Production trend identification and forecast for shop-floor business intelligence

Viharos, Zsolt János and Csanaki, J and Nacsa, János and Edelényi, M and Péntek, C and Kis, Krisztián Balázs and Fodor, Ádám and Csempesz, János (2016) Production trend identification and forecast for shop-floor business intelligence. In: 14th IMEKO TC10 Workshop on Technical Diagnostics 2016: New Perspectives in Measurements, Tools and Techniques for Systems Reliability, Maintainability and Safety. International Measurement Confederation (IMEKO), Milano, pp. 300-306.


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The paper introduces a methodology to define production trend classes and also the results to serve with trend prognosis in a given manufacturing situation. The prognosis is valid for one, selected production measure (e.g. a quality dimension of one product, like diameters, angles, surface roughness, pressure, basis position, etc.) but the applied model takes into account the past values of many other, related production data collected typically on the shop-floor, too. Consequently, it is useful in batch or (customized) mass production environments. The proposed solution is applicable to realize production control inside the tolerance limits to proactively avoid the production process going outside from the given upper and lower tolerance limits. The solution was developed and validated on real data collected on the shop-floor; the paper also summarizes the validated application results of the proposed methodology. © 2016, IMEKO-International Measurement Federation Secretariat. All rights reserved.

Item Type: Book Section
Uncontrolled Keywords: Floors; Tolerance limits; Shop floor; Quality dimension; Production process; Production data; Mass production; Surface roughness; production control; Maintainability
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Research Laboratory on Engineering & Management Intelligence
SWORD Depositor: MTMT Injector
Depositing User: MTMT Injector
Date Deposited: 13 Jan 2017 15:11
Last Modified: 21 Jul 2019 14:11

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