A recommender system applied to the indirect materials selection process (RS-IMSP) for producing automobile spare parts
| Autor: | Carlos Alberto Hernández-Lira, Selene Hernández-Rodríguez, O. Vázquez-Cuchillo, Adolfo Aguilar-Rico, Javier Flores-Méndez, Georgina Flores-Becerra |
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| Rok vydání: | 2016 |
| Předmět: |
Engineering
General Computer Science Process (engineering) business.industry General Engineering Brute-force search 02 engineering and technology Recommender system computer.software_genre Task (project management) Set (abstract data type) Order (business) 020204 information systems Spare part 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining business computer Selection (genetic algorithm) |
| Zdroj: | Computers in Industry. 82:233-244 |
| ISSN: | 0166-3615 |
| DOI: | 10.1016/j.compind.2016.07.004 |
| Popis: | We develop a recommender system to improve the process of selecting indirect materials to develop auto parts.Using this system, the exhaustive search and analysis of long catalog lists are avoided.The proposed algorithm starts with a filtering step to select orders requested under similar circumstances.The set of filtered orders are used to approximate the indirect materials to suggest, along with the number of elements to suggest for each material.We could conclude that this process was automated and improved. In this work, the development of a recommender system that aims to facilitate the indirect materials selection task for the creation of spare parts is proposed. In the industrial sector there are spare parts manufacturing companies, where there is a high rotation of staff and this leads to loss of knowledge as new users do not know what indirect materials they should select in the warehouse to create certain parts. The proposed system aims to integrate an indirect materials recommender system to assist this warehouse task. The proposed system is based on the non-personalized approach and similar order circumstances, to perform the recommendation process. From the evaluation of the proposed system, we could conclude that the indirect materials selection process for producing auto parts was improved. |
| Databáze: | OpenAIRE |
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