22-12-2012, 04:35 PM
Simulation for analysis of scheduling rules for a flexible manufacturing system
[attachment=44986]
Introduction
A flexible manufacturing system (FMS), through a
careful combination of computer control, communications,
manufacturing processes and related equipment,
enables a section of the production-oriented aspects of an
organization to respond rapidly and economically, in an
integrated manner, to significant changes in its operating
environment. Such systems typically comprise: process
equipment, material handling equipment, a communications
system and a sophisticated computer control
system. Some of the advantages of FMS include:
improved capital/equipment utilization, reduced work-inprogress
and set up, substantially reduced throughput
times/lead times, reduced inventory and smaller batches,
and reduced manpower.
The high investment cost of FMS justifies the use of
computer simulation support. For example, in the
operation phase of the installed manufacturing system, it
is required to maintain high system performance by
predicting the system behaviour under any feasible
production schedule which can meet the daily production
requirements and by selecting the most effective
production schedule among the alternatives prior to its
implementation. These considerations may dictate the
use of computer simulation techniques during the design
and operation phases of FMS.
Development of the model
The simulation model
The objectives of the present simulation model include:
l To model a typical FMS system in an easy-tounderstand
programming language and to
develop a simulation model in a PC-based
environment so that the model can be used as a
pedagogical tool while teaching FMS.
l To study the effect of various loading rules at the
buffer and the workstation.
The first step in any FMS simulation study is to establish
the system configuration and then to develop a
simulation model. In this regard, keeping the objectives of
the simulation model, PASCAL has been chosen as a
programming vehicle. The advantages of using PASCAL
include:
l general purpose language;
l portability;
l de-bugging facilities available with the compiler;
l insights the analyst gets while developing the
model.
A short-term scheduling problem is attempted in this
article. Simulation methodology has been used to
examine the effect of scheduling rules. Various measures,
such as throughput, utilization, etc., are examined.
A simulation model is developed to address scheduling
rules in a typical FMS environment such as depicted in
Figure 1. This is a typical prototype of FMS with six jobs
and three workstations. The same situation could have
been very difficult to model through an analytical model.
Through simulation one can address various “what if”
scenarios. A scheduling rule is used to select a job to be
processed from a set of jobs waiting for service. These
rules can also be used to introduce workpieces into the
system, to route parts in the system and also to assign
parts to facilities. Scheduling rules may be static or
dynamic. Because of the large number of scheduling
rules, it is not obvious which scheduling rule to select in a
given environment. Thus there has been a tendency to
select a simple rule randomly (e.g. FCFS). This rule is
then hardwired into the automated FMS system.
Studies[5,6], however, have shown that the selection of the
scheduling rules can have a significant impact on system
performance.
Workstation utilization
For the given set of data, the variation in average
workstation utilization, when different scheduling rules
are applied at the loading buffer to the system, is in the
range of 95 to 99 per cent. A common trend noticed is that,
irrespective of which rule is applied at the workstation,
the lowest machine utilization is given by the SPT
(shortest processing time) rule at the loading buffer.
The EDD (earliest due date) rule also does not perform
very well. The SIO (shortest imminent operation time),
LPT (longest processing time) and FCFS (first come first
served) rules are consistently good performers.The best
performance, however, is shown by a minimum cost
based rule.
The difference in average workstation utilization by the
best rule, i.e. MINCOST and the next best rule, i.e. LPT is
statistically significant (done by a t-test) at 5 per cent
level.
Concluding remarks
The study reported in this article is only a pilot study
carried out on the FMS configured as a part of pedagogical
material being developed to understand the strength
of simulation as a modelling tool for FMS. The major
emphasis is on presenting the salient features of the FMS,
the details of the simulation model developed and the
results obtained.
[attachment=44986]
Introduction
A flexible manufacturing system (FMS), through a
careful combination of computer control, communications,
manufacturing processes and related equipment,
enables a section of the production-oriented aspects of an
organization to respond rapidly and economically, in an
integrated manner, to significant changes in its operating
environment. Such systems typically comprise: process
equipment, material handling equipment, a communications
system and a sophisticated computer control
system. Some of the advantages of FMS include:
improved capital/equipment utilization, reduced work-inprogress
and set up, substantially reduced throughput
times/lead times, reduced inventory and smaller batches,
and reduced manpower.
The high investment cost of FMS justifies the use of
computer simulation support. For example, in the
operation phase of the installed manufacturing system, it
is required to maintain high system performance by
predicting the system behaviour under any feasible
production schedule which can meet the daily production
requirements and by selecting the most effective
production schedule among the alternatives prior to its
implementation. These considerations may dictate the
use of computer simulation techniques during the design
and operation phases of FMS.
Development of the model
The simulation model
The objectives of the present simulation model include:
l To model a typical FMS system in an easy-tounderstand
programming language and to
develop a simulation model in a PC-based
environment so that the model can be used as a
pedagogical tool while teaching FMS.
l To study the effect of various loading rules at the
buffer and the workstation.
The first step in any FMS simulation study is to establish
the system configuration and then to develop a
simulation model. In this regard, keeping the objectives of
the simulation model, PASCAL has been chosen as a
programming vehicle. The advantages of using PASCAL
include:
l general purpose language;
l portability;
l de-bugging facilities available with the compiler;
l insights the analyst gets while developing the
model.
A short-term scheduling problem is attempted in this
article. Simulation methodology has been used to
examine the effect of scheduling rules. Various measures,
such as throughput, utilization, etc., are examined.
A simulation model is developed to address scheduling
rules in a typical FMS environment such as depicted in
Figure 1. This is a typical prototype of FMS with six jobs
and three workstations. The same situation could have
been very difficult to model through an analytical model.
Through simulation one can address various “what if”
scenarios. A scheduling rule is used to select a job to be
processed from a set of jobs waiting for service. These
rules can also be used to introduce workpieces into the
system, to route parts in the system and also to assign
parts to facilities. Scheduling rules may be static or
dynamic. Because of the large number of scheduling
rules, it is not obvious which scheduling rule to select in a
given environment. Thus there has been a tendency to
select a simple rule randomly (e.g. FCFS). This rule is
then hardwired into the automated FMS system.
Studies[5,6], however, have shown that the selection of the
scheduling rules can have a significant impact on system
performance.
Workstation utilization
For the given set of data, the variation in average
workstation utilization, when different scheduling rules
are applied at the loading buffer to the system, is in the
range of 95 to 99 per cent. A common trend noticed is that,
irrespective of which rule is applied at the workstation,
the lowest machine utilization is given by the SPT
(shortest processing time) rule at the loading buffer.
The EDD (earliest due date) rule also does not perform
very well. The SIO (shortest imminent operation time),
LPT (longest processing time) and FCFS (first come first
served) rules are consistently good performers.The best
performance, however, is shown by a minimum cost
based rule.
The difference in average workstation utilization by the
best rule, i.e. MINCOST and the next best rule, i.e. LPT is
statistically significant (done by a t-test) at 5 per cent
level.
Concluding remarks
The study reported in this article is only a pilot study
carried out on the FMS configured as a part of pedagogical
material being developed to understand the strength
of simulation as a modelling tool for FMS. The major
emphasis is on presenting the salient features of the FMS,
the details of the simulation model developed and the
results obtained.