Implementation of intelligent manufacturing algorithms in agile architectures for production: world models for systems incorporating binary and continuous variables

Agile Manufacturing, Intelligent systems, AlgorithmsBuilding in previous works of the authors, the present paper focuses on the extension of the Algorithms described for the specific case study of binary systems (systems in which each variable can take one out of two values), to cases that also incorporate continuous variables (those which can take any continuous value within a range). This extension of the Algorithms makes possible the incorporation of new possibilities and functionalities for the treatment of the information received by the sensors of the manufacturing systems and in particular reduce the number of variables in which to monitor the states and costs of execution. The Construction of World Models based on this logical theory -that incorporates the knowledge derived from the results of a set of experiments conducted by the system utilizing a set of different algorithms- is applicable to a wide range of production systems topologies, which is also visited in the present work.Postprint (published version

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Towards a robot task ontology standard

Ontologies serve robotics in many ways, particularly in de- scribing and driving autonomous functions. These functions are built around robot tasks. In this paper, we introduce the IEEE Robot Task Representation Study Group, including its work plan, initial development efforts, and proposed use cases. This effort aims to develop a standard that provides a comprehensive on- tology encompassing robot task structures and reasoning across robotic domains, addressing both the relationships between tasks and platforms and the relationships between tasks and users. Its goal is to develop a knowledge representation that addresses task structure, with decomposition into subclasses, categories, and/or relations. It includes attributes, both common across tasks and specific to particular tasks and task types

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

Designing a dexterous reconfigurable packaging system for flexible automation

This paper presents a design for a reconfigurable packaging system that can handle cartons of different shape and sizes and is amenable to ever changing demands of packaging industries for perfumery and cosmetic products. The system takes structure of a multi-fingered robot hand, which can provide fine motions, and dexterous manipulation capability that may be required in a typical packaging-assembly line. The paper outlines advanced modeling and simulation undertaken to design the packaging system and discusses the experimental work carried out. The new packaging system is based on the principle of reconfigurability, that shows adaptability to simple as well as complex carton geometry. The rationale of developing such a system is presented with description of its human equivalent. The hardware and software implementations are also discussed together with directions for future research

Changing Patterns in Process Management and Improvement: Using RPA and RDA in Non- Manufacturing Organizations

Being, from the first sight, a complementary part of process management within an organization, process management automation draws a very broad and promising perspective to the whole business field since it is a step closer to the smarter and next level efficiency. Therefore, this particular theoretical scientific research elaborates the topic of the application of Robotic Process Automation (RPA) and Robotic Desktop Automation (RDA) concepts within the work activities in non-manufacturing organizations as this is a non-widely examined area and offers the whole specter of opportunities. Therefore, focuses are based on process management in organizations where client service is key activity and direction with soft systems and operations used as working tools. In addition, a comparative analysis of key similarities and differences of terms and practical application of RPA/RDA within the manufacturing and non-manufacturing sector is provided. Problematic areas, which this particular topic escalates, have a wide framework: first, it is noticed that the scientific field regarding the application of RPA and related concepts in combination with other process management methods (for example, Lean, Agile or Business Process Management (BPM)) has not been widely discussed. Second, in generally most of the past and ongoing scientific researches and practices tendencies and problems in process automation within the manufacturing sector field have been investigated. Accordingly, it is missing both quantitative and qualitative analyses of past and current situations in non-manufacturing business and public organizations. To generalize, it is agreed that process automation has made a notorious impact not only on the tendencies of process management within the business field but also on a society as a human resource. Therefore, investigation of this topic as a very relevant subject is essential since it has a direct and very strong impact on business cycles, technological evolution, and job market

Towards autonomous system: flexible modular production system enhanced with large language model agents

In this paper, we present a novel framework that combines large language models (LLMs), digital twins and industrial automation system to enable intelligent planning and control of production processes. Our approach involves developing a digital twin system that contains descriptive information about the production and retrofitting the automation system to offer unified interfaces of fine-granular functionalities or skills executable by automation components or modules. Subsequently, LLM-Agents are designed to interpret descriptive information in the digital twins and control the physical system through RESTful interfaces. These LLM-Agents serve as intelligent agents within an automation system, enabling autonomous planning and control of flexible production. Given a task instruction as input, the LLM-agents orchestrate a sequence of atomic functionalities and skills to accomplish the task. We demonstrate how our implemented prototype can handle un-predefined tasks, plan a production process, and execute the operations. This research highlights the potential of integrating LLMs into industrial automation systems for more agile, flexible, and adaptive production processes, while also underscoring the critical insights and limitations for future work