The continuously increasing number of Photovoltaic (PV) plants has stimulated the research in order to increment their overall efficiency. Usually, the efforts have been focused on the research of innovative materials and in general on the optimization of the photovoltaic conversion. Pollution due to the traffic, to the industrial activities or to the residential heating can reduce the efficiency of the PV plant. However, this phenomenon has been rarely investigated. It is important to highlight that these losses may have a significant impact in PV module and plant performances thus reducing the financial incomes in a nonnegligible way. This paper present and discuss a method which allows to choose the optimal maintenance interval for a PV plant. The method, starting from the costs related to the cleaning of the panels, compares them to the economic losses due to the decrease of the efficiency

Management of moveable assets is a key issue in most industrial manufacturing companies.With complex production systems, numerous and various machining centers, it becomes quite hard to carry out an effective and cost-efficient management of the tools and fixtures needed for ensuring the correct and timely execution of the planned production cycles. A pre-requisite for a correct management of moveable assets is the adoption of proper identification systems to support the traceability and data collection of those pieces of information, which could turn out to be relevant along the life cycle of an asset. Aim of the paper is to provide an empirical model for evaluating the benefits and costs related to the adoption of RFId tags as identifications systems for moveable assets, and in particular in managing machinery tools in a production premise. In order to provide a practical example of applicability of the model, a case study is reported with an in-depth analysis of the potential pros and cons deriving from the implementation of RFId tags.

Management of moveable assets is a key issue in most industrial manufacturing companies. With the increasing complexity of production systems, characterized by numerous and heterogeneous machining centers, it becomes quite hard to carry out an effective and cost-efficient management model of the tools and fixtures needed for ensuring a correct and timely execution of the planned production cycles. A pre-requisite for a proper management of moveable assets is the adoption of identification systems to support the traceability and data collection of the most relevant pieces of information along the life cycle of an asset. Aim of the paper is to provide an assessment model for evaluating the benefits and costs related to the adoption of RFId tags as identifications systems for moveable assets, and in particular in managing machinery tools in a production premise. In order to present a practical example of applicability of the model, an industrial application is reported with an in-depth analysis of the potential benefits and issues deriving from the implementation of RFId tags.

Due to the commodisation and globalization of the markets, manufacturing companies have been pursuing new business models based on productservice bundles, which in literature have been investigated under the broad term of Product-Service Systems (PSS). Efficient provision of PSS is not immediate since it requires as a first condition a deep integration of product and service components and the related delivery processes. As regards durable equipment, maintenance is one of the most relevant and common services offered to the market. The identification of the best maintenance policy, and the expected improvement of availability and productivity of the industrial asset depends upon the knowledge, cognition, and expertise that the provider has on the machine and the related operating conditions. With this regard, it is fundamental to wisely collect and analyze data related to the machine and its delivery process, extracting useful information guiding the policy selection. By investigating the case of a durable equipment manufacturer, the paper focuses on the problem related to the creation of a proper engineering process and data infrastructure for supporting a gradual and robust transition towards a PSS-based business model. A dual perspective vision for ensuring a continuous improvement of maintenance services is proposed and discussed, based on a cross-analysis of the on-field collected data from the industrial asset and the maintenance delivery processes.