Hybrid Systems for Production Control

An overview of knowledge-based systems for industrial scheduling is provided, with emphasis on systems which have undergone concrete development. Three perspectives are employed: knowledge representation, temporal reasoning and control. Where appropriate, developments in AI which could prove useful from the viewpoint of industrial scheduling are referred to. Some general conclusions and pointers for future development are offered. >

We pose a multi-model system parameter estimation problem. A multi-model system is a linearly parameterized system H(z, p)=/spl Sigma//sub i=1//sup np/p/sub i/H/sub i/(z). The parameter estimation problem is: given the set of systems {H/sub i/(z)}/sub i=1//sup np/, describing the multi-model system, find a causal system that assumes as an input the input/output signals of the multi-model system and produces as an output the parameter estimate. We propose an easy to implement suboptimal solution. The algorithm that realizes it selects the best linear combination of the estimates produced by the Kalman filters designed for the models {H/sub i/(z)}/sub i=1//sup np/. Best is defined in the sense of minimization of the output error of estimation covariance. The algorithm is appropriate for fault detection and can be viewed as an observer for the discrete state of a hybrid system.

A Scheduling system shall support the human scheduler in his daily work in creating and revising schedules of the production. Several criteria influence the requirements for such a system, e.g., the area of production and the preferences of the producing company as well as the need for presentation of specific information and sophisticated scheduling algorithms. Most of the existing scheduling systems have been built from scratch. To improve the building of scheduling systems an intelligent support system for the implementation of hybrid scheduling systems is presented which integrates different scheduling techniques, knowledge about their appropriateness for specific problem scenarios and knowledge about the design of scheduling systems. Using this knowledge it helps the user designing adequate scheduling systems for different application scenarios.

Task Scheduling is the establishment of specific guidelines for the consecutive execution of activities. Within the domain of parallel computing, the process of scheduling becomes complex, requiring the use of several processors and the allocation of resources to each individual processor. The goal is to effectively distribute particular tasks across processors and computers to accomplish predetermined objectives. It is essential to focus on work scheduling and resource management, as these are the main problems in numerical comparison. This study employs a metaheuristic hybrid strategy to address the inherent challenges of task scheduling. The primary objective is to enhance the efficiency of resource allocation and work scheduling, which is achieved by utilizing a Hybrid Genetic Algorithm (HGA). The results obtained from implementing the HGA algorithm on 40 operational tasks demonstrate its higher performance in comparison to other algorithms. The approach is very effective in tackling task scheduling problems in multiprocessor computing systems. This approach is notable for its faster convergence time and more efficient utilization of resources compared to other algorithms. The HGA technique is a reliable solution for improving work scheduling and resource management in parallel computing environments.

This study evaluated wireless power transfer (WPT) technologies for electric vehicles (EVs), focusing on inductive (IPT), capacitive (CPT), and hybrid (HPT) systems. IPT utilizes resonant magnetic fields, CPT employs resonant electric fields, and HPT combines both methods to optimize the use of electromagnetic fields and electronic components. Pilot experiments were conducted using WPT standards and the relevant literature to investigate the efficiency and practical implementation of these WPT technologies. The evaluation included measuring system efficiencies with multimeters, assessing input and output waveform smoothness using oscilloscopes, detecting power losses through thermal scans, and monitoring electromagnetic field (EMF) exposure with EMF detectors. The results demonstrated that IPT achieved higher efficiency, smoother waveforms, and lower EMF exposure than CPT and HPT at lower frequencies. Moreover, IPT has a more straightforward circuit design owing to the lack of high-frequency components, further enhancing its practicality. The study also examined the effects of ground clearance and misalignment on WPT performance, and addressed safety concerns and potential solutions for all three types of WPT systems.

Scheduling of energy storage systems of distributed generation is a key element for optimal renewable energy sources (RES) exploitation in smart grids, demand side response strategies implementation and prosumers interaction with Distribution System Operators (DSOs). In this context, this paper presents the implementation of a management system for energy storage scheduling, which allows taking appropriate account of the storage system behavior in real cases. To properly consider the real system operation, the employed battery model is modified, in order to include also the hysteresis phenomena in state of charge estimation in both charging and discharging operation. The validation of the proposed methodology is supported by experimental tests which allow comparing two different battery models. The obtained results show that better results can be obtained with the model including the hysteresis effect.

This paper discusses the implementation of a knowledge-based system for the dynamic scheduling of a two-stage production process. It is an interactive, real-time, menu-driven system written in Prolog. The system architecture is delineated and the rules and problem-solving logic to be used under various dynamic situations are described. Results of a sample system test session are included to illustrate its use.

Representation of quantum states by statistical ensembles on the quantum phase space in the Hamiltonian form of quantum mechanics is analyzed. Various mathematical properties and some physical interpretations of the equivalence classes of ensembles representing a mixed quantum state in the Hamiltonian formulation are examined. In particular, non-uniqueness of the quantum phase space probability density associated with the quantum mixed state, Liouville dynamics of the probability densities and the possibility to represent the reduced states of bipartite systems by marginal distributions are discussed in detail. These considerations are used to study ensembles of hybrid quantum-classical systems. In particular, nonlinear evolution of a single hybrid system in a pure state and unequal evolutions of initially equivalent ensembles are discussed in the context of coupled hybrid systems.

Enhancing electricity-driven methanogenesis by assembling biotic-abiotic hybrid system in anaerobic membrane bioreactor

We present TRACE-cs, a novel hybrid system that combines logical reasoning with large language models (LLMs) to address contrastive queries in course scheduling problems. TRACE-cs leverages logic-based techniques to encode scheduling constraints and generate provably correct explanations, while utilizing an LLM to process natural language queries and refine logical explanations into user-friendly responses. This system showcases how combining symbolic KR methods with LLMs creates explainable AI agents that balance logical correctness with natural language accessibility, addressing a fundamental challenge in deployed scheduling systems.

Smart grid is an inevitable choice for the future development of the grid. Smart scheduling is one of the cores to build the strong and smart grid in China. Optimization and Management System for Grid Maintenance Scheduling is an in-depth exploration to achieve dispatching digitalization, intellectualization and visualization. This paper gives a rather detailed description about the functionality and implementation of Optimization and Management System for Grid Maintenance Scheduling. With received maintenance schedules as the basic data, OCCI-based data processing techniques and PSO-based optimization methodology are adopted to achieve the standardization and intellectualization of the grid maintenance scheduling. Moreover, the maintenance schedules generated and related information are managed in a standardized way. The design from this paper together with its programs has been applied in practice, achieving satisfying effect.

Traditional approaches to planning and control of manufacturing (MRPII) focus on discrete parts manufacturing industries (e.g. automotive). The chemical industry, however, presents unique challenges. Cross-contamination of production is a key issue among some chemical facilities. A considerable amount of capacity is lost as a result of changeovers which involve performing thorough clean-ups to wash away the impurities which may contaminate the next product to be produced. Therefore, planning for sequence-dependent changeovers becomes crucial and complicates the master production scheduling process. This paper shows how improved master production scheduling performance can be obtained by using a two-level master production schedule (MPS) to focus on key plant processes, and by incorporating a scheduling heuristic which considers sequence-dependent changeovers and capacity constraints. This approach is illustrated using actual operating data from a chemical firm typical of many process industry operations. Simulation experiments are reported that test the performance of the proposed master scheduling method in a single-stage sequence-dependent process. The experimental factors include both the introduction of the two-level MPS with the scheduling heuristic, and the effect of changes in the MPS batch size. The results demonstrate that important simultaneous improvements in process changeover time and delivery performance can be achieved using the proposed MPS scheduling approach against a more traditional (single-level) MPS approach which does not consider sequence-dependent changeovers. Further, we find that delivery performance is relatively insensitive to adjustments in the MPS batch size when using the two-level MPS approach.

This paper aims to discuss the design and implementation of automatic control system for chemical production line based on PLC. With the rapid development of chemical industry and the intensification of market competition, it has become an important demand for chemical enterprises to improve production efficiency, ensure product quality and realize automation and intelligence of production process. Firstly, this paper analyzes the characteristics and requirements of chemical production line, as well as the requirements and objectives of automatic control system. Then, the overall architecture design, hardware design, software design, system implementation and testing process of the automatic control system of chemical production line based on PLC are described in detail. The feasibility and effectiveness of the system are verified by the analysis of practical application cases. The research results show that the automatic control system of chemical production line based on PLC can significantly improve production efficiency, reduce production costs, ensure product quality and enhance the market competitiveness of chemical enterprises. The research in this paper provides new ideas and methods for the design and implementation of automatic control system in chemical industry.

Software systems have been used in chemical industry process safety operation and design to improve its efficiency. This paper provides a brief review and analysis of the state of the art and impacts of software systems in process safety. A study was carried out by interviewing personnel in charge of process safety practices in the Malaysian chemical process industry and digging into literature of technology for process safety. This article explores the functional and operational characteristics of software systems for safety and attempts to categorize the software according to its level of impact in the management hierarchy. The study contributes to better understanding of the roles of Information Communication Technology in process safety, the future trends and possible gaps for research and development.
 Keywords: process safety; software systems; computer-aided plant safety; process safety management system.

Modular control system with intelligent scheduling