Measuring the efficiency of outsourcing: An illustrative case study from the aerospace industry

Outsourcing is related to the action which an organization deals with its suppliers through a kind of business contract where a specific activity or service has been hired to be made. The outsourcing of some activities has become a common practice in the industry, nowadays. It reduces costs, significantly, in the production process and, at the same time, adds some values to the business organization. However it is necessary to measure the performance of these activities. Data Envelopment Analysis (DEA) is a non-parametric method useful to measure comparative performance. It has a wide range of applications measuring comparative efficiency. The Analytic Hierarchy Process (AHP) is a multiple criteria decision-making method that uses hierarchic structures to represent a decision problem and then develops priorities for the alternatives based on the decision-maker's judgments. This paper presents an integrated application based on DEA and AHP to evaluate the efficiency of subcontracted companies in a Brazilian aerospace factory. © 2007 Springer-Verlag London Limited.

Development of a model to measure the efficiency of outsourced companies in the process of aircraft spare parts technical publications

This paper presents a proposal of a model to measure the efficiency of outsourced companies in the aeronautical industry applying the methods DEA and AHP. It also proposes an evaluation in the relation between the variables of the process and the value obtained for the effiiency. The criteria of Quality, Time and Cost were considered the outputs of the process, and those criteria were quantified by AHP for DEA matrix.The number of technical documents received by those outsorced companies were considered the input of the process. The other purpose is to separate the companies in groups considered able to receive an investment to improve their process. Copyright © 2008 SAE International.

How the delphi and AHP methods are aiding to define the critical success factors priorities in a digital factory project implementation

Digital factory is a concept that offers a collaborative approach to enhance product and production engineering processes through simulation. Products, processes and resources are modeled to be used to develop and test the product conception and manufacturing processes, before their use in the real factory. The purpose of this paper is to present the steps to identify the Critical Success Factors (CSF) priorities in a digital factory project implementation in a Brazilian company and how the Delphi and AHP Methods are aiding to identify these CSF priorities. Copyright © 2008 SAE International.

A comparative study of glycerol dehydration catalyzed by micro/mesoporous MFI zeolites

The catalytic properties of monomodal microporous and bimodal micro-mesoporous zeolites were investigated in the gas-phase dehydration of glycerol. The desilication methodology used to produce the mesoporous zeolites minimized diffusion limitations and increased glycerol conversion in the catalytic reaction due to the hierarchical system of secondary pores created in the zeolite crystals. The chemical and structural properties of the catalyst were studied by X-ray diffraction, nitrogen adsorption-desorption isotherms, NH3-TPD and pyridine chemisorption followed by IR-spectroscopy. Although the aim was to desilicate to create mesoporosity in the zeolite crystals, the desilication promoted the formation of extra-framework aluminum species that affected the conversion of glycerol and the products distribution. The results clearly show that the mesoporous zeolites with designed mesopore structure allowed a rapid diffusion and consequently improved the reaction kinetics. However, especial attention must be given to the desilication procedure because the severity of the treatment negatively interfered on the Brønsted and Lewis acid sites relative concentration and, consequently, in the efficiency of the catalysis performed by these materials. On the other hand, during the catalytic reaction, the intracrystalline mesopores allowed carbonaceous compounds to be deposited herein, resulting in less blocked micropores and catalysts with higher long-term stability.

Planet formation in a triple stellar system: implications of the third star's orbital inclination

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mating system parameters at hierarchical levels of fruits, individuals and populations in the Brazilian insect-pollinated tropical tree, Tabebuia roseo-alba (Bignoniaceae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mapping the knowledge covered by library classification systems

This study explores, in 3 steps, how the 3 main library classification systems, the Library of Congress Classification, the Dewey Decimal Classification, and the Universal Decimal Classification, cover human knowledge. First, we mapped the knowledge covered by the 3 systems. We used the 10 Pillars of Knowledge: Map of Human Knowledge, which comprises 10 pillars, as an evaluative model. We mapped all the subject-based classes and subclasses that are part of the first 2 levels of the 3 hierarchical structures. Then, we zoomed into each of the 10 pillars and analyzed how the three systems cover the 10 knowledge domains. Finally, we focused on the 3 library systems. Based on the way each one of them covers the 10 knowledge domains, it is evident that they failed to adequately and systematically present contemporary human knowledge. They are unsystematic and biased, and, at the top 2 levels of the hierarchical structures, they are incomplete.

Toward a hierarchical concept of plant stress

A number of attempts have been made to obtain a clear definition of biological stress. However, in spite of the efforts, some controversies on the concept of plant stress remain. The current versions are centered either on the cause (stress factor) or on the effect (stress response) of environmental stress. The objective of this study was to contribute to the definition of stress, using a hierarchical approach. Thus, we have performed an analysis of the most usual stress concepts and tested the relevance of considering different observation scales in a study on plant response to water deficit. Seedlings of Eucalyptus grandis were grown in vitro at water potentials ranging from -0.16 to -0.6 MPa, and evaluated according to growth and biochemical parameters. Data were analyzed through principal component analysis (PCA), which pointed to a hierarchical organization in plant responses to environmental disturbances. Growth parameters (height and dry weight) are more sensitive to water deficit than biochemical ones (sugars, proline, and protein), suggesting that higher hierarchical levels were more sensitive to environmental constraints than lower hierarchical ones. We suggest that before considering an environmental fluctuation as stressful, it is necessary to take into account different levels of plant response, and that the evaluation of the effects of environmental disturbances on an organism depends on the observation scale being used. Hence, a more appropriate stress concept should consider the hierarchical organization of the biological systems, not only for a more adequate theoretical approach, but also for the improvement of practical studies on plants under stress.

The hierarchical model of branch planning with random coefficients

We consider the management branch model where the random resources of the subsystem are given by the exponential distributions. The determinate equivalent is a block structure problem of quadratic programming. It is solved effectively by means of the decomposition method, which is based on iterative aggregation. The aggregation problem of the upper level is resolved analytically. This overcomes all difficulties concerning the large dimension of the main problem.

Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision

Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.

RESTRUCTURING of SYSTEMS and LOGISTICS of MOVEMENT and ITS IMPACT on URBAN and REGIONAL PLANNING PAULISTA

Report some of the changes in production and consumption occurring in the state of São Paulo. through the restructuring in motion systems, logistics and standards and taxation, as well as the impacts on urban spaces through new economic dynamics, imposed by the demands of corporate, is the purpose of this article. The decentralization of production and consumption towards the interior was made possible by the combination of hierarchical and ordered some basic elements such as technological innovations (ways and means of transport) and organizational (logistics, standards and taxation) which optimized the flow territorial state São Paulo. It is noteworthy, therefore: 1) the improvement of logistics as a strategy, planning and management of transport, storage and communications (including the granting of public services to private), 2) the technological improvement and expansion of motion systems (infrastructure, means of transport) and 3) the systems of rules and regulations through taxation and deregulation affect the circulatory system of a given space. Thus, both systems aims to disentangle the economic flows (goods, services, information, capital and people) and provide a more fluid territorial. The impacts on the State of São Paulo, mainly through its economic dynamics, revert positively and negatively, by changing the way one thinks and performs planning.

Extended Hierarchical Censored Production Rules (EHCPRs) system: An approach toward generalized knowledge representation

One common problem in all basic techniques of knowledge representation is the handling of the trade-off between precision of inferences and resource constraints, such as time and memory. Michalski and Winston (1986) suggested the Censored Production Rule (CPR) as an underlying representation and computational mechanism to enable logic based systems to exhibit variable precision in which certainty varies while specificity stays constant. As an extension of CPR, the Hierarchical Censored Production Rules (HCPRs) system of knowledge representation, proposed by Bharadwaj & Jain (1992), exhibits both variable certainty as well as variable specificity and offers mechanisms for handling the trade-off between the two. An HCPR has the form: Decision If(preconditions) Unless(censor) Generality(general_information) Specificity(specific_information). As an attempt towards evolving a generalized knowledge representation, an Extended Hierarchical Censored Production Rules (EHCPRs) system is suggested in this paper. With the inclusion of new operators, an Extended Hierarchical Censored Production Rule (EHCPR) takes the general form: Concept If (Preconditions) Unless (Exceptions) Generality (General-Concept) Specificity (Specific Concepts) Has_part (default: structural-parts) Has_property (default:characteristic-properties) Has_instance (instances). How semantic networks and frames are represented in terms of an EHCPRs is shown. Multiple inheritance, inheritance with and without cancellation, recognition with partial match, and a few default logic problems are shown to be tackled efficiently in the proposed system.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.