Publikation

Product Lifecycle Management as Data Repository for Manufacturing Problem Solving

Alvaro Camarillo, José Ríos, Klaus-Dieter Althoff

In: Eva M. Rubio, Ana M. Camacho (Hrsg.). Materials - Special Issue of the Manufacturing Engineering Society 11 1469 Seiten 1-19 MDPI 8/2018.

Abstrakt

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.

Weitere Links

materials-11-01469-v2.pdf (pdf, 6 MB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence