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| dc.contributor.author | Gebremariam, Tewachew Asmare | |
| dc.date.accessioned | 2022-11-25T06:36:10Z | |
| dc.date.available | 2022-11-25T06:36:10Z | |
| dc.date.issued | 2022-02 | |
| dc.identifier.uri | http://ir.bdu.edu.et/handle/123456789/14557 | |
| dc.description.abstract | Overall equipment effectiveness (OEE) is key equipment effectiveness measuring tool in the implementation of total productive maintenance (TPM). Due to the limitations of handling dynamic production loss, a deterministic method of handling OEE is not recommended, because it doesn,t consider the dynamic nature of loss parameter that cause to have daynamic result of OEE. Addtionaly, hidden losses are not investigated and considerd well in deterministic method. As a result, the uncertainty method has been introduced to reduce decision risk. Using the data collected during the production of 10-and 20-liter jerry cans, a study was conducted to investigate the effect of uncertain OEE at the Amhara Golden pipe fitting technology company. Operator log sheets were used to collect primary data for 45 days or 90 shifts to assess the blowing machine's OEE for both products. The analysis has been conducted using four OEE models: model 1 with three deterministic parameters, model 2 with three uncertain parameters, model 3 with five deterministic parameters, and model 4 (proposed) with all five parameters being uncertain. The availability, performance, quality, and OEE world-class evaluation are 90%, 95%, 99%, and 85%, respectively. Model 1's results in availability, performance, quality and OEE are 78.84%, 66.84%, 97.45%, and 50.83% respectively for a 20L product. Model 2 results are expressed as fuzzy numbers; availability (44.5%, 78%, 100%), performance (44.5%, 78.6%, 100%), quality (97.7%, 98.2%, 98.7%), and OEE (19.3%, 60.3%, 98.3%) with a defuzzification value of 44.5%. Model 3 of availability, usability, human factors, performance, and quality is 94.49%, 98.9%, 75.8%, 78.6%, 98.2%, and 54.6%, respectively. Model 4 yielded the following results: availability (89.8%, 92.3%, 94.2%), usability (72.4%, 98.3%, 98.5%), human factor (73.4%), 98.3%, 98.5%), performance (44.9%, 78.6%, 100%), quality (98.1%, 98.2%, 98.3%), and OEE (21.1%, 61.3%, 89.8%) with a defuzzification value of 43.1%. The daily production variation for the 26 days is (10.3%, 50.83%, and 86.84%). The closest models to the daily variation are models 2 and 4 since the result is closer to the daily variation value. Model 4 is selected for its additional importance, which is the visibility of loss. Finally, the uncertainty impact would have been displayed if the planner and scheduler used this OEE result separately. Key Words: TPM, OEE, Uncertain, Deterministic, Modified, Fuzzy Set, Defuzzification. | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Mechanical and Industrial Engineering | en_US |
| dc.title | The Effect of Uncertainty in the Analysis of Overall Equipment Effectiveness (OEE) for Improved productivities. | en_US |
| dc.type | Thesis | en_US |
