SUDIHA; Holonique Architecture using Kanban Card to dynamic scheduling in Manufacturing

Khadiri, Hassan; Sekkat, Souhail; Azri, Zineb El; Herrou, Brahim

doi:10.1109/iceccme52200.2021.9591051

Cited by 1 publication

(5 citation statements)

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“…We develop Digital Twin based SUDIHA architecture (DT-SUDIHA). However, before describing the DT-based architecture we propose, we first review the SUDIHA architecture we have proposed for dynamic scheduling of CPPS [8].…”

Section: Dt Design Processmentioning

confidence: 99%

“…We used distributed scheduling and proposed an architecture that includes both a Supervised part and a Distributed part. On the one hand, in the Supervised part, a supervisory agent used the Optimized Production Technology OPT method to identify a bottleneck station, such as example station C in the case of Figure 2, and on the other hand, in the distributed part it used the Kanban method between the bottleneck and the upstream station and the priority rules in the other stations [8]. Since Holonic Architecture is relevant to achieve distributed control [7], we proposed it to achieve shopfloor scheduling and adopted the Multi-Agent methodology to develop this Holonic architecture [27,28].…”

Section: Sudiha Proposed Holonic Architecturementioning

confidence: 99%

“…We were inspired by the model of the Product Agent architecture proposed by Kovalenko [44] and used the BDI model proposed by Phung [45]. In [8] we proposed a sequence diagram showing the interaction between the three Holons of SUDIHA architecture.…”

Section: Sudiha Proposed Holonic Architecturementioning

confidence: 99%

“…To address the autonomy requirement and achieve dynamic scheduling, Holonic Architecture can be used [7]. We used, then, in the International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), an agent-oriented development process to propose a Supervised and Distributed Holonic architecture we called SUDIHA [8].…”

Section: Introductionmentioning

confidence: 99%

“…Then, we carried out a case study at the ENSAM-Meknes flexible work cell to prove the effectiveness of the proposed approach. We propose, then, the design and implementation of a framework based on DTs for Cyber Physical Production System scheduling; it is an extension of our paper [8] where we proposed SUDIHA Supervised and Distributed Holonic architecture for dynamic scheduling. We will improve the SUDIHA architecture by using a DT Model and develop Digital Twin based SUDIHA architecture (DT-SUDIHA).…”

Section: Introductionmentioning

confidence: 99%

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Digital Twin Based SUDIHA Architecture to Smart Shopfloor Scheduling

Khadiri

Sekkat

Herrou

2023

JMMP

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Standing on the brink of the fourth industrial revolution, Cyber Physical Systems (CPS) are considered the basic components of the Smart Factory. One important challenge in cyber physical production systems is dynamic scheduling that can handle random disruptions such as failures, raw material shortages and quality defects. To achieve dynamic scheduling, we have proposed a Supervised and Distributed Holonic architecture we called SUDIHA. This architecture incorporates three Holons: Product Holon, Resource Holon and Order Holon and combines global supervision, achieved by Product Holon, with dynamic local control, achieved by Resource Holon. The Digital Twin (DT) concept is generally used to design CPS; it is virtual copies of the system that can interact with the physical counterparts in a bi-directional way. It seems to be promising to tackle the complexity and increase manufacturing system flexibility. In this paper, we use a DT Model to improve the SUDIHA architecture. We propose a Digital Twin based SUDIHA architecture (DT-SUDIHA). The paper will describe Digital Twins’ configuration of each Holon of the SUDIHA Architecture, and the intelligent and real time data driven operation control of this architecture. A case study is carried out at the ENSAM-Meknes flexible workshop to prove the effectiveness of the proposed approach.

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Section: Dt Design Processmentioning

confidence: 99%