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Some
Models on Value of Information Sharing in Supply Chain Management
--
S P Sarmah, D Acharya and S K Goyal
The
recent advancement of information technology has helped the
partners of supply chains to share information with each other.
But the frequently raised question is about the benefits that
can be gained through such sharing of information. In the
supply chain literature, different models have been developed
in recent times to study the value of information sharing.
In this paper, the models dealing with benefits accrued due
to information sharing between the partners of a supply chain
have been reviewed and classified. An effort has also been
made to identify the critical issues and the scope for future
research.
©
2006 IUP . All Rights Reserved.
Impact
of Focused Improvement and
Autonomous Maintenance on OEE: A Study
--
Anil
S Badiger and R Gandhinathan
Focused
(continuous) improvement is an essential requirement for sustaining
and gaining a competitive advantage for organizations. A successful,
continuous improvement program is one wherein operational
defects are eliminated at the root cause level and are prevented
from reoccurring. It is necessary that employees at all levels
of an organization are involved in problem-solving activities,
and select and incorporate the changes that will eliminate
the defects at the root level to prevent from reoccurrance.
Organizations can increase productivity, reduce downtime,
and increase profit. This is possible through the necessary
cultural changes and involvement of the workforce eliminating
equipment failures. A comprehensive root cause analysis tool
is necessary to provide organizations with an effective, systematic
and consistent process for individuals and teams. The 5-Why
root cause analysis (RCA) technique is a practical and proven
tool for elimination of root causes. This method can be used
to solve the one-off problems and improve the existing conditions.
This paper reports the benefits of using a systematic approach
to problem-solving demonstrated by a case study in a manufacturing
company. It is noted here that the Overall Equipment Effectiveness
(OEE) of the equipment has improved from 34% to 65%.
©
2006 IUP . All Rights Reserved.
Metaheuristic
Strategies for Nonlinear Multi-response Grinding Process Optimization
-- Indrajit
Mukherjee and Pradip Kumar Ray
The
nonlinear multi-response grinding process is too difficult
to optimize due to a large number of interacting process variables.
Conventional experimentation techniques such as factorial
designs, evolutionary operations, response surface methodology
(RSM), and the Taguchi method may not be implementable or
economical for many types of mass production lines involving
grinding, boring, turning and other necessary operations.
Particular, for the grinding processes, in the absence of
a reliable and generalized mechanistic (analytical) model
that is applicable in varied situations, researchers and practitioners
in general prefer empirical modeling (static or dynamic) technique(s)
to understand the inherent complex characteristics of the
grinding processes. In this context, a simple and easy-to-implement
modeling and optimization technique for grinding processes
in mass production lines is a prime necessity. The potential
of the nonlinear multivariate Artificial Neural Network (ANN)
technique and metaheuristic search strategies needs to be
explored, either in their original form or in the form of
their variants. In this paper, an integrated approach of ANN,
the composite desirability function, and the metaheuristic
strategy is proposed for modeling and optimizing the parameters
of the grinding processes. Independent computational run results
based on two different metaheuristicsreal-valued genetic algorithm
(RGA) and simulated annealing (SA)show that RGA is more efficient
to determine multiple near-optimal (approximate) solutions
[in terms of sample mean of the overall fitness (objective)
measure], that is less likely to be trapped in local optimal,
and which requires comparatively less computational time as
compared to SA.
©
2006 IUP . All Rights Reserved.
Variability
of a Manufacturing Process and its Economic Loss
--
M
S Prabhuswamy and P Nagesh
This
article provides an extensive discussion on quantifying the
variability of a manufacturing process with the objectives
and advantages of reducing variability in a manufacturing
process. The process capability analysis is used to quantify
the variability of a process. The Taguchi loss function approach
is used to relate the variability and economic loss. Computation
of various process capability ratios is carried out, which
are evaluated and tested with respect to process centering.
The process capability ratios are tested with confidence intervals.
The hypothesis about the process capability ratio is carried
out to demonstrate whether the process capability ratio (Cp)meets
or exceeds the target value. The process capability analysis
helps in quantifying the process variability and assists manufacturing
by eliminating or greatly reducing the variability.
©
2006 IUP . All Rights Reserved.
Case
Study
Project
ScorpioThe Making of India's First Indigenous Sports Utility
Vehicle -- Shirisha Regani
©
2005 ICMR. All Rights
Reserved. For accessing and procuring the case study, log
on to www.icmrindia.org or www.ecch.cranfield.ac.uk |
