Page 98 - DCAP601_SIMULATION_AND_MODELING

Simulation and Modelling

Notes Monte Carlo methods originated in physics, where the integrals desired involved hydrodynamics
in complicated geometries with internal heating, i.e., designing nukes. The statisticians were
surprisingly slow to pick up on it, though by now they have, especially as “Markov chain Monte
Carlo,” abbreviated “MC Monte Carlo” (suggesting an gambling rapper) or just “MCMC”.
Along the way they picked up the odd idea that Monte Carlo had something to do with Bayesians.
In fact it’s a general technique for estimating sample distributions and related quantities, and as
such it’s entirely legitimate for frequentists. Physicists now sometimes use the term for any kind
of stochastic estimation or simulation procedure, though I think it’s properly reserved for
estimating integrals and averages.

Notes Monte Carlo simulation is a technique for iteratively estimating a deterministic
model using sets of random numbers as inputs. This method is frequently used when the
model is complex, nonlinear, or includes more than just a couple unsure parameters. A
simulation can normally involve over 10,000 evaluations of the model, a task which in the
past was only realistic using super computers.

 IT Adoption in Manufacturing

Case Study
midst all the sectors, barring probably the construction industry which is still
nascent in IT adoption, manufacturing is probably in the evolving side of the
Acurve, feels Uma Balakrishnan, CEO, Axcend Automation & Software Solutions
Pvt Ltd, Bangalore (http://bit.ly/F4TAxcend).
While retail and BFSI adopted early on, mainly because of size/scale of operations, diverse
geographies, and direct consumer interface with the using population, manufacturing has
shown a mixed trend, she observes, during the course of a recent e-mail interaction with
eWorld. Indian manufacturing enterprises that acquired global companies and turned
multinational have been early in the increased scale of adoption cycle, while smaller
entrepreneurial operations are still very nascent in IT adoption, explains Uma.
Three primary factors drive IT adoption, she elaborates: (a) Sheer size and scale that
necessitate moving into IT automated systems, as manually it becomes challenging to run
business; (b) external world in the form of clients or statutory regulatory bodies that make
the manufacturers align to some best business practices using IT systems; and (c) internal
management maturity to leverage IT and gain competitive advantage in business through
quality, cost, operational excellence, or shortened time to market with product.
Excerpts from the interview.

What are the prevalent technologies in manufacturing — especially in discrete industries
— considering that India is fast becoming a global manufacturing hub in some sectors?
Manufacturing organisations have multiple functional needs and technologies can be
broadly mapped under horizontal and vertical dimensions. Business IT enablers such as
ERP (enterprise resource planning) systems have reached a higher level of adoption as
general business IT tools of the manufacturing.

The prevalent technologies vary across functions in the organisations. At the shop floor
level, CNC (computer numerically controlled), PLC (programmable logic controls), and
HMI (human machine interface) provide the industrial automation technologies that serve
in the automated control of the physical manufacturing. Contd...

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