Facilities Planning Manufacturing Layout Bob Devine & Ed Foerster

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Facilities Planning
A Simulation Study of a Flow Shop Vs. a Job Shop
Manufacturing Layout
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
The Flow Shop (Product Layout)
Characterized by:
• Product-oriented layout composed mainly of a few lines.
• Specialized equipment dedicated to the manufacture of a particular product is used.
• Processing and Assembly facilities are analyzed in accordance with the products’ sequence of operations.
Advantage:
• Can have very high production rates
Disadvantage:
• Investment is high in the specialized machine.
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
The Flow Shop (Product Layout) - Continued
[Talk about the diagram here]
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
The Job Shop (Process Layout)
Characterized by:
• Functional design
• Variety of products manufactured
• Performs a wide variety of manufacturing processes
• General Purpose production equipment, grouped according to the type of manufacturing process (i.e. the
lathes are in one department, saws in another, and mill in another)
Advantage:
• Ability to make a wide variety of products
Disadvantage:
• Parts can spend an exuberant amount of time waiting or being transported.
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
The Job Shop (Process Layout) - Continued
[Talk about the diagram here]
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
Problem Formulation & Objectives
• At issue is the best layout for a proposed plant that will be manufacturing 3 different types of
specialty parts for the automotive industry (i.e. gears, pistons, valves).
• A job shop with a process layout will be compared to a flow shop with a product layout.
• Performance parameters will include:
- Machine Utilization (% Empty and % Partially Occupied).
- Work in Process.
- Throughput.
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
Model Conceptualization & Translation Flow Shop
Data Assumptions: (Ideally based on the collection of reliable data and correct statistical
analysis)
• Arrivals of unfinished parts from the foundry follow a triangular distribution.
• Source times follow a normal distribution.
• The normal distribution was chosen because it is often used to model the distribution of a process which
can be thought of as the sum of a number of component processes.
• Parts are assumed to move along linear paths between departments.
Structural Assumptions: (Involve simplifications and abstractions from reality)
• Elements that would be common to both layouts and would not be dependent upon the plant layout were
omitted.
• Breaks, shift changes, and equipment malfunctions would occur regardless of which plant was employed
and were therefore not factored in the simulation.
• The plant operates 7 days a week for 3 shifts/day.
• A machinist is always available to transport the finished parts between stations.
• Parts wait a particular location until a specified number accumulates and then transported as one unit.
• Machines are considered to be “dedicated.”
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
Model Conceptualization & Translation Job Shop
Data Assumptions: (Ideally based on the collection of reliable data and correct statistical
analysis)
• Arrivals of unfinished parts from the foundry have the same arrival and service times distributions as the
flow shop.
•Parts are assumed to move along linear paths between departments based on estimates of the proposed
plant layout specified in the flow diagram.
• The time required to convert a machine over from processing gears to pistons and vice versa follows a
normal distribution with a mean of 10 minutes and a standard deviation of 2 minutes.
Structural Assumptions: (Involve simplifications and abstractions from reality)
• Same assumptions as the flow shop except:
- Machining stations are no longer considered “dedicated.”
- Pistons have a higher priority than gears.
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
Data Collection
Difficulties Encountered:
1. Unable to attain viable data for the desired manufacturing processes.
2. Data which was obtained from Niebels’ “Time and Motion Study” (1972) was specific: cutting times
were based on factors such as the lubrication used, the type of material being cut, the number of revolutions
per minute of the blade, and the feed rate of the material.
3. The summation of these “tolerances” would have compounded the estimation error which would be
introduced by the assumption of a normally distributed processing time with a specified standard deviation.
4. Normal distribution was selected because it often used to model the distribution of a process which can be
thought of as the sum of a number of component processes (mentioned earlier).
5. The triangular distribution was chosen to model the arrival time of parts from the foundry because this
process was thought to be relatively constant plus or minus a small amount.
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
Verification and Validation
• Validation is the overall process of comparing the model and its behavior with the real
system.
• If the system is in the planning stages and no system operating data can be collected,
complete input-output validation is not possible. (DESS, 410)
• An iterative process was employed to troubleshoot the model.
• The model was broken down into its constituent parts; yet, viable results were not achieved.
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
Experimental Design
• Both models are considered to be non-terminating systems because they are trying to
represent steady-state behavior. (DESS, 436)
• One simulation run consisting of 14 replications (R) with each being 336 hours in duration
- Used the formulas for determining R for a terminating system from data points after 5
replications - justified. (DESS, 462)
- Runs of 168, 336, and 672 hours used to simulate steady-state.
- No change between 336 and 672 hours.
• Specifications:
- 95% Confidence Interval
- Standard Criterion = 0.005
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
Conclusion
• Two models were compared: Flow Shop & Job Shop.
• Both models need further refinement.
• This is part of the iterative process of modeling.
• While it is essential to identify when your models accurately reflect reality, it is of equal
importance to be cognizant of the fact when your models are somewhat flawed and are in need
of further production runs and analysis.
Bob Devine & Ed Foerster
“Simulation & Modeling”
Term Project
December 7, 1999
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