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Lab2

Lab2. Objectives: Introduction to awesim environment (Network and control parts, Running models, Opening/saving models), introduction to simple modeling structures (arrivals, queuing, service, termination), and probabilistic branching, getting time in the system (attributes and collect block).

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Lab2

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  1. Lab2 • Objectives: Introduction to awesim environment (Network and control parts, Running models, Opening/saving models), introduction to simple modeling structures (arrivals, queuing, service, termination), and probabilistic branching, getting time in the system (attributes and collect block). • “Simple machining center” model M2 Parts departs Parts arrive M1 Queue1 Queue2 M3 stage 2 stage 1

  2. Lab2 • “Simple machining center” model Processing time uniform (6, 10) min Identical parallel machines M2 Parts departs Parts arrive M1 Queue1 Queue2 M3 Inter arrival times exponential with lambda=0.2 part/min Processing time uniform (2.5, 5.5) min What are the machine utilization? What are the queue lengths and times? Simulate it for 30 days (8 hours working time per day)

  3. Lab2 • Embellishment 1: Add an inspection station at the end, and assume that 5% of the jobs fail inspection and they require rework starting from beginning. Ins. time Normal (10,2) • Embellishment 2: After inspection, 2 % requires rework in stage 2 only (not from beginning) in addition to the 5% in embellishment 1. • Embellishment 3: Obtain time in the system for parts.

  4. Lab2 • Assignment 2: Model the following system and answer the same questions answered in the lab. M1 normal(10,2) Parts arrive Inspec- tion Queue2 Queue1 M2 Inter arrival times exponential with mean=15 min. Processing time (identical machines) normal (mean=22.5, std=5.7) min 3% rework Submit a print out of model, control, output, and your answers.

  5. Lab 3 • Objectives; To cover; Entity dependent processing times, routing (conditional branching), and naming of attributes to make the model easier to read.

  6. Lab 3 Simple machining center with inspection • Embellishment 1; There are two types of parts coming to system, type A and type B, as depicted in next slide. Type A has to go thorough a different machine in the second stage. We want to get time in the system separately by item type, and overall as well. Use renaming of the attributes for arrival time.

  7. Lab 3 Simple machining center with inspection (Embellishment 1) Gamma(1,2) min Type A M4 Queue3 Normal(10,2) min Type A M2 Type B Insp. Queue4 M1 Queue2 Queue1 M3 Type B uniform (2.5, 5.5) min Parts arrive uniform (4, 6) min (identical machines) 5% rework Inter arrival times exponential ; with lambda=0.005 part/min Type A with lambda=0.015 part/min Type B

  8. Lab3In-lab work-out Normal (8,2) Queues are not depicted here Type B Ins1 Gamma(2,2) Type A 40% 5% rework M2 M1 Type B 50% Normal (6,1) uniform(5.5, 7.5) Inter arrival times; gamma(2,5) Run simulation for 5000 parts Where is the bottleneck? Ins2 Type A 3% rework

  9. Lab 4 • 1. Entity dependent processing times and entity dependent numbering of collect block. 2. Balking blocking 3.Different uses of collect block and histogram.

  10. Lab 4 Simple machining center with inspection • Embellishment 1; Inspection timedepends on job type. For type A inspection time is Normal (8,2) for type B inspection time is Normal (15,3). Use one collect block to get time in the system separately by numbering the collect block using attribute. • Embellishment 2; Assume that if there are more than 5 parts waiting in queue 1, the arriving parts will be sent to another shop for processing. Obtain how often this happens. We would like to obtain histogram of time in the system as well.

  11. Lab4In-lab work-out; Maintenance shop • Maintenance facility of a large manufacturer performs two operations in series . The units that are maintained are heavy, and the space in the shop is available only for 8 units including the units being worked on. The proposed design allocates 4 units for first queue, 2 units for second queue. Company subcontracts incoming units if the maintenance shop is full. If the second queue is full, the first workstation is blocked.

  12. Lab4In-lab work-out; Maintenance shop • Arrivals; exponential with mean 0.4 time units • Processing times; first station exponential with mean 0.25, second station exponential with mean 0.5 • No significant time for transfer from first station to next. • Evaluate proposed design for 300 time units in terms of • utilizations, time in the system, time between the subcontracting, queue lengths, fraction of time work station 1 is blocked (The correct answers avr. tims = 2.7, time btw balk = 1.5) • Any better design???

  13. LAB 5 • Objective: 1. To complete the in-lab workout started in previous lab and the embellishment of it. 2. To learn how to do batch arrivals, use of NQ(), multiple runs, the ranking in queues, flexible use of attributes.

  14. LAB 5 In-lab workout • Complete the model for the problem described in previous lab. • Embellishment: Assume that there are two types of units that comes to the system, and second stage operation time depends on type of unit as follows; Type A Gamma(0.5,0.6) and Type B Gamma(1, 0.8). Use one collect block to get time in the system separately by type. Produce a histogram of time in the system for both types.

  15. 85% to packing Ins1 Queue1 TVs 85% to packing Ins2 Queue2 Adj. Queue3 Return of adjusted sets LAB 5TV inspection station • Consider the following TV inspection & adjustment station where we have two inspectors and one adjuster. TV sets arrive in sets of two TVs with uniform btw 7 and 15. Incoming TVs join the shorter queue. The processing time in inspection stations are uniform(6, 12). Adjustment takes shifted gamma(2, 2) with min 1.5. Obtain time in the system based on 1000 parts leaving the system. Do 50 runs.

  16. LAB 5TV inspection station • Embellishment: Assume that in all queues, we use shortest process time first rule. After adjustment, make sure the TVs go back to the same inspector queue that they came from.

  17. LAB 5 – Assignment 3TV inspection station • Embellishment of TV inspection model: There are two types of TV sets. 40% type A and 60% type B. Adjustment time depends on the type of TV set as follows; Type A gamma(2, 2) with min 1.5 and Type B gamma(1.8, 2.5) with min 1. Also assume that if a TV is adjusted before, it passes the inspection 95% of the time. Change ranking rule to longest processing time first. Do your simulation for 40 runs, obtain time in the system by type.

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