Abstract: This paper presents a genetic algorithm based permutation and non-permutation scheduling heuristics (GAPNP) to solve a multi-stage finite capacity material requirement planning (FCMRP) problem in automotive assembly flow shop with unrelated parallel machines. In the algorithm, the sequences of orders are iteratively improved by the GA characteristics, whereas the required operations are scheduled based on the presented permutation and non-permutation heuristics. Finally, a linear programming is applied to minimize the total cost. The presented GAPNP algorithm is evaluated by using real datasets from automotive companies. The required parameters for GAPNP are intently tuned to obtain a common parameter setting for all case studies. The results show that GAPNP significantly outperforms the benchmark algorithm about 30% on average.
Abstract: This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.
Abstract: A sensory network consists of multiple detection
locations called sensor nodes, each of which is tiny, featherweight
and portable. A single path routing protocols in wireless sensor
network can lead to holes in the network, since only the nodes
present in the single path is used for the data transmission. Apart
from the advantages like reduced computation, complexity and
resource utilization, there are some drawbacks like throughput,
increased traffic load and delay in data delivery. Therefore, multipath
routing protocols are preferred for WSN. Distributing the traffic
among multiple paths increases the network lifetime. We propose a
scheme, for the data to be transmitted through a dominant path to
save energy. In order to obtain a high delivery ratio, a basic route
reconstruction protocol is utilized to reconstruct the path whenever a
failure is detected. A basic reconstruction routing (BRR) algorithm is
proposed, in which a node can leap over path failure by using the
already existing routing information from its neighbourhood while
the composed data is transmitted from the source to the sink. In order
to save the energy and attain high data delivery ratio, data is
transmitted along a multiple path, which is achieved by BRR
algorithm whenever a failure is detected. Further, the analysis of
how the proposed protocol overcomes the drawback of the existing
protocols is presented. The performance of our protocol is compared
to AOMDV and energy efficient node-disjoint multipath routing
protocol (EENDMRP). The system is implemented using NS-2.34.
The simulation results show that the proposed protocol has high
delivery ratio with low energy consumption.
Abstract: The feedbacks obtained regarding the sense of
presence from pilot users operating a Mobile Robotic presence
(MRP) system to visit a simulated museum are reported in this paper.
The aim is to investigate how much the perception of system’s
usefulness and ease of use is affected by operators’ sense of social
telepresence (presence) in the remote location. Therefore, scenarios
of visiting a museum are simulated and the user operators are
supposed to perform some regular tasks inside the remote
environment including interaction with local users, navigation and
visiting the artworks. Participants were divided into two groups,
those who had previous experience of operation and interaction with
a MRP system and those who never had experience. Based on the
results, both groups provided different feedbacks. Moreover, there
was a significant association between user’s sense of presence and
their perception of system usefulness and ease of use.
Abstract: This paper discusses on power spectral density (PSD) characteristics which are extracted from three-dimensional (3D) electroencephalogram (EEG) models. The EEG signal recording was conducted on 150 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, the values of maximum PSD were extracted as features from the model. These features are analyzed using mean relative power (MRP) and different mean relative power (DMRP) technique to observe the pattern among different brain balancing indexes. The results showed that by implementing these techniques, the pattern of brain balancing indexes can be clearly observed. Some patterns are indicates between index 1 to index 5 for left frontal (LF) and right frontal (RF).
Abstract: This paper presents the findings of the investigation of ERP implementation, challenges experiences by a South African Company in ERP implementation, success factors, failures, and propose recommendations to improve ERP implementation. The data collections methods used are questionnaires. The paper contributes to discussion on ERP implementation in developing economics.
Abstract: Many companies have excel, it is economy and well perform to use in material requirement planning (MRP) on excel. For several products, it, however, is complex problem to link the relationship between the tables of products because the relationship depends on bill of material (BOM). This paper presents algorithm to create MRP on excel, and links relationship between tables. The study reveals MRP that is created by the algorithm which is easier and faster than MRP that created by human. By this technique, MRP on excel might be good ways to improve a productivity of companies.
Abstract: Manufacturing, production and service industries within Libya have struggled with many problems during the past two decades due to many difficulties. These problems have created a negative impact on the productivity and utilization of many industries around the country. This paper studies the implementation levels of the manufacturing control systems known as Manufacturing Resource Planning (MRPII) being adapted within some Libyan industries. A survey methodology has been applied for this research, based on the survey analysis, the results pointed out that the system within these industries has a modest strategy towards most of the areas that are considered as being very crucial in implementing these systems successfully. The findings also show a variation within these implementation levels with a respect to the key-elements that related to MRPII, giving the highest levels in the emphasise on financial data accuracy. The paper has also identified limitations within the investigated manufacturing and managerial areas and has pointed to where senior managers should take immediate actions in order to achieve effective implementation of MRPII within their business area.
Abstract: This paper aims to develop an algorithm of finite
capacity material requirement planning (FCMRP) system for a multistage
assembly flow shop. The developed FCMRP system has two
main stages. The first stage is to allocate operations to the first and
second priority work centers and also determine the sequence of the
operations on each work center. The second stage is to determine the
optimal start time of each operation by using a linear programming
model. Real data from a factory is used to analyze and evaluate the
effectiveness of the proposed FCMRP system and also to guarantee a
practical solution to the user. There are five performance measures,
namely, the total tardiness, the number of tardy orders, the total
earliness, the number of early orders, and the average flow-time. The
proposed FCMRP system offers an adjustable solution which is a
compromised solution among the conflicting performance measures.
The user can adjust the weight of each performance measure to
obtain the desired performance. The result shows that the combination
of FCMRP NP3 and EDD outperforms other combinations
in term of overall performance index. The calculation time for the
proposed FCMRP system is about 10 minutes which is practical for
the planners of the factory.
Abstract: In this paper, we propose a single sample path based
algorithm with state aggregation to optimize the average rewards of
singularly perturbed Markov reward processes (SPMRPs) with a
large scale state spaces. It is assumed that such a reward process
depend on a set of parameters. Differing from the other kinds of
Markov chain, SPMRPs have their own hierarchical structure. Based
on this special structure, our algorithm can alleviate the load in the
optimization for performance. Moreover, our method can be applied
on line because of its evolution with the sample path simulated.
Compared with the original algorithm applied on these problems of
general MRPs, a new gradient formula for average reward
performance metric in SPMRPs is brought in, which will be proved
in Appendix, and then based on these gradients, the schedule of the
iteration algorithm is presented, which is based on a single sample
path, and eventually a special case in which parameters only
dominate the disturbance matrices will be analyzed, and a precise
comparison with be displayed between our algorithm with the old
ones which is aim to solve these problems in general Markov reward
processes. When applied in SPMRPs, our method will approach a fast
pace in these cases. Furthermore, to illustrate the practical value of
SPMRPs, a simple example in multiple programming in computer
systems will be listed and simulated. Corresponding to some practical
model, physical meanings of SPMRPs in networks of queues will be
clarified.