Roberto Gabbrielli

Monte Carlo simulation approach for a modified FMECA in a power plant

This paper presents a new tool for failure mode and effect analysis developed for a new Integrated Gasification and Combined Cycle plant in an important Italian oil refinery. The methodology is based on the integration between a modified Failure Mode Effect and Criticality Analysis (FMECA) and a Monte Carlo simulation as a method for testing the weights assigned to the measure of the risk priority numbers (RPNs). The RPN proposed consists of a weighted sum of six parameters (safety, machine importance for the process, maintenance costs, failure frequency, downtime length, and operating conditions) multiplied by a seventh factor (the machine access difficulty). Adopting this tool and considering the budget constraints, the best maintenance policy has been selected for each plant facility (about 140 in total). Copyright

ANP/RPN: a multi criteria evaluation of the risk priority number

This paper presents an advanced version of the failure mode effects and criticality analysis (FMECA), whose capabilities are enhanced; in that the criticality assessment takes into account possible interactions among the principal causes of failure. This is obtained by integrating FMECA and Analytic Network Process, a multi-criteria decision making technique. Severity, Occurrence and Detectability are split into sub-criteria and arranged in a hybrid (hierarchy/network) decision-structure that, at the lowest level, contains the causes of failure. Starting from this decision-structure, the Risk Priority Number is computed making pairwise comparisons, so that qualitative judgements and reliable quantitative data can be easily included in the analysis, without using vague and unreliable linguistic conversion tables. Pairwise comparison also facilitates the effort of the design/maintenance team, since it is easier to place comparative rather than absolute judgments, to quantify the importance of the causes of failure. In order to clarify and to make evident the rational of the final results, a graphical tool, similar to the House of Quality, is also presented. At the end of the paper, a case study, which confirms the quality of the approach and shows its capability to perform robust and comprehensive criticality analyses, is reported. Copyright

Dimensional analysis for investment selection in industrial robots

Investment evaluation and selection of industrial robots is a complex multicriteria decision-making task. This paper considers the possibility of applying to the robot selection problem a known mathematical method based on Dimensional Analysis (DA) theory. It is shown how it is possible to obtain an easy, efficient and robust decision-making support system which overcomes all attribute dimension problems. In particular, the robustness of the DA approach when compared with judgements made by a group of experts concerning different factors and weights, is evaluated. DA low sensitivity is compared with a weightedpoint decision method found in the literature.

Small-scale wood-fuelled CHP plants: A comparative evaluation of the available technologies

Actually, several applications of small (≤1 MWe) CHP (Combined Heat and Power) plants fuelled with solid wood can be found in Europe. Innovative technologies are facing the market, giving new perspectives for wood utilisation in district heating and/or in industrial-commercial activities. However, while the energy saving and the environmental benefits of CHP plants are undoubted, technological and no technological barriers still obstacle their large diffusion. The present study reports a comparative evaluation of the different available technologies in terms of thermal and electric efficiencies and their possible applications. Taking into consideration the electricthermal performances of each configuration and the actual economic incentives guaranteed by the Italian government, a preliminary estimation of economic convenience of each plant is given.

A Novel Game Theory Based Exit Selection Model In Emergency Conditions

In this paper, a new game theory based approach for the evacuees exit selection in emergency conditions is presented. It is founded on the theoretical concepts of multi-stage games with perfect information. In particular, an evacuee is a player and the available actions for a generic player are the accessible emergency exits. The developed mathematical model involves several psychological parameters, in order to make the emergency exit choice also affected by the individual character. Moreover, an evacuation simulation model incorporating this novel approach is shown. The model involves many other parameters and aspects attempting to obtain a satisfactory representation of the actual evacuation process and of the human behavior in emergency conditions. Finally, the effectiveness of the model is demonstrated with a simulative study.

A decision support system for locational analysis in paper industry

In this paper, an effective Decision Support System (DSS) concerning the site selection of a new paper mill is reported. The analysis is executed adopting the Analytic Hierarchy Process (AHP) technique. In particular, a specific wide hierarchy structure has been defined considering 49 criteria outlined via questionnaires and interviews with several logistics and production managers of the paper mills located in the district of Lucca (Italy), one of the most important areas for the production and converting of pulpboard and tissue in Europe. A sensitivity analysis based on a particular case study demonstrates the robustness of the proposed decision structure.

A genetic approach for setting parameters of reorder point systems

In this paper, we consider the packing storage management problems for an Italian machine-manufacturing company. Because of the limitations of a material requirements planning approach for this particular firm, the packing purchase process is managed by adopting the economic order quantity (EOQ) philosophy. Considering the number of packing types and the constraints that concern the purchase phase, a genetic algorithm approach is proposed to calculate the EOQ and reorder point values for each product. The validity of this approach was tested using a deterministic simulation based on historical data relevant to the packing consumption. This methodology has proved to be very efficient, simple and useful in practice for the definition of good packing inventory management.

Stock diffusion theory: a dynamic model for inventory control

Abstract This paper proposes a dynamic approach for inventory management, which can be used for a definitely non stationary demand whose rate evolves both in mean and in variance. Specifically, the stock consumption is modelled as a Markov process with a slow diffusion term and the Fokker Planck equation is used to derive the probability distribution of the stock consumption and that of the reorder time. The knowledge of these distributions makes it possible to manage the inventory in a dynamical way and to keep the safety stock to a minimum level. To test the model, some typical demand patterns are used: results demonstrate its ability to capture both the evolution of the mean and that of the variance of the demand.

Process Engineering and Optimization

Process planning plays a fundamental role within modern industrial facilities in that it is devoted to select the manufacturing processes and parameters and the sequences that are needed to convert a part from the initial to the final form. Evaluating the quality of a process plan from both a technological and an economic perspective becomes vital. Indeed, a valid process plan not only ensures the required quality of manufactured parts, but also reduces the production cost. The present chapter is aimed at presenting the essential concepts and the historical evolution of the process planning approaches, starting from a general point of view and then introducing the most important and recent real-world applications. In addition, it introduces the fundamental aspect regarding the interactions between process planning and production scheduling, pinpointing the strengths and weaknesses of the available proposed solutions. Doing so, it addresses students, researchers as well as practitioners.

Validation of a Small Scale Woody Biomass Downdraft Gasification Plant Coupled with Gas Engine

Validation of a Small Scale Woody Biomass Downdraft Gasification Plant Coupled with Gas Engine Roberto Gabbrielli*, Maurizia Seggiani, Stefano Frigo, Monica Puccini, Sandra Vitolo, Giovanni Raggio, Fulvio Puccioni a Department of Civil and Industrial Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy. b Department of Energy, System, Territory and Construction Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy. C Glass Service s.r.l , Via Cascina Lari , 56028 San Miniato, Italy. r.gabbrielli@ing.unipi.it