Fault diagnosis presents a considerable difficulty to human operators in supervisory control of manufacturing systems. Implementing Internet of Things (IoT) technologies in existing manufacturing facilities implies an investment, since it requires upgrading them with sensors, connectivity capabilities, and IoT software platforms. Aligned with the technological vision of Industry 4.0 and based on currently existing information databases in the industry, this work proposes a lower-investment alternative solution for fault diagnosis and problem solving. This paper presents the details of the information and communication models of an application prototype oriented to production. It aims at assisting shop-floor actors during a Manufacturing Problem Solving (MPS) process. It captures and shares knowledge, taking existing Process Failure Mode and Effect Analysis (PFMEA) documents as an initial source of information related to potential manufacturing problems. It uses a Product Lifecycle Management (PLM) system as source of manufacturing context information related to the problems under investigation and integrates Case-Based Reasoning (CBR) technology to provide information about similar manufacturing problems.

During the execution of manufacturing processes, problems arise and they have to be solved systematically to reach and exceed production targets. Normally, a production team analyzes and solves these problems, with the support of different methodologies and working directly on the shop floor. This paper presents an ontology-based approach to easily capture and reuse the knowledge generated in such a process of Manufacturing Problem Solving (MPS). The proposed ontology is used as basis in an ad-hoc MPS software system. The architecture of the MPS system is based on the integration of three technologies: PLM (Product Lifecycle Management), CBR (Case-Based Reasoning) and software agents. The PLM system is used as an automatic source of the problem context information. The CBR system is used as repository of cases and artificial intelligence tool to support the efficient reuse of knowledge during the resolution of new problems. A software agent platform allows developing an integrated prototype of an ad-hoc software system. This paper shows the architecture of the MPS system prototype.