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To cope with the growing
complexity in the real manufacturing environment, developing
realistic yet not too complex mathematical models plays an
important role in decision making at the operational level.
In this issue, three of the five articles have been devoted
to three such models in the areas of `inventory', `job-shop
scheduling', and `transportation of materials'.
In
the paper, "Order Level Lot Size Inventory Model for
Weibull Distributed Deteriorating Units Having Salvage Value
with Price Breaks", the authors, Nita H Shah, Poonam
Pandey and Ravi Gor have developed a deterministic inventory
model, taking into account the price breaks and partial backordering
when the units in inventory are subject to deterioration with
time following a Weibull distribution having salvage value.
A numerical example has been given by the authors to validate
the mathematical model they have developed which would be
useful particularly to retailers who encounter such situations.
Job-Shop
Scheduling is often a very complex situation to optimize,
and the paper, "Powers of Two-Based Heuristic for Job-Shop
Scheduling" by V Mahesh, Sandeep Dulluri, A Chennakesava
Reddy and C S P Rao deals with a real time scheduling problem
of a turbine manufacturer. As a job-shop scheduling problem
with the makespan minimization criterion is a non-deterministic
polynomial type of optimization problem, conventional optimization
algorithms cannot be effectively applied. This paper proposes
a heuristic, based on the powers-of-two-policy in inventory,
for solving the minimum makespan problem. The proposed heuristic
is easy to implement and can be adapted to various industrial
settings for decision making.
The
paper, "Development of Optimum Transportation Plan from
Raw Coal Feed to Washeries of a Coal Producing Company Using
Stochastic Programming Approach" by Chandan Bhar deals
with finding the optimum transportation routes for allocating
production of various plants to several warehouses. In a transportation
model, the parameters of the system are assumed to be deterministic,
whereas in real life situations, the values of the parameters
are random in nature. The author has used stochastic techniques
to determine the optimum route for transportation. In this
paper the model has been applied for transportation of coal
from 15 collieries to two washeries of a coal producing company.
Failure
Mode and Effect Analysis is a method used to investigate and
evaluate the potential failure of a product or a process prior
to its release. For each failure mode, a team assesses the
severity, likelihood of occurrence, and its detectability.
Traditional FMEA technique has limitations when two or more
failure modes have the same risk priority number or the team
has a disagreement in the ranking scale for severity, occurrence
and detection. The paper, "Modified Method for Evaluation
of Risk Priority Number in Design FMEA" by N Sellappan
and R Sivasubramanian presents a new approach to overcome
these limitations.
The
case study on "Nestlé: Streamlining Operations"
by C Vijaya deals with how the Switzerland-based food and
beverages company was able to achieve higher profits in spite
of a business downturn mainly because of its operational reforms,
product innovations, and other strategic interventions. The
case discusses the various operational efficiency programs
and operation strategies adopted by Nestlé to counter
the difficult market conditions in Europe and to exploit the
opportunities in the developing markets.
We
hope that the articles in this issue provide useful insights
into a few thoughts and practices in the area of operations
management.
-
Sumitro Saha
Consulting
Editor
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