Measurement of equipment effectiveness in a fully autonomous chemical plant
2019 (English)Independent thesis Basic level (professional degree), 10 credits / 15 HE credits
Student thesis
Abstract [en]
Linde PLC AB have in combination with the opening of a new fully automated factory acquired the need for an equipment effectiveness measurement tool in order to monitor the availability, performance and quality output for different machines and workstations throughout their fully automated process chain. The overall aim of the project has been to carry out a preliminary study on how to implement such a monitoring system to be able to measure the data more precisely as well as identify possible bottlenecks and the root causes for process disturbances, downtimes and inactivity.
The survey has been conducted using a deductive research approach by studying the internationally known theory of Overall Equipment Effectiveness (OEE). This theoretical framework together with a field study and a quantitative data analysis serves as the foundation for the survey’s results.
The result has shown that OEE as a tool will help the company to better visualize and achieve their main production goals. The analysis is indicating a low but steady increase of the OEE for Carousel 1 at the given sampling frame which was expected due to the incompletion of the plant construction. The survey has also shown that the data extraction points from the PLC’s are not yet fully utilized which makes the equipment down-time hard to pinpoint to a specific improvement area.
The main recommendation for Linde, based on this survey, is to increase the amount of logging datapoints to increase the understanding of stop times. After a successful implementation on Carousel 1, the next logical move would be to implement OEE analysis for the remaining carousels and other automated machines and processes within the plant.
With the latest technology and while still in an early project phase, Linde are in a great position to fully implement OEE as a KPI for process improvements and machine utilization.
Place, publisher, year, edition, pages
2019. , p. 37
Keywords [en]
Overall Equipment Effectiveness, OEE, TPM, Optimization, Automation, data analysis
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-36942Local ID: ET-V19-G3-028OAI: oai:DiVA.org:miun-36942DiVA, id: diva2:1346112
Subject / course
Electrical Engineering ET2
Educational program
Automationsingenjör TAUMG 180 GR
Supervisors
Examiners
2019-08-272019-08-272019-08-27Bibliographically approved