Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation
The accuracy of stockpile estimations is of immense criticality to process optimisation and overall financial decision making within manufacturing operations. Despite well-established correlations between inventory management and profitability, safe deployment of stockpile measurement and inspection...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/17/3356 |
| _version_ | 1797520993583890432 |
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| author | Ahmad Alsayed Akilu Yunusa-Kaltungo Mark K. Quinn Farshad Arvin Mostafa R. A. Nabawy |
| author_facet | Ahmad Alsayed Akilu Yunusa-Kaltungo Mark K. Quinn Farshad Arvin Mostafa R. A. Nabawy |
| author_sort | Ahmad Alsayed |
| collection | DOAJ |
| description | The accuracy of stockpile estimations is of immense criticality to process optimisation and overall financial decision making within manufacturing operations. Despite well-established correlations between inventory management and profitability, safe deployment of stockpile measurement and inspection activities remain challenging and labour-intensive. This is perhaps owing to a combination of size, shape irregularity as well as the health hazards of cement manufacturing raw materials and products. Through a combination of simulations and real-life assessment within a fully integrated cement plant, this study explores the potential of drones to safely enhance the accuracy of stockpile volume estimations. Different types of LiDAR sensors in combination with different flight trajectory options were fully assessed through simulation whilst mapping representative stockpiles placed in both open and fully confined areas. During the real-life assessment, a drone was equipped with GPS for localisation, in addition to a 1D LiDAR and a barometer for stockpile height estimation. The usefulness of the proposed approach was established based on mapping of a pile with unknown volume in an open area, as well as a pile with known volume within a semi-confined area. Visual inspection of the generated stockpile surface showed strong correlations with the actual pile within the open area, and the volume of the pile in the semi-confined area was accurately measured. Finally, a comparative analysis of cost and complexity of the proposed solution to several existing initiatives revealed its proficiency as a low-cost robotic system within confined spaces whereby visibility, air quality, humidity, and high temperature are unfavourable. |
| first_indexed | 2024-03-10T08:05:24Z |
| format | Article |
| id | doaj.art-e521828c093545baa107ef8bffb829f0 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T08:05:24Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e521828c093545baa107ef8bffb829f02023-11-22T11:07:36ZengMDPI AGRemote Sensing2072-42922021-08-011317335610.3390/rs13173356Drone-Assisted Confined Space Inspection and Stockpile Volume EstimationAhmad Alsayed0Akilu Yunusa-Kaltungo1Mark K. Quinn2Farshad Arvin3Mostafa R. A. Nabawy4Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester M1 3BB, UKDepartment of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester M1 3BB, UKDepartment of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester M1 3BB, UKDepartment of Electrical and Electronic Engineering, The University of Manchester, Manchester M1 3BB, UKDepartment of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester M1 3BB, UKThe accuracy of stockpile estimations is of immense criticality to process optimisation and overall financial decision making within manufacturing operations. Despite well-established correlations between inventory management and profitability, safe deployment of stockpile measurement and inspection activities remain challenging and labour-intensive. This is perhaps owing to a combination of size, shape irregularity as well as the health hazards of cement manufacturing raw materials and products. Through a combination of simulations and real-life assessment within a fully integrated cement plant, this study explores the potential of drones to safely enhance the accuracy of stockpile volume estimations. Different types of LiDAR sensors in combination with different flight trajectory options were fully assessed through simulation whilst mapping representative stockpiles placed in both open and fully confined areas. During the real-life assessment, a drone was equipped with GPS for localisation, in addition to a 1D LiDAR and a barometer for stockpile height estimation. The usefulness of the proposed approach was established based on mapping of a pile with unknown volume in an open area, as well as a pile with known volume within a semi-confined area. Visual inspection of the generated stockpile surface showed strong correlations with the actual pile within the open area, and the volume of the pile in the semi-confined area was accurately measured. Finally, a comparative analysis of cost and complexity of the proposed solution to several existing initiatives revealed its proficiency as a low-cost robotic system within confined spaces whereby visibility, air quality, humidity, and high temperature are unfavourable.https://www.mdpi.com/2072-4292/13/17/3356dronestockpile modellingvolume estimationcement industryconfined spaceprocess safety |
| spellingShingle | Ahmad Alsayed Akilu Yunusa-Kaltungo Mark K. Quinn Farshad Arvin Mostafa R. A. Nabawy Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation Remote Sensing drone stockpile modelling volume estimation cement industry confined space process safety |
| title | Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation |
| title_full | Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation |
| title_fullStr | Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation |
| title_full_unstemmed | Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation |
| title_short | Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation |
| title_sort | drone assisted confined space inspection and stockpile volume estimation |
| topic | drone stockpile modelling volume estimation cement industry confined space process safety |
| url | https://www.mdpi.com/2072-4292/13/17/3356 |
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