DISCRETE EVENT SIMULATION
Assignment
Create the model and optimise the revenue for the plant over ten days operation after an appropriate warm-up period.
Description
Gears are manufactured in a separate plant and arrive via a 20 m conveyor according to a distribution defined in the excel file supplied. This conveyor feeds an assembly area where gearboxes are assembled with two gears and two bearings (always available). The conveyor is of a belt type; the gears have a footprint of 80 by 80 by 100 mm and can be spaced on the conveyor 100 mm apart. The maximum capacity is 180 parts and speed 5 m/min.
The gearboxes are drawn from stock as castings and are loaded to a CNC workstation for additional machining and boring. An operator loads each casting to the workstation (0.5 – 1.0 minute) and unloads them to a bin (maximum capacity 50) or a sample inspection station. Unloading takes 0.5 – 0.9 minutes and the machining cycle takes 2.3 minutes.
Every 20th gearbox machined is passed to an inspection station, the others to a buffer. The inspection operation cycle time is triangularly distributed with a minimum of 0.8 minutes, a maximum of 2.2 minutes with a mode of 1.1 minutes. This is carried out by the operator(s). Previous tests have shown that after 20 samples inspected there is a 78% chance that the critical dimensions (bores for bearings) are at the upper tolerance limit. When this occurs, the tools in the CNC workstation need to be replaced and the machine cleaned. This operation time is triangularly distributed with a minimum of 2.5, maximum 3.7 and mode of 3.2 minutes. The failed gearbox is scrapped.
Machined gearboxes are assembled with two gears and two bearings by an operator. This takes a mean of 3 minutes with a standard deviation of 0.7 minutes, but no less than 2.2 minutes and no greater than 5. The assemblies are put into a buffer for testing. The test bench runs the gearboxes for 10 minutes and can initially take up to five at a time. An operator loads and unloads them to the test points. Loading and unloading both take from 0.2 to 0.4 minutes for each gearbox. There is a 93% chance of passing the gearbox for shipping; the failures are sent directly to a disassembly station where an operator will remove the gears and replace on the conveyor 5 m from its end. The gearbox castings and bearings are discarded. Disassembly takes a mean of 2.3 minutes with standard deviation 0.4, but no less than 1.7 and no greater than 3.5 minutes.
The plant is staffed by a number of operators (to be decided) who are trained in all activities.
Costs and Budget
You have purchased the CNC workstation for £72K, which needs to be repaid in three years. The plant operates on an eight-hour shift. Operators have 15 minute break in the morning and afternoon and one hour for lunch.
Additionally you have a budget of £15K to set up the remainder of the plant. This expenditure must be repaid within one year.
Costs
Assembly stations with appropriate tooling: £1800
Additional bin for machined gearboxes: £200
Test bench space per gearbox: £2200
Fixed cost for hiring an operator (advertising, training etc.): £1500
Operator hourly rate including on-costs: £15.60
Task
Optimise the plant to achieve maximum revenue with budget. You may need to optimise the plant for the priorities of the machines first. The expected revenue for each completed and working gearbox is £80.
Investigate what effect a breakdown of each of the CNC workstation and the conveyor for 90 minutes has on the daily production rate.
Write a report describing your model and present results on a series of tests on the model. In your conclusions, present an evaluation of the model in the light of all assumptions made and what limitations they place on the model.
The report must be in the form of a standard technical report or article to include:
Abstract
Introduction
This should include some explanation of stochastic modelling and methods and tools available to carry out discrete-event simulation to form a literature review. For example, you might want to discuss software packages other than Witness and techniques such as Petri Net models.
You should also introduce the problem either by description of using a block diagram.
Methods
Describe your modelling technique and the structure of the Witness model. Justify your approaches to building the model and include any relevant references. Describe the approach to optimisation and describe all equations or functions used.
Results
Present the results of the optimisation(s) and experiments and the expected daily and hourly production and revenue from the plant.
Discussion
Discuss the model, its performance and implications on the real system. Discuss and evaluate the limitations of the model.
Conclusions
Provide some conclusions in a form that will advise the company management on the feasibility and expected returns for the plant.
The report will be submitted to turn it in as a PDF or WORD document, with a copy of your model and optimisation / experimentation files. Assessment will be based on your research, the explanation of the model generation, description of the experimentation / optimisation, the presentation of results and conclusions. An element of assessment will be for a sensible and logical graphical presentation of the model in Witness.