Abstract: The heuristic decision rules used for project
scheduling will vary depending upon the project-s size, complexity,
duration, personnel, and owner requirements. The concept of project
complexity has received little detailed attention. The need to
differentiate between easy and hard problem instances and the
interest in isolating the fundamental factors that determine the
computing effort required by these procedures inspired a number of
researchers to develop various complexity measures.
In this study, the most common measures of project complexity are
presented. A new measure of project complexity is developed. The
main privilege of the proposed measure is that, it considers size,
shape and logic characteristics, time characteristics, resource
demands and availability characteristics as well as number of critical
activities and critical paths. The degree of sensitivity of the proposed
measure for complexity of project networks has been tested and
evaluated against the other measures of complexity of the considered
fifty project networks under consideration in the current study. The
developed measure showed more sensitivity to the changes in the
network data and gives accurate quantified results when comparing
the complexities of networks.
Abstract: Green Lean Total Quality Management (TQM)
System is a system comprises of Environmental Management System
(EMS) practices which is integrated to TQM with Lean
Manufacturing (LM) principles. The ultimate goal of this system is to
focus on achieving total customer satisfaction and environmental care by removing eight wastes available in any process in an
organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by
SPSS v.17. It was found out that some vendors have been practicing TQM and LM while some have started to implement EMS. This
study is only focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development
Program. This is the first study conducted to know the current status of TQM, LM and EMS practices in highly active automotive companies in Malaysia. It was found out that EMS has been
practiced by 16 companies out of 30. Within these 16 companies the
approach is more holistic and green. This is a preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production
System SAEJ4000, MAJAICO Lean Production System and EMS.
Abstract: Knowledge Discovery of Databases (KDD) is the
process of extracting previously unknown but useful and significant
information from large massive volume of databases. Data Mining is
a stage in the entire process of KDD which applies an algorithm to
extract interesting patterns. Usually, such algorithms generate huge
volume of patterns. These patterns have to be evaluated by using
interestingness measures to reflect the user requirements.
Interestingness is defined in different ways, (i) Objective measures
(ii) Subjective measures. Objective measures such as support and
confidence extract meaningful patterns based on the structure of the
patterns, while subjective measures such as unexpectedness and
novelty reflect the user perspective. In this report, we try to brief the
more widely spread and successful subjective measures and propose
a new subjective measure of interestingness, i.e. shocking.
Abstract: Integration of process planning and scheduling
functions is necessary to achieve superior overall system
performance. This paper proposes a methodology for integration of
process planning and scheduling for prismatic component that can be
implemented in a company with existing departments. The developed
model considers technological constraints whereas available time for
machining in shop floor is the limiting factor to produce multiple
process plan (MPP). It takes advantage of MPP while guarantied the
fulfillment of the due dates via using overtime. This study has been
proposed to determinate machining parameters, tools, machine and
amount of over time within the minimum cost objective while
overtime is considered for this. At last the illustration shows that the
system performance is improved by as measured by cost and
compatible with due date.
Abstract: Within the domain of Systems Engineering the need
to perform property aggregation to understand, analyze and manage
complex systems is unequivocal. This can be seen in numerous
domains such as capability analysis, Mission Essential Competencies
(MEC) and Critical Design Features (CDF). Furthermore, the need
to consider uncertainty propagation as well as the sensitivity of
related properties within such analysis is equally as important when
determining a set of critical properties within such a system.
This paper describes this property breakdown in a number of
domains within Systems Engineering and, within the area of CDFs,
emphasizes the importance of uncertainty analysis. As part of this, a
section of the paper describes possible techniques which may be used
within uncertainty propagation and in conclusion an example is
described utilizing one of the techniques for property and uncertainty
aggregation within an aircraft system to aid the determination of
Critical Design Features.
Abstract: Facility Layout Problem (FLP) is one of the essential
problems of several types of manufacturing and service sector. It is
an optimization problem on which the main objective is to obtain the
efficient locations, arrangement and order of the facilities. In the
literature, there are numerous facility layout problem research
presented and have used meta-heuristic approaches to achieve
optimal facility layout design. This paper presented genetic algorithm
to solve facility layout problem; to minimize total cost function. The
performance of the proposed approach was verified and compared
using problems in the literature.
Abstract: The response surface methodology (RSM) is a
collection of mathematical and statistical techniques useful in the
modeling and analysis of problems in which the dependent variable
receives the influence of several independent variables, in order to
determine which are the conditions under which should operate these
variables to optimize a production process. The RSM estimated a
regression model of first order, and sets the search direction using the
method of maximum / minimum slope up / down MMS U/D.
However, this method selects the step size intuitively, which can
affect the efficiency of the RSM. This paper assesses how the step
size affects the efficiency of this methodology. The numerical
examples are carried out through Monte Carlo experiments,
evaluating three response variables: efficiency gain function, the
optimum distance and the number of iterations. The results in the
simulation experiments showed that in response variables efficiency
and gain function at the optimum distance were not affected by the
step size, while the number of iterations is found that the efficiency if
it is affected by the size of the step and function type of test used.
Abstract: Complex engineering design problems consist of
numerous factors of varying criticalities. Considering fundamental features of design and inferior details alike will result in an extensive
waste of time and effort. Design parameters should be introduced gradually as appropriate based on their significance relevant to the
problem context. This motivates the representation of design parameters at multiple levels of an abstraction hierarchy. However, developing abstraction hierarchies is an area that is not well
understood. Our research proposes a novel hierarchical abstraction methodology to plan effective engineering designs and processes. It
provides a theoretically sound foundation to represent, abstract and stratify engineering design parameters and tasks according to causality and criticality. The methodology creates abstraction
hierarchies in a recursive and bottom-up approach that guarantees no
backtracking across any of the abstraction levels. The methodology consists of three main phases, representation, abstraction, and layering to multiple hierarchical levels. The effectiveness of the
developed methodology is demonstrated by a design problem.
Abstract: Although services play a crucial role in economy,
service did not gain as much importance as productivity management
in manufacturing. This paper presents key findings from literature
and practice. Based on an initial definition of complex services, seven
productivity concepts are briefly presented and assessed by relevant,
complex service specific criteria. Following the findings a complex
service productivity model is proposed. The novel model comprises
of all specific dimensions of service provision from both, the
provider-s as well as costumer-s perspective. A clear assignment of
identified value drivers and relationships between them is presented.
In order to verify the conceptual service productivity model a case
study from a project engineering department of a chemical plant
development and construction company is presented.
Abstract: Due to the recovering global economy, enterprises are
increasingly focusing on logistics. Investing in logistic measures for
a production generates a large potential for achieving a good starting
point within a competitive field. Unlike during the global economic
crisis, enterprises are now challenged with investing available capital
to maximize profits. In order to be able to create an informed and
quantifiably comprehensible basis for a decision, enterprises need an
adequate model for logistically and monetarily evaluating measures
in production. The Collaborate Research Centre 489 (SFB 489) at the
Institute for Production Systems (IFA) developed a Logistic
Information System which provides support in making decisions and
is designed specifically for the forging industry. The aim of a project
that has been applied for is to now transfer this process in order to
develop a universal approach to logistically and monetarily evaluate
measures in production.
Abstract: In this paper we propose a method for vision systems
to consistently represent functional dependencies between different
visual routines along with relational short- and long-term knowledge
about the world. Here the visual routines are bound to visual properties
of objects stored in the memory of the system. Furthermore,
the functional dependencies between the visual routines are seen
as a graph also belonging to the object-s structure. This graph is
parsed in the course of acquiring a visual property of an object to
automatically resolve the dependencies of the bound visual routines.
Using this representation, the system is able to dynamically rearrange
the processing order while keeping its functionality. Additionally, the
system is able to estimate the overall computational costs of a certain
action. We will also show that the system can efficiently use that
structure to incorporate already acquired knowledge and thus reduce
the computational demand.
Abstract: The service sector continues to grow and the percentage
of GDP accounted for by service industries keeps increasing. The
growth and importance of service to an economy is not just a
phenomenon of advanced economies, service is now a majority of the
world gross domestic products. However, the performance evaluation
process of new service development problems generally involves
uncertain and imprecise data. This paper presents a 2-tuple fuzzy
linguistic computing approach to dealing with heterogeneous
information and information loss problems while the processes of
subjective evaluation integration. The proposed method based on group
decision-making scenario to assist business managers in measuring
performance of new service development manipulates the
heterogeneity integration processes and avoids the information loss
effectively.
Abstract: This paper presents methodologies for developing an
intelligent CAD system assisting in analysis and design of
reconfigurable special machines. It describes a procedure for
determining feasibility of utilizing these machines for a given part
and presents a model for developing an intelligent CAD system. The
system analyzes geometrical and topological information of the given
part to determine possibility of the part being produced by
reconfigurable special machines from a technical point of view. Also
feasibility of the process from a economical point of view is
analyzed. Then the system determines proper positioning of the part
considering details of machining features and operations needed.
This involves determination of operation types, cutting tools and the
number of working stations needed. Upon completion of this stage
the overall layout of the machine and machining equipment required
are determined.
Abstract: In order to reduce cost, increase quality, and for
timely supplying production systems has considerably taken the
advantages of supply chain management and these advantages are
also competitive. Selection of appropriate supplier has an important
role in improvement and efficiency of systems.
The models of supplier selection which have already been used by
researchers have considered selection one or more suppliers from
potential suppliers but in this paper selecting one supplier as partner
from one supplier that have minimum one period supplying to buyer
is considered.
This paper presents a conceptual model for partner selection and
application of Degree of Adoptive (DOA) model for final selection.
The attributes weight in this model is prepared through AHP
model. After making the descriptive model, determining the
attributes and measuring the parameters of the adaptive is examined
in an auto industry of Iran(Zagross Khodro co.) and results are
presented.
Abstract: The objective of this research is to study plant layout
of iron manufacturing based on the systematic layout planning
pattern theory (SLP) for increased productivity. In this case study,
amount of equipments and tools in iron production are studied. The
detailed study of the plant layout such as operation process chart,
flow of material and activity relationship chart has been investigated.
The new plant layout has been designed and compared with the
present plant layout. The SLP method showed that new plant layout
significantly decrease the distance of material flow from billet
cutting process until keeping in ware house.
Abstract: Activity-Based Costing (ABC) represents an
alternative paradigm to traditional cost accounting system and
it often provides more accurate cost information for decision
making such as product pricing, product mix, and make-orbuy
decisions. ABC models the causal relationships between
products and the resources used in their production and traces
the cost of products according to the activities through the use
of appropriate cost drivers. In this paper, the implementation
of the ABC in a manufacturing system is analyzed and a
comparison with the traditional cost based system in terms of
the effects on the product costs are carried out to highlight the
difference between two costing methodologies. By using this
methodology, a valuable insight into the factors that cause the
cost is provided, helping to better manage the activities of the
company.
Abstract: Noise has adverse effect on human health and
comfort. Noise not only cause hearing impairment, but it also acts as
a causal factor for stress and raising systolic pressure. Additionally it
can be a causal factor in work accidents, both by marking hazards
and warning signals and by impeding concentration. Industry
workers also suffer psychological and physical stress as well as
hearing loss due to industrial noise. This paper proposes an approach
to enable engineers to point out quantitatively the noisiest source for
modification, while multiple machines are operating simultaneously.
The model with the point source and spherical radiation in a free field
was adopted to formulate the problem. The procedure works very
well in ideal cases (point source and free field). However, most of the
industrial noise problems are complicated by the fact that the noise is
confined in a room. Reflections from the walls, floor, ceiling, and
equipment in a room create a reverberant sound field that alters the
sound wave characteristics from those for the free field. So the model
was validated for relatively low absorption room at NIT Kurukshetra
Central Workshop. The results of validation pointed out that the
estimated sound power of noise sources under simultaneous
conditions were on lower side, within the error limits 3.56 - 6.35 %.
Thus suggesting the use of this methodology for practical
implementation in industry. To demonstrate the application of the
above analytical procedure for estimating the sound power of noise
sources under simultaneous operating conditions, a manufacturing
facility (Railway Workshop at Yamunanagar, India) having five
sound sources (machines) on its workshop floor is considered in this
study. The findings of the case study had identified the two most
effective candidates (noise sources) for noise control in the Railway
Workshop Yamunanagar, India. The study suggests that the
modification in the design and/or replacement of these two identified
noisiest sources (machine) would be necessary so as to achieve an
effective reduction in noise levels. Further, the estimated data allows
engineers to better understand the noise situations of the workplace
and to revise the map when changes occur in noise level due to a
workplace re-layout.
Abstract: Guaranteeing the availability of the required parts at
the scheduled time represents a key logistical challenge. This is
especially important when several parts are required together. This
article describes a tool that supports the positioning in the area of
conflict between low stock costs and a high service level for a
consumer.
Abstract: In this paper we present the information life cycle and analyze the importance of managing the corporate application portfolio across this life cycle. The approach presented here corresponds not just to the extension of the traditional information system development life cycle. This approach is based in the generic life cycle. In this paper it is proposed a model of an information system life cycle, supported in the assumption that a system has a limited life. But, this limited life may be extended. This model is also applied in several cases; being reported here two examples of the framework application in a construction enterprise and in a manufacturing enterprise.
Abstract: We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.