Combining Adaptive Holonic Control and ISA-95 Architectures to Self-Organize the Interaction in a Worker-Industrial Robot Cooperative Workcell

Sadik, Ahmed R.; Urban, Bodo

doi:10.3390/fi9030035

Cited by 7 publications

(9 citation statements)

References 21 publications

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“…The difficulty of answering this question stands from the fact that the answer is beyond an efficient scheduling algorithm only, since it needs an intelligent information control and communication solution which can understand the overall status of the workcell and monitor the worker time to be able to take logical decisions and therefore can apply the scheduling algorithm. During this research, we extend the research in [3] by applying Johnson algorithm to schedule the cooperation at the case-study. The required solution components as well as Johnson algorithm are going to be explained in details in the next section.…”

Section: Case-study Description and Problem Formulationmentioning

confidence: 99%

“…Every pump order has a different customization level and a specific required quantity. However, the pump customization is out of the focus of this article (refer to [3]). The jobs scheduling is based on the previously mentioned Johnson algorithm for our case-study.…”

Section: Holonic Control Architecture Implementationmentioning

confidence: 99%

“…Sadik, and Urban are addressing the problem of self-organization in the cooperative workcell in [3]. They are mainly answering the question of how the cooperative workcell can continuously adapt to the variation in the number of workers or cobots during the cooperative manufacturing.…”

Section: Introduction and Related Researchmentioning

confidence: 99%

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Flow Shop Scheduling Problem and Solution in Cooperative Robotics—Case-Study: One Cobot in Cooperation with One Worker

Sadik

Urban

2017

Future Internet

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This research combines between two different manufacturing concepts. On the one hand, flow shop scheduling is a well-known problem in production systems. The problem appears when a group of jobs shares the same processing sequence on two or more machines sequentially. Flow shop scheduling tries to find the appropriate solution to optimize the sequence order of this group of jobs over the existing machines. The goal of flow shop scheduling is to obtain the continuity of the flow of the jobs over the machines. This can be obtained by minimizing the delays between two consequent jobs, therefore the overall makespan can be minimized. On the other hand, collaborative robotics is a relatively recent approach in production where a collaborative robot (cobot) is capable of a close proximity cooperation with the human worker to increase the manufacturing agility and flexibility. The simplest case-study of a collaborative workcell is one cobot in cooperation with one worker. This collaborative workcell can be seen as a special case of the shop flow scheduling problem, where the required time from the worker to perform a specific job is unknown and variable. Therefore, during this research, we implement an intelligent control solution which can optimize the flow shop scheduling problem over the previously mentioned case-study.

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Section: Case-study Description and Problem Formulationmentioning

confidence: 99%

Section: Holonic Control Architecture Implementationmentioning

confidence: 99%

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Flow Shop Scheduling Problem and Solution in Cooperative Robotics—Case-Study: One Cobot in Cooperation with One Worker

Sadik

Urban

2017

Future Internet

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“…The research in [13] proposes the idea of linking the concept of holonic manufacturing architecture to the international society of automation (ISA)-95 standard to obtain this integration. On the horizontal level, the research proposes a supervisor holon which is providing coordination services when it is needed to cooperate outside the boundaries of the cooperative workcell.…”

mentioning

confidence: 99%

“…Self-organization is an adaptation mechanism which is used by the cooperative workcell to overcome the variations in the manufacturing environment. The articles in [13][14][15] mention four important sources of variations that can be found in the cooperative workcell. The first source comes from the variation in the production requirements such as the production customization and volume.…”

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confidence: 99%

An Ontology-Based Approach to Enable Knowledge Representation and Reasoning in Worker–Cobot Agile Manufacturing

Sadik

Urban

2017

Future Internet

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Abstract:There is no doubt that the rapid development in robotics technology has dramatically changed the interaction model between the Industrial Robot (IR) and the worker. As the current robotic technology has afforded very reliable means to guarantee the physical safety of the worker during a close proximity interaction with the IR. Therefore, new forms of cooperation between the robot and the worker can now be achieved. Collaborative/Cooperative robotics is the new branch of industrial robotics which empowers the idea of cooperative manufacturing. Cooperative manufacturing significantly depends on the existence of a collaborative/cooperative robot (cobot). A cobot is usually a Light-Weight Robot (LWR) which is capable of operating safely with the human co-worker in a shared work environment. This is in contrast with the conventional IR which can only operate in isolation from the worker workspace, due to the fact that the conventional IR can manipulate very heavy objects, which makes it so dangerous to operate in direct contact with the worker. There is a slight difference between the definition of collaboration and cooperation in robotics. In cooperative robotics, both the worker and the robot are performing tasks over the same product in the same shared workspace but not simultaneously. Collaborative robotics has a similar definition, except that the worker and the robot are performing a simultaneous task. Gathering the worker and the cobot in the same manufacturing workcell can provide an easy and cheap method to flexibly customize the production. Moreover, to adapt with the production demands in the real time of production, without the need to stop or to modify the production operations. There are many challenges and problems that can be addressed in the cooperative manufacturing field. However, one of the most important challenges in this field is the representation of the cooperative manufacturing environment and components. Thus, in order to accomplish the cooperative manufacturing concept, a proper approach is required to describe the shared environment between the worker and the cobot. The cooperative manufacturing shared environment includes the cobot, the co-worker, and other production components such as the product itself. Furthermore, the whole cooperative manufacturing system components need to communicate and share their knowledge, to reason and process the shared information, which eventually gives the control solution the capability of obtaining collective manufacturing decisions. Putting into consideration that the control solution should also provide a natural language which is human readable and in the same time can be understood by the machine (i.e., the cobot). Accordingly, a distributed control solution which combines an ontology-based Multi-Agent System (MAS) and a Business Rule Management System (BRMS) is proposed, in order to solve the mentioned challenges in the cooperative manufacturing, which are: manufacturing knowledge representation, sharing, and reasoning.

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Self-Organization in Smart Manufacturing— Background, Systematic Review, Challenges and Outlook

et al. 2023

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The concept of smart manufacturing has attracted huge attention in the last years as an answer to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces the notion of autonomous and self-organized elements, capable of self-management and self-decision-making under a context-aware and intelligent infrastructure. While dealing with dynamic and uncertain environments, these solutions are also contributing to generating social impact and introducing sustainability into the industrial equation thanks to the development of task-specific resources that can be easily adapted, re-used, and shared. A lot of research under the context of self-organization in smart manufacturing has been produced in the last decade considering different methodologies and developed under different contexts. Most of these works are still in the conceptual or experimental stage and have been developed under different application scenarios. Thus, it is necessary to evaluate their design principles and potentiate their results. The objective of this paper is threefold. First, to introduce the main ideas behind self-organization in smart manufacturing. Then, through a systematic literature review, describe the current status in terms of technological and implementation details, mechanisms used, and some of the potential future research directions. Finally, the presentation of an outlook that summarizes the main results of this work and their interrelation to facilitate the development of self-organized manufacturing solutions. By providing a holistic overview of the field, we expect that this work can be used by academics and practitioners as a guide to generate awareness of possible requirements, industrial challenges, and opportunities that future self-organizing solutions can have towards a smart manufacturing transition.

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Combining Adaptive Holonic Control and ISA-95 Architectures to Self-Organize the Interaction in a Worker-Industrial Robot Cooperative Workcell

Cited by 7 publications

References 21 publications

Flow Shop Scheduling Problem and Solution in Cooperative Robotics—Case-Study: One Cobot in Cooperation with One Worker

Flow Shop Scheduling Problem and Solution in Cooperative Robotics—Case-Study: One Cobot in Cooperation with One Worker

An Ontology-Based Approach to Enable Knowledge Representation and Reasoning in Worker–Cobot Agile Manufacturing

Self-Organization in Smart Manufacturing— Background, Systematic Review, Challenges and Outlook

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