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Application of Performance Measurement on Manufacturing Simulations for Knowledge-Based Decision Support

Lorentzon, Johan LU and Fredlund, Johan LU (2017) MTT820 20171
Engineering Logistics
Abstract
Manufacturing systems are becoming increasingly more complex at the same time
as competition requires manufacturers to continuously improve their effectiveness
and efficiency. The use of discrete event simulation to model manufacturing systems
is well-established and generally considered to be the method of choice when
analysing what-if scenarios. Simulation is currently predominantly applied when
evaluating manufacturing system design and manufacturing rules and policies.
These applications studies specific attributes and dimensions of the manufacturing
system. To make full use of simulation-based decision-support in operations and
inventory management, a performance measurement system needs to established
to enable evaluation of... (More)
Manufacturing systems are becoming increasingly more complex at the same time
as competition requires manufacturers to continuously improve their effectiveness
and efficiency. The use of discrete event simulation to model manufacturing systems
is well-established and generally considered to be the method of choice when
analysing what-if scenarios. Simulation is currently predominantly applied when
evaluating manufacturing system design and manufacturing rules and policies.
These applications studies specific attributes and dimensions of the manufacturing
system. To make full use of simulation-based decision-support in operations and
inventory management, a performance measurement system needs to established
to enable evaluation of simulated scenarios.
In this study, manufacturing simulation and knowledge-based decision support
are linked to performance measurement practises used on real systems. By examining
the characteristics of manufacturing simulation applications as well as the
modelling conditions of discrete event simulation, measurable performance dimensions
on manufacturing simulations are identified. Furthermore, a proposition on
how to design a manufacturing simulation and a performance measurement system
to provide effective decision support is formulated. Based on this, the authors
present a suggestion for a manufacturing organisation on how they should develop
their simulation-based decision support system. (Less)
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author
Lorentzon, Johan LU and Fredlund, Johan LU
supervisor
organization
course
MTT820 20171
year
type
H2 - Master's Degree (Two Years)
subject
keywords
discrete event simulation, simulation, performance measurement, manufacturing, DES, production, DSS, DSSS, knowledge-based decision support, decision support, decision support system, metric, KPI, case, industrial engineering, production economics, operations, management, industry, decision, measure, performance, evaluation
report number
5838
language
English
id
8919520
date added to LUP
2017-06-28 14:32:01
date last changed
2017-06-28 14:32:01
@misc{8919520,
  abstract     = {Manufacturing systems are becoming increasingly more complex at the same time
as competition requires manufacturers to continuously improve their effectiveness
and efficiency. The use of discrete event simulation to model manufacturing systems
is well-established and generally considered to be the method of choice when
analysing what-if scenarios. Simulation is currently predominantly applied when
evaluating manufacturing system design and manufacturing rules and policies.
These applications studies specific attributes and dimensions of the manufacturing
system. To make full use of simulation-based decision-support in operations and
inventory management, a performance measurement system needs to established
to enable evaluation of simulated scenarios.
In this study, manufacturing simulation and knowledge-based decision support
are linked to performance measurement practises used on real systems. By examining
the characteristics of manufacturing simulation applications as well as the
modelling conditions of discrete event simulation, measurable performance dimensions
on manufacturing simulations are identified. Furthermore, a proposition on
how to design a manufacturing simulation and a performance measurement system
to provide effective decision support is formulated. Based on this, the authors
present a suggestion for a manufacturing organisation on how they should develop
their simulation-based decision support system.},
  author       = {Lorentzon, Johan and Fredlund, Johan},
  keyword      = {discrete event simulation,simulation,performance measurement,manufacturing,DES,production,DSS,DSSS,knowledge-based decision support,decision support,decision support system,metric,KPI,case,industrial engineering,production economics,operations,management,industry,decision,measure,performance,evaluation},
  language     = {eng},
  note         = {Student Paper},
  title        = {Application of Performance Measurement on Manufacturing Simulations for Knowledge-Based Decision Support},
  year         = {2017},
}