131,171 research outputs found
Software Package for Supplier Selection in Manufacturing Supply Networks
No full textTrattasi di pacchetto software sviluppato presso il Dipartimento di Ingegneria dei Materiali e della Produzione. Questo tipo di prodotto è stato inserito nella tipologia "Altro (ministeriale)" su suggerimento dei responsabili del CSI. Si riportano qui di seguito alcune delle principali pubblicazioni scientifiche facenti riferimento al pacchetto software in argomento.
D’Addona, D., Teti, R., 2010, Tool Delivery Prediction through Adaptive Neuro-Fuzzy Inferencing, Vimation Journal, Special Issue on Interactive Systems in Healthcare, ISSN 1866-4245: 65-72
D’Addona, D., Teti, R., 2010, Distributed Multi-Agent System for Tool Inventory Management in a Supply Network, 7th CIRP Int. Conference on Intelligent Computation in Manufacturing Engineering – CIRP ICME ‘10, 23-25 June, Capri, Italy
D’Addona, D., Teti, R., 2010, Diverse Risk/Cost Balancing Strategies for Flexible Tool Management in a Supply Network, Chapter 10 in Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management, Springer Series in Advanced Manufacturing, Editors L. Benyoucef, B. Grabot, Springer Publisher, ISBN 978-1-84996-118-9 (Print) 978-1-84996-119-6 (Online), ISSN: 1860-5168, DOI: 10.1007/978-1-84996-119-6_10: 271-313
D'Addona, D., Teti, R., 2006, Java-Based Multi-Agent System Design for Tool Management in a Supply Network, 5th CIRP Int. Sem. on Intelligent Computation in Manufacturing Engineering – CIRP ICME ‘06, Ischia, 25-28 July: 647-652
Teti, R., D’Addona, D., 2006, Emergent Synthesis in Supply Network Tool Management, J. of Advanced Engineering Informatics, Vol. 20, No. 3, Elsevier, ISSN 1474-0346: 233-246
D’Addona, D., Teti, R., 2005, Intelligent Tool Management in a Multiple Supplier Network, Annals of the CIRP, Vol. 54/1, ISBN 3-905 277-43-3, ISSN 007-8506 (CIRP Annals), ISSN 1660-2773 (CD Rom): 459-46
Feasibility study of using microorganisms as lubricant component in cutting fluids
No full textThis work intends to lay the basis for a Biological Transformation in Manufacturing (BTM) industrial breakthrough aimed at developing new sustainable microbial-based cutting fluids for greener machining processes. The point of departure is that conventional cutting fluids for machining are either entirely based on mineral oils or, in the case of water-based cutting fluids, contain significant percentages of mineral oils. The world annual consumption of cutting fluid concentrate amounts to several billion litres, highlighting their importance for the manufacturing industry and their criticality in terms of environmental impact. Furthermore, the depletion of mineral oil reserves worldwide is already driving cutting fluid industries to search for new renewable raw materials. A contribution to the solutions of these problems can be provided by the development of microbial-based cutting fluids, incorporated in the machine tool, that contain microorganisms with significant lubricating properties in order to substitute mineral oil-based cutting fluids for use in metal alloy machining
Confessions of a Dangerous (Arab) Mind: Orientalism and Confession Beyond Said and Foucault
No full textThe effect of R&D expenses on financial performance: high vs. low R&D intensity industries
No full textThis paper examines the effect of R&D expenditure on the financial performance of companies, by comparing a low R&D intensity industry (consumer goods) to a high R&D intensity industry (pharmaceutical). We find that in both industries innovation activities and R&D expenses bring about better financial performance. Specifically, increasing R&D intensity boosts revenues. However, this occurs, but with a time lag. Low R&D intensive companies gain benefits from R&D investments more rapidly than high R&D intensive companies. In the two industries, time lag varies due to the specificities and peculiarities of R&D procedures, product production, distribution, and other processes. Finally, the paper shows that the effect of R&D expenses varies across the companies in the industries analysed. R&D expenses in pharmaceutical companies induce higher revenue growth, compared to consumer goods firms
FIT MANUFACTURING: PRODUCTION FITNESS AS THE MEASURE OF PRODUCTION OPERATIONS PERFORMANCE
No full textRapid changes in market demands have resulted in manufacturing companies having to remain competitive in order to survive. Therefore, a combination of manufacturing capabilities, such as leanness, flexibility, agility, responsiveness, and sustainability, is essential to manufacturing companies. However, the performance of manufacturing capabilities has not yet been measured through integrated manufacturing concepts. Consequently, the thesis presents a model for evaluating operational performance from the specific viewpoint of production capability, termed Production Fitness. In this respect, determination of Production Fitness refers to Fit Manufacturing systems in general. An assessment of Production Fitness is developed based on the concept of multidimensional performances through integration of three distinctive concepts: (i) Lean Manufacturing (leanness), (ii) Agile Manufacturing (agility), (iii) Sustainability.
The aim is to provide an index for Production Fitness, determined through a simpler, more useful, and objective system of assessment. In this way, the Production Fitness measures can be used as a decision support tool for production and marketing (e.g., Production Waste Index ( PWI), Production Profitability Index ( PAI), Production Stability Index (PSI), and Production Fitness Index ( PFI), as well as providing a means of avoiding common conflict between these two areas.
The Production Fitness measures were applied to six case studies of micro-SMEs with batch manufacturing processes in various industries. Results from the six case studies show that it is crucial for manufacturing companies to sustain an ideal PFI, which can be achieved through maximum PPI, consistent PAI, and ideal PSI. In the meantime, it is also important for manufacturing companies to achieve a higher PFI, especially in highly competitive market environments. Factors influencing the fitness indices are indentified from the aspect of company and production characteristics. SWOT analysis results indicate that the PFI can be affected by company strengths, weakness, opportunities, and threats. Suggestions for improving Production Fitness are made using empirical evidence from previous studies on relevant aspects.
This thesis concludes that the Production Fitness measures can be applied to batch process types in various manufacturing industries where common production and sales data are applied
Application of Spiking Neural Networks and the Bees Algorithm to Control Chart Pattern Recognition
No full textStatistical process control (SPC) is a method for improving the quality of products. Control charting plays the most important role in SPC. A control chart can be used to indicate whether a manufacturing process is under control. Unnatural patterns in control charts mean that there are some unnatural causes for variations. Control chart pattern recognition is therefore important in SPC. In recent years, neural network techniques have increasingly been applied to pattern recognition. Spiking Neural Networks (SNNs) are the third generation of artificial neural networks, with spiking neurons as processing elements. In SNNs, time is an important feature for information representation and processing. Latest research has shown SNNs to be computationally more powerful than other types of artificial neural networks. This PhD Thesis proposes the application of SNN techniques to control chart pattern recognition. The thesis work focuses on the architecture and the learning procedure of the network. Experiments show that the proposed architecture and the learning procedure give high pattern recognition accuracies
Ross, S., Hillier, D, Westerfield,R., Jaffe, J., Jordan, B., “Finanza Aziendale”,
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