Abstract: Human Resource (HR) applications can be used to
provide fair and consistent decisions, and to improve the
effectiveness of decision making processes. Besides that, among
the challenge for HR professionals is to manage organization
talents, especially to ensure the right person for the right job at the
right time. For that reason, in this article, we attempt to describe
the potential to implement one of the talent management tasks i.e.
identifying existing talent by predicting their performance as one of
HR application for talent management. This study suggests the
potential HR system architecture for talent forecasting by using
past experience knowledge known as Knowledge Discovery in
Database (KDD) or Data Mining. This article consists of three
main parts; the first part deals with the overview of HR
applications, the prediction techniques and application, the general
view of Data mining and the basic concept of talent management
in HRM. The second part is to understand the use of Data Mining
technique in order to solve one of the talent management tasks, and
the third part is to propose the potential HR system architecture for
talent forecasting.
Abstract: When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.
Abstract: The supply chains (SCs) have to appeal to new management paradigms to improve their ability to respond rapidly and cost effectively to unpredictable changes in markets and increasing levels of environmental turbulence, both in terms of volume and variety. In this highly demanded context, the Agile paradigm provides the capabilities to SC quickly adapt to changes in the market requirements. The purpose of this paper is to suggest an Agile Index to assess the agility of the automotive companies and corresponding SCs. The proposed integrated assessment model incorporates Agile practices weighted according to their importance to the automotive SC competitiveness and obtained from the Delphi technique.
Abstract: Normally business changes are made in order to
change a level of activity in some way, whether it is sales, cash flow,
productivity, or product portfolio. When attempts are made to make
such changes, too often the business reverts to the old levels of
activity as soon as management attention is diverted. Risk
management is a field of growing interest to project managers as well
as in general business and organizational management. There are
several approaches used to manage risk in projects and this paper is a
brief outline of some that you might encounter, with an indication of
their strengths and weaknesses.
Abstract: Augmented Reality (AR) shows great promises for
its usage as a tool for simulation and verification of design proposal
of new technological systems. Main advantage of augmented reality
application usage is possibility of creation and simulation of new
technological unit before its realization. This may contribute to
increasing of safety and ergonomics and decreasing of economical
aspects of new proposed unit. Virtual model of proposed workcell
could reveal hidden errors which elimination in later stage of new
workcell creation should cause great difficulties. Paper describes
process of such virtual model creation and possibilities of its
simulation and verification by augmented reality tools.
Abstract: A manufacturing feature can be defined simply as a
geometric shape and its manufacturing information to create the shape.
In a feature-based process planning system, feature library plays an
important role in the extraction of manufacturing features with their
proper manufacturing information. However, to manage the
manufacturing information flexibly, it is important to build a feature
library that is easy to modify. In this paper, a Wiki-based feature
library is proposed.
Abstract: Activity-Based Costing (ABC) which has become an important aspect of manufacturing/service organizations can be defined as a methodology that measures the cost and performance of activities, resources and cost objects. It can be considered as an alternative paradigm to traditional cost-based accounting systems. The objective of this paper is to illustrate an application of ABC method and to compare the results of ABC with traditional costing methods. The results of the application highlight the weak points of traditional costing methods and an S-Curve obtained is used to identify the undercosted and overcosted products of the firm.
Abstract: A Decision Support System/Expert System for stock
portfolio selection presented where at first step, both technical and
fundamental data used to estimate technical and fundamental return
and risk (1st phase); Then, the estimated values are aggregated with
the investor preferences (2nd phase) to produce convenient stock
portfolio.
In the 1st phase, there are two expert systems, each of which is
responsible for technical or fundamental estimation. In the technical
expert system, for each stock, twenty seven candidates are identified
and with using rough sets-based clustering method (RC) the effective
variables have been selected. Next, for each stock two fuzzy rulebases
are developed with fuzzy C-Mean method and Takai-Sugeno-
Kang (TSK) approach; one for return estimation and the other for
risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation
method. In parallel, for fundamental expert systems,
fuzzy rule-bases have been identified in the form of “IF-THEN" rules
through brainstorming with the stock market experts and the input
data have been derived from financial statements; as a result two
fuzzy rule-bases have been generated for all the stocks, one for return
and the other for risk.
In the 2nd phase, user preferences represented by four criteria and
are obtained by questionnaire. Using an expert system, four estimated
values of return and risk have been aggregated with the respective
values of user preference. At last, a fuzzy rule base having four rules,
treats these values and produce a ranking score for each stock which
will lead to a satisfactory portfolio for the user.
The stocks of six manufacturing companies and the period of
2003-2006 selected for data gathering.
Abstract: This study was aimed for investigating of
manufacturing high aluminum content Mg alloys using a horizontal
twin roll caster. Recently, weight saving has been key issues for lighter
transport equipments as well as electronic component parts. As
alternative materials to aluminum alloys, developing magnesium alloy
with higher strength has been expected. Normally high Aluminum
content Mg alloy has poor ductility and is difficult to be rolled because
of its high strength. However, twin roll casting process is suitable for
manufacturing wrought Mg alloys because materials can be cast
directly from molten metal. In this study, manufacturing of high
aluminum content magnesium alloy sheet using the roll casting
process has been carried out. Effects of manufacturing parameter, such
as roll velocity, pouring temperature and roll gap, on casting was
investigated. A microscopic observation of the crystals of cross section
of as cast strip as well as rolled strip was conducted.
Abstract: The current trend of increasing quality and demands
of the final product is affected by time analysis of the entire
manufacturing process. The primary requirement of manufacturing is
to produce as many products as soon as possible, at the lowest
possible cost, but of course with the highest quality. Such
requirements may be satisfied only if all the elements entering and
affecting the production cycle are in a fully functional condition.
These elements consist of sensory equipment and intelligent control
elements that are essential for building intelligent manufacturing
systems. The intelligent manufacturing paradigm includes a new
approach to production system structure design. Intelligent behaviors
are based on the monitoring of important parameters of system and
its environment. The flexible reaction to changes. The realization and
utilization of this design paradigm as an "intelligent manufacturing
system" enables the flexible system reaction to production
requirement as soon as environmental changes too. Results of these
flexible reactions are a smaller layout space, be decreasing of
production and investment costs and be increasing of productivity.
Intelligent manufacturing system itself should be a system that can
flexibly respond to changes in entering and exiting the process in
interaction with the surroundings.
Abstract: A pilot project was carried out in 2007 by the senior
students of Cyprus International University, aiming to minimize the
total cost of waste collection in Northern Cyprus. Many developed
and developing countries have cut their transportation costs – which
lies between 30-40% – down at a rate of 40% percent, by
implementing network models for their route assignments.
Accordingly, a network model was implemented at Göçmenköy
district, to optimize and standardize waste collection works. The
work environment of the employees were also redesigned to provide
maximum ergonomy and to increase productivity, efficiency and
safety. Following the collection of the required data including waste
densities, lengths of roads and population, a model was constructed
to allocate the optimal route assignment for the waste collection
trucks at Göçmenköy district.
Abstract: This paper presents an experimental investigation on
the machinability of laser-sintered material using small ball end mill focusing on wear mechanisms. Laser-sintered material was produced
by irradiating a laser beam on a layer of loose fine SCM-Ni-Cu powder. Bulk carbon steel JIS S55C was selected as a reference steel.
The effects of powder consolidation mechanisms and unsintered
powder on the tool life and wear mechanisms were carried out. Results indicated that tool life in cutting laser-sintered material is
lower than that in cutting JIS S55C. Adhesion of the work material and chipping were the main wear mechanisms of the ball end mill in
cutting laser-sintered material. Cutting with the unsintered powder
surrounding the tool and laser-sintered material had caused major fracture on the cutting edge.
Abstract: This paper presents a cold chain monitoring system which focuses on assessment of quality and dynamic pricing information about food in cold chain. Cold chain is composed of many actors and stages; however it can be seen as a single entity since a breakdown in temperature control at any stage can impact the final quality of the product. In a cold chain, the shelf life, quality, and safety of perishable food throughout the supply chain is greatly impacted by environmental factors especially temperature. In this paper, a prototype application is implemented to retrieve timetemperature history, the current quality and the dynamic price setting according to changing quality impacted by temperature fluctuations in real-time.
Abstract: In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used standard sets of instances from the project scheduling problem library (PSPLIB). The results are computationally compared respect to different metrics taken from the literature on evolutionary multi-objective optimization.
Abstract: In recent years, an increased competition and lower profit margins have necessitated a focus on improving the performance of the product development process, an area that traditionally have been excluded from detailed steering and evaluation. A systematic improvement requires a good understanding of the current performance, wherefore the interest for product development performance measurement has increased dramatically. This paper presents a case study that evaluates the performance of the product development performance measurement system used in a Swedish company that is a part of a global corporate group. The study is based on internal documentation and eighteen in-depth interviews with stakeholders involved in the product development process. The results from the case study includes a description of what metrics that are in use, how these are employed, and its affect on the quality of the performance measurement system. Especially, the importance of having a well-defined process proved to have a major impact on the quality of the performance measurement system in this particular case.
Abstract: Innovational development of regions in Russia is generally faced with the essential influence from federal and local authorities. The organization of effective mechanism of innovation development (and self-development) is impossible without establishment of defined institutional conditions in the analyzed field. Creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The paper presents an analysis of institutional conditions in the field of creation and development of innovation activity infrastructure and transferring of knowledge and skills between different economic agents in Russia. Knowledge is mainly privately owned, developed through R&D investments and incorporated into technology or a product. Innovation infrastructure is a strong concentration mechanism of advanced facilities, which are mainly located inside large agglomerations or city-regions in order to benefit from scale effects in both input markets (human capital, private financial capital) and output markets (higher education services, research services). The empirical results of the paper show that in the presence of more efficient innovation and knowledge transfer and transcoding system and of a more open attitude of economic agents towards innovation, the innovation and knowledge capacity of regional economy is much higher.
Abstract: As there has been a recognizable transition in
automotive industry from mass production to mass customization,
automobile manufacturers and their suppliers have been seeking ways
for more flexible and efficient processes. Eventually, modular
production is currently being applied to manage the changing orders of
the industry. In this paper, two different modular assembly line
concepts were studied: conveyor line and box assembly line.
Mathematical model for two assembly line concepts were developed
and their production line efficiency were compared as a performance
measure to improve their assembly line balancing.
Abstract: The network of delivering commodities has been an important design problem in our daily lives and many transportation applications. The delivery performance is evaluated based on the system reliability of delivering commodities from a source node to a sink node in the network. The system reliability is thus maximized to find the optimal routing. However, the design problem is not simple because (1) each path segment has randomly distributed attributes; (2) there are multiple commodities that consume various path capacities; (3) the optimal routing must successfully complete the delivery process within the allowable time constraints. In this paper, we want to focus on the design optimization of the Multi-State Flow Network (MSFN) for multiple commodities. We propose an efficient approach to evaluate the system reliability in the MSFN with respect to randomly distributed path attributes and find the optimal routing subject to the allowable time constraints. The delivery rates, also known as delivery currents, of the path segments are evaluated and the minimal-current arcs are eliminated to reduce the complexity of the MSFN. Accordingly, the correct optimal routing is found and the worst-case reliability is evaluated. It has been shown that the reliability of the optimal routing is at least higher than worst-case measure. Two benchmark examples are utilized to demonstrate the proposed method. The comparisons between the original and the reduced networks show that the proposed method is very efficient.
Abstract: This paper deals with the project selection problem. Project selection problem is one of the problems arose firstly in the field of operations research following some production concepts from primary product mix problem. Afterward, introduction of managerial considerations into the project selection problem have emerged qualitative factors and criteria to be regarded as well as quantitative ones. To overcome both kinds of criteria, an analytic network process is developed in this paper enhanced with fuzzy sets theory to tackle the vagueness of experts- comments to evaluate the alternatives. Additionally, a modified version of Least-Square method through a non-linear programming model is augmented to the developed group decision making structure in order to elicit the final weights from comparison matrices. Finally, a case study is considered by which developed structure in this paper is validated. Moreover, a sensitivity analysis is performed to validate the response of the model with respect to the condition alteration.
Abstract: Hydrogen sulfide (H2S) is a very toxic gas that is produced in very large quantities in the oil and gas industry. It cannot be flared to the atmosphere and Claus process based gas plants are used to recover the sulfur and convert the hydrogen to water. In this paper, we present optical characterization of an atmospheric pressure microwave plasma torch for H2S dissociation into hydrogen and sulfur. The torch is operated at 2.45 GHz with power up to 2 kW. Three different gases can simultaneously be injected in the plasma torch. Visual imaging and optical emission spectroscopy are used to characterize the plasma for varying gas flow rates and microwave power. The plasma length, emission spectra and temperature are presented. The obtained experimental results validate our earlier published simulation results of plasma torch.