Exploring the benefits of scheduling with advanced and real-time information integration in Industry 4.0: A computational study

Fernández-Viagas, Victor

doi:10.1016/j.jii.2021.100281

Cited by 18 publications

(9 citation statements)

References 47 publications

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“…For instance, Framinan, Fernandez-Viagas [30] showed that rescheduling improves the performance of the shopfloor with low to medium variability in processing times, and that investments in capturing real-time data at the scheduling level could be worthwhile. Further, Fernandez-Viagas and Framinan [31] demonstrated that the advantages of using realtime, integrated data rely extensively on the appropriate selection of both the scheduling approach and the solution approach.…”

Section: Schedulingmentioning

confidence: 99%

Production Scheduling Using Production Feedback Data; An Illustrative Case Study

Rahmani,

Romsdal,

Syversen

et al. 2023

IFIP Advances in Information and Communication Technology

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Industry 4.0 is providing unprecedented opportunities for the capture and use of data into production planning and control (PPC). The accuracy of such data for PPC has been found to have a direct positive effect on operational performance. This study builds on a dynamic approach where production feedback data is used to improve the accuracy of master data used in tactical planning. The study applies a model-based approach using data from a real case. Two illustrative sensitivity analyses indicate that even small deviations in the accuracy of master data have an impact on the production schedule in terms of job sequence and makespan. The paper's main theoretical contribution is the development of six propositions on this relationship, where in short, the sequence appears to be sensitive to the accuracy of both changeover time and processing time. The paper illustrates how sensitivity analysis can be used in investment decisions about which production feedback data to capture and use for PPC purposes. Further research should test the propositions in more real cases and other production environments and carry out sensitivity analyses with more types of master data, variables, and combinations.

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Section: Schedulingmentioning

confidence: 99%

Production Scheduling Using Production Feedback Data; An Illustrative Case Study

Rahmani,

Romsdal,

Syversen

et al. 2023

IFIP Advances in Information and Communication Technology

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“…In addition, I4.0 technologies were adopted into optimization models in another application [20] where the new system and mathematical model were described and showed a major advantage. On the other side, a study showed that the benefit of using integrated real-time in the designed models in the scheduling process depended on the proper choice of both the scheduling approach and the solution procedures, and in a few scenarios, this usage was even counterproductive [21], which encourages further research regarding the design of approaches and solution procedures that allow fully exploiting the technological advances of I4.0 for decision-making in scheduling.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy Consumption Optimization of Milk-Run-Based In-Plant Supply Solutions: An Industry 4.0 Approach

Akkad

Bányai

2023

Processes

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Smart factories are equipped with Industry 4.0 technologies including smart sensors, digital twin, big data, and embedded software solutions. The application of these technologies contributes to better decision-making, and this real-time decision-making can improve the efficiency of both manufacturing and related logistics processes. In this article, the transformation of conventional milk-run-based in-plant supply solutions into a cyber–physical milk-run supply is described, where the application of Industry 4.0 technologies makes it possible to make real-time decisions regarding scheduling, routing, and resource planning. After a literature review, this paper introduces the structure of Industry 4.0 technologies supported by milk-run-based in-plant supply. A mathematical model of milk-run processes is described including both scheduling and routing problems of in-plant supply. This mathematical model makes it possible to analyze the impact of Industry 4.0 technologies on the efficiency, performance, and flexibility of in-plant supply logistics. The scenarios’ analysis validates the mathematical model and shows that significant performance improvement and energy savings can be achieved using Industry 4.0 technologies. This performance improvement can lead to a more cost-efficient and sustainable in-plant supply solution, where not only logistics aspects but also energy efficiency and emissions can be taken into consideration.

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“…By empowering machines to simulate human intelligence, artificial intelligence has achieved rapid progress in computer vision, image recognition, and language processing, gradually moving from academic research to commercialization for a wide range of applications. Entering the industrial 4.0 era, the traditional manufacturing industry has transformed into intelligent manufacturing and realized the industrial IoT to create value and save costs (Bellini et al, 2022; Ehret & Wirtz, 2017; Fernandez‐Viagas & Framinan, 2021; Karnik et al, 2021; Xu, 2020).…”

Section: Technology Entrepreneurshipmentioning

confidence: 99%

From ideas to entrepreneurial opportunity: A study on AI

Wang

Yao

2022

Syst Res Behav Sci

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Artificial intelligence technology is applied in numerous fields. Several countries around the world have introduced national policies on artificial intelligence, and the competition for this emerging technology has become an important driving force for industrial development. In recent years, interdisciplinary research on artificial intelligence has made great progress. From the perspective of idea‐driven technology entrepreneurship, we discuss the concept of AI with other emerging technologies. For the early stage of the entrepreneurial process, from idea generation to entrepreneurial opportunity exploitation, we elaborate on the role played by AI. Finally, the future research prospects are proposed.

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Exploring the benefits of scheduling with advanced and real-time information integration in Industry 4.0: A computational study

Cited by 18 publications

References 47 publications

Production Scheduling Using Production Feedback Data; An Illustrative Case Study

Production Scheduling Using Production Feedback Data; An Illustrative Case Study

Energy Consumption Optimization of Milk-Run-Based In-Plant Supply Solutions: An Industry 4.0 Approach

From ideas to entrepreneurial opportunity: A study on AI

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