Reference no: EM132721687

ME7713 Industrial Operation Management & Resources Simulation - Kingston University London

Flexsim modelling, Linear Programming and Simulation case study

Learning Outcome 1: Deploy special techniques and software systems to optimise resources through eliminating waste and prioritising constraints.

Learning Outcome 2: Demonstrate an in-depth understanding of specialised techniques in resources optimisation and management.

Learning Outcome 3: Perform critical analysis of operational resources and bottlenecks through using simulation modelling.

Assignment details

Part A - Using FlexSim software to create a simulation model for the following problems:

Flexsim model 1 - create a simulation model for a medical centre

In a medical centre, a patient arrives on average once every 20 minutes exponentially. Patients first join a queue and wait there for registration. They then go to a registration desk staffed by a medical assistant, providing their name and insurance data. This process takes anytime from 30 seconds and 2 minutes. During the registration process, the medical assistant will assign patients to one of the two waiting rooms. Waiting room 1 is for urgent cases (30%), and room 2 is for normal cases (70%). Change the colour of urgent patients to RED, and normal patients to YELLOW. RED patients will be given higher priority to see the doctor.

After registration, patients will be escorted by the same medical assistant to their designated waiting rooms, and sit there until the doctor is available. The doctor calls the patients on a FIFO order, but those in waiting room 1 (RED patients) will be called first. For normal patients (YELLOW), the consultation time with the doctor takes on average 15 minutes, with a standard deviation of 3 minutes. But for urgent patients (RED) it will take longer on average 30 minutes, with a standard deviation of 4 minutes. After the consultation, about half of the patients will need a prescription, and it will be done by the doctor in 2 minutes on average.
Both prescription and non-prescription patients then go to the check-out desk to pay the fee and schedule the next appointment. This typically takes 45 to 60 seconds. The same medical assistant is staffing the check-in and the check-out desks. Patients then exit to one of the two queues (one for RED patients, one for YELLOW patients) to wait for their buses. Paint the two bus queues with the right colours. There is one bus for the RED patients going on a one-directional loop and take them to the outside world. Similarly a separate bus is on another one-directional loop will take the YELLOW patients to the outside world. Both buses have a capacity of 20 people, and they won't start until there are 20 people onboard. Their speed, acceleration and deceleration are all constant of 120.

Model this medical centre using FlexSim, and simulate the model for 5 replications of 8 hours. Save the model as ‘model1_1'

Task 1: On average, what is the total time spent in the medical centre by a RED patient and a YELLOW patient?
Task 2: What is the maximum waiting time and average waiting time in each of the waiting rooms (room 1-RED and room 2-YELLOW)?
Task 3: What is the utilization % of the medical assistant and the doctor?
Task 4: The doctor is considering to hire a second medical assistant to help the check-in and check-out processes. Implement this change in a separate model (name it ‘model 1_2'). Discuss if you think it is a good idea?
Task 5: Although not compulsory, bonus marks will be rewarded if you create new things in the model. For e.g. replace default icons with something more visually suitable, park the bus when resetting, change the layout, use information billboard to display essential information, etc. If you do this, then save it as ‘model 1_3'.
Task 6: Based on your observation of ‘model 1_1' and ‘model 1_2', and the report you generate, make some recommendations what can be improved, with some creditable evidence, e.g. flow diagrams, estimate of benefits. There is no need to build another model.

Model 2 (use MTBF & MTTR, rework, itemtype increment counter)
A product arrives in a Queue every 14 seconds exponentially distributed and then routed to any one of 3 machines where it is processed for 20 seconds (24 seconds for rework). Machined parts are placed in a common queue and wait to be tested, 20% are found faulty and must be reprocessed. The test time is a constant 9 seconds. Parts passing test enter another Queue and wait to be packaged at an automatic packaging machine.
The packaging machine accumulates 10 products into a box and then closes, seals, and labels the box in 57 seconds. The supply of boxes comes from a Queue fed by a box forming machine having a cycle time of normal(50,2) seconds. The box former jams regularly per Weibull (151.1,50,24.9) and takes between 20 and 30 seconds to fix uniformly distributed.
1. Inter-arrival time for source is Exponential(0,14,1)

2. The Tester has an output of 80% acceptable and 20% faulty by chance

3. Cycle time for box forming machine is Normal (50,2)

4. MTBF for box forming machine is Weibull (151.1, 50, 24.9)

5. MTTR for box forming machine is uniform (20,30)

6. Save your model as ‘K?????_K?????? Model_2'.

After you have completed the above model, add the following extras:
1. Use a conveyor to route failed flowitems back to the queue.

2. Increase the ‘Increment ItemType' by 1 each time a flowitem fails, and change the flowitem's colour according to how many times it fails: 1- green, 2- yellow, 3- red. You will need to use this function ‘inc(itemtype(item),1)' to change the ItemType each time when a part enters the rework loop.
3. You will get some bonus marks if you include additional FlexSim functions from the Visual object library (e.g. Billboard to show real-time statistics, not compulsory)
4. Save your model as ‘K?????_K?????_Model_2_extra'.

Part B. To create a Linear Programming model using MS Excel Solver

A metal works manufacturing company produces four products fabricated from sheet metal in a production line that consist of four operations: 1) Stamping, 2) Assembly, 3) Finishing and 4) Packaging. The processing times per unit for each operation and total available hours per month are as follows:

	Product (hour/unit)
Operation	1	2	3	4	Total Hours available per month
Stamping	0.07	0.2	0.1	0.15	700
Assembly	0.15	0.18	--	0.12	450
Finishing	0.08	0.21	0.06	0.10	600
Packaging	0.12	0.15	0.08	0.12	500

The sheet metal required for each product, the maximum demand per month, the minimum required contracted production, and the profit per product are given as follows:

		Monthly sales demand
Product	Sheet Metal (ft2)	Minimum	Maximum	Profit(£)
1	2.1	300	3,000	11
2	1.5	200	1,400	12
3	2.8	400	4,200	10
4	3.1	300	1,800	14

The company has 5,200 square feet of fabricated metal available each month. Formulate a linear programming model and use Excel Solver function to suggest the best mix of products which would result in the highest profit within the given constraints.

You must include the Objective Function and all the constraint equations in your main report. Also please find and briefly discuss ONE commercial software which is used by companies to perform similar resources optimisation.

You should submit the LP Excel model in the same folder for the main report.

Part C. Write a short essay (max 2500 words +/- 10%) to discuss the use of Discrete Event Simulation based on one selected case study (40%)

You may choose a suitable case study either from an international engineering company (e.g., Honda, Rolls-Royce, Boeing, BAE Systems, Siemens etc) or from a company in the service sector (including telecommunication, hospitality, waste disposal, healthcare, mass media, transport, hospital, energy and retail etc). Where possible, please attach a link to the full text of the case study so that I can compare it when marking your assignment. Don't use any case study which is more than 10 years old.

Discuss the following in your report:

a) Discuss the main reasons why the company chose to implement DES. You may talk about their problems before using simulation.
b) The benefits that the company has achieved by implementing DES. Where appropriate, you should include quantifiable evidence such as tables, statistics, graphs etc. to indicate their improvement after using DES.
c) Discuss the problems they had to overcome in order to benefit the full DES experience.
d) Include and discus, where possible, some simulation layouts and flow diagrams available for this company (multiple materials may be used for the same company, but only one main case study article).
e) Discuss briefly of the DES software that this company has chosen. Include some pictures if available. Don't
f) Discuss, in your opinion, how this company could improve their operations and business further through using DES.

Attachment:- internal moderation.rar