SYROCO: A novel multi-agent shop-floor control system

The high cost and long development cycle of shop floor control systems and the lack of true system integration capabilities are identified as one of the most challenging obstacles in deploying e-Manufacturing systems. Overcoming these obstacles is essential for manufacturers to execute a make-to-order business model in order to stay competitive and remain profitable in the future. We propose a formal method to generate the desired control trajectories and provide true integration mechanisms for shop floor control systems. Using the proposed architecture can result in the development of an e-Manufacturing system capable of achieving a substantial reduction of both the high cost and long development cycle currently required to engineer shop floor control systems. By taking advantage of both the linear growth of the complexity function in a structured adaptive supervisory control model and the information-centric characteristics of a virtual production line in a manufacturing execution system, a formal model, which we call an extended structured adaptive supervisory control, for a discrete manufacturing system is introduced. A shop floor control system based on the extended structured adaptive supervisory control model is built for an industrial testbed system. The shop floor control system is fully tested and evaluated.

In the previous chapter we presented an information technology reference architecture for FC and PAC. We now describe some Information Technology tools and standards, currently available and under development, which we believe may be important in realizing successful implementations of FC and PAC. Our primary objective in this chapter is to examine our information technology reference architecture for shop floor control systems, and associate with it specific hardware and software tools. We briefly review the most important information technology tools and standards, and give examples of how these tools can be applied in real-life shop floor control systems. Furthermore, we stress the importance of portability, flexibility and inter-operability for shop floor control systems, attributes which we believe are vitally important in a multi-vendor computing environment. The structure of this chapter is as follows: 1 We present an initial overview of information technology, highlighting the importance of flexibility, inter-operability and portability of IT systems. A general computing model is then introduced, and this contains four essential elements required to realize an information technology implementation of shop floor control. These elements are communication systems, data management systems, processing systems and user-interface systems. 2 The main body of the chapter describes the relevant state-of-the-art technologies of the four elements included in the general computing model. At the conclusion of each section, a synthesis of what we believe are the most suitable technologies is presented, in the form a shop floor control model for each particular computing element. Thus, we also present a communication systems model, a data management model, a processing model and an user-interface model for the implementation of FC and PAC systems. 3 Finally, we focus our attention on the emerging object-oriented technology, which holds the promise of highly portable, flexible and interoperable solutions within the domain of shop floor control.

As the complexity and scale of modern buildings increase, there is a growing need for efficient, scalable, and flexible control systems to manage the myriad of sensors, actuators, and meters involved in building automation. Traditional building management systems (BMS) struggle with scalability, especially when dealing with multi-agent control setups that require extensive manual configuration. This limitation poses significant challenges in deploying advanced control strategies across different building environments, leading to inefficiencies and underutilization of building automation technologies.Previous research has explored various aspects of multi-agent systems (MAS) in building automation, including agent-based modeling, decentralized control strategies, and the application of machine learning to optimize building operations. However, much of the existing work has focused on small-scale implementations or specific applications, such as energy management or HVAC control. The problem of automating the setup of multi-agent control systems to adapt to different building environments with minimal manual intervention remains largely unaddressed.The aim of this work is to develop a scalable framework for the automated setup of multi-agent control systems in buildings. This framework will enable the seamless integration of sensors, actuators, and meters into a unified control system, significantly reducing the need for manual configuration. The framework will leverage large language models (LLMs) for semantic tagging and context understanding, thereby facilitating the automated configuration of action and input spaces for individual agents within the control system.The proposed framework will consist of three key components: (1) an LLM-based system for semantic tagging and context interpretation, (2) an automated setup process for defining the action and input spaces of the agents, (3) and an initial offline training of the agents. The LLM will be trained on a diverse dataset of building management setups to ensure it can accurately tag and interpret various building elements. The system will be tested in real-world office buildings to evaluate its scalability, accuracy, and effectiveness.Preliminary simulations indicate that the automated setup framework can significantly reduce the time and effort required to deploy multi-agent control systems in buildings. We expect that this framework will enable more scalable and flexible building management systems, ultimately leading to improved energy efficiency, occupant comfort, and overall operational performance. The significance of this work lies in its potential to transform the deployment of building automation systems, making advanced control strategies more accessible and cost-effective across various building types and scales.

Production-Monitoring Integration in Planning and Control of FMS

This paper examines the role that both the planning and shop floor control systems play in the operation and performance of a dual resource constrained (DRC) job shop. Using causal analysis, the results show an effective planning system, as it accounts for the largest gain in shop performance. Generating and releasing smoothed schedules (work loads) allows the use of simplified shop floor control procedures such as Order Review/Release (ORR), job dispatching and labour assignment rules without adversely affecting performance. This study uses the results to resolve the current paradox surrounding ORR systems and shows that the ORR rules' performance is strongly dependent on the planning system, and that ORR rules can be considered moderating variables. Further, the study develops a variance control framework that indicates the necessary managerial actions to improve shop performance. This paper demonstrates that the planning system, not the shop floor control system, is the major determinant of shop perfor...

A shop floor control system (SFCS), which is the most important component of any production control system, ff has a direct e ect on the productivity of a tool room. The SFCS presented in this paper aims at streamlining various tool room activities, such as process planning, operations scheduling, loading, progress monitoring, and performance monitoring. The system discussed in this paper is characterized by simplicity and is user friendly. Basic information, consisting of three types of information (order details, process details, and part details), is input through interactive dialogue sessions. On-line updating of the process information is carried out, again through interactive dialogue sessions. The basic input to the system along with the on-line updating enables a number of useful and important reports and documents to be generated ff by the system for e ective control of the shop floor. The reports generated include operations scheduling, process sheet, part list, ffi job card, load pending report, e ciency report, etc. This SFCS is developed for a medium sized tool room in an automotive company and its successful implemention reduced paperwork and improved resource management and has resulted in productivity. It can be said that this system offers a first venture into computer integrated manufacturing (CIM) for a tool room.

Implementing an Information Control System for Manufacturing

Intelligent workstation controller for computer-integrated manufacturing: Problems and models

Ever-stricter environmental legislation over the past decade has led to the emergence of the end-of-life (EOL) industrial sector, e.g. remanufacturing of products, recycling of material and the recovery of energy. Due to uncertainties over returned product quantities, product quality and product diversity, production planning and control in EOL activities is quite different from those in the forward supply chain. In fact, those uncertainties can be diminished by enhancing the exploitation of the related information generated throughout the product lifecycle. Product lifecycle management provides an opportunity to access and share the distributed information generally available in the product lifecycle, while agent-based systems have been found to be effective tools in such large, uncertain environments. In this article, a product lifecycle information system that deploys agents is introduced into a typical EOL shop floor control system to provide lifecycle information for the returned product for decision-making. Supported by radio frequency identification technology, the product itself controls processes aggressively and autonomously in a system designed to minimise uncertainty. A case study of how the system supports shop floor planning and control in a plastics recycling plant is described at the end of the article.

In this dissertation, new algorithms for formation control of multi agent systems (MAS) based on continuum mechanics principles will be suggested. For this purpose, agents of the MAS are considered as particles in a continuum, evolving in R^n, whose desired configuration is required to satisfy an admissible deformation function. Considered is a specific class of mappings that are called homogenous where the Jacobian of the mapping is only a function of time and is not spatially varying. The primary objectives of this dissertation are to develop the necessary theory and its validation on a mobile-agent based swarm test bed that includes two primary tasks: 1) homogenous transformation of MAS and 2) deployment of a random distribution of agents on a desired configuration. Developed will be a framework based on homogenous transformations for the evolution of an MAS in an n-dimensional space (n=1,2, and 3), under1) no inter-agent communication (predefined motion plan), 2) local inter-agent communication, and 3) intelligent perception by agents. In this dissertation, different communication protocols for MAS evolution that are based on certain special features of a homogenous transformation will be developed. It is also aimed to deal with the robustness of tracking of a desired motion by an MAS evolving in R^n. Furthermore, the effect of communication delays in an MAS evolving under consensus algorithms or homogenous maps is investigated. In this regard, the maximum allowable communication delay for MAS evolution is formulated on the basis of eigen-analysis.

The cyber-security of multi-agent control systems has become vital in practice. To protect the communication process between the individual agents over TCP/IP networks, one must encrypt the messages to be sent, which is costly in a large-scale network when high-level security is demanded. To lessen the burden of heavy encryption and decryption processes, we introduce the Homomorphic Encryption to reduce the number of encryption/decryption terminals that are supposed to equip with every agent. The security is enhanced by the quantum key distribution technology, which can generate secret keys that are theoretically absolutely secure even against quantum computation. We proposed a hybrid method that make good use of the randomness of quantum keys, one-time pad and symmetric encryption to make sure the overall security of homomorphic encryption algorithms. Numerical simulations are provided to illustrate how our scheme.

New Approaches to Shop Floor Scheduling in the Engineering Industry

This paper proposes a new multiagent control system (MACS) for service restoration in distribution systems with integrated distributed generation (DG) units. First, the MACS detects and locates faults, then decides the optimal reconfiguration of the network for restoring de-energized loads, and finally regulates the nodes voltages. Unintentional islanding operation of DG units is avoided and different postfault response modes of DG unit are addressed in the MACS design. The MACS has a hybrid centralizeddecentralized structure where agents are arranged in two layers with different responsibilities and communication capabilities. Agents at load buses in the first layer can only communicate directly with its next neighbor load agents on the same feeder and to its feeder agent, whereas the higher level agents in the second layer can communicate directly with each other. This MACS structure reduces the possibilities of control system failures for a moderate communication network infrastructure. Full dynamic simulation model for evaluating the MACS is implemented.

This paper proposes a multiagent control system (MACS) for a fossil-fuel power unit (FFPU). The MACS consists of fossil-fuel power unit agent (FFPUA), reference agent (RA), feedforward control agents (FFCAs), feedback control agents (FBCAs) and coordinator agent (COA). The reference agent decomposes the task of the MACS by multiobjective optimization. The FFCAs make decision using the neuro-fuzzy systems and the FBCAs make decision using the genetic algorithm-based fuzzy systems. The coordinator agent coordinates the agents in the MACS according to different operating conditions.

In this paper, a new multi-agent control system (MACS) is proposed for smart distribution networks. It can: 1) eliminate the feeders' congestion, 2) globally correct voltage violations, and 3) coordinate the operation of reactive power control devices. In performing its functions, the MACS must prevent overstress on the substation voltage regulator tap changer under all operating conditions, and avoid selective active power curtailment from DG units. This can help to improve reliability, economic revenue, and power quality. A fuzzy rule-based system is employed for decision-making support in MACS. The proposed MACS can achieve the self-healing requirement of smart distribution network. It eliminates feeders' congestion by properly reconfiguring the distribution network. Meanwhile, it amends most of voltage violation problems by coordinated operation of voltage control devices in the distribution system. The MACS overcomes the severe voltage violation problems via distribution network reconfiguration. It is applied to the IEEE 33-bus test feeder. A full dynamic model is constructed using a parallel MATLAB-JADE simulation arrangement. Comparative performance evaluations of the MACS and other schemes are presented under various conditions.