Simulation of Plant Scale Manufacturing

7/29/2019 Simulation of Plant Scale Manufacturing

1/6

Timothy Chege, 2061182

MSc Product Design Engineering

Advanced Manufacture Assignment 1

SIMULATION OF PLANT-SCALE MANUFACTURING

Introduction

The simulation of plant-scale manufacturing is the technical activity of modelling and virtually

executing a collective system of manufacturing and assembly processes in a manufacturing

and assembly plant by use of computer software packages. This activity allows manufacturing

engineers, plant designers and/or process planners to determine how efficient and viable a

system of manufacturing and assembly operations will be even before physically building the

system. Through this evaluation the manufacturing engineers, plant designers and/or process

planners can improve and optimise the model of the system before building it. The activity of

plant-scale manufacturing simulation also enables the manufacturing engineers, plant designers

and/or process planners to design the layout of a manufacturing plant so that the layout of the

plant is of optimised and efficient production.

1. State-of-the-Art Plant-Scale Simulation

Today there are various types of simulation processes and software packages used collectively

to simulate plant-scale manufacturing. Which process and software package used is determined

by the manufacturing processes used in the plant, as each of the simulation processes is best

suited for particular manufacturing processes. These simulation processes are discussedhereafter:

1.1. Discrete-Event Simulation

A discrete-event simulation model is both stochastic and dynamic with the special discrete-

event property that the system state variables change value at discrete times only (Leemis &

Park, 2004). This method is therefore more suitable for simulating processes whereby changes

in variables only occur at particular points in time. An example of such processes would be

inventory changes. The inventory in a warehouse does not change throughout time but only

when a purchase is made, or when the stock is replenished.

1.1.1. SimPy

SimPy is a popular open-source discrete-event simulation package. It is an object-oriented

package with the process variables required to build the simulation of their plant. It also has the

capability of Graphical-User-Interface building that allows the user to create an easier to use


2/6

simulation model. See Figure 1:

Figure 1: A helpdesk model for simulation in Simpy (http://onlamp.com)

1.2. Continuous Simulation

Continuous simulation is concerned with modeling a set of equations, representing a system,

over time (McHaney, 2009). Therefore, unlike discrete-event simulation; continuous simulation

is most suitable for simulating systems with variables that are constantly changing with time. An

example of a process with continuously changing variables is weather. Whereby variables such

as temperature, humidity, e.t.c change throughout time.

1.2.1. Simcad Pro

Simcad Pro is a commercial continuous simulation software package widely used in

manufacturing plants. It is ideal for purposes of simulating continuous processes such as

assembly lines. The software allows the user to build a simulation package with ease through its

Graphical-User-Interface. See Figure 2:


3/6

Figure 2: Simulation of an assembly line in Simcad Pro (http://manufacturingsimulation.com)

1.3. Monte Carlo Simulation

Monte Carlo simulation, the name given by John van Neumann and Stanislaw M.Ulam to

reflect its gambling similarity, utilizes models of uncertainty where representation of time is

unnecessary (Albrecht, 2010). Therefore unlike continuous simulation and discrete-event

simulation; In Monte Carlo Simulation the inclusion of time as a variable is not required as the

occurrence of the relevant events are random and not in a particular time or constant time. This

method is widely used for risk management, as risk factors are variables of uncertainty. For

example, what the success of a product to be launched by a manufacturer would be is unknown

and can therefore only be simulated through the methods such as the Monte Carlo simulation

method.

1.3.1. GoldSim

GoldSim is a commercial simulation software package that supports the simulation of uncertain

events in risk analysis. The software package uses the Monte Carlo simulation method to

compute uncertain variables in the simulation model of a particular system and/ or process. It is

therefore ideal for simulating designs, layouts and processes with the aim of managing risk. See

Figure 3:


4/6

Figure 3: Simulation of uncertain events in GoldSim (http://ids-environment.com)

2. Possible Future Developments

2.1. Simulation of Rapid Prototyping Methods

Rapid prototyping methods such as additive layer manufacturing are gaining popularity and

are being further developed to increase their performance and more-so speed. Many are

forecasting a future whereby rapid prototyping methods will be fast and reliable enough to

adopted for batch manufacturing. Therefore, the field of process simulation could be of great

use in contributing to the achievement of this future whereby methods such as additive layer

manufacturing is used as the means of manufacturing a variety of day to day goods by largeplants. Manufacturing engineers can use simulation to analyse rapid prototyping methods and

uncover ways of making them more reliable and fast enough for mainstream manufacturing.

See Figure 4:


5/6

Figure 4: The popular Makerbot Replicator 3D Printer (http://makerbot.com)

2.2. Simulation for Ecological Sustainability

Traditionally, plant-scale simulation has mainly been used with the aim of designing reliable,

cost-effective and speedy plant layouts and manufacturing processes. This is because, speed,

reliability, running costs, and plant safety have been the main concerns of the corporations.

However, ecological sustainability is a growing concern for corporations today and will become

even more pressing in the future. Therefore, plant simulation can be exploited with the aim

of improving manufacturing plants ecological sustainability. Manufacturing engineers can

simulate the manufacturing processes in plants and with the results optimise the processes for

production of goods with a minimised carbon footprint.

Conclusion

As discussed in these report, there are various simulation processes suited for different

manufacturing processes. Therefore, to carry out plant-scale manufacturing simulation there are

three options:


6/6

1. Use a collection of process dedicated simulation software for the different manufacturing

assembly processes in the plant

2. Use hybrid simulation software for all of the manufacturing and assembly processes in

the plant

3. Use a combination of process dedicated and hybrid simulation software accordingly for

the manufacturing and assembly processes in the plant

The use of hybrid simulation software would probably the most cost-effective, least time

consuming, and least human resource dependent of the three options. An example of such a

software is Envision by Dassault Systems and Delmia Corporation. This simulation package

can simulate almost if not all of an entire assembly line with inclusion of human operators

represented as manikins in its graphical user interface system.

Bibliography

1. Albrecht, M. C., Introduction to Discrete Event Simulation, 2010

2. Kalpakjian, S., Schmid, S. R., Manufacturing Processes for Engineering Materials, 2003

3. Leemis, L., Park, S., Discrete-Event Simulation: A First Course, 2004

4. McHaney, R., Understanding Computer Simulation, 2009, Ventus Publishing ApS

Documents

Simulation of Plant Scale Manufacturing