The Nexus of Corporate Entrepreneurship and Radical Innovation

This paper explores the linkage between the entrepreneurial orientation of established firms and the development of radical innovation. Through five case studies in firms involved in radical innovation, three propositions are developed, suggesting that proactiveness, risk‐taking and autonomy stimulate the development of radical innovation, whereas competitive aggressiveness does not necessarily do so, as radical innovations are directed towards the creation of entirely new arenas of business, where existing competitors are not present.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Bio-layer management in anaerobic membrane bioreactors for wastewater treatment.

Membrane separation technology represents an alternative way to achieve biomass retention in anaerobic bioreactors for wastewater treatment. Due to high biomass concentrations of anaerobic reactors, cake formation is likely to represent a major cause of flux decline. In the presented research, experiments are performed on the effect of biomass concentration and level of gas sparging on the hydraulic capacity of a submerged anaerobic membrane bioreactor. Both parameters significantly affected the hydraulic capacity, with biomass exerting the most pronounced effect. After 50 days of continuous operation the critical flux remained virtually unchanged, despite an increase in membrane resistance, suggesting that biomass characteristics and hydraulic conditions determine the bio-layer formation rather than the membrane's fouling level. The concept of bio-layer management is introduced to describe the programmed combination of actions performed in order to control the formation of biomass layer over membranes.     

Nitric oxide reduction and carbon monoxide oxidation over carbon-supported copper-chromium catalysts

Carbon supported copper-chromium catalysts are shown to be very active for both the reduction of nitric oxide with carbon monoxide and the oxidation of carbon monoxide with oxygen. Mixed copper-chromium oxide active phases have good activity in the simultaneous removal of nitric oxide and carbon monoxide from exhaust gases. The influence of several catalyst variables has been investigated. The activity per volume of catalyst increases with increasing loading, while the intrinsic activity shows a maximum around C/M=100−50. An optimum catalyst for nitric oxide reduction and carbon monoxide oxidation has a copper/chromium ratio of 2/1. The apparent activation energy for the carbon monoxide oxidation over carbon supported copper-chromium catalysts is 77 kJ/mol, suggesting that the Cu---O bond rupture is the rate-limiting process. The reduction of nitric oxide takes place at higher temperatures. Since all catalysts have a low selectivity for molecular nitrogen formation at lower temperatures, the dissociation of nitric oxide is probably rate determining, resulting in a slightly reduced catalyst system. In an excess of carbon monoxide the reaction is first-order in nitric oxide and zero-order in carbon monoxide. Moisture inhibits the reaction by reversible competitive adsorption, whereas carbon dioxide does not. Oxygen completely inhibits the reduction of nitric oxide due to the more rapid reoxidation of the catalytic sites compared to nitric oxide. Therefore, the reduction of nitric oxide takes place only when all oxygen has been converted and, hence, is shifted to higher temperatures. As a possible consequence, the production of nitrous oxide is reduced. Nitric oxide and molecular oxygen react preferentially with carbon monoxide, so, in an excess of oxidizing component, gasification of the carbon support occurs at higher temperatures after carbon monoxide has been completely consumed.     

Intramolecular crosslinking of poly(vinyl alcohol)

Poly(vinyl alcohol) is crosslinked in dilute solution (c=0.1 wt%) with glutaraldehyde. The reaction product is characterized by viscometry and gel permeation chromatography (g.p.c.). The intrinsic viscosity decreases with increasing degree of crosslinking and does not depend on temperature. G.p.c. reveals that the reaction product is not homogeneous, but consists of a mixture of particles with different sizes, possibly both intra- and intermolecularly crosslinked molecules. The intramolecularly crosslinked molecules are smaller in size than the initial polymer molecules and their size depends on the degree of crosslinking. They possess a narrow particle size distribution even if the initial polymer sample had a broad molecular weight distribution.     

Impact Fracture of Thermally Tempered Glass Helicopter Windshields

In-service fracture of helicopter windshields was studied. Simulated catastrophic fracture tests were conducted by firing alumina and steel spheres onto stationary tempered and as-received glass panels. The results were studied by Hertzian analysis and modified Auerbach's relations. Thermally tempered glass shows much higher impact resistance than that estimated from superposition of residual stresses. Subcritical impact sites exhibit slow crack growth in tempered plates, eventually leading to fracture of the entire plate.     

Modeling tool wear in end-milling using enhanced GMDH learning networks

This paper presents an enhanced approach to predictive modeling for determining tool-wear in end-milling operations based on enhanced-group method of data handling (e-GMDH). Using milling input parameters (speed, feed, and depth-of-cut) and response (tool wear), the data for the model is partitioned into training and testing datasets, and the training dataset is used to realize a predictive model that is a function of the input parameters and the coefficients determined. In our approach, we first present a methodology for modeling, and then develop predictive model(s) of the problem being solved in the form of second-order equations based on the input data and coefficients realized. This approach leads to some generalization because it becomes possible to predict not only the test data obtained during experimentation, but other test data outside the experimental results can also be used. Moreover, this approach makes it easy to present the realized solution in a form that can be further optimized for the input parameters using some optimization techniques. The results realized using our e-GMDH method are promising, and the comparative study presented shows that the e-GMDH outperforms polynomial neural network (PNN); moreover, it is more flexible than the conventional GMDH, which tends to produce nonlinear solutions even for simple problems. In the investigation, the extended particle swarm optimization (PSO) technique was applied to obtain the optimal parameters. Consequently, the modeling approach is extremely useful in realizing a computer-aided process-planning system in an advanced manufacturing environment.     

A Web-based Kanban system for job dispatching, tracking, and performance monitoring

A Kanban system facilitates lean principles in a simple and effective way. While reportedly successful in many manufacturing firms, the conventional Kanban systems using physical cards suffer from human errors, limited tracking capability, and so on. To make the information flow leaner, software providers add new features to their existing programs for manufacturing systems to computerize Kanban activities. As Web-based technologies advance rapidly, developing an entirely Web-based Kanban system appears to be feasible and promising. This paper presents the advantages, limitations, and challenges of Web-based Kanban systems. An experimental program has been developed based on PHP+MySQL, a popular Web programming platform. The server-executed program features cross-platform compatibility, real-time tracking and performance monitoring, and greatly enhanced information contents compared to physical Kanbans. Human errors are minimized by the automated transactions; nevertheless, the interfacing and data maintenance require further research efforts.