| Title: | Comparative analysis of human and artificial intelligence planning in production processes |
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| Authors: | ID Roblek, Matjaž (Author)
ID Kern, Tomaž (Author)
ID Krhač Andrašec, Eva (Author)
ID Brezavšček, Alenka (Author) |
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| Files: |  processes-12-02300.pdf (3,27 MB)
MD5: 85CDF0D55CA93CED3A531CB731B01FED
 https://www.mdpi.com/2227-9717/12/10/2300
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FOV - Faculty of Organizational Sciences in Kranj
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| Abstract: | Artificial intelligence (AI) has found applications in enterprises′ production planning
processes. However, a critical question remains: could AI replace human planners? We conducted a
comparative analysis to evaluate the main task of planners in an intermittent process: planning the
duration of production orders. Specifically, we analysed the results of a human planner using master
data and those of an AI algorithm compared to the actual realisation. The case study was conducted
in a large production company using a sample of production products and machines. We were able
to confirm two of the three research questions (RQ1 and RQ3), while the results of the third question
(RQ2) did not meet our expectations. The AI algorithms demonstrated significant improvement with
each iteration. Despite this progress, it is still difficult to determine the exact threshold at which AI
outperforms human planners due to the unpredictability of unexpected events. Even though AI
significantly improves prediction accuracy, the inherent variability and incomplete input data pose a
major challenge. As progress is made, robust data collection and management strategies need to be
integrated to bridge the gap between the potential of AI and its practical application, fostering the
symbiosis between human expertise and AI capabilities in production planning. |
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| Keywords: | artificial intelligence, machine learning, production processes, production planning, production scheduling |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 13.09.2024 |
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| Article acceptance date: | 18.10.2024 |
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| Publication date: | 21.10.2024 |
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| Year of publishing: | 2024 |
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| Number of pages: | 23 str. |
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| Numbering: | Vol. 12, iss. 10, [article no.] 2300 |
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| PID: | 20.500.12556/DKUM-91239  |
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| UDC: | 658.5 |
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| COBISS.SI-ID: | 212367363 |
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| DOI: | 10.3390/pr12102300 |
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| Publication date in DKUM: | 04.12.2024 |
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| Views: | 250 |
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| Downloads: | 38 |
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| Metadata: |    |
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| Categories: | Misc.
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