Industrial Management Studies

Abstract One of the trench that is used in quality desiccation is Quality
Function Deployment. One of the factors which has been used in this
method is accomplishing the house of quality and as a result is
determining the degree of importance of the customer's requirements.
Kano model is a kind of two dimensional model which help the
producers to divide the consumer's requirements in to five categories
including, basic, performance, attractive, indifferent quality and
reverse quality. In the survey by identifying the customer's
requirements we determine kind of them and then according to the
improvement ratio and the degree of importance is assigned. The
degrees of importance can be used for completing the house of quality
which is one of the useful tools in QFD. This research is public
algorithms that it can use for every product. For example it has been
used in Cement Company of larestan, product II Portland cement

Abstract Estimating the optimal number of clusters in an unsupervised
partitioning of data sets has been a challenging area in recent years.
These indices usually use two criteria called compactness and
separation to evaluate the efficiency of the performed clustering. In
this paper a new separation measure for ECAS cluster validity index,
proposed by Fazel et al. [1] is identified, which uses Jaccard distance
in order to consider the whole shape of clusters. Jaccard distance uses
the size of intersection and union of fuzzy sets, giving the cluster
validity index more information about the overlap and separation of
clusters. This property results in high robustness of the proposed index
dealing with various degrees of fuzziness in comparison with ECAS.
To test the efficiency of the proposed index in comparison with nine
other indices existing in the literature, 15 data sets (3 existing datasets
and 12 artificial data sets) have been used. Computational results
indicate robustness and high capability of the proposed index in
comparison with previous indices

Abstract In this research, we use Artificial Bee Colony (ABC) algorithm to
solve cell to switch assignment problem (CTSAP) that is NP-hard. In
CTSAP, there are cells and switches in which cells locations are
predetermined. The objective of problem is optimal assigning of cells
to switches with minimum cost. Here, we have two kinds of costs,
handoff and cabling costs. Call handling capacity for every switches
are given and equal. The model of our work is single homed that is
each cell must connect to only one switch. The mathematical model is
binary and nonlinear.
The program is coded by MATLAB 7.8.0 (R2009a). After estimating
parameters values of model, approving performance accuracy of code
and adjusting control parameters, the efficiency of algorithm by
determining experimental problems compared to Ant Colony
Optimization (ACO) that is one of the best for solving this problem.
Results show satisfactory performance of ABC algorithm

Abstract Despite the extensive use of failure mode and effects analysis (FMEA) in
the manufacturing and services, emphasis on the results of this method with
concern to the disadvantages such as providing definitive results is not
correct. This paper tries to clarify the main disadvantages of FMEA
conventional method and explain the concept of cluster analysis and
specifications of different models of C-Means to classify harmful modes and
effects in the steel making factory of Iran's alloy steel company using FMEA
and fuzzy clustering techniques. In this context, homogeneous harmful
modes and effects based on occurrence, severity and frequency indicators
with Fuzzy C-Means clustering (FCM) were identified. In this study, the
fuzzy cluster analysis in terms of before and after improvement was
performed by Data Engine 4.0 software. The results of this research will be
useful for researchers, managers, and safety professionals for developing
practical strategies in order to prevent the consequences of harmful modes
and effects

Abstract The Analytic Hierarchical Process (AHP) determines the relative
importance of a set of alternatives in a multi-criteria decision problem.
AHP has a hierarchial structure and based on pairwise comparisons of
the project alternatives as well as pairwise comparisons of the multi
criteria. Two separate algorithms have been presented for measuring
the inconsistency ratioes of pairwise comparisons matrix and
hierarchical structure. In this paper these algorithms and one of the
approximation methods, have been extended for measuring the
inconsistency ratioes and alternatives’ weights in fuzzy AHP. A
numerical example is used to illustrate these methods.

Abstract In this paper, to make flexible job shop scheduling problem (FJSP)
more realistic, an operational factor is considered in its model. This
factor, which is called optimizing total consumed electric power per
month, is known as the most important factor in calculation of the
electric cost of the industries. Considering this factor, specifically
after subsides elimination of the country, has became more important.
In addition to this objective, two other common objectives, called
complementation time and critical work load of machines, are
considered. To solve the multi-objective model, two algorithms,
called multi-objective biogeography-based optimization algorithm
(MOBBO) and multi-objective harmony search algorithm (MOHS),
are developed and introduced to scheduling area for the first time.
Finally, by developing some famous libraries of the problem,
performance of the algorithms is compared statistically

Abstract The earned value management is a powerful and important technique
in analyzing and controlling the project performance. While it allows
exact measurement of project progress, it lets corrective actions in a
timely manner. In fact, the earned value allows project managers to
find out any project time and cost deviations by calculating the
performance indices. In this paper, to improve the applicability of the
traditional earned value technique, we develop an integrated approach
by combining statistical quality control charts with traditional earned
value technique, to monitor and control project time and cost
performances. The results applied to a real construction project
compete favorly against traditional approaches