A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems
Nowadays, manufacturers are shifting from a traditional product-centric business paradigm to a service-centric one by offering products that are accompanied by services, which is known as Product-Service Systems (PSSs). PSS customization entails configuring products with varying degrees of different...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/6/2118 |
| _version_ | 1797442433724710912 |
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| author | Laila Esheiba Iman M. A. Helal Amal Elgammal Mohamed E. El-Sharkawi |
| author_facet | Laila Esheiba Iman M. A. Helal Amal Elgammal Mohamed E. El-Sharkawi |
| author_sort | Laila Esheiba |
| collection | DOAJ |
| description | Nowadays, manufacturers are shifting from a traditional product-centric business paradigm to a service-centric one by offering products that are accompanied by services, which is known as Product-Service Systems (PSSs). PSS customization entails configuring products with varying degrees of differentiation to meet the needs of various customers. This is combined with service customization, in which configured products are expanded by customers to include smart IoT devices (e.g., sensors) to improve product usage and facilitate the transition to smart connected products. The concept of PSS customization is gaining significant interest; however, there are still numerous challenges that must be addressed when designing and offering customized PSSs, such as choosing the optimum types of sensors to install on products and their adequate locations during the service customization process. In this paper, we propose a data warehouse-based recommender system that collects and analyzes large volumes of product usage data from similar products to the product that the customer needs to customize by adding IoT smart devices. The analysis of these data helps in identifying the most critical parts with the highest number of incidents and the causes of those incidents. As a result, sensor types are determined and recommended to the customer based on the causes of these incidents. The utility and applicability of the proposed RS have been demonstrated through its application in a case study that considers the rotary spindle units of a CNC milling machine. |
| first_indexed | 2024-03-09T12:42:45Z |
| format | Article |
| id | doaj.art-573106bb413441c1bd784d8e379629b2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T12:42:45Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-573106bb413441c1bd784d8e379629b22023-11-30T22:16:29ZengMDPI AGSensors1424-82202022-03-01226211810.3390/s22062118A Data Warehouse-Based System for Service Customization Recommendations in Product-Service SystemsLaila Esheiba0Iman M. A. Helal1Amal Elgammal2Mohamed E. El-Sharkawi3Faculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, EgyptFaculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, EgyptFaculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, EgyptFaculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, EgyptNowadays, manufacturers are shifting from a traditional product-centric business paradigm to a service-centric one by offering products that are accompanied by services, which is known as Product-Service Systems (PSSs). PSS customization entails configuring products with varying degrees of differentiation to meet the needs of various customers. This is combined with service customization, in which configured products are expanded by customers to include smart IoT devices (e.g., sensors) to improve product usage and facilitate the transition to smart connected products. The concept of PSS customization is gaining significant interest; however, there are still numerous challenges that must be addressed when designing and offering customized PSSs, such as choosing the optimum types of sensors to install on products and their adequate locations during the service customization process. In this paper, we propose a data warehouse-based recommender system that collects and analyzes large volumes of product usage data from similar products to the product that the customer needs to customize by adding IoT smart devices. The analysis of these data helps in identifying the most critical parts with the highest number of incidents and the causes of those incidents. As a result, sensor types are determined and recommended to the customer based on the causes of these incidents. The utility and applicability of the proposed RS have been demonstrated through its application in a case study that considers the rotary spindle units of a CNC milling machine.https://www.mdpi.com/1424-8220/22/6/2118data analyticsdata warehousingdecision support systemsproduct-service systems (PSSs)product-service systems customizationproduct usage data |
| spellingShingle | Laila Esheiba Iman M. A. Helal Amal Elgammal Mohamed E. El-Sharkawi A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems Sensors data analytics data warehousing decision support systems product-service systems (PSSs) product-service systems customization product usage data |
| title | A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems |
| title_full | A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems |
| title_fullStr | A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems |
| title_full_unstemmed | A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems |
| title_short | A Data Warehouse-Based System for Service Customization Recommendations in Product-Service Systems |
| title_sort | data warehouse based system for service customization recommendations in product service systems |
| topic | data analytics data warehousing decision support systems product-service systems (PSSs) product-service systems customization product usage data |
| url | https://www.mdpi.com/1424-8220/22/6/2118 |
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