1,721,086 research outputs found
Size and stability of dipalmitoylphosphatidylcholine/cholesterol unilamellar vesicles are affected by interaction with proteins.
No full textSimulating effects of a human-based maintenance on production lines: a case from the pharmaceutical industry
No full textThe authors propose a theoretical approach aiming at identifying stochastic variables which mainly affect system performance. The approach is firstly applied to a theoretical case of stochastic variables defined in [0,1] range, distributed according to Beta probability density function.
A general conclusion achieved relies on the system attitude in smoothing or boosting stochastic variability of system performance, given stochastic variability of independent system variables. The attitude mainly relies on deterministic relationship between system performance and system variables.
The approach is applied to an industrial case consisting of a production line of sterile syringes. The aim of the management was to identify work stations requiring improvements on maintenance performance in order to increase system availability.
System availability has been evaluated by simulation. A simulation model coded by ARENA® was built up. Results outline the capability of the approach proposed in identifying most sensitive relationship between system availability and time to repair
Sustainable Order Quantity of Repairable Spare Parts
No full textIn the last few years companies and researchers have focused their attention on the sustainable issues of supply chain management. In spare parts (SPs) research, traditionally focused on inventory modeling, supply chain aspects have become of relevant interests. Many contributions could be found in scientific literature about logistics of spare parts, but there is a lack of attention on the sustainable issues. In this paper, authors give a contribution to the concept of sustainable management of spare parts, by defining a spare parts logistic model. The model considers the environmental impacts and benefits related to the possibility of repairing failed parts rather than purchasing new ones. It aims at identifying the optimal means of transport, as well as the optimal SP order quantity minimizing the global logistic costs function in which economic and environmental costs of both the options of repairing and purchasing SPs are considered. The capability of the model has been tested with reference to a numerical example based on real data of a leader manufacturer of bearings
A model based on artificial neural network for risk assessment to polycyclic aromatic hydrocarbons in workplace
No full textPolycyclic aromatic hydrocarbons (PAHs) are formed during incomplete combustion in different production processes; exposure to PAH-containing substances increases the risk of cancer in humans. The environmental monitoring used to assess human exposure to airborne PAHs during work, generally involves the employment of diagnostic methods derived from analytical chemistry, characterised by an elevated cost and the use of a "trial and error" approach. The aim of this study is to develop a decision support tool that, through the characteristic parameters of a workplace and using an artificial neural network, simulates the concentration of different species of pollutants (PAHs groups) statistically present in the environment. In this way it is possible to perform a preliminary risk assessment that, besides allowing an immediate perception of the level of risk to which workers are exposed, can undertake environmental monitoring analysis on the detection of a limited number of pollutant species, in order to reduce costs and increase the sustainability of the production syste
Modelling the 2D object recognition task in manufacturing context: An information-based model
No full textIn the last decays, manufacturing systems evolved to meet the high product variety required by the market. Different products can be manufactured in the mixed-model assembly lines, with an increase in the process complexity. In these production systems, the required flexibility is mainly provided by operators in the final assembly stages. Here, human errors could lead to high economic losses. A lack is observed in available research concerning a formal quantification of manufacturing complexity considering the joint effect of shape complexity and similarity in the mix variety. This paper focuses on operator decision-making in 2D object recognition tasks, since this is the most critical task performed in mixed model assembly systems. A novel model to quantify the information content in 2D object recognition task is proposed. The model is based on the Shannon's Entropy theory and considers both shape complexity and object similarities. Numerical experiments are provided, and results obtained show the effectiveness of the model in capturing the joint effect of shape complexity and similarities on the task information content. The proposed model can be adopted in a production environment for re-allocating tasks/sub-tasks to avoid the high amount of information to be processed affecting operators' performance
Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making
Full text linkIn recent years the maritime freight transport has rapidly increased, causing congestion in many port areas. In some cases, in order to improve the capacity and the reliability of the temporary storage, a solution, recommended by industry officials, is the expansion of the terminal capacity. When this solution is not available, the ‘dry port’ area represents an effective alternative. The adoption of a dry port, if on one hand leads to benefits on terminal congestion, on the other hand requires resources and investments due to the transport of the container from port to dry port and vice versa. In the evaluation of the strategy to be adopted different aspects shall be evaluated to estimate time required for the container handling inside and outside the terminal on the basis of the congestion degree. In this paper, to support decision makers in identifying the best strategy to be adopted, a mathematical model allowing to identify the number of containers to be stocked in port and/or in dry port is defined considering the intra-/inter-terminal handling of the containers, in order to minimize the overall running costs and of the carbon footprint. The model, based on a computational algorithm for non-linear programming, is able to provide the number of containers to be stocked in port and/or in dry port, ensuring an effective strategy dependent on ‘road’ and ‘non-road' material handling equipment adopted, on the number and size of containers, as well as on the distance from port to dry port. Results obtained from numerical experiments show that, on the basis of the running cost and the carbon footprint of the container handling activities, it is possible to identify the most economic and eco-friendly container handling configuration. The case study of the Port of Bari (Italy) is investigated. In this case, given the overall number of containers to be stocked and the distance between port and dry port, the solutions found by the model identify a configuration able to ensure a reduction of 7% and 11% of the running cost and of the carbon footprint, respectively, when compared to the configuration in which all containers are stored in the port
Simulating effects of a human-based maintenance on production lines: a case from the pharmaceutical industry
No full textThe authors propose a theoretical approach aiming at identifying stochastic variables which mainly affect system performance. The approach is firstly applied to a theoretical case of stochastic variables defined in [0,1] range, distributed according to Beta probability density function.
A general conclusion achieved relies on the system attitude in smoothing or boosting stochastic variability of system performance, given stochastic variability of independent system variables. The attitude mainly relies on deterministic relationship between system performance and system variables.
The approach is applied to an industrial case consisting of a production line of sterile syringes. The aim of the management was to identify work stations requiring improvements on maintenance performance in order to increase system availability.
System availability has been evaluated by simulation. A simulation model coded by ARENA® was built up. Results outline the capability of the approach proposed in identifying most sensitive relationship between system availability and time to repair
A model based on artificial neural network for risk assessment to polycyclic aromatic hydrocarbons in workplace
No full textPolycyclic aromatic hydrocarbons (PAHs) are formed during incomplete combustion in different production processes; exposure to PAH-containing substances increases the risk of cancer in humans. The environmental monitoring used to assess human exposure to airborne PAHs during work, generally involves the employment of diagnostic methods derived from analytical chemistry, characterised by an elevated cost and the use of a "trial and error" approach. The aim of this study is to develop a decision support tool that, through the characteristic parameters of a workplace and using an artificial neural network, simulates the concentration of different species of pollutants (PAHs groups) statistically present in the environment. In this way it is possible to perform a preliminary risk assessment that, besides allowing an immediate perception of the level of risk to which workers are exposed, can undertake environmental monitoring analysis on the detection of a limited number of pollutant species, in order to reduce costs and increase the sustainability of the production syste
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