Search results

This work aims at proposing a novel Internet of Things (IoT)-based and cloud-assisted monitoring architecture for smart manufacturing systems able to evaluate their overall status and detect eventual anomalies occurring into the production. A novel artificial intelligence (AI) based technique, able to identify the specific anomalous event and the related risk classification for possible intervention, is hence proposed.

The proposed solution is a five-layer scalable and modular platform in Industry 5.0 perspective, where the crucial layer is the Cloud Cyber one. This embeds a novel anomaly detection solution, designed by leveraging control charts, autoencoders (AE) long short-term memory (LSTM) and Fuzzy Inference System (FIS). The proper combination of these methods allows, not only detecting the products defects, but also recognizing their causalities.

The proposed architecture, experimentally validated on a manufacturing system involved into the production of a solar thermal high-vacuum flat panel, provides to human operators information about anomalous events, where they occur, and crucial information about their risk levels.

Thanks to the abnormal risk panel; human operators and business managers are able, not only of remotely visualizing the real-time status of each production parameter, but also to properly face with the eventual anomalous events, only when necessary. This is especially relevant in an emergency situation, such as the COVID-19 pandemic.

The monitoring platform is one of the first attempts in leading modern manufacturing systems toward the Industry 5.0 concept. Indeed, it combines human strengths, IoT technology on machines, cloud-based solutions with AI and zero detect manufacturing strategies in a unified framework so to detect causalities in complex dynamic systems by enabling the possibility of products’ waste avoidance.

The purpose of this paper is to provide the description of an original framework for maintenance management plan development. The research aims to use in an integrated way different World Class Manufacturing (WCM)-based tools, in order to obtain a model which can be used for preventive maintenance in different industrial contexts.

In this research, a conceptual framework of preventive maintenance was described and then it was evaluated through a qualitative study in an Italian company. The company was chosen based on an initial interview with the operations team and the model area was selected. Then, the location was reorganized in order to obtain a green field which could sustain the implementation of the framework tools.

The case study was carried out in a small-medium manufacturing company which produces quick-release couplings and multiconnections, ranging from medium to ultra-high pressure. The defined framework has proved to be easy to implement in a company with a corrective maintenance plan, allowing the maintenance department to embrace the preventive maintenance culture. The maintenance model has been well received from the employees.

The framework allows a standardization of maintenance plans. Firstly, the standardization design itself allows finding previous wastes and consequent improvement areas. Then, it brings the improvement of a single machine which impacts all other machines in its family.

The added value of this study is the ability to integrate different WCM-based tools. Since the framework depicts a step-by-step process; it is also a starting point for companies that want to approach preventive maintenance for the first time.

The active role that the tourism sector assumes in increasing the Gross Domestic Product is by now recognized and this fact makes the operators in the sector considerably more responsible. So all the companies that operate in the sector need a continous managerial adaptation such that renders them able to answer, time after time, the demand necessities.