The document outlines a simulation project for a new photovoltaic panel production facility in Akureyri, Iceland, aiming for a production rate of 1.0 megawatt/month. It details objectives including process planning, capital investment assessment, and staffing requirements, with an emphasis on resource utilization and modeling assumptions. The team's conclusions recommend increasing a-grade material storage capacity to enhance production efficiency, while listing unsuccessful improvement attempts and the overall production results achieved during the simulation.

1. SIMIO SIMULATION PROJECT
Team Name: SIMBIT
Piyush Ambekar (1001164020)
Japan Shah (1001154714)
Vishrut Mehta (1001160569)

2. Problem statement and objectives
o Problem statement :
• New World Energy is planning the creation of a new 1.0 Megawatt/Month photovoltaic (PV)
panel production facility in Akureyri Iceland. Our consulting firm , Technology Exporters U.S.A. ,
has been hired by New World Energy’s board to assist in the planning and design of the proposed
1.0 Megawatt/month PV panel production facility. For this study it is assumed that the average
cell can produce 1.335 Watts of power. The baseline system produces 78-600 kg Ignots and 19-
400 kg Ignots per year. We have to build the baseline model and do a design experiment to
determine what additional resources and capital expenditures are required to increase production
rate in the project time span of 10 months.
o Objectives :
• Generate a process plan , based on the information provided.
• Decide how much capital investment will NWE have to make to develop a pilot production
facility in Akureyri Iceland.
• Find out NEW’s total capital investment for the final production facility that is capable of
producing the targeted 1.0 Megawatt/month production rate.
• After the facility is up and running , the NWE board will allocate a maximum of $3,50,000/month
in new capital investment. Based on this funding profile , our objective is decide that if 10 month
funding plant providing an additional $35,00,000 be sufficient to reach the 1.0 Megawatt/month
production rate.
• Decide the staffing requirements for the pilot production facility.
• Decide shift pattern and staffing levels to run the Akureyri facility during each phase of the
production expansion.

3. Process Flow
Mine Truck Vendor
Hopper 2 Size crucibles
5 Chemical processes Paint Booth
Drying process Bake in oven
Spray release agent
Grade : A
Crucible
Grade : B
Packed Crucible
Furnace
400 kgs
Cooling station
Grade A Grade B Byproduct
Mine
Two production Processes
Hydraulic crushing station
Chunks sorting station
400 kg Ignot
The figure here shows the total process flow of
the project. The major processes to be completed
here are:
1. Raw silicon cleaning process under which
we have to do 5 chemical processes.
2. Preparing the crucible.
3. Packing the crucible for purification and
production.
4. Sending the cubicles to the furnace.
5. Separating the crucible into two categories
after they come out of the cooling station.
1
2
3
4
5

4. Process Timelines/logic and Assumptions
• As we had to do 5 chemical process in the “Raw Silicon Process” , we have used the task
sequence to merge the processes into a single process and each were assigned the necessary time
of 5 mins to complete the process.
• For making a total of 600-kg crucible we take the A-grade material which is available with us and
mixed with B-Grade material or raw silicon ore , whichever is available first. In the mixture we
use 80-kg of A-grade material and 520-kg of B-grade material or raw silicon ore. To develop a
logic in selecting the material from B-grade or raw silicon ore , we have used the priority logic. In
which the B-grade material is given the first priority and the raw silicon ore is given the second
priority and also when there is scarcity of the B-Grade material , we will take raw silicon ore into
the mixture.
• For making a 400-kg crucible , we will use 400-kg of A-grade material only.
• The 600-kg and 400-kg crucibles are coming into the cooling station. After the process we need
to separate these crucibles and send them to their assigned next stations. To separate these
crucibles , we have used the “add-on process” logic in which we have put “decide” and “transfer”
process to separate the crucibles. If the incoming crucible is of 600-kg we send it to the crushing
buffer for further process and if the incoming crucible is of 400-kg , we send it to the ignot buffer.

5. In this model , we have made some assumptions according to the given instruction. The assumptions are:
• In this model , we have assumed that 1 entity = 1 kg of material.
• The crucible of both sizes will be available to the NWE facility as needed.
• We have assumed that the 800-kg of A-grade material is already available at the facility when operation of
filling the crucible first begin.

6. Team Conclusion:
From the analysis we performed , we can conclude that increasing the production of A-grade material
will eventually increase the overall productivity of the facility.
To prepare the 400-kg ingots , we need only A-grade material. Since we will increase the productivity
of the A-grade material , we can directly increase the number of ingots prepared of 400-kg crucible.
For filling the purification crucible , we take 80-kg of A-grade material and 520-kg of B-grade material
and/or raw silicon ore. Here we assume that we have 800-kg A-grade material readily available at the
facility while the operations first begin. We need a resource of A-grade material.
The capacity of the storage of material bin is 2000-kg. If this capacity is increased , we can increase the
overall production of 400-kg ingots.
We recommend that instead of having 800-kg A-grade material readily available at the facility ,
increase the quantity of the material which is already available. Also we can increase the capacity of
material storage bin or we can add another bin in which we can store the incoming material.
The investment cost for a 2000-kg material bin is $150k.

7. Baseline Model Results
These results are obtained while running the facility for 8
weeks.
Number of crucibles produced for
600-kg are 335 and for 400-kg are
109.
Number of 600-kg Ingots are 8 and
number of 400-kg Ingots are 3.

8. Here the number exited from the
GradeAbin is 2,644 but the
number entered in the
GradeAStorage is 2,122. Here
the process is having a bottleneck
because the capacity of the
storage is 2000kg. The remaining
quantity ( 522kg ) are not getting
stored in the storage bin for A-
grade material.
The table shows the key machine
utilizations which are relevant to
the material flow in the system.
The table shows the key resource
utilization which are relevant to
material flow.

9. Model Validation:
Model validation is required to see if the model which we made , is working according to the customer’s
requirement and we are getting the expected results.
Here for validation , we were given that the baseline system production was stated up front at 78-600kg Ingots and
19-400 kg ingots. In our model , we found out that we could produce 8-600 kg Ingots and 3-400 kg Ingots in 8
weeks. If we extrapolate the results for 1 year (52 weeks) , we could produce 52-600 kg Ingots and 19-400 kg
Ingots. As for further processes we only required 400-kg Ingots , we can say that our model results validates with
the given baseline system production results considering the fact that all the equipment's were purchased in the
time span of 10 months and given the money spending limit of 350k/month.

10. Before implementing the improvements
After implementing the improvements
Here , the to increase the productivity of the plant , we have added another A-grade material
storage bin to the facility. By doing so , we are able to provide more A-grade material during the
cycle of the process.
After implementing this strategy , we found out that the number of ingots for 600-kg material
increased from 8 to 9. Which is a 12.5% increment. And number of ingots for 400-kg material
increased from 3 to 4. Which is a 33.33% increment.

11. After all the equipment were purchased and the facility was up and running , we had a total of $3,500,000
available with us. We managed to buy three additional equipment with it but it failed to improve any production.
The candidate improvements that we assessed but did not improve production are:
1. Adding a silicon chunk sorting station to the facility.
2. Adding crucible packing stations for 600-kg crucible as well as for 400-kg crucible.
3. Add another furnace.
The silicon chunk sorting station had a cost of $50k. We ran the model , adding this station but it did not improve
any productivity.
We also tried adding an additional crucible packing stations for both 600-kg and 400-kg crucibles. The total cost
of them were $200k. This method was also a failure in improving the production of the facility.

12. There is a process in which we have to apply the release agent on the 600kg purification crucible.The operator
needed to fill the crucible with 80 kg of A-grade silicon and 520 kg of raw silicon ore and/or B-grade material.
According to us , this was the hardest technical part . Because merging the two different crucible and selecting
520 kg crucible from raw silicon and/or B-grade material was a real challenge.
We overcame this problem by brainstorming and taking into consideration different ideas and finally came to
a common solution.
At the early stage , we were using complex logics for different processes. Later on we came to know that some
of the processes can be merged together and we can use a single logic for all of them.
As a team , we decided to take one topic each time we met and come with some research on that topic and
develop a logic for the process.Whenever we met , we brainstormed the ideas of all the group members and
finally come to a solution and implemented it in the simio model.We went ahead following this steps for each
process and each step of the project.

13. PiyushAmbekar
Japan Shah
Vishrut Mehta