FINAL REPORT (DRAFT) 2

Concordia University
Supply Chain Project (SCOM 498), Section AA
Fall 2014
Presented to Professor Satyaveer S. Chauhan
Prepared by:
Denis Noskov - 6308759
Stephanie Ghaly - 5975549
Maria Luisa De Ocampo - 9420274
Tarek Al Kayyali - 5973619
Juliane Fortin-Latreille – 6281680
December 8th, 2014
Monthly Production Plan for Mining Rope

ABSTRACT
The purpose of the project is to create a monthly production plan for Wire
Rope. The current production plan is highly unreliable because of the ambiguity of
the implemented formula and its reliance on constant manual inputs and
modifications. The reason behind the current production plan’s unreliability is due to
the fact that the annual forecast allocation is simply divided by 12 in order to find the
monthly forecast. When dealing with a product line with consistent demand, this
method might be successful to a certain extent. When dealing with a product such as
the dragline, the demand is highly volatile and very inconsistent especially when
customers would only order once to three times a year. That being said, the dragline
is the product that was used to develop the new production plan. The objective is to
develop a production plan that would be more reliable and applicable to all products
manufactured by Wire Rope Industries, regardless of their demand volatility and
order frequency. Thus, the objective is to develop a fully automated production-
scheduling tool that is to be used by Wire Rope. The decision tool will take into
consideration several constraints such as the minimum production quantity and
ordering periods for the different set, the report will generate various requirements
that will all translate into a general production plan for the parent rope.

EXECUTIVE SUMMARY
Wire Rope Industries had a need to actualize their current production
schedule for the rope code 1293000. The need is due to the fact that the current
production schedule does not take into consideration sales history, which gives an
opportunity to develop a more accurate production schedule.
The latter was produced by creating a reusable tool where the demand
planner can either use the provided suggested forecast or ignore it and provide his
own forecast. The provided suggested forecast is based on a series of formulas that
takes into account sales history, which provides a good insight on future demand.
The tool also provides an output where the amount to be produced monthly is
clearly stated and where adjustments are still possible.
The new and current production schedule were then tested in order to
determine which one provided more advantages for Wire Rope Industries. By using
the Rockwell Arena Software, many simulations were run using different scenarios in
order to compare both production schedules. The analysis shows that the new
production schedule performs better in terms of higher demand filled, lower stock-
out probability and lower backorder levels.
In the next few years, Wire Rope Industries should look into implementing a
mean absolute percent error tool in order to obtain an even better forecast .They
should consider using the costs linked to production when creating a new
production schedule or simply adding them as constraints.

TABLE OF CONTENTS
ABSTRACT ...................................................................................................................................2
EXECUTIVE SUMMARY ............................................................................................................3
LIST OF TABLES..........................................................................................................................5
LIST OF FIGURES........................................................................................................................5
1.0 BACKGROUND INFORMATION...................................................................................6
1.1 PRODUCTION PROCESS.............................................................................................6
2.0 INTRODUCTION & PROJECT DESCRIPTION...........................................................7
2.1 PURPOSE............................................................................................................................8
2.2 PROJECT GOALS & OBJECTIVES....................................................................................9
3.0 DATA COLLECTION .......................................................................................................10
3.1 QUANTITATIVE ............................................................................................................10
4.0 METHODOLOGY..............................................................................................................11
4.1 FORECASTING ..............................................................................................................11
4.2 PRODUCTION SCHEDULE.......................................................................................11
6.0 ANALYSIS OF RESULTS...................................................................................................12
6.1 CURRENT MODEL VS. NEW MODEL....................................................................12
6.2 CONCLUSION...............................................................................................................15
7.0 FINAL PRODUCT..............................................................................................................16
7.1 SHEET A: RAW DATA.................................................................................................16
7.2 SHEET B: FORCAST ALLOCATION........................................................................16
7.2.1 SECTION A .............................................................................................................16
7.2.2 SECTION B..............................................................................................................18
7.2.3 SECTION C .............................................................................................................19
7.2.3 SECTION D.............................................................................................................21
7.2.4 SECTION E..............................................................................................................22
7.2.4 SECTION F ..............................................................................................................23
7.3 SHEET C: PRODUCTION SCHEDULE....................................................................24
7.4 USEFULNESS OF TOOL ..............................................................................................26
8.0 CONCLUSION...................................................................................................................27
9.0 RECOMMENDATIONS ....................................................................................................27
10.0 REFERENCES.....................................................................................................................29
11.0 APPENDICES.....................................................................................................................30
11.1 APPENDIX 1: FINAL PRODUCT ............................................................................30
11.2 APPENDIX 2: PROJECT TIMELINE/SCHEDULE .................................................31
11.2 PROJECT TASK LIST ..................................................................................................33
11.3 RESOURCES..................................................................................................................35
11.4 MINUTES .......................................................................................................................36
11.5 LEARNING EXPERIENCE..........................................................................................68

LIST OF TABLES
Table 1: ProductionRun Input Values....................................................................................12
Table 2: vOnHand Input Values..............................................................................................12
Table 3: Different Scenarios ....................................................................................................13
Table 4: Current Model Scenario’s Result ...........................................................................14
Table 5: New Model Scenario’s Result .................................................................................14
Table 6: Comparison of Results..............................................................................................15
LIST OF FIGURES
Figure 1: Forecasting Allocation Section A ..........................................................................17
Figure 2: Forecast Allocation Section B................................................................................18
Figure 3: Forecast Allocation Section C ...............................................................................20
Figure 4: Forecast Allocation Section D ...............................................................................21
Figure 5: Forecast Allocation Section E ................................................................................22
Figure 7: Forecast Allocation Section F ................................................................................23
Figure 8: Production Schedule ................................................................................................25

1.0 BACKGROUND INFORMATION
Wire Rope Industries is a manufacturer of high-performance ropes and
industrial steel cables in North America, founded in 1900s. This company provides
solutions for a wide variety of applications, including “general industrial and
construction, mining, oil, and gas, fishing and marine, forestry and utilities industries,
as well as for ski lifts, bridges, supported structures and the U.S. Navy” (Wire Rope
Industries, 2014).
1.1 PRODUCTION PROCESS
The production process of Wire Rope starts by ordering the wires and
receiving their orders. Once a certain type of rope needs to be produced, the wires
are then turned into strands. Multiple strands are then being processed and turned
into a rope. The rope gets dipped into a blue plastic coating. The rope is cut when a
customer order is placed. Each type of rope has a particular code. One type of rope
can have many assembly codes. The difference is that an assembly code is of a
different length or has an extra hook. Each difference creates a new assembly code.
The rope is placed on a coil, which is then placed under the right inventory section
in order to be docked on the right docking station. The rope is finally shipped to the
customer.

2.0 INTRODUCTION & PROJECT DESCRIPTION
The purpose of the project is to develop a monthly production plan for the
dragline segment of the company in an effort to satisfy and predict customer
requirements based on the demand forecast. By using excel, a more accurate
forecast will be improved to satisfy customer demand. Minimizing unmet demand is
prioritized more than the possibility of excess inventory. Given that they currently
have an unreliable production plan that fails to meet the demand for the clients of
the dragline code “1293000”. This unreliability is due to highly volatile demand and
inconsistent orders throughout the years. We will tackle the problem by analyzing
the demand for every rope code based on historical data in an effort to resolve the
problem with the current production plan. That being said, the production plan to
be developed will be done by applying several constraints such as seasonality and
minimum production quantity, which will generate various requirements that will all
translate into a general production plan for the parent rope.
The issue with the current production plan at Wire Rope is that it is very
inaccurate when planning the demand for the assembly codes that have a volatile
demand or when clients that do not order frequently. This is due to the fact that the
aggregate production plan for every rope code is developed by multiplying the
forecast of each assembly item by its length, thus indicating the overall rope length
required to be produced every month. The monthly forecast for every assembly
item is derived by simply dividing by its 12-month forecast. For example, if a client
only orders twice a year, the demand will be evenly spread out through the 12-
month time-period, which is highly problematic. The demand planner requested that
we work on the production plan for the draglines segment because it requires more
customization per client, whereas the shovel segment is mass produced. The
production plan for the dragline segment will need more analysis given that the
demand is less predictable than the one for the shovel rope.
Through this project, it will be necessary to generate the output of a MRP
system by reproducing a production plan for the rope “1293000”, indicating the
specific month and quantity that needs to be produced. Currently, Wire Rope

Industries uses Excel for their production planning needs and therefore not an ERP
system. That being said, the production plan that will be generated is not going to be
used as a master schedule that outlines the daily production plan of each machine in
details, but will rather be a long-term production outline. It can be used to make the
actual master schedule, manage inventory and plan for the resources such as
knowing how much raw materials to order ahead of time. Keeping in mind that the
finished goods manufactured by Wire Rope Industries are made up of various costly
materials that need to be ordered in large quantities, it is important to have a
production plan as reliable as possible, in order to place the raw materials orders
ahead of time. Since the plant cannot simply produce several months of inventory of
different ropes, a more accurate long-term production plan is needed in order to
produce new batches of rope that would satisfy customer demand before the next
production run.
2.1 PURPOSE
The purpose of the project is to develop a monthly production plan for the
dragline segment of the company in an effort to satisfy and predict customer
requirements based on the demand forecast. By using excel, and the knowledge
gained from the diverse supply chain courses, a more accurate forecast will be
improved to satisfy customer demand whilst making sure that it is within the capacity
of the facility. Minimizing unmet demand is prioritized more than the possibility of
excess inventory. The latter however is not neglected and any issues regarding
overstock will be addressed and dealt with.

2.2 PROJECT GOALS & OBJECTIVES
The main goal of this project is to improve Wire Rope’s monthly production
plan for their rope’s dragline segment. The objective is to solve how the current
production schedule can be improved by providing a decision tool. This decision
tool will be used by the demand planner to help him create a monthly production
schedule that will not only satisfy customer’s demand but will also avoid backorders,
excess inventory, and waste.

3.0 DATA COLLECTION
3.1 QUANTITATIVE
The quantitative data used for this project was given to the team by Mr. Erik
Sagoo and Mr. Andrew Patterson, as an Excel Spreadsheet. The sheet contained
general information like the type of customer and the customer number; it also
captured more detailed information relating to the assembly and the rope code and
described in detailed the specifications relating to the length and weights. The order
multiples were also given for each assembly code. It contained a total of 255 rope
codes, which translate into 129 dragline rope codes and 108 shovel rope codes, the
remanding being either dump rope or trip rope. Moreover, it included the detailed
sales history for each month in term of number of feet and units, for 2013 and 2014.
This sheet also included the warehouse number and name for each rope code.
Lastly, the data given contained the next 12 month forecast in units and in feet and
the date of the last forecast modification. All in all, the Excel spreadsheet contained a
total of 64 columns and 255 rows, which were then taken by the team and filtered
down in order to contain solely the information critical to the project. The filtered
Excel sheet contained only the information relating to the dragline rope code
1293000, which meant that the team only dealt with 10 assembly codes. Also, it
included the sales history and forecast information for each assembly code along
with the order multiples.
Both excel spreadsheet mentioned above will be provided on a CD.

4.0 METHODOLOGY
4.1 FORECASTING
4.2 PRODUCTION SCHEDULE

6.0 ANALYSIS OF RESULTS
6.1 CURRENT MODEL VS. NEW MODEL
The primary goal of this section is to compare the new production schedule
model with the current production schedule model. The objective of this analysis is
to determine which production schedule model is superior. Since monetary costs
are not provided and treated irrelevant for this report, cost benefits cannot be
measured. Thus, key performances measure will be used instead.
In order to compare the models in a simple and straightforward manner,
simulation models were created using Rockwell ARENA software. Two simulations
based models were created, one representing the current production schedule
model and the other one representing the new production schedule model. The
models are relatively similar; the only difference that can be seen is the production
input value under the variable “ProductionRUN” and beginning inventory input value
under “vOnHand”.
Both production schedule models have suggested value to be produced;
however, this value is not necessary the one that will end up getting produced. To
maintain consistency in the analysis, it is assumed that the value suggested is equal to
the actual production. Table1 shows the production value for each month in 2015
that is entered in both models, and Table 2 shows the beginning inventory for each
model.
Table 1: ProductionRun Input Values
Table 2: vOnHand Input Values

It is also assumed that whatever is
produced for this month will be used to fulfill demand for next month. Since there is
no forecast for the year 2016 and the production schedule mainly focused on 2015
forecast, there was no demand allocated for the month of January 2016, creating a
production run of equal to 0 in December (see Table 1). To avoid distortion in the
model and maintain consistency, the model will be run for only 11 months (excluding
month of December) or 330 days.
In both models, orders arrive constantly every 30 days (1month), and
production cycle is also every 30 days. Lead-time is equal to 14 days (2 weeks).
When demand arrives, if there is enough on hand inventory, demand is filled.
However, if the inventory on hand is not enough to satisfy demand, it becomes
backordered. Backorder is queued and only leaves the system once a signal is sent
that there is enough on hand and the demand can be filled.
Once the models were created, different scenarios were applied. These
scenarios are demand alternatives that compare both models on equal grounds.
By testing each model’s performance under different situations, it is possible to
identify which model is superior under a specific demand condition, as well as finding
the effect of variability in each model. Below is the list of the scenarios that are
applied in both models:
Table 3: Different Scenarios
Scenario A
 Demand distribution is derived from 2013 Sales History.
Scenario B
 Demand distribution is derived from 2014 Sales History.
Scenario C
 Demand Distribution is the average of 2013 and 2014 Sales History.
Scenario D
 Demand Distribution is equal to the mean 2015 forecast.
Scenario E
 Demand Distribution is 25% higher than forecast demand.

To apply all these scenarios to both models, Process Analyzer was used. The
different demand values were entered respectively on each month and the results
can be seen in Table 3 and 4.
Table 4: Current Model Scenario’s Result
CURRENT MODEL
SCENARIOS
Avg.
Backorder
Avg. Demand
Filled
Avg. Inventory
Level
Stock Out
Probability
A 843 10473 5479 0
B 0 6136 9816 0
C 188 8539 7413 0
D 1214 15952 0 1
E 7065 14391 1562 0
F 273 12603 3349 0
Table 5: New Model Scenario’s Result
NEW MODEL
SCENARIOS
Avg.
Backorder
Avg. Demand
Filled
Avg. Inventory
Level
Stock Out
Probability
A 655 10661 6724 0
B 0 6136 11249 0
C 80 8648 8737 0
D 1595 15571 1814 0
E 6242 15214 2171 0
F 91 12785 4600 0
The first key performance measure is Average Backorder. A lower average is
desirable as it reflects the number of demands unsatisfied during demand arrivals.
When it comes to Average Demand Filled (Fill Rate), it is desirable to have a higher
average, as it has to do with customer demand satisfaction. It is desirable to have a
lower Average Inventory level since inventory incurs holding cost. Lastly, having low
Stock Out Probability is desirable since it reflects the probability of not having

inventory on hand. Since the monthly demands arrives constantly and are based on
the different scenarios, applying a measurement for confidence interval (half-width) is
not needed.
Knowing these, we compared both models to see which option has the most
desirable key performance measure in each scenario. Table 5 shows the results in
this tally.
Table 6: Comparison of Results
KEY PERFORMANCE METRIC TALLY
SCENARIOS
Avg.
Backorder
Avg. Demand
Filled
Avg. Inventory
Level
Stock Out
Probability
A NEW NEW CURRENT -
B - - CURRENT -
C NEW NEW CURRENT -
D CURRENT CURRENT CURRENT NEW
E NEW NEW CURRENT -
F NEW NEW - -
6.2 CONCLUSION
After comparing both models, the new model had better performances than
the current model in terms of lower backorders; higher demand filled, and lowers
stock out probability. Although the current model dominated the new model when
it comes to inventory level – and inventory level is related to holding cost; therefore
we can assumed that this performance measurement can be ignored since cost is an
irrelevant concern. Also, we can see that the new model performed well in four
scenarios, which conveys that the new model is robust to demand forecast error.
Generally, since the new model follows the demand sales history, a much more
accurate suggested production schedule is produced which causes higher
performances when it comes to satisfying demand.

7.0 FINAL PRODUCT
The final product is a decision tool, which is an integration of automatic
formulas and manual inputs. When used by one with the necessary knowledge and
experience, it helps create a production schedule that will satisfy customer demand.
The tool contains automatic formulas and aggregate graphs that aid the demand
planner when forming a production schedule for the upcoming year. The decision
tool is an Excel file that contains three sheets, the raw data sheet, the forecasting
allocation sheet, and the production schedule. The raw data sheet is linked to the
forecasting allocation sheet and the forecasting allocation sheet is linked to the
production plan sheet.
7.1 SHEET A: RAW DATA
The first part of the decision tool created is the Raw Data sheet. This Excel
sheet is the one that was provided by Wire Rope Industries and that is discussed in
Data Collection section. The purpose of this data sheet is to be the basis of all
calculations that will be done in future sections of the decision tool. The suggested
forecast table is based on a formula that is based on sales history and demand trends
of 2013 and 2014. The formula takes into account the order multiples, assembly
units lengths, and minimum production runs. All the necessary calculations regarding
the forecasting allocation sheet are done in the raw data sheet. After viewing the
Raw Data sheet, the user will turn to the forecasting allocation sheet where all the
necessary analysis and adjustments are made to the forecast.
7.2 SHEET B: FORCAST ALLOCATION
The second sheet of the Final Product is called Forecast Allocation. This
sheet’s main purpose is to allocate the 2015 forecast. The final data (2015
ADJUSTED) that is produced in this sheet is what will be used to produce the data in
SHEET C: PRODUCTION SCHEDULE. This sheet is divided into six parts (See
Appendix 1 for visual). Each part has its purpose and use for the demand planner.
7.2.1 SECTION A

The main purpose of this section is to isolate the assembly code that needs
analysis. It presents the data associated with the chosen assembly code for easy
analysis and decision-making. The Forecast Allocation (Section A) is composed of 8
parts as shown in Figure 1, and below are the explanation of each part
Figure 1: Forecasting Allocation Section A
Assembly Code Drop Down Menu  This will be the first step the
demand planner will have to do when using this section of the forecast allocation. He
will have to click on the drop box in order to select the assembly code he wishes to
analyze. It contains the 10 assembly codes for the Rope Code: 1293000.
Sales History  Once the assembly code is chosen, the data associated
with that code would show up. This section shows the sales history of that code for
the year of 2013 and 2014. By providing this information to the demand planner, he
would see which months there are actual sales for that specified assembly code. This
adds value because this can help the demand planner when he is making a decision in
allocating the demand. By confirming sales in a specific month, the demand planner
can confirm or deny production for that month.
12 Months Forecast  The value that shows up in this part is also
associated with the assembly code chosen. It shows the 2015 forecast of that
particular code.
2015 Suggested  The value that shows up in this part is derived from
calculation. The calculation takes into account the sales history and the minimum
production based on sets/multiples. This formula is what makes the difference in
terms of the forecast allocation. Because this formula takes into account some

criteria, it distributes 2015 forecast more accurately—as if following the demand
distribution, rather than an even forecast distribution (current model).
Once the data are all presented to the demand planner, he would have 2
options: whether to use the suggested value provided in the 2015 SUGGESTED or
adjust the suggested value based to his liking. To do so, he would have these sections
and buttons:
Use Suggested Button  If the demand planner wishes to keep the value
from 2015 SUGGESTED, he would just click this button and the value would appear
in 2015 ADJUSTED.
Enter New Values  If the demand planner feels that the value that is
shown in 2015 SUGGESTED is too small to be produced in a month, he could adjust
that value by entering a new value in this section.
Populate and Clear Buttons  If the demand planner puts new values in
the ENTER NEW VALUE section, then he can either click the CLEAR button if he
made a mistake or wants to redo it, or he can click POPULATE button to enter the
new value to the 2015 ADJUSTED.
2015 Adjusted  The value that will show in this section is the actual value
that will be considered for production for that specific assembly code.
Overall, this section is the core of the Forecast Allocation sheet. This part is
where all the decision-making happens. What happens in this section greatly affects
the rest of the final product.
7.2.2 SECTION B
This section shows the graphical representation of the data that is presented
in Section A of the Forecast Allocation sheet. This section is divided into two parts
that shows different graphical output of the data (see Figure 2).
Figure 2: Forecast Allocation Section B

Assembly Code Bar Graph  This graph shows the individual assembly
code’s data in a bar graph form. This graph changes for each assembly code that is
chosen. This graph will show the demand planner the distribution of demand based
on sales history, suggested forecast allocation, and the adjusted forecast allocation.
This graph adds value since it would give the demand planner a visual aid of how his
decision is affecting the demand forecast distribution for a specific assembly code.
Aggregate Overview Line Graph  This graph shows the overall
demand distribution for all the assembly codes. The blue and red line represents the
overall past sales history of all the codes, and it is unchangeable, meaning the line
graph does not change at all. The green line represents the 2015 suggested or the
suggested forecast allocation for 2015, which is also permanent. The only line that
changes depending on the input is the purple line, which represents the 2015
adjusted. This line changes automatically every time the demand planner changes the
value on Section A- 2015 ADJUSTED. Having this graph will show the demand planner
an overall view of how his decision with an individual code is affecting the overall
demand distribution.
In general, this section is a visual aid for the demand planner when making
decision regarding the allocation of the demand forecast. This section adds value
because it is an efficient way to see how each decision can affect the overall demand
distribution.
7.2.3 SECTION C

This section is added in the sheet in order to provide the demand planner
some valuable information in order to make decision. It can be either viewed or
ignored by the demand planner and it is composed of two parts (see Figure 3).
Figure 3: Forecast Allocation Section C

1 & 2 Buttons  Whether the demand planner wants to view or ignore
the information provided in this section, he can choose to do so by using these
buttons. When button 1 is clicked, the whole section will be hidden- as if section C
does not exist. However, if the demand planner wishes to view this section, the
button 2 will expand the section and all the information can be viewed.
Assembly Code Information  This part provides the basic information
of all the assembly codes of the rope code 1293000. It lists all ten assembly codes
and the associated data for each code such as the length and the order multiples.
This specific section of the forecast allocation sheet is added to provide the
demand planner an efficient way to view basic information. Instead of going back to
the SHEET A: RAW DATA to look for basic information, by providing this section—
going back and forth between Sheet A and Sheet B is avoided.
7.2.3 SECTION D
This section is a table that represents 2013 and 2014 Sales History. The data
in the table is extracted from SHEET A: RAW DATA –Sales History. The data in this
section is fixed and consists of two parts (see Figure 4).
Figure 4: Forecast Allocation Section D

Monthly Sales History  This part shows the monthly sales history for
the year 2013 and 2014.
Total Monthly Sales  This part provides the sum of all the sales in each
month.
This section is included for the purpose of visual aid. The table will help the
demand planner to refer back to the sales history when making a decision. With this
table, the demand planner can view all the sales that is made for all the assembly
codes –compared to Section A – Part 2, which only shows sales history of an
individual assembly code. The demand planner can also see the exact amount of
length that is sold for each month – compared to Section B – Part 2, which is a
graph, so it is harder to know what is the exact value of the sales history.
7.2.4 SECTION E
This section is a table that represents the 2015 Suggested Forecast
Allocation. The data in the table is extracted from SHEET A: RAW DATA – Suggested
Forecast. The data in this section is fixed and consists of three parts (see Figure 5).
Figure 5: Forecast Allocation Section E
Monthly Suggested Forecast  This part shows the monthly-suggested
forecast for each assembly code for the year 2015.

Total Monthly Suggested Forecast  This part provides the sum of the
suggested forecast for each month.
Total Yearly Suggested Forecast  This part provides the sum of all the
suggested forecast for each assembly code, and the total annual demand forecast.
This section is also included for the purpose of visual aid. The table will help
the demand planner to get an overall view of the suggested forecast for all the
assembly codes. This table gives an actual number value rather than a graphical
representation. Thus, the demand planner can use this table if he wants to verify the
overall numerical value of the suggested forecast data.
7.2.4 SECTION F
The last section of the forecast allocation sheet is a table that represents the
Adjusted Forecast Allocation. This section is interrelated to the Section A – Part 8.
Whatever the value that is inputted in Section A- Part 8 will show up in this table.
However, the demand planner could also use this table to edit the numerical value
and it will show up in the Section A – Part 8. This section is divided into 4 parts (see
Figure 6).
Figure 6: Forecast Allocation Section F

Monthly Adjusted Forecast  This part shows the monthly-adjusted forecast for
each assembly code for the year 2015. This is also where the demand planner can
input a numerical value directly.
Total Monthly Adjusted Forecast  This part shows the sum of
monthly-adjusted forecast for each assembly code for the year 2015.
Total Yearly Adjusted Forecast  This part provides the sum of all the
adjusted forecast for each assembly code, and the total annual demand forecast.
Adjusted Vs. Suggested This part shows the numerical value of
differences between suggested forecast and adjusted forecast.
The purpose of this section is not only to serve as a visual aid for the demand
planner to see an overall view of the adjusted forecast. The data that is presented in
this section will be the backbone of SHEET C: Production Schedule. The values that are
shown in this section – Part 2 Total Monthly Adjusted Forecast is going to be extracted
and will be use in SHEET C: Production Schedule. In general, this section is the final
steps when it comes to decision making of forecast allocation.
Once the forecast is allocated accordingly while taking into account all the
issues that was mentioned before, SHEET C: PRODUCTION SCHEDULE can be now
presented.
7.3 SHEET C: PRODUCTION SCHEDULE
The purpose of the Production Schedule is to provide the demand planner
with an adequate plan for production. The production schedule designed is user-
friendly and is presented in an effort to replicate the output of the SAP systems
commonly used by production planners.
At this point, the data’s manipulation is already done. Since all the data
presented in this sheet is derived from the Forecast Allocation sheet, the data
should be reliable enough to be considered for production. In the production
schedule, it is important to note that the demand of a certain month (i.e. February)
is produced the previous month (i.e. January). The production schedule sheet
consists of six parts (see Figure 7).

Figure 7: Production Schedule
1 & 2 Buttons  Just like in Sheet B: Forecast Allocation, this part is an
optional view of the assembly codes. Whether the demand planner wants to view or
not the information provided in this section, he could choose to do so by using
these buttons.
Beginning Inventory  Displays the amount of units on-hand at the
beginning of the month. If in a previous month, the demand planner inputs a
production that is lower than the demand for the current month, automatically, this
cell will show “Low Inventory”. Ultimately, this part also serves as a guide for the
demand planner whether his production for a previous month is sufficient.
Suggested Production  Displays the “suggested production” found using
the automatic formulas through the forecasting allocation sheet. The value that is
shown up here is derived from SHEET B: Forecast Allocation – Section F – Part 2
(Adjusted Production) and also adds an extra five feet of rope length to be produced
based on the number of assembly codes that is being produced. However, once the
demand planner inputs a new value in the Production Quantity, the value that is
displayed here will disappear automatically to avoid confusion.
Production Quantity  This cell is where the demand planner can input
the actual production value with further consideration of other factors that was not
included in the forecast allocation calculation (e.g. higher actual orders). Whatever
value is entered in this section will be considered for actual production. Also, any

last minute emergencies that could affect the production schedule are added in this
cell.
Demand  Displays the forecasted demand for a given month derived from
SHEET B: Forecast Allocation – Section F – Part 2 (Adjusted Production)
Ending Inventory  Displays the amount of units on-hand at the end of
the month, including the extra five feet per assembly code produced. The extra five
feet is added because when Wire Rope Industries has to cut the rope into many
assembly codes, it is safe to add extra length because of the cutting process. Also,
when the last assembly is cut from the production run, it is unfortunate to not be
able to use it and having to scrap a whole rope short of a few feet instead of
scrapping a few feet for safety every time.
7.4 USEFULNESS OF TOOL
The tool built for Wire Rope Industries has been tailored for their specific needs.
Since the company operates on a length based production, contrary to unit based,
this type of tool could be sold to companies that also operate in a similar industry.
A company in the cable production industry must have a production plan that is
well developed and partially automated to ensure that demand is met consistently.
The manual aspect of the tool gives the demand planner the freedom to manipulate
the data to fit the constantly changing demands of the clients.
Wire Rope Industries should invest in this unique tailored tool because it will help
accurately plan the demand for each month and will give a competitive edge to Wire
Rope Industries since this field requires filling in orders in a timely manner.

8.0 CONCLUSION
In order to improve Wire Rope’s monthly production schedule, it is
important to identify the point of improvement. The main weakness in Wire Rope’s
current model is the way they allocate their forecast, which highly affects their
production schedule. As a result, the project mainly focuses on solving the issue by
taking into account not only satisfying monthly demand but as well as avoiding
backorder and waste. By creating an Excel file that act as a decision tool, we were
able to create an improved production schedule. The decision tool takes into
account the sales history for the past two years, which in turns make sure that the
forecast allocation follows the past demand distribution. As a result, not only
demand is filled, excess inventory and stock out situations are avoided. The decision
tool also takes into account the minimum multiples and sets that is required in each
demand; thus, minimizing waste. While it is hard to accurately measure the new
model’s improvements, we were able to at least conclude that it is an improvement
from the current model by conducting an analysis. When compared, the current
model only thrives in a situation where the demand distribution is constant. This
explains why the current model works well in other product segment of the
company such as the shovel rope, which has a constant demand. However, when it
comes to the dragline segment – a product segment that has a volatile demand, the
new model definitely provides a more robust production schedule (as shown in
Table 5 of the Analysis section).
9.0 RECOMMENDATIONS
The core of the project focuses more on refining the forecast allocation to
improve the production schedule; therefore, it is imperative that the forecast that is
being allocated is highly accurate. Forecasts can never be 100% accurate, but by
implementing a way to measure its accuracy, it can be adjusted to take into account
possible errors and bias. For a short-term recommendation, Wire Rope should
invest in inserting some type of Mean Absolute Percent Error (MAPE) tool when
calculating their forecast. A better communication between Sales and Operations
should be considered as well. Sales should provide the Operations with information

regarding the month-to-month sales, changes in the forecast that was initially
proposed, and significant changes in demand such as new customers and leaving
customers. Implementing a quarterly meeting between different departments within
the organization will caused a better communication not only between the sales and
operation department, but as well as with other departments.
To further develop our proposed improvements in the production schedule,
in the long run, we recommend that the company should include inventory related
cost in the analysis. Although it seems that cost will not have an impact on the
decision of whether certain length of rope is going to be produced, by identifying
some standard production cost, perhaps it will be possible to create a new
production schedule – a schedule that will not only satisfy demand, minimize excess
inventory and avoid waste, but as well as minimize cost by giving optimal rope length
to produce per month.
The recommendations that are mentioned above will not only fortify the
new model that is being proposed, they also provide a possible future improvement
of the proposed new model.

10.0 REFERENCES
The individuals that were consulted in the preparation of this project are the
following:
 Mr. Andrew Patterson, Demand Planner at Wire Rope Industries
 Mr. Erik Sagoo, Raw Material Buyer at Wire Rope Industries
 Dr. Satyaveer S. Chauhan, Professor at John Molson School of Business
 Dr. Danielle Morin, Professsor at John Molson School of Business

11.0 APPENDICES
11.1 APPENDIX 1: FINAL PRODUCT

11.2 APPENDIX 2: PROJECT TIMELINE/SCHEDULE

11.2 PROJECT TASK LIST
Name Task Allocation
Juliane
 Wrote down minutes for every
meeting
 Corrected and formatted project
proposal
 Wrote background information for
the final project
 Wrote production process for the
final project
 Analyzed data provided by Wire
Rope
 Took notes during meetings
 Sent email to the professor and to
Wire Rope representatives
 Scheduled meetings
 Edited data collection
 Edited and corrected all sections of
the final project
 Wrote learning experience
 Provided recommendations
 Wrote References for Appendix
 Wrote Task List for Appendix
 Wrote the progress report 1 vs.
progress report 2 for progress
report 2
 Wrote task allocation for progress
report 2
Denis
 Wrote project proposal
 Created Excel sheet with tables and
graphs
Rope
 Researched Excel features
 Posted reminders for the team
 Researched theories
 Wrote Methodology
 Created Excel sheet with tables and
graph
 Created production schedule

Stephanie
 Took formal meeting notes
 Researched abstract and executive
summary
 Emailed professors that could help
us validate the methodology used
 Analyzed assembly code to see
flawed ones (forecasting)
Rope
 Wrote Data Collection
 Edited and corrected all sections of
final project
 Corrected and formatted project
proposal
 Wrote Major progress and
achievements
 Wrote Resources for the Appendix
 Wrote the References
 Provided Recommendations
Maria
 Built timeline for the whole project
 Kept it up-to-date
 Notified when a task should be done
or when to start one
Rope
 Created a template of the
PowerPoint
 Wrote summary of progress
 Created PowerPoint for 2nd Progress
Report
 Wrote Analysis of Results
 Provided project timeline/schedule
 Wrote Plan for progress report 2
 Provided timeline for the progress
report 2
 Wrote conclusion and
recommendation
Tarek
 Wrote project proposal
Rope
 Wrote goals and objectives for
final project
 Wrote Abstract, Executive
Summary and Introduction and
Final product
Wrote Project Goals & Objectives

11.3 RESOURCES
The order to complete this project, the resources required were
transportation, software, location and equipment.
Transportation Software Location of
meetings
Equipment
 Car
 Metro
 Bus
 Microsoft
Excel which
was
obtained
from either
the school
computer
or laptops
 Rockwell
ARENA
 Process
Analyzer
 Wire Rope
Industries
for meeting
with Mr.
Andrew
Patterson
and Mr.
Erik Sagoo
 John
Molson
School of
Business
for group
and teacher
meetings
 Starbucks
and Tim
Horton’s
for group
meetings
 Laptops
 School
computers

11.4 MINUTES
Meeting Minutes
1. Purpose of Meeting on September 12, 2014
Start to build a timeline, give tasks to all the team members and prepare the first
meeting with Wire Rope.
2. Time and Location
Location: John Molson School of Business
1450 Guy Street
Montreal, QC, H3H 0A1
MB. 5-234
Scheduled Start Time: 6:15 pm Actual Start Time: 6:15 pm
Scheduled End Time: 8:15 pm Actual End Time: 8:15 pm
3. Attendance
Name Attended Comments
Denis Noskov Yes
Maria Luisa De Ocampo Yes
Stephanie Ghaly Yes
Tarek Al Kayyali Yes
Juliane Fortin-Latreille Yes
4. Meeting Agenda:
 Determine everyone’s role:
o Stephanie will take notes during meetings
o Juliane will do the minutes and write the announcements/reminders
o Maria is in charge of the dropbox and google documents and calendar
o Tarek will email the representative of Wire Rope
o Denis is the team leader and will make sure everyone stay on track
 Decide the day and time of our weekly meetings
o We will be meeting twice a week (after visiting Wire Rope and
Fridays)
5. Meeting Notes:
o Juliane emailed Erik and Tarek will take over in order to determine
the meeting next week.
o Denis went to talk with the professor in order to determine what
was needed for the proposal
o Bring recorder to Wire Rope meeting and ask them if they mind that
we record beforehand.
 Proposal
 Juliane and Stephanie will read the Wire Rope website and do an
overview in bulletpoints.
 Denis and Tarek will write the draft and the rest of the team will
review.

6. Post Meeting Action Items:
 Everybody needs to send their school schedule to Maria.
 Juliane and Stephanie – read and write bulletpoints for company
overview by Tuesday.
 Maria – Open the dropbox for the project and create the Google
calendar.
 Denis – Create a overall timeline for the project
 Tarek – Email Erik if we still have no answer by Monday afternoon
7. Next Scheduled Group Meeting:
 Tuesday September 16 from 9:30am – 12pm next meeting
o Talk about what was discussed during the Wire Rope meeting
o Create a clearer timeline and separation of task for the
proposal

Meeting Minutes
Overview of first meeting at Wire Rope and start building proposal
1450 Guy Street
MB. 3-287
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
Tarek Al Kayyali No Didn’t attend due to
sickness
4. Meeting Agenda:
 Go over the meeting that was held with Erik:
o Brief people who could not attend what was said during that meeting
o Explain the project in depth
 Separate tasks for the proposal
o Decide who is doing what
o Determine the timeline of the proposal
o Start a bullet point outline together to make sure everyone is on the
right track
 Prepare Wire Rope meeting that will be on Monday
o Prepare questions that might rise up during this meeting
o Determine what we will bring to the meeting
5. Meeting Notes:
o Purpose is to determine a production plan
o For 3 months or 6 months
o Choose the 3 most high volume rope
o Based on # of assembly or forecasting of the length needed?
 Juliane and Stephanie – Company Overview

 Juliane – Do an outline of the final proposal, give reminder for
meeting
 Maria – Learn about Excel Solver
 Denis – Start writing proposal
 Tarek – Start writing proposal
 Monday September 22 from 11:00 am – 1:00 pm next meeting
o Talk about what was discussed during the Wire Rope meeting
o Finish and modify the proposal in accordance with the Wire
Rope meeting

Meeting Minutes
Review Wire Rope meeting and prepare the proposal
Location: Tim Hortons
305 Boulevard Brunswick
Pointe-Claire, QC H9R 4Y2
Scheduled Start Time: 11:30 am Actual Start Time: 11:30 am
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Review what was discussed during the Wire Rope meeting
o Compare notes taken during meeting with Andrew
o Make sure everyone understands the production process
 Prepare the proposal
o Discuss what is missing
o Fill in the information that is missing
o Decide who is doing what
5. Meeting Notes:
o Write notes taken from the Wire Rope meeting and divide them into
subjects
o Next meeting is Friday September 26.
 Proposal
 Denis and Tarek starts writing proposal
 Maria starts doing timeline
 Stephanie – Find company information for background
 Juliane – Correct and review proposal
 Maria – Finish Timeline
 Denis – Write proposal
 Tarek – Write proposal

 Friday September 26 from 12:30 pm – 2 pm next meeting
o Decide how to fix problem

Meeting Minutes
Discuss approach to fix Wire Rope problem
1450 Guy Street
MB-2.287
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
Tarek Al Kayyali No
4. Meeting Agenda:
 Discuss approach to prepare the production plan
o Find what method will we use to create the forecast
o Run many options to others in order to determine best approach
5. Meeting Notes:
o Next meeting is October 1st.
 Create 3 groups
 Group 1 would be for constant demand
 Group 2 would be for patterns
 Group 3 would be for non-constant demand
 Stephanie – Write meeting notes
 Juliane – Email teacher and Andrew in order to set up meeting and
prepare meeting minute
 Maria – Create a timeline for the whole project
 Everyone – Play with the excel file in order to find other possible
options
 October 1st from 3:30 pm – 5:30 pm next meeting
o Start building our approach
o Start analyzing data

Meeting Minutes
1. Purpose of Meeting on October 1, 2014
Apply the approach discussed with Professor Chauhan
1450 Guy Street
MB-5.280
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Review meeting with Professor Chauhan
o Discuss suggestions provided to us
o Decide how to apply them
 Start analyzing the excel sheet
o Use the 3 groups determined previously
o Use color coding
o Write comments to compare during next meeting
5. Meeting Notes:
 Next meeting is October 6.
 Do we go weekly or monthly for the forecast
 Create 3 groups
 Group 1 would be for constant demand
 Group 2 would be for patterns
 Group 3 would be for non-constant demand
 Juliane – Prepare template for final project
 Everyone – Analyze data for first code

 October 6 from 12:00 pm – 2:00 pm next meeting
o Discuss the analysis of the demand
o Decide the groups of each code
o Discuss what method to apply to each code

Meeting Minutes
Discuss meeting with Andrew and discuss applying analysis method of the
dragline
Location: Tim Horton’s
305 Boulevard Brunswick
Pointe-Claire, QC H9R 4Y2
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Review meeting with Andrew
o Discuss alternatives proposed
 Separate tasks for the next week
o Pacification of abstract, executive summary and introduction
o Write process planning
o Reviewing
o Writing
o Data analysis
5. Meeting Notes:
 Next meeting is October 10.
 Have to re-do timeline
 Focus on dragline
 Juliane – Write the production process section
 Maria – Review timeline and modify it
 Stephanie – Find out what is in Abstract,
 Denis – Send template and create demand overview
 Tarek - Start writing project description

o Discuss analysis of the demand
o Review and determine the dragline forecast

Meeting Minutes
Discuss strategy to create our forecast with the data provided.
1450 Guy Street
MB. 6.534
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes Left at 5:45 pm
Tarek Al Kayyali No
4. Meeting Agenda:
 Brainstorm on a way to come up with our technique to analyze our forecast.
o Provide ideas
o Discuss each technique
o Try to prove the technique is right or wrong
 Discuss and review powerpoint template created by Maria
o Review in order to make sure all the elements wanted are there
5. Meeting Notes:
 Use the average of 2013 and 2014
 Calculate overall production from the average of 2013 and 2014
 Find % of each month divided by the overall demand
 Ex: January=2,000 units, overall demand=10,000 units, %=20%
 Multiply % from overall forecast and this will give the production
planned for that month.
 Even out numbers if the numbers are not whole.
 Juliane – Write meeting minutes, plan meeting with Andrew and with
Professor Chauhan
 Stephanie – Find out what is in an abstract,

 Denis – Automate the demand overview and code
 Tarek - Start writing project description
o Separate task for the final paper
o Denis will explain how the new features added to the Excel
sheet works
o Analyze and discuss the forecast by assembly code

Meeting Minutes
Separate primary tasks for final paper and analyze and discuss the forecast for
each assembly code
1450 Guy Street
MB. 2.189
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Separate tasks for Final paper
o Based on strengths, who should start writing some sections
 Analyze and discuss forecast by assembly code
o Review in order to make sure all the elements wanted are there
o
5. Meeting Notes:
 Tasks for final project
o Juliane – will write background information and production
process.
o Tarek – will write introduction and project description, and
project goals
o Denis – will be in charge of the data collection and
methodology section
 Analyze and discuss the forecast
o Add a constraint for when there is some leftover that if the
demand is smaller, it should go take it from there.
o Change number to whole numbers in order to have an easier
production number.

 Stephanie – Write meeting notes, analyze all the assembly code in
order to determine which one are flawed.
 Juliane – Write meeting minutes, write production process and
background information
 Maria – Review timeline and modify it, continue working on
powerpoint
 Denis – Add constraint for the excess rope to be used when the size
fits a required length.
 Tarek - Write project description
 October 17 from 5:30 am – 6:00 pm next meeting
o Ask information about the progress report
o Ask for feedback on our forecast method

Meeting Minutes
Ask Professor Chauhan for some feedback on our forecasting method and for
information about the progress report
1450 Guy Street
MB. 5.234
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Ask information about the progress report
o What does it entails?
o Is there a presentation?
 Feedback on the forecast method used
o Any changes should be applied?
5. Meeting Notes:
 Information about progress report
o Timeline of what we did, what is left to do
o 1 page report
o Presentation  this is how we are fixing the problem
 Feedback on forecasting method
o Instead of doing the forecast month by month, do it in
quarters in order to not have averages with a 0.
o Incorporate a cost option for when scrapping a rope. How
much money do they get when recycling it.
order to determine which one are flawed.

 Juliane – Write meeting minutes, write production process and
background information
 Denis – Add constraint for the excess rope to be used when the size
fits a required length.
 Tarek - Write project description
o Ask if a quarter approach would be better
o Ask for feedback on our forecast method

Meeting Minutes
Ask Andrew Patterson for some feedback on our forecasting method
Location: Wire Rope Industries
5501 Route Transcanadienne
Pointe-Claire, QC
3. Attendance
Denis Noskov Yes
Maria Luisa De Ocampo No
Stephanie Ghaly No
4. Meeting Agenda:
 Feedback on the forecast method used
o Any changes should be applied?
5. Meeting Notes:
 Forecasting method
o Aggregate overview but still with details that could be grouped
and hidden
o Ropes should always be multiples of 470 ft.
o Should do a bar graph instead
o Receive $130/ton when scrapping metal
o Produce May, April, June and July, August together was a good
idea
o Remove previous run
o Try vertical production plan
o In 2 weeks, should be almost finalized and will decide if we do
one rope code or we integrate the 2 other rope codes.
order to determine which one are flawed, email Professor
Navneet.

 Juliane – Write meeting minutes, write task allocation for progress
report and appendix.
 Maria – Review timeline and modify it, write plan, prepare outline of
powerpoint
 Denis – write major progress and achievements, add modifications to
the Excel sheet
 Tarek - Write progress versus project proposal
o Finish analyzing forecast

Meeting Minutes
Finish analyzing forecast
Location: JMSB
1450 Guy Street
MB. 5310
Scheduled Start Time: 11:30 am Actual Start Time: 2:15 pm
Scheduled End Time: 11:30 am Actual End Time: 2:15 pm
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
Juliane Fortin-Latreille Yes Arrived at 11:45 am
4. Meeting Agenda:
 Allocate tasks for progress report
o Separate sections
 Allocate sections for powerpoint of progress report
 Go over forecast analysis done by Stephanie
5. Meeting Notes:
 Powerpoint slides
o Send slides by Monday night to Maria
o Include text that will be said
 Forecast Analysis
o Assembly code 300 and 315, have to ask Andrew for
confirmation
o Other codes, we keep the same method as the previous one
 Stephanie – make project description slides
 Juliane – Prepare challenge slide and finish writing task allocation for
progress report
 Maria – Prepare timeline slides and write plan for the progress report
 Denis – write major progress and achievements, prepare
achievements slides
 Tarek - Write progress versus project proposal and prepare company
overview slides problem overview slide.

o Prepare presentation

Meeting Minutes
Prepare presentation
Location: JMSB
1450 Guy Street
MB. S2
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes Arrived at 3:00 pm
4. Meeting Agenda:
 Practice Presentation
o Every teammate has to go over his or her part and the other
teammates have to give feedback
5. Meeting Notes:
 Presentation
o Change of speaker has to be done differently for Denis
 Stephanie – practice presentation and review progress report
 Juliane – practice presentation and review progress report
 Maria – practice presentation and review progress report
 Denis – practice presentation
 Tarek – practice presentation
 November 2nd from 12:00 pm – 5:00 pm next meeting
o Finish production plan

Meeting Minutes
1. Purpose of Meeting on November 1, 2014
Finish production schedule
Location: JMSB
1450 Guy Street
MB. 5.107
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Finalize production schedule
o Decide the best scheduling tool
o Decide planned order method
5. Meeting Notes:
 Production schedule
o Use 470 feet as the dividable measure
o We are taking the vertical schedule
o Create dropdown for rope code in final production schedule if
given extra rope code
o Assembly code 300 and 315
 Current state of inventory/orders
o Main question is whether he wants us to produce a snapshot
for 3-6 months or a schedule that can be easily updated and
orders and inventory on hand.
 Stephanie – Write notes taken
 Juliane – write meeting minutes
 Denis – change the 0 to “-“ in the excel sheet and change graphs to
bar graphs

 November 3rd from 10:00 pm – 3:00 pm next meeting
o Finish production plan

Meeting Minutes
Show to the Wire Rope representative the production schedule
Location: Wire Rope
Pointe-Claire, QC
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Get feedback on production schedule
o Provide information on any changes that should be applied
5. Meeting Notes:
 Presentation of the tables and graphs
o Split planned order and inventory on-hand
o Put the production schedule horizontally
o Have 1 recommended quantity and 1 actual quantity column
 Suggestions
o Weighting of the forecast
o Production schedule = planned order and change to horizontal
o If you make a table, everything has to be clear
o Present something that is super clear, give a table, a title and a
header
 Stephanie – write note taken during meeting
 Juliane – write minutes
 Maria – start writing analysis of results
 Denis – apply changes to the excel sheet
 Tarek – write introduction, project goals & objectives

 November 7 from 6:30 pm – 7:00 pm next meeting
o Get feedback from professor Chauhan on production schedule

Meeting Minutes
Show to professor Chauhan the production schedule
Location: JMSB
1450 Guy Street
MB. 5.345
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Get feedback on production schedule
o Provide information on any changes that should be applied
5. Meeting Notes:
 Presentation of the tables and graphs
o Change the formula for the forecast allocation, should be on
12 months
 Suggestions
o Consider 12 months
o Ask Andrew for the 2 extra months of sales history
o Ask Dr. Morin for analysis and statistical side to our forecast
 Stephanie – write note taken during meeting, review introduction,
project goals & objectives, email Dr. Morin
 Juliane – write minutes, review introduction, project goals &
objectives
 Maria – provide outline for analysis of results, analyze all the sets
 Denis – apply changes to the excel sheet
 Tarek – provide outline for final product

 November 14 from 10:00 am – 2:00 pm next meeting
o Fix production schedule
o Analyze assembly codes sets

Meeting Minutes
Fix production schedule and analyze assembly codes sets
Location: JMSB
1450 Guy Street
MB. 5.110
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Analysis of assembly codes sets
o Determine what assembly codes are sets
o Look at analysis and method used by Maria
 Determine the best method for the forecast allocation
o Denis presents his version that he created to fix issues brought by
professor Chauhan and Wire Rope representative
5. Meeting Notes:
 Analysis of assembly codes sets
o Change production schedule in order for them to be
produced at the same time
 Determine the best method for forecast allocation
o Provide 3 versions to the Wire Rope representative in order
for them to decide which one they prefer.
 Stephanie – write note taken during meeting
 Juliane – write minutes
 Denis – apply changes to the excel sheet, start writing methodology
 Tarek – start writing final product

 November 17 from 10:00 am – 2:00 pm next meeting
o Show to the Wire Rope representative the 3 versions of the
production schedules
o Fix production schedule based on feedback

Meeting Minutes
Show to the Wire Rope representative the 3 versions of the production
schedules and fix the production schedule based on feedback
Location: Wire Rope
Pointe-Claire, QC
3. Attendance
Denis Noskov Yes
Stephanie Ghaly Yes
4. Meeting Agenda:
 Show the 3 versions of the production schedule
o Which one is best
o Any recommendations on the version chosen
 Determine how to fix the production schedule
o Discuss in group what method should be used
5. Meeting Notes:
 Show the 3 versions of the production schedule
o Preferred version 2.0
o Sets should go with 470 feet  can do any length with it
o Use multiples to drive the production
o Production run is too small in July and September
 Determine how to fix the production schedule
o Minimize scrap with assemblies
o Change units per rope
o Add constraint in the already built forecast
 Stephanie – write note taken during meeting, write data collection,

 Juliane – write minutes, write data collection, write progress report 1
vs. progress report, write task allocation, write learning experience
 Denis – apply changes to the excel sheet, write methodology
 Tarek – start writing final product and abstract
 November 28 from 5:00 pm – 6:00 pm next meeting
o Practice presentation for progress report 2

11.5 LEARNING EXPERIENCE
During the term, many learning experiences occurred due to the difficulty
and the involvement required. Throughout those experiences team members
noticed the importance of punctuality in order to make the most of the time when
all teammates could meet. Due to different schedules, preparation was a key success
factor in order to make the meetings as efficient as possible. By providing many
different ideas and solutions, which sometimes were not always the best one, it was
important to provide answers that promoted self-respect towards other teammates
in order to have a peaceful and productive environment. By having a group of five
individuals, everyone had a different set of skills, which would complement the
strengths of the other teammates. In addition, when someone’s weakness prevented
from making progress, it was encouraged that another teammate who exceled in
such field offered help.

FINAL REPORT (DRAFT) 2

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