CHAMBER #2 UNTIL THESLICING STAGE

HAM BARS SPECIFICATIONS:

The ham bars have weight and length parameters that are controlled in the inlaying stage. Inthis part of the process every 20 minutes 5 ham bars are sampled to make sure that the inlaymachine do not have any deviations and the portion of the ham paste be of 10.5 kg for every100 cm.

Figure #3: Weight control and size of

the ham bars..


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HAM BARS ROTATION FROM COOLING CHAMBER #2 TO COOLING CHAMBER #3

DAILY PRODUCTION DEMAND

Reference Daily use of barsQuantity of daily

packages

113.5 grams 33 bars 3,000 packages

227 grams 33 bars 3,000 packages

454 grams 22 bars 500 packages

Table #4: Daily Production Demand (Hams Bars).

Taking into account that the diary demand for the reference of 227 grams is constant, thiscalculated ham bars that should be transported from the cooling chamber #2 to coolingchamber #3.

In this stage of the process the sequence FCFS (First Come First Serve) will be chosen forthe dispatch of the ham bars because they should be rotated in inventories with respect totheir dates of entry to the cooling chamber #2.

Example: If we need 3,000 packages of 227 g and each bar weights 10.5 kg, how many

theoretical bars are necessary to cover this demand?

This data is theoretical because in reality there is assigned 33 ± 3 additional ham bars to coverthe quantity of the nonconforming product of reference 227 g.

BOTTLENECK PROBLEM IN COOLING CHAMBER #3

The cooling chamber #3 was a new acquisition from the company with the goal of fixing the process in the ham product line. But the proposed solution did not fix the problem at a 100% because the required study for it was not done before it was purchased.

The first ham bars to enter cooling chamber #3 correspond to all the references of 113.5 g,later the reference of 227 g, and finally the reference of 454 g.

(3,000 packages)(0.227kg)/10.5 kg

We Need = 33 Ham bars aprox.


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Next, we will explain the following problem: To start the production process of the 227 g packages we need 198 bars to cover the production demand. The total capacity of the coolingchamber #3 is 100 bars, so the needed bars exceed the chamber capacity in almost 50%. Thiscapacity is not enough, thus not being able to store in the cooling chamber all bars to fulfill

production.The cooling chamber #1 have the function of intensive cooling and is programmed for rangesof temperatures of -15°C to -18°C for storage carts. The cooling chamber #2 have thefunction of cooled storage and is where the arrival and rotation of the ham bars occur. At lastthe cooling chamber #3 is the chamber specialized to get the right slicing stage and its rangegoes from -8°C to -6°C. The cooling chamber #3 is the bottleneck of the process because it’ssmaller than the other two cooling chambers this causes a deviation from the process that canturn into defects. We can use the following flowchart to describe the existent coolingprocess:

Figure #4 – Ham Cooling System Arrangement

From the information above we can analyze the current problem in the cooling chamber

#3. The cooling chamber #3 can’t handle the same WIP as the other two cooling chambers,

this cause some extra time to get in the overall time in the process since the total time for

the cooling process to finish is Ttotal = TC#1+TC#2+TC#3. In addition the cooling chamber#3 TR will not be the same from cooling chamber #2 and #1, since it will be lower this will

cause the process to lag in this stage and this could cause that some hams with a lower

freezing point could get extremely frozen causing defects in the cutting process and in the

same way a ham that needs more time in the cooler could be softer than the optimal

consistency and cause defects in the cutting process. Since you have a need of capacity and

a way to control the ham temperature since not all the hams that are put in the coolers

Cooling Chamber#1

WIP#1

TR#1

TC#1

Cooling Chamber #2

WIP#1

TR#2

TC#2

Cooling Chamber

#3

WIP#3

TR#3


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have the same freezing points and will not reach the desired temperature at the same time.

A solution for both problems is adding a new cooling chamber that can handle the other

part of the production that comes from cooling chamber #1 and #2 and by doing this they

will have the flexibility to divide hams by freezing point and they will be more likely to reach

the desired temperature at the desired time and reduce any further cutting defects. Thenew arrangement would be as follows:

Figure #5 – New Ham Cooling System Arrangement

By doing this upgrades we can reduce the variation in the process since the hams will be

frozen in groups by freezing point in cooling chamber #3 or cooling chamber #4 reducing

the variation in the desired temperature and reducing the defects in cut and decrease

reprocessing. The total time of the process will be reduced too since by making two parallel

processes (cooling in cooling chamber #3 and #4) there will be two parallel batches to cool,

so when both cooling chambers are done all the production that entered will be coming out

of the cooling process hopefully at the desired temperature.

Cooling Chamber

#1

WIP#1

TR#1

TC#2

Cooling Chamber #2

WIP#2

TR#2

TC#2

Cooling Chamber #3

WIP#3

TR#3

TC#3

Cooling Chamber #4

WIP#4

TR#4

TC#4


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STARVING PROBLEM IN THE SLICING PROCESS

In this stage of the process several critical variables such as time, temperature and themachine parameters are handled for each reference. The slicing velocity, number of slicesand thickness of the slices are verified in this stage.

Slicing

This process depends on cooling chamber #3,which in many occasions do not poses thecapacity to deliver the necessary quantity ofham bars at the right temperature in the requiredtime. The variation in these parameters is notoptimal for the slicing process.

Given this situation the production staff, due tothe internal demand, tries to fulfill their production programing even if the conditionsare not optimal.

Results when forcing the process:

1. Product losses

2.

Overweight in final product

Slicing Process

Involves 8 activities that are:

1. Start of the slicing process

2. Find and bring bar from cooling

chamber3. Temperature measurement

4. Peel the bar

5.

Feed Treif = 3 bars

6.

Treif machine

7.

Advance and fixing

8. End of slicing process


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Reprocess in the ham product line: is the total quantity of hams in kilograms obtained dailyin a work day that can not get to the packaging stage because it is considered a nonconforming product due to a deviation from the process or due to a quality aspect.

Currently reprocess is established due to two aspects:

1. Tip cuts: The machine have a system in which a claw exerts pressure in the upper andlower tip of the ham bar, so for every three bars that feeds the machine there is 6 tipsin the loss of product and depending in the texture of the ham it will be the portion ofthe tip. When the ham bars are too soft they are cut in half because they are fragileand break, and when they do this there is double product loss. Instead of 6 there is 12tips that go to waste for every 3 ham bars

2.

Bad cuts in the slicing machine: the parameters of the slicing machine - which are:slicing velocity, number of slices, and weight for each slice - are directly associatedwith the weight and the bad cuts because if the temperature is very high the ham barsare very soft and we get many slices with bad cuts and if we lower the velocity theslices get out thicker thus increasing the weight of the final product. The final producthas a cost per weight of $ 2.40/kg.


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MONITORING DATA TABLE OF COOKED HAM WEIGHT IN MAY

PRODUCT GRAMS (g)

NET WEIGHT 227PACKING WEIGHT 2

LABEL WEIGHT 6TOTAL WEIGHT 235

PK1 PK2 PK3 PK4 PK5 PK1 PK2 PK3 PK4 PK5 PK1 PK2 PK3 PK4 PK5 PK1 PK2 PK3 PK4 PK5

5/2/15 237 241 238 239 239 238.8 4.0 238 238 238 239 238 238.2 1.0 241 237 238 237 238 238.2 4.0 239 239 237 238 238 238.2 2.0 238.4

5/4/15 237 238 239 238 238 238.0 2.0 238 238 238 239 238 238.2 1.0 239 241 239 237 237 238.6 4.0 239 237 238 238 239 238.2 2.0 238.3

5/5/15 238 238 238 237 239 238.0 2.0 238 238 237 238 238 237.8 1.0 238 237 238 239 238 238.0 2.0 233 238 238 239 239 237.4 6.0 237.8

5/6/15 236 232 237 237 232 234.8 5.0 231 233 235 236 233 233.6 5.0 232 235 233 234 234 233.6 3.0 232 235 233 235 234 233.8 3.0 234.0

5/8/15 237 238 237 239 239 238.0 2.0 238 238 234 239 238 237.4 5.0 238 233 238 239 238 237.2 6.0 237 239 233 238 239 237.2 6.0 237.5

5/9/15 238 237 241 241 237 238.8 4.0 239 238 239 238 239 238.6 1.0 237 239 239 238 237 238.0 2.0 235 237 241 237 239 237.8 6.0 238.3

5/11/15 241 239 239 239 238 239.2 3.0 238 239 239 239 239 238.8 1.0 238 239 238 239 240 238.8 2.0 238 238 238 241 239 238.8 3.0 238.9

5/12/15 235 236 235 240 235 236.2 5.0 240 238 239 240 239 239.2 2.0 238 238 238 238 239 238.2 1.0 239 238 238 240 238 238.6 2.0 238.1

5/13/15 234 237 234 240 237 236.4 6.0 239 239 234 234 239 237.0 5.0 237 239 239 234 235 236.8 5.0 237 240 241 237 234 237.8 7.0 237.0

5/14/15 239 239 234 234 240 237.2 6.0 239 234 239 237 239 237.6 5.0 234 239 240 234 239 237.2 6.0 234 237 239 241 234 237.0 7.0 237.3

5/15/15 239 239 234 234 234 236.0 5.0 234 239 234 236 234 235.4 5.0 236 232 235 235 235 234.6 4.0 239 240 234 237 236 237.2 6.0 235.8

5/16/15 240 238 238 240 240 239.2 2.0 238 238 238 240 238 238.4 2.0 241 238 236 240 238 238.6 5.0 238 240 243 238 238 239.4 5.0 238.9

5/18/15 240 238 243 239 240 240.0 5.0 241 239 239 240 240 239.8 2.0 243 241 237 238 236 239.0 7.0 238 240 238 238 238 238.4 2.0 239.3

5/19/15 238 240 240 240 240 239.6 2.0 237 238 241 241 238 239.0 4.0 241 237 239 241 238 239.2 4.0 237 237 236 239 240 237.8 4.0 238.9

5/20/15 236 236 236 237 239 236.8 3.0 238 240 241 240 240 239.8 3.0 241 236 237 241 236 238.2 5.0 235 235 241 238 235 236.8 6.0 237.9

5/21/15 235 236 236 236 235 235.6 1.0 238 236 237 240 237 237.6 4.0 238 240 239 235 236 237.6 5.0 235 236 235 236 235 235.4 1.0 236.6

5/22/15 235 238 237 238 239 237.4 4.0 235 236 236 235 235 235.4 1.0 241 238 236 240 237 238.4 5.0 236 239 237 243 241 239.2 7.0 237.6

5/23/15 240 239 240 238 237 238.8 3.0 241 240 240 237 237 239.0 4.0 238 237 238 240 237 238.0 3.0 237 238 236 239 240 238.0 4.0 238.5

5/25/15 240 237 237 240 240 238.8 3.0 237 240 240 241 240 239.6 4.0 237 240 240 238 240 239.0 3.0 239 240 241 240 237 239.4 4.0 239.2

5/26/15 238 235 235 235 236 235.8 3.0 237 239 238 240 236 238.0 4.0 237 240 238 235 237 237.4 5.0 235 236 235 238 237 236.2 3.0 236.9

5/27/15 240 240 241 242 239 240.4 3.0 238 240 242 242 240 240.4 4.0 239 241 241 240 238 239.8 3.0 242 240 241 241 239 240.6 3.0 240.3

5/28/15 240 242 244 241 243 242.0 4.0 239 242 243 238 240 240.4 5.0 245 240 247 240 242 242.8 7.0 246 242 240 242 242 242.4 6.0 241.9 5/29/15 237 236 239 238 236 237.2 3.0 238 237 236 236 235 236.4 3.0 238 237 237 239 236 237.4 3.0 240 239 242 244 238 240.6 6.0 237.9

5/30/15 243 241 244 242 247 243.4 6.0 244 242 247 245 241 243.8 6.0 245 241 242 247 242 243.4 6.0 240 242 240 246 245 242.6 6.0 243.3

238.3

SLICED COOKED HAM BLUE RIBBON - WEIGHT 227 g

Product Final - Weights Monitoring in May - Grams ( g )

DATE \ PKG

SAMPLING 1 SAMPLING 2 SAMPLING 3 SAMPLING 4

LOWER SPECIFICATIONLIMIT (LSL)

234

UPPER SPECIFICATIONLIMIT (USL)

242


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FREQUENCY HISTORGRAM AND PROCESS OVERVIEW OF COOKED HAM WEIGHTSSAMPLING IN MAY

Graphic #2 – Frequency Histogram

Graphic #3 – Process Overview based on Frequency HistogramBy plotting the sampling data of cooked ham for the month of May based on table n we cansee if the process is inside or outside the specification limits, how large is the area below the

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0

20

40

60

80

100

120

230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250

F R E Q U E N C Y

WEIGHT (G)

Process Overview

Frequency

Probability

LSL USL


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curve that define possible defects in the final product (low weight or overweight) and if thisis happening, identify what can be happening in the previous stages that causes this defectsin the final product.

Graphic #4 – X-Bar Chart for cooked ham sampling data in the month of May.

From the information obtained by analyzing the histogram we can say for sure that there arequality controls that not are being followed that are causing defects in the final product andvariation in the overall process. By implementing control charts using data from samplingsin the final product we can obtain information about the process and see if it is inside thespecified control limits. If we analyze the control chart from figure n we can obtain someinformation like:

1. The production from the May 6th labeled as the sample #4 is out of lower controllimit, telling us that some ham packages from the production could have gone out

without the required weight.2. The production from May 30th and May 28th labeled as sample #24 and #22 are outof the upper control limit, telling us that some packages from the production couldhave gone out with overweight which represents looses for the company.


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With the information obtained from our x-bar chart, the company can see how the process isgoing and try to correct any problem in a previous stage of the process that is causingvariation and defects in the final production.In addition to the X-bar chart we have to make an R-bar chart as the one shown in figure n:

Graphic #5 – R-Bar Chart for cooked ham sampling data in the month of May.

If we analyze the R-bar chart from figure n after analyzing the X-bar chart from figure n wecan obtain information about variation in the process. Some of this information is:

1. If we look for sample #4 in the R-bar chart we can see that the variation in sample #4is not as great as we could think by analyzing the X-bar chart since the mean range between the larger weight sample and the lower weight sample is at 4 g. We can saythat the production of that day had values near the lower control limit and at some point those values were below the lower control limits, this caused a decrease in the

mean as we saw in the X-bar chart.2. On the other side on samples #22 and #24 the mean range is at 5.5 – 6.0 g on average,what is somewhat closer to the upper control limit. So this value can give us an alarmthat probably there were some packages from the production that could have gone outwith overweight

ALTERNATIVE TO IMPROVE THE COOLING PROCESS


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Further we investigate a found an ideal solution that will be to get a cooling spiral systeminstead of three cooling chambers that have very limited capacity. The cooling spiral will beautomated with a moving conveyor belt instead of manually moving the carts containing the

ham from one cooling chamber to another one. Thus reducing time within the system. Thecooling spiral works as a buffer storage between the oven and the slicing and packaging. Therotation speed of the conveyor belt is kept at constant speed (it can be adjusted) according tothe cooling time required in order to keep the product between the oven and slicing as evenas possible. Temperature control is controlled through the provided PLC controller. The inputof this data is provided through the use of multiple RTD sensors and programmablecontroller. The RTD sensors or resistance temperature detectors are used to measure thetemperature by associating the resistance of the RTD element with temperature. The RTDelement is usually made from a pure material such as nickel, copper or platinum and thiselement has a predictable change in resistance as the temperature varies. This predictable

change is used to determine the temperature of the product we are interested in.

Figure # 6: Cooling

Spiral Machine


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STAGES OF FLOWCHART WITH IMPROVEMENTS PROPOSALS AND STATISTICALCONTROL ANALYSIS

DRY STORAGEINGREDIENTS

DOSAGE

COLD MEATSTORAGE

DOSAGE

BRINE

PREPARATION MILLING

MIXED

REST OF THEMIXED

INLAY

THERMAL

PROCESS

NEW ICE

MACHINE


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COOLING #1

UNMOLDING

COOLING #2

COOLING #3

SLICING

PACKING

TRANSPORT TO THE

SALE PLACE

ADITIONAL

COOLING CHAMBERWITH MORE

CAPACITY

PACKING

FINISHED PRODUCT

STORAGE

ADD STATISTICAL

CONTROL OF

PRODUCTION LOSSESWEIGTH

STATISTICAL

ANALYSIS WITH

LOWER AND UPPERCONTROL LIMITS


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IMPACTS OF THE IMPROVEMENTS PROPOSED IN THE PROCESS

Acquisition of a new ice machine:

Having an ice machine would represent continuity in the process since they would reduce oreliminate wait times by shortages and would generate significant savings by eliminating thefrequent purchase of bags of ice to the supplier.

Acquisition of a new cooling chamber and better controls in Statistical Process:

A remarkable problematic at this production plant is the variation and lack of control in thetexture of the ham bars; But if they quantify the losses that causes them to have a reducedcapacity in the cooling chamber # 3 and condition the size based on demand, they wouldachieve:

1.

Decrease in losses at the stage of slicing and the reduction would be almost 50 % ofthe current, which would help achieve the goal of less rework.

2. The need to modify the slicing parameters is reduced, and linked to this, the presenceof the line overweight’s hams have significant decreases.

3.

To acquire and expand the cooling # 3 the bottleneck at this stage and slicing barstage would be eliminated, thus speeding the process continuity. This bottleneck isalso the cause of starving at the stage of slicing and packaging.

4. With these improvements would be optimized processing times and might evenincrease the current manufacturing capacity, obtaining as much final product.

5.

With statistical controls we recommend are reinforced, it is possible to identifyimportant variations in the process and to seek the causes for their prompt correction.

6. Product quality also would benefit being as pack the product to the right temperaturerange allows the lifetime is reached and market returns would decrease greatly.

final proyect'operations managment

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