Simulating JIT Manufacturing: Prospects and Pitfalls
| DOI | https://doi.org/10.1108/EUM0000000001439 |
| Date | 01 July 1991 |
| Pages | 3-5 |
| Published date | 01 July 1991 |
| Author | Sylvia Bedwell‐Brace,R. Anthony Inman |
| Subject Matter | Economics,Information & knowledge management,Management science & operations |
Simulating JIT
Manufacturing:
Prospects and
Pitfalls
Sylvia Bedwell-Brace and R. Anthony Inman
SIMULATING
JIT
MANUFACTURING: PROSPECTS
AND
PITFALLS
3
Industrial Management & Data Systems, Vol. 91 No. 7, 1991, pp. 3-5
© MCB University Press Limited, 0263-5577
T
he use of computer simulation for testing
a just-in-time system is desirable to
manufacturing organisations for many
reasons.
While just-in-time (JIT) systems have been successfully
implemented in a number of organisations, some
implementations have resulted in failure. In order to
increase the likelihood that an implementation will meet
all proposed objectives and work as effectively as possible,
organisations may wish to analyse the manner in which
JIT will affect their operations before the initial investment
towards implementation is made. Computer simulation
provides a tool for organisations to test JIT systems before
implementation. The purpose of this paper is twofold.
First, the reasons for simulating JIT manufacturing and
its prospective benefits are presented. Second, the special
problems associated with the use of simulation to test a
JIT system are analysed. Specifically offered are potential
pitfalls that can occur when simulating JIT manufacturing
and guidelines for avoiding them.
Why Simulate JIT?
Organisations choose to simulate JIT manufacturing for
a variety of reasons, some externally oriented and others
internally oriented. External factors involve changes in the
computer industry and manufacturing industry in general.
Internal factors include acquisition of JIT experience,
reduction of problems brought on with systems transitions,
and feedback on JIT variables (e.g. lot sizes).
Changes in computers have contributed substantially to
the increased use of simulation. Reduced computer costs,
brought about by microcomputers and engineering
workstations, improvements in memory capacity and
processing capability and enhanced graphics have helped
to make simulation desirable for manufacturing
organisations.
Another form of external motivation for JIT simulation is
the increase in automation[l]. Automation results in
manufacturing systems that are complex and difficult to
understand. Simulation offers management a condensed
look at the "big picture"; a machine that is a bottleneck
today may not be one tomorrow. This type of overview
can be instrumental in gaining understanding of a large
and complex JIT system. For example, it could show how
an operating policy in a seemingly isolated area would affect
product flow elsewheref[l].
Many American organisations are inexperienced with JIT
manufacturing. Computer simulation will help management
and staff
to
gain some insightful JIT experience. Simulation
will involve management in a JIT system before many of
the changes required by JIT implementation are actually
made. Improved preparation, a result of simulation, can
facilitate the transition from the current system to the JIT'
system.
The planning process leading to the simulation process
provides management with the opportunity to resolve
equipment, technical system, plant layout, and philosophy
problems before the JIT implementation occurs[l]. The
cost of
a
planning mistake could be very
high[l],
so, a major
underlying advantage is the reduced cost associated with
the resolution of problems before they actually occur
within the operating JIT system. For example, AT&T,
through JIT simulation, discovered that in order to meet
capacity requirements, preventive maintenance had to be
scheduled so as not to interfere with production. Also,
they found, through simulation, that balanced production
scheduling was absolutely critical.
JIT variables include process times, set-up times,
production levels, production schedules, inventory levels,
queue lengths, buffer sizes, machine uptime/downtime,
lot sizes, conveyor speeds, preventive maintenance
scheduling, and machine repair time. Simulation allows
these variables to be easily controlled and altered. By
changing these variables, management can view the
simulated effects, thus allowing solutions to be formulated
in advance of actual implementation. Questions such as:
What capital equipment
vs.
inventory tradeoffs can be made?
What yield levels should be achieved before deployment of
efforts to other areas would prove more beneficial?
What reductions in set-up time should we try to obtain?
can be addressed prior to actual expenditure, possibly
saving thousands of dollars[l].
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