| 1. |
- Flores-García, Erik, et al.
(författare)
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Characterizing Digital Dashboards for Smart Production Logistics
- 2022
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Ingår i: Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. - Cham : Springer Nature Switzerland AG. - 9783031164101 - 9783031164118 ; , s. 521-528, s. 521-528
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Konferensbidrag (refereegranskat)abstract
- Developing digital dashboards (DD) that support staff in monitoring, identifying anomalies, and facilitating corrective actions are decisive for achieving the benefits of Smart Production Logistics (SPL). However, existing literature about SPL has not sufficiently investigated the characteristics of DD allowing staff to enhance operational performance. This conceptual study identifies the characteristics of DD in SPL for enhancing operational performance of material handling. The study presents preliminary findings from an ongoing laboratory development, and identifies six characteristics of DD. These include monitoring, analysis, prediction, identification, recommendation, and control. The study discusses the implications of these characteristics when applied to energy consumption, makespan, on-time delivery, and status for material handling. The study proposes the prototype of a DD in a laboratory environment involving Autonomous Mobile Robots.
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| 2. |
- Flores-García, Erik, et al.
(författare)
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Machine learning in smart production logistics : a review of technological capabilities
- 2024
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Ingår i: International Journal of Production Research. - 0020-7543 .- 1366-588X. ; , s. 1-35
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Tidskriftsartikel (refereegranskat)abstract
- Recent publications underscore the critical implications of adapting to dynamic environments forenhancing the performance of material and information flows. This study presents a systematicreview of literature that explores the technological capabilities of smart production logistics (SPL)when applying machine learning (ML) to enhance logistics capabilities in dynamic environments.This study applies inductive theory building and extends existing knowledge about SPL in threeways. First, it describes the role of ML in advancing the logistics capabilities of SPL across variousdimensions, such as time, quality, sustainability, and cost. Second, this study demonstrates the applicationof the component technologies of ML (i.e. scanning, storing, interpreting, executing, andlearning) to attain superior performance in SPL. Third, it outlines how manufacturing companiescan cultivate the technological capabilities of SPL to effectively apply ML. In particular, the studyintroduces a comprehensive framework that establishes the technological foundations of SPL, thusfacilitating the successful integration of ML, and the improvement of logistics capabilities. Finally,the study outlines practical implications for managers and staff responsible for the planning andexecution of tasks, including the movement of materials and information in factories.
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| 3. |
- Jeong, Yongkuk, et al.
(författare)
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Digital Twin-Based Services and Data Visualization of Material Handling Equipment in Smart Production Logistics Environment
- 2022
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Ingår i: Advances in Production Management Systems. Smart Manufacturing and Logistics Systems. - Cham : Springer Nature. ; , s. 556-564
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Konferensbidrag (refereegranskat)abstract
- Smart production logistics has introduced in manufacturing industries with emerging technologies such as digital twin, industrial internet of things, and cyber-physical system. This technological innovation initiates the new way of working, working environment, and decision-making process. Especially the decision-making process has changed from experience and intuition to knowledge and data driven. In this paper, digital twin-based services, and data visualization of material handling equipment in smart production logistics environment are presented. There are several applications of digital twin in manufacturing industries already, however feedback from the virtual environment to physical environment and interactions between them which are the essential features of digital twin are very weak in many applications. Therefore, we have developed digital twin-based services in the laboratory scale including feedback and interaction. In addition, data visualization application of material handling equipment in automotive industry is presented to provide insights to the users. Both applications have developed based on the same framework including database and middleware, so it has possibilities to develop further in the future.
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