**Quality 4.0 in Action: Smart Hybrid Fault Diagnosis System in Plaster Production**

#### **Javaneh Ramezani \* and Javad Jassbi**

Faculty of Sciences and Technology and Uninova CTS, NOVA University of Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal; j.jassbi@uninova.pt

**\*** Correspondence: m.ramezani@campus.fct.unl.pt or ramezanijavaneh@gmail.com

Received: 9 April 2020; Accepted: 21 May 2020; Published: 26 May 2020

**Abstract:** Industry 4.0 (I4.0) represents the Fourth Industrial Revolution in manufacturing, expressing the digital transformation of industrial companies employing emerging technologies. Factories of the future will enjoy hybrid solutions, while quality is the heart of all manufacturing systems regardless of the type of production and products. Quality 4.0 is a branch of I4.0 with the aim of boosting quality by employing smart solutions and intelligent algorithms. There are many conceptual frameworks and models, while the main challenge is to have the experience of Quality 4.0 in action at the workshop level. In this paper, a hybrid model based on a neural network (NN) and expert system (ES) is proposed for dealing with control chart patterns (CCPs). The idea is to have, instead of a passive descriptive model, a smart predictive model to recommend corrective actions. A construction plaster-producing company was used to present and evaluate the advantages of this novel approach, while the result shows the competency and eligibility of Quality 4.0 in action.

**Keywords:** statistical process control; control chart pattern; disruptions; disruption management; fault diagnosis; Industry 4.0; construction industry; plaster production; neural networks; decision support systems; expert systems; failure mode and effects analysis (FMEA); discriminant analysis

#### **1. Introduction, Background, and Problem Statement**
