Modeling,analysis and performance evaluation for fault diagnosis and Fault Tolerant Control in bottle-filling plant modeled using Hybrid Petri nets

In this paper, an approach to achieve fault diagnosis and Fault Tolerant Control in a typical bottle-filling plant using event based techniques is discussed. For this purpose, the plant is modeled using Hybrid Petri nets which enable study and analysis with regard to the working of the plant. Once effective modeling is done based on two different case studies considered, new algorithms are proposed to achieve fault diagnosis and Fault Tolerant Control on the models developed. Finally, performance measures with regard to the models proposed are evaluated to check the correctness of the models developed. Both analytical and numerical results are obtained which are highly useful to understand plant behavior.     

Representation and analysis of behavior for multiprocess systems by using stochastic Petri nets

This paper proposes a new approach to visually represent the behavior of multiprocess in a computer network system using stochastic Petri net (SPN) and an aggregate approach of SPN and Markov renewal process (MRP) to conduct behavior analysis and performance evaluation for the system. SPN is employed because of its highly visual nature that can give insight into the nature of the modeled system and because of its expressive power for an exponentially distributed event. In order to increase the analytical power of the SPN model, MRP is introduced and an embedded transference probability matrix is applied to obtain the steady-state solution of the model, from which it is possible to obtain automatically the performance measures of the multiprocess computer network system.     

Group performance evaluation, an application of data envelopment analysis

The contribution of this paper is to provide an approach for evaluating the performance of a group of decision making units (DMUs) based on the production technology. Group evaluation is an application of data envelopment analysis (DEA). DEA uses linear programming to provide a suitable technique to estimate a multiple-input/multiple-output empirical efficient function. This paper applies group evaluation to evaluate the performance of Iranian commercial banks.     

Human resource management and performance: A neural network analysis

This study utilizes an innovative research methodology (Kohonen’s Self-Organizing Maps) to explore a subject relatively understudied in Europe. It focuses on the connection between human resource management as a source of competitive advantage and perceived organizational performance in the European Union’s private and public sectors. While practices in these two sectors did not differ significantly, three diverse but overlapping HRM models did emerge, each of which involved a different set of EU member states. Training & Development practices were strongly related to performance in all three models and Communication practices in two. These results show the usefulness of an innovative technique when applied to research so far conducted through traditional methodologies, and brings to the surface questions about the universal applicability of the widely accepted relationship between superior HRM and superior business performance.     

A fresh approach to performance evaluation in a multi-item production scenario

In a truly flexible production environment, it is feasible to interchange the production rate of two items, as long as this does not affect the constraint imposed on total manufacturing time. Performance evaluation in a multi-item production scenario has many facets, and its improvement is possible in many ways. After adopting certain benchmarking or analytical process, usually a facility runs at certain performance level with respect to total system cost. It may be a unique approach to explore the possibility of interchanging the production rate of any item with that of another appropriate item in the group. This is discussed in the present paper with the objective of further improvement in the total cost.     

Network DEA model for supply chain performance evaluation

This paper constructs an alternative network DEA model that embodies the internal structure for supply chain performance evaluation. We take the perspective of organization mechanism to deal with the complex interactions in supply chain. Three different network DEA models are introduced under the concept of centralized, decentralized and mixed organization mechanisms, respectively. Efficiency analysis including the relationship between supply chain and divisions, and the relationship among the three different organization mechanisms are discussed. As a further extension, we investigate internal resource waste in supply chain.     

MC-based Algorithm for a telecommunication network under node and budget constraints

It is an important issue to design some performance indexes in order to measure the performance for a telecommunication network. Network analysis is an available approach to solve the performance problem for a real-life system. We construct a two-commodity stochastic-flow network with unreliable nodes (arcs and nodes all have several possible capacities and may fail) to model the telecommunication network. In which, all types of commodity are transmitted through the same network simultaneously and compete the capacities. This paper defines the system capacity as a 2-tuple vector, and then proposes a performance index, the probability that the upper bound of the system capacity equals a demand vector subject to the budget constraint. An upper boundary point is a vector representing the capacities of arcs and nodes, and is the maximal vector exactly meeting the demand vector. A simple algorithm based on minimal cuts (or named MC-based algorithm) is then presented to generate all upper boundary points in order to evaluate the performance index. The storage and computational time complexity of this algorithm are also analyzed. The performance evaluation for the multicommodity case can be extended easily.     

Performance evaluation: An integrated method using data envelopment analysis and fuzzy preference relations

In a multi-attribute decision-making (MADM) context, the decision maker needs to provide his preferences over a set of decision alternatives and constructs a preference relation and then use the derived priority vector of the preference to rank various alternatives. This paper proposes an integrated approach to rate decision alternatives using data envelopment analysis and preference relations. This proposed approach includes three stages. First, pairwise efficiency scores are computed using two DEA models: the CCR model and the proposed cross-evaluation DEA model. Second, the pairwise efficiency scores are then utilized to construct the fuzzy preference relation and the consistent fuzzy preference relation. Third, by use of the row wise summation technique, we yield a priority vector, which is used for ranking decision-making units (DMUs). For the case of a single output and a single input, the preference relation can be directly obtained from the original sample data. The proposed approach is validated by two numerical examples.     

Spectral analysis of a high-order Hermitian algorithm for structural dynamics

The spectral analysis of an efficient step-by-step direct integration algorithm for the structural dynamic equation is presented. The proposed algorithm is formulated in terms of two Hermitian finite difference operators of fifth-order local truncation error and it is unconditionally stable with no numerical damping presenting a fourth-order truncation error for period dispersion (global error). In addition, although it is in competition with higher-order algorithms presented in the literature, the computational effort is similar to that of the classical second-order Newmark’s method. The numerical application for nonlinear structural dynamic problems is also considered.     

Spectral discretization of a model for organic pollution in waters

We are interested in a mixed reaction diffusion system describing the organic pollution in stream‐waters. In this work, we propose a mixed‐variational formulation and recall its well‐posedness. Next, we consider a spectral discretization of this problem and establish nearly optimal error estimates. Numerical experiments confirm the interest of this approach. Copyright © 2016 John Wiley & Sons, Ltd.     

A Spectral Method for the Electrohydrodynamic Flow in a Circular Cylindrical Conduit

This paper presents a combination of the hybrid spectral collocation technique and the spectral homotopy analysis method(SHAM for short) for solving the nonlinear boundary value problem(BVP for short) for the electrohydrodynamic flow of a fluid in an ion drag configuration in a circular cylindrical conduit. The accuracy of the present solution is found to be in excellent agreement with the previously published solution. The authors use an averaged residual error to find the optimal convergence-control parameters. Comparisons are made between SHAM generated results, results from literature and Matlab ode45 generated results, and good agreement is observed.     

On some methods for performance ranking and correspondence analysis in the DEA context

Two novel methods named performance baseline and performance correspondence matrices are proposed to evaluate the performance of decision making units (DMUs) based on the techniques of singular value decomposition (SVD). The performance baseline matrix can be used to rank all the DMUs because it provides a common basis for performance comparison. The performance correspondence matrix can be used to conduct performance cluster analysis, with which to explore the structure of input/output variables that are associated with DMUs. The analysis can reveal the performance difference of the DMUs and the key input/output variables determining the efficiency of a certain DMU, and provides valuable quantitative information for adjusting variables to improve efficiency of the DMU. Three case studies are presented to demonstrate that the proposed methods in this work are effective and easy to use and can provide insights into proper selection of input/output variables for performance comparison to avoid over manipulating DEA models in practice.     

Specification and verification of safety properties along a crossing region in a railway network control

Modeling the controller of the railway network, having resource sharing based on mutual exclusion constraints, is an important problem. This paper firstly addresses the specification of safety properties for the model of a complex railway crossing. The operations, i.e., occupied, free and block, are formalized to describe the safety properties along railway crossing. Second, to develop the control model of the crossing system we construct the subnet representing the train flow along the tracks in the crossing region and the set of monitors or supervisors are also modeled as subnets. Arc-constant colored Petri net (ac-CPN) is used to construct the train flow subnet while the monitors are modeled using the place/transition-net. Arc-constant colored Petri net enforces the specification of not to shift the train from a track to another one. Bottom-up approach is adopted to model the control for railway crossing as a synchronous synthesis of the subnets is applied to build the final model. Finally, to verify the safety properties in the developed controller, the coverability tree method is used for the analysis of the final model.     

The Spectral Characterization of Hypersurfaces with Constant Mean Curvature in a Unit Sphere

Let M be an n-dimensional compact hypersurface of Sn+1 (1) with the same constant mean curvature as an H(r)-torus Sn-1(r)×S1(1-r2) for some r.If specp(M)=specp(H(r)) for p=0,1,2, then M is H(r).     

Modeling centrality measures in social network analysis using bi-criteria network flow optimization problems

Centrality measures play an important role in the field of network analysis. In the particular case of social networks, the flow represents the way in which information passes through the network nodes. Freeman et al. (1991) were the first authors to relate centrality measures to network flow optimization problems in terms of betweenness, closeness, and the influence of one node over another one. Such measures are single dimensional and, in general, they amalgamate several heterogeneous dimensions into a single one, which is not suitable for dealing with most real-world problems. In this paper we extend the betweenness centrality measure (or concept) to take into account explicitly several dimensions (criteria). A new closeness centrality measure is defined to deal not only with the maximum flow between every ordered pair of nodes, but also with the cost associated with communications. We shall show how the classical measures can be enhanced when the problem is modeled as a bi-criteria network flow optimization problem.     

Incorporating performance measures with target levels in data envelopment analysis

Data envelopment analysis (DEA) is a technique for evaluating relative efficiencies of peer decision making units (DMUs) which have multiple performance measures. These performance measures have to be classified as either inputs or outputs in DEA. DEA assumes that higher output levels and/or lower input levels indicate better performance. This study is motivated by the fact that there are performance measures (or factors) that cannot be classified as an input or output, because they have target levels with which all DMUs strive to achieve in order to attain the best practice, and any deviations from the target levels are not desirable and may indicate inefficiency. We show how such performance measures with target levels can be incorporated in DEA. We formulate a new production possibility set by extending the standard DEA production possibility set under variable returns-to-scale assumption based on a set of axiomatic properties postulated to suit the case of targeted factors. We develop three efficiency measures by extending the standard radial, slacks-based, and Nerlove–Luenberger measures. We illustrate the proposed model and efficiency measures by applying them to the efficiency evaluation of 36 US universities.     

A new methodology for evaluating sustainable product design performance with two-stage network data envelopment analysis

Sustainable product design has been considered as one of the most important practices for achieving sustainability. To improve the environmental performances of a product through product design, however, a firm often needs to deal with some difficult technical trade-offs between traditional and environmental attributes which require new design concepts and engineering specifications. In this paper, we propose a novel use of the two-stage network Data Envelopment Analysis (DEA) to evaluate sustainable product design performances. We conceptualize “design efficiency” as a key measurement of design performance in terms of how well multiple product specifications and attributes are combined in a product design that leads to lower environmental impacts or better environmental performances. A two-stage network DEA model is developed for sustainable design performance evaluation with an “industrial design module” and a “bio design module.” To demonstrate the applications of our DEA-based methodology, we use data of key engineering specifications, product attributes, and emissions performances in the vehicle emissions testing database published by the US EPA to evaluate the sustainable design performances of different automobile manufacturers. Our test results show that sustainable design does not need to mean compromise between traditional and environmental attributes. Through addressing the interrelatedness of subsystems in product design, a firm can find the most efficient way to combine product specifications and attributes which leads to lower environmental impacts or better environmental performances. This paper contributes to the existing literature by developing a new research framework for evaluating sustainable design performances as well as by proposing an innovative application of the two-stage network DEA for finding the most eco-efficient way to achieve better environmental performances through product design.     

The expected length of a random line segment in a rectangle

We calculate the expected length of a random line segment in a rectangle, using a line making a random angle with the horizontal axis and having a random distance to a corner of the rectangle. Our result differs from previous calculations based upon two randomly placed points, and can be viewed as extending Bertrand's paradox to an important problem in geometric probability.     

Supply chain performance evaluation using fuzzy network data envelopment analysis: a case study in automotive industry

Supply chain performance evaluation problems are evaluated using data envelopment analysis. This paper proposes a fuzzy network epsilon-based data envelopment analysis for supply chain performance evaluation. In the common data envelopment analysis models which are used for evaluation of decision-maker units efficiency, there are several inputs and outputs. One of the bugs of such models is that the intermediate products and linking activities are overlooked. Considering these intermediate activities and products, the current study evaluates the performance of decision-maker units in an automotive supply chain. There are ten decision-maker units in the supply chain in which there are three suppliers, two manufacturers, two distributors, and four customers. Moreover, the overall efficiency of input-oriented (input-based) model and input-oriented divisional efficiency are calculated. In order to improve the efficiencies, the projections onto the frontiers are obtained by using the outputs of the solved model and Lingo software. In order to show the applicability of the proposed model, it is applied on automotive industry, as a case study, to evaluate supply chain performance. Then, the overall efficiencies of DMUs and each sections (divisions) of DMUs were calculated separately. Therefore, every organization can apply this evaluation method for improving the performance of alternative factors.