In application of industrial philosophies like lean principles and

In production environment simulation and optimization
of system is done by taken some assumptions from the philosophies. With more
increased in complexity of the today’s production design and manufacturing
robust, more optimal approaches and tools required to support the design and
manufacturing of product. In recent years the simulation based optimization in
production systems are implemented by application of industrial philosophies
like lean principles and theory of constraints. By using simulation tools in
production systems based on multi-objective optimization targeting variables
e.g., throughput, buffers, and work-in-process has been proven very strong concept.
Simulation and optimization has potential to create optimal solution analysis
and decision support (Leif Pehrsson, 2011). The potential of applying
simulation and optimization tools in production environment can take factors
like productivity and financial for making decision, has been very beneficial
to industrial applications.  

From the book of factory physics, developing a science
of manufacturing system not a tiny job. It is as hard applying this science to
solve production problems. System approach is regarded as helpful approach for
any process (Wallace J.Hopp, 2000). System analysis is a structured approach
for problem solving characterised by five steps includes a system view,
means-ends analysis, creative alternative generation, modelling and
optimization and iteration. To compare objectives of a system a kind of tool or
qualification is required. Modelling and optimization is the tool for that
mathematical modelling of each variables and choosing minimum possible cost.
The approximate level varies depending on complexity of the problem and
magnitude of potential impact of actions. In every system analysis, variables,
objectives, model and other are repeatedly revised. It’s due to complexity of
system to avoid errors and rejections. The user is able to build simple models i.e.
using fixed lead time variables, perspective models for instance capacitated
scheduling problems using conveyer models, accounting models and production
planning. It is easy to implement tactical and strategic modelling in simulation
since it not reality. It is intended to assist design the model depending on
appropriate formulation. In this model parameters are assumed as constraints
for the tactical decision making which is often subjected to strategic level. There
are many uncertainties in manufacturing management includes demand fluctuations,
variable yield loss, machine break downs disruption in materials procurement
and so on. These can be represented in simulation which saves time and money. In
traditional management only gives unrealistic due dates for the customers when
they order the products. It may be delayed due to detractors such as setup
times, operator efficiency, and machine failure etc. In other hand they measure
throughput, cycle time and Work-in-process WIP are difficult to deal with. For
this problem scientific approach is gives best solution by including all such
factors using simulation.

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After 1980’s the attention has been drawn to
importance of bottlenecks in production environment (Goldratt, 1984). In this discussion
certainly occurred bottlenecks are very important since it blocks the line
capacity. To get the good performance of the production system the experiment
is run, analyse the result and then arrange the process depending on production
philosophies such as theory of constraints. By using optimization user is able
to visualize the different results and are chosen best desired solution from
the set of solutions. Depending on the required output system variables are
taken in to account and modelling is done with one which has best performance.  Cause of bottlenecks will creates loss in
money, increase in cycle time and excessive inventories. Simulation and
optimization with the help of TOC gives solution for this problem to analyse
and shift the bottlenecks one after other (Goldratt, 1984). Modelling a system
based on TPS and lean principles which including variables such as Kanban and arranging
of shop floor and increase of variants helps to attain attractive results. The
scientific approach theory is based on F.W.Taylor which is applicable here to
create a modelling and simulation tool to avoid physical waste, save time and increases
productivity by analysing the systems performance in optimizer. For lean
enterprise integrated tools and integrated development and other tools are very
important. Lean principles with engineering optimization concepts give faster
and more efficient designs. From the lean principles push type production
system is easy to simulate and pull much is complex system. The new
computational techniques are developed which can express production control
parametrically makes easy with simulation based optimization. Lean practitioners
will be able to make decisions easier, cheaper by saving time. Not only in
production simulation and optimization use in product development in
combination with lean principles drives organisation in better position in
terms of results.