|Bibliography||Wieland, Matthias; Hirmer, Pascal; Steimle, Frank; Gröger, Christoph; Mitschang, Bernhard; Rehder, Eike; Lucke, Dominik; Abdul Rahman, Omar; Bauernhansl, Thomas: Towards a Rule-Based Manufacturing Integration Assistant. |
In: Westkämper, Engelbert (ed.); Bauernhansl, Thomas (ed.): Proceedings of the 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016); Stuttgart, Germany, May 25-27, 2016.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
Procedia CIRP; 57, pp. 213-218, english.
Elsevier, January 2017.
Article in Proceedings (Conference Paper).
|CR-Schema||H.4.0 (Information Systems Applications General)|
J.2 (Physical Sciences and Engineering)
I.2.1 (Applications and Expert Systems)
I.2.4 (Knowledge Representation Formalisms and Methods)
|Keywords||Rules; Integration; Manufacturing; Smart-Factory; Industrie 4.0|
Recent developments and steadily declining prices in ICT enable an economic application of advanced digital tools in wide areas of manufacturing. Solutions based on concepts and technologies of the Internet of Things¯ or Cyber Physical Systems can be used to implement monitoring as well as self-organization of production, maintenance or logistics processes. However, integration of new digital tools in existing heterogeneous manufacturing IT systems and integration of machines and devices into manufacturing environments is an expensive and tedious task. Therefore, integration issues on IT and manufacturing level significantly prevent agile manufacturing. Especially small and medium-sized enterprises do not have the expertise or the investment possibilities to realize such an integration. To tackle this issue, we present the approach of the Manufacturing Integration Assistant - MIALinx. The objective is to develop and implement a lightweight and easy-to-use integration solution for small and medium-sized enterprises based on recent web automation technologies. MIALinx aims to simplify the integration using simple programmable, flexible and reusable IF-THEN rules that connect occurring situations in manufacturing, such as a machine break down, with corresponding actions, e.g., an automatic maintenance order generation. For this purpose, MIALinx connects sensors and actuators based on defined rules whereas the rule set is defined in a domain-specific, easy-to-use manner to enable rule modeling by domain experts. Through the definition of rule sets, the workersā€™ knowledge can be also externalized. Using manufacturing-approved cloud computing technologies, we enable robustness, security, and a low-effort, low-cost integration of MIALinx into existing manufacturing environments to provide advanced digital tools also for small and medium-sized enterprises.
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|Department(s)||University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems|
|Entry date||January 17, 2017|