An ERP software selection process with using artificial neural network based on analytic network process approach

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to fact that it considers criteria and sub criteria relations and interrelations in selecting the software.Opinions of many experts are obtained while building ANP model for the selection ERP then opinions are reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert’s opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation.An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision.     

Calibration of Expert Judgments Applied to Uncertainty Assessment

Abstract:

This article contributes a methodology for eliciting expert judgment in support of decision analysis associated with the conceptual design of advanced engineering systems. To provide a basis for decision making in the presence of model and input parameter uncertainties, experts in several disciplines can be utilized to provide model parameter estimates to facilitate analyses. The judgment elicitation methodology was developed to cover a multitude of system disciplines using multiple experts. To address consistency in expert assessments, the methodology includes expert assessment calibration means. A sample application of the resultant expert judgment methodology is discussed. An engineering manager can use the methodology described in this article to assess viability of potential courses of action in high-risk or advanced state-of-the-art technology systems development ventures.     

A new algorithm and multi-response Taguchi method to solve line balancing problem in an automotive industry

One of the most important issues in an assembly line balancing problem is to control a flow of production and manufacturing to provide continuous flow to balance the production line. For this purpose, a line balancing problem was considered for a special assembly line in an automotive factory. A new algorithm was required to deal with balancing an assembly line which consisted of the same job which must be performed by more than one worker at the same time. In this way, the new algorithm was expected to be effective in such a case that jobs were simultaneously completed in a parallel way. In order to measure effectiveness of the proposed algorithm, performance criteria were identified as total number of assembly station, total number of workers, and line productivity. As a result of the application of the proposed algorithm with taking into consideration factors such as cycle time, an allowable number of workers in an assembly station, and an allowable idle time of a worker, alternative solutions were determined in order to measure these criteria. However, these alternative solutions do not give any information about which of the solutions provide not only minimization of the number of assembly station and number of workers on the line but also maximize the line productivity at the same time. Hereby, a multi-response Taguchi method was applied in order to investigate levels of factors which directly affected system performance criteria.     

Hypersurfaces of special configurations of serial manipulators and related concepts. part II: Passive joints,configurations, component manifolds and some applications

In this article the novel concepts of passive/active joints, component/subcomponent manifolds of the HSC, configurations/subconfigurations and their applications are presented. The article also contains a theorem which predicts the existence of passive joints and a synthesis procedure for passive joints. The concepts introduced here and in Part I are illustrated by way of examples which include three existing industrial manipulators.     

Hypersurfaces of special configurations of serial manipulators and related concepts. part III: Measures for the position and orientation space of 6 dof manipulators

In this article two alternatives are introduced as measures for the position and orientation space of 6 DOF manipulators which include considerations of joint limitations and scale. The cumulative freedom of the end effector, considered as a rigid body in 3D space, can thus be quantified. These alternative measures are shown to be equivalent for manipulators with spherical wrists. Applications are presented and the new concepts are illustrated by an example.     

The impact of wrong-path memory references in cache-coherent multiprocessor systems

The core of current-generation high-performance multiprocessor systems is out-of-order execution processors with aggressive branch prediction. Despite their relatively high branch prediction accuracy, these processors still execute many memory instructions down mispredicted paths. Previous work that focused on uniprocessors showed that these wrong-path (WP) memory references may pollute the caches and increase the amount of cache and memory traffic. On the positive side, however, they may prefetch data into the caches for memory references on the correct-path. While computer architects have thoroughly studied the impact of WP effects in uniprocessor systems, there is no comparable work for multiprocessor systems. In this paper, we explore the effects of WP memory references on the memory system behavior of shared-memory multiprocessor (SMP) systems for both broadcast and directory-based cache coherence. Our results show that these WP memory references can increase the amount of cache-to-cache transfers by 32%, invalidations by 8% and 20% for broadcast and directory-based SMPs, respectively, and the number of writebacks by up to 67% for both systems. In addition to the extra coherence traffic, WP memory references also increase the number of cache line state transitions by 21% and 32% for broadcast and directory-based SMPs, respectively. In order to reduce the performance impact of these WP memory references, we introduce two simple mechanisms—filtering WP blocks that are not likely-to-be-used and WP aware cache replacement—that yield speedups of up to 37%.     

Yarn evenness parameters optimization in jetring spinning process

Abstract

In this study, the effects of air nozzles called jetring or nozzlering, on yarn quality which is used as an additional process in conventional ring spinning machines have been investigated. The response surface methodology (RSM) was used to investigate the yarn properties value. In the experiment, Ne30/1 100% cotton fibers were used. In all jetring yarn productions, the air pressure was kept at 125?kPa (gauge). In all samples, the nozzle length was kept 27?mm and twisting chamber diameter was kept Ø2mm. The number of injectors has been kept constant as 4 pieces. Giving the best yarn quality as a result of RSM, injector diameter Ø0.5?mm and injector angle 35° as determined. With this nozzle structural configuration, yarn hairiness values were reduced by 9.2% but yarn irregularity values were increased by 0.7%, yarn elongation values were decreased by 6.2% and yarn tenacity (cN/tex) values decreased to 5.6.     

Using dual response surfaces to reduce variability in launch vehicle design: A case study

Space transportation system conceptual design is a multidisciplinary process containing considerable element of risk. Uncertainties from one engineering discipline may propagate to another through linking parameters and the final system output may have an accumulation of risk. This may lead to significant deviations from expected performance. An estimate of variability or design risk therefore becomes essential for a robust design. This study utilizes the dual response surface approach to quantify variability in critical performance characteristics during conceptual design phase of a launch vehicle. Using design of experiments methods and disciplinary design analysis codes, dual response surfaces are constructed for the mean and standard deviation to quantify variability in vehicle weight and sizing analysis. Next, an optimum solution is sought to minimize variability subject to a constraint on mean weight. In this application, the dual response surface approach lead to quantifying and minimizing variability without much increase in design effort.     

Selection of dispatching rules in FMS: ANP model based on BOCR with choquet integral

Scheduling policy which depends on selection of dispatching rules is one of the reasons which affect FMS’ productivity. Selection of a dispatching rule can only be based on one or two criteria such as processing time, due date, or system components at traditional methods such as mathematical programming, simulation, and heuristic algorithms. However, traditional methods have some weakness; the first one is about selection criteria based on only one dispatching rule or a few combination of the rules, the second one is related with not considering most of the manufacturing system information, and the last one is to deal with selection decision is not a dynamic structure. In this study, an analytical network process (ANP) model has been developed in order to eradicate these weaknesses. The model based on multiple criteria decision-making process. In addition, most of manufacturing system information have been employed, and it consists of a dynamic decision-making process. The proposed model has a comprehensive structure which consists of a company’s manufacturing criteria and macro-strategies. Although interdependence is accepted among criteria in ANP, non-interaction is assumed among them (i.e., additive measure). Because of existence of interactivities among criteria, a choquet integral has been adapted in an ANP model.