Abstract:
This thesis investigates the effectiveness (doing the right thing) and efficiency (doing
the thing right) of computer-based discrete-event simulation for designing
manufacturing systems. This investigation looked at the use of this technology in the
manufacture of discrete
components in aerospace, automotive and consumer electrical
(white goods) industries and for material handling (warehousing). Continuous and
quasi-continuous manufacture have not been investigated and hence, the conclusions of
this thesis cannot be
generalised to cover these areas.
Working hypotheses were developed and tested which looked at how discrete-event
simulation influences the
understanding of, confidence in and credibility of a system's
design. Testing these working hypotheses lead to conclusions about how discrete-event
simulation affects the quality of decision making and the lead-time to develop,
commission and ramp-up a manufacturing facility. The following five factors were
identified as
influencing the efficiency of delivery of discrete-event simulation:
l.
Management of the simulation study and its intended benefits.
2.
Management of customers' expectations.
3. Use of geometric animation.
4. Validation and
establishing credibility.
5. How simulation's effectiveness varies over the life of a manufacturing
system development project.
A
qualitative research methodology was employed to test these working hypotheses and
to
explore these efficiency factors. Twenty-three research subjects, in twelve companies,
were drawn from the
following three groups:
°
Modellers
(who provide the modelling service).
°
Team members
(who are closely involved with supporting the execution of a
simulation study).
Senior decision makers (who are not closely involved with the execution of the
study, but who review its findings).
A
good practice model was developed for the efficient acquisition and application of the
technology. This model consists of the following six elements:
1.
Establishing and maintaining a DES modelling capability in the organisation.
2.
Knowing whether to use DES modelling for this manufacturing system and
when.
3.
Defining the study's objectives and their means of measurement.
4.
Specify responsibilities for supporting the study and implementing its
findings.
5. There is no improvement in the effectiveness of DES modelling in using 2D
rather
than 3D geometric animation.
6. 3D
geometric animation can increase the efficiency of a study, if used
appropriately.
Conclusions were made about the effectiveness of discrete-event simulation, how the
above mentioned factors influence its efficiency of delivery and how to implement the
good practice model.