Strip tracking in hot strip mills

In the finishing mill, steel strip is rolled from thick slabs through pairs of rollers housed in a continuous train of seven roll stands. As the strip is rolled, unwanted lateral movement, known as strip tracking, can cause the strip to collide with the edge of the mill. Strip tracking control is currently a manual operation, relying on the skill of the operators. When tracking is observed, the stand tilt is adjusted asymmetrically, causing a camber in the strip, steering it towards the centreline. Tracking control can be automated if a reliable measurement of position is available. A vision-based system was developed to measure strip position. Cooling water, steam, high temperatures and electrical noise create a hazardous environment for electronic equipment and hamper image analysis. Hardware was specified to protect all equipment against the environment. A novel image analysis method combining predictive elements, filtering and Bezier curve fitting was created to allow measurements to be made with large amounts of cooling water obscuring the strip edges. The measurement system was designed to integrate with the existing mill systems, using the OPC protocol for communication. The system was created as a development system with only two cameras included, but allowed for additional cameras to be easily added and automatically detected. The results of the system showed that the image analysis techniques were effective, providing an estimated final resolution of 3.5mm/pixel, with measurements ±2mm within 60% confidence. Hardware performance provided good protection of the equipment against the environment but poor quality installation limited overall system performance. A computer model was developed to simulate tracking behaviour in the mill with non-linear variations of strip properties across the strip. The model was not completed to a satisfactory standard capable of producing useful results but the theories described could be developed further.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Strip tracking in hot strip mills

In the finishing mill, steel strip is rolled from thick slabs through pairs of rollers housed in a continuous train of seven roll stands. As the strip is rolled, unwanted lateral movement, known as strip tracking, can cause the strip to collide with the edge of the mill. Strip tracking control is currently a manual operation, relying on the skill of the operators. When tracking is observed, the stand tilt is adjusted asymmetrically, causing a camber in the strip, steering it towards the centreline. Tracking control can be automated if a reliable measurement of position is available. A vision-based system was developed to measure strip position. Cooling water, steam, high temperatures and electrical noise create a hazardous environment for electronic equipment and hamper image analysis. Hardware was specified to protect all equipment against the environment. A novel image analysis method combining predictive elements, filtering and Bezier curve fitting was created to allow measurements to be made with large amounts of cooling water obscuring the strip edges. The measurement system was designed to integrate with the existing mill systems, using the OPC protocol for communication. The system was created as a development system with only two cameras included, but allowed for additional cameras to be easily added and automatically detected. The results of the system showed that the image analysis techniques were effective, providing an estimated final resolution of 3.5mm/pixel, with measurements ±2mm within 60% confidence. Hardware performance provided good protection of the equipment against the environment but poor quality installation limited overall system performance. A computer model was developed to simulate tracking behaviour in the mill with non-linear variations of strip properties across the strip. The model was not completed to a satisfactory standard capable of producing useful results but the theories described could be developed further

Closed-loop control of product properties in metal forming

Metal forming processes operate in conditions of uncertainty due to parameter variation and imperfect understanding. This uncertainty leads to a degradation of product properties from customer specifications, which can be reduced by the use of closed-loop control. A framework of analysis is presented for understanding closed-loop control in metal forming, allowing an assessment of current and future developments in actuators, sensors and models. This leads to a survey of current and emerging applications across a broad spectrum of metal forming processes, and a discussion of likely developments.Engineering and Physical Sciences Research Council (Grant ID: EP/K018108/1)This is the final version of the article. It first appeared from Elsevier via https://doi.org/10.1016/j.cirp.2016.06.00

Knowledge-driven Artificial Intelligence in Steelmaking: Towards Industry 4.0

With the ongoing emergence of the Fourth Industrial Revolution, often referred to as Indus-try 4.0, new innovations, concepts, and standards are reshaping manufacturing processes and production, leading to intelligent cyber-physical systems and smart factories. Steel production is one important manufacturing process that is undergoing this digital transfor-mation. Realising this vision in steel production comes with unique challenges, including the seamless interoperability between diverse and complex systems, the uniformity of het-erogeneous data, and a need for standardised human-to-machine and machine-to-machine communication protocols. To address these challenges, international standards have been developed, and new technologies have been introduced and studied in both industry and academia. However, due to the vast quantity, scale, and heterogeneous nature of industrial data and systems, achieving interoperability among components within the context of Industry 4.0 remains a challenge, requiring the need for formal knowledge representation capabilities to enhance the understanding of data and information. In response, semantic-based technologies have been proposed as a method to capture knowledge from data and resolve incompatibility conflicts within Industry 4.0 scenarios. We propose utilising fundamental Semantic Web concepts, such as ontologies and knowledge graphs, specifically to enhance semantic interoperability, improve data integration, and standardise data across heterogeneous systems within the context of steelmaking. Addition-ally, we investigate ongoing trends that involve the integration of Machine Learning (ML)techniques with semantic technologies, resulting in the creation of hybrid models. These models capitalise on the strengths derived from the intersection of these two AI approaches.Furthermore, we explore the need for continuous reasoning over data streams, presenting preliminary research that combines ML and semantic technologies in the context of data streams. In this thesis, we make four main contributions: (1) We discover that a clear under-standing of semantic-based asset administration shells, an international standard within the RAMI 4.0 model, was lacking, and provide an extensive survey on semantic-based implementations of asset administration shells. We focus on literature that utilises semantic technologies to enhance the representation, integration, and exchange of information in an industrial setting. (2) The creation of an ontology, a semantic knowledge base, which specifically captures the cold rolling processes in steelmaking. We demonstrate use cases that leverage these semantic methodologies with real-world industrial data for data access, data integration, data querying, and condition-based maintenance purposes. (3) A frame-work demonstrating one approach for integrating machine learning models with semantic technologies to aid decision-making in the domain of steelmaking. We showcase a novel approach of applying random forest classification using rule-based reasoning, incorporating both meta-data and external domain expert knowledge into the model, resulting in improved knowledge-guided assistance for the human-in-the-loop during steelmaking processes. (4) The groundwork for a continuous data stream reasoning framework, where both domain expert knowledge and random forest classification can be dynamically applied to data streams on the fly. This approach opens up possibilities for real-time condition-based monitoring and real-time decision support for predictive maintenance applications. We demonstrate the adaptability of the framework in the context of dynamic steel production processes. Our contributions have been validated on both real-world data sets with peer-reviewed conferences and journals, as well as through collaboration with domain experts from our industrial partners at Tata Steel

Aeronautical engineering: A continuing bibliography with indexes (supplement 293)

This bibliography lists 476 reports, articles, and other documents introduced into the NASA scientific and technical information system in July, 1992. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Aeronautical engineering: A continuing bibliography with indexes (supplement 267)

This bibliography lists 661 reports, articles, and other documents introduced into the NASA scientific and technical information system in June, 1991. Subject coverage includes design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; theoretical and applied aspects of aerodynamics and general fluid dynamics; electrical engineering; aircraft control; remote sensing; computer sciences; nuclear physics; and social sciences

Aeronautical engineering: A continuing bibliography with indexes (supplement 279)

This bibliography lists 759 reports, articles, and other documents introduced into the NASA scientific and technical information system in May 1992. Subject coverage includes: design, construction, and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics