During the last 10 years, manufacturing companies have faced new challenges for improving their value proposition and being more efficient and effective on the market, satisfying the customer needs. According to this trend, several technologies have been developed and applied in different sectors and with different aims, in order to support such the companies in their reconfiguration. For example, the recent advances in Information and Communications Technologies (ICT) could give also to manufacturing industries the competences required to develop novel sustainable products embedded with a dedicated infrastructure able to provide more service functionalities to customer. In this context, the application of Internet of Things (IoT) have allowed developing the so named Product Service Systems (PSSs). Moreover, the cross-fertilization between such the technologies with the development of other ones have fostered the application of these novel ICT technologies inside the manufacturing companies also at process level. This approach has encouraged the study and development of Cyber-Physical Systems (CPSs). The present paper deals with a real industrial use case, where the application of ICT technologies and specifically the adoption of IoT at a plant of plastic extrusion pipes have allowed optimizing the production process in terms of energy efficiency
The topic of digital manufacturing is increasingly emerging in industry. One of the main scope of data digitalization is achieving more efficient factories. Different techniques and tools under the Industry 4.0 paradigm were already discussed in literature. These are aimed mostly at boosting company efficiency in terms of costs and environmental footprint. However, from a sustainability point of view, the social theme must be equally considered. While energy flows or costs can be already monitored in a production plant, this is not valid for data related to human effort. Monitoring systems aimed at supervising factory social sustainability were not already discussed in literature. The aim of this paper is to propose a method to acquire social related data in a production plant. The method is supported by a smart architecture within the concept of IoT factory. Such architecture permits to monitor the parameters that could influence social sustainability in a production site. After a discussion on production plants facilities and features, the parameters that need to be considered to guarantee socially sustainable manufacturing processes are identified. A set of sensors controls these data taken from different sources, including operator vital signs. Operations as well as humans are monitored. Data acquired by sensors are collected by a central server. A decision maker can interpret the data and improve the production system from a social point of view, implementing corrective actions. Data can be exploited not only for social assessments but even for other analyses on the production system. Guaranteeing social sustainability could boost the factory productivity.\ud
A case study is included in the paper: smart sensors are implemented in a production line to understand the operations efficiency in terms of social sustainability
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