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advanced process control: Opportunities, benefits, and barriers

COMPUTING & control ENGINEERING JOURNAL 2003年第5期14卷 10-15页

作者： Eder, HH

advanced process control offers substantial improvements to industry, but widespread misunderstandings and a lack of knowledge have hindered its implementation.

关键词： control equipment and processes in production engineering control applications in manufacturing processes operations improvements Industrial processes Manufacturing processes control in industrial production systems plant operations objectives process control technology advanced process control process control

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advanced process control DEVELOPMENT IN RESIDUA CATALYTIC CRACKER control

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石油学报(石油加工) 2000年第5期16卷 85-87页

作者： WANG Li xing 1,GUO Jin biao 2 (1 SINOPEC, Beijing 100029,China 2 Research Institute of Petroleum processing,SINOPEC,Beijing 100083,China) SINOPEC 北京 100029 Research Institute of Petroleum Processing SIN OPEC 北京 100083

process calculations and rigorous dynamic model with detailed coke combustion kine tics for two stage regeneration FCC process were developed and integrated into the advanced process control (APC) context The package was implemented in 6 SINOPEC commercial RFCCUs Typical 0 5%～0 8% improvement of target product yields was achieved Significant energy consumption was saved with tighter control over coke burning

关键词： advanced process control residua catalytic cracker model predictive control technique

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advanced process control aimed at energy efficiency improvement in process industries 19

Advanced Process Control aimed at energy efficiency improvem...

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19th IEEE International Conference on Industrial Technologies (ICIT)

作者： Zanoli, Silvia Maria Barboni, Luca Cocchioni, Francesco Pepe, Crescenzo Univ Politecn Marche UNIVPM DII Via Brecce Bianche I-60131 Ancona AN Italy I Proc Srl Via Consorzio 2 I-60015 Falconara M Ma AN Italy

ISBN: (纸本)9781509059492

This paper proposes an advanced process control framework aimed at energy efficiency achievement and improvement in process industries. Model Predictive control is the adopted control strategy: an architecture based on several cooperating blocks is proposed. The developed basic control framework has been enriched and customized for its installation on industrial processes. Steel industry billets reheating furnaces and cement industry clinker rotary kilns are examples of customized applications. With respect to the previous control systems, based on standalone controllers and/or plant operators manual conduction, strategic trade-offs between opposing objectives, e.g. production targets meeting, product quality specifications fulfillment, and energy efficiency achievement, have been ensured, together with significant improvements on process control.

关键词： advanced process control Model Predictive control clinker production reheating furnace energy efficiency

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advanced process control Modeling from an advanced Planning and Scheduling Perspective 10th

Advanced Process Control Modeling from an Advanced Planning ...

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10th IFAC Triennial Conference on Manufacturing Modelling, Management and control (MIM)

作者： Kelly, Jeffrey D. Menezes, Brenno C. Ind Algorithms Ltd Toronto ON M1P 4C3 Canada Hamad Bin Khalifa Univ Qatar Fdn Coll Sci & Engn Div Engn Management & Decis Sci Doha Qatar

Further to basic process control strategies, advanced process control (APC) aims to improve the performance of the control by actuating towards input moves against effects of process disturbances. Typically addressing economic-based goals as objectives, APC includes a wide range of techniques embedded in process control systems generally found in continuous-process industries such as processing of food, fuels, bulk chemicals, metals, minerals, pulp and paper, among others. Different from the well-known APC techniques such as feedforward, decoupling, inferential, constraint control, etc., we address a novel approach to the dependent-independent or controlled-manipulated pairing of variables of the model predictive control (MPC), also known as moving horizon control (MHC). We introduce manipulated variables as batch-processes into the MPC formulation to build the dynamic model with their paired controlled variables. The manipulated-controlled MPC formulation is configured as an advanced planning and scheduling (APS) problem as opposed to a traditional APC problem whereby the manipulated-batch-process variables are considered with relative-time yields representing their finite impulse-responses or differenced step-responses. As we shall show, APC problems can be equally formulated as a batch-process in APS perspective. To eliminate the steady-state offset between the actual controlled value and its target or setpoint, it is well-known to apply bias-updating though other forms of parameter-feedback are possible. Typically, APS applications only employ variable-feedback, i.e., opening or starting inventories, properties, etc., but this alone will not alleviate the steady-state offset. A small and representative example highlights the APC as an APS modeling with parameter feedback. Copyright (C) 2022 The Authors.

关键词： advanced process control Model predictive control Parameter feedback Batch-process modeling Relative-time yield

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advanced process control for energy efficiency increase in a walking beam reheating furnace 26

Advanced Process Control for energy efficiency increase in a...

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26th IEEE International Symposium on Industrial Electronics (ISIE)

作者： Zanoli, Silvia Maria Pepe, Crescenzo Barboni, Luca Cocchioni, Francesco Univ Politecn Marche Univ DII Via Brecce Bianche I-60131 Ancona AN Italy I Proc Srl Via Consorzio 2 I-60015 Ancona AN Italy

ISBN: (纸本)9781509014125

In this paper, an advanced process control framework based on the cooperation of several key blocks is proposed. A Supervisory control and Data Acquisition system communicates with a two-layer linear Model Predictive control block. An additional block online determines the set of process variables to be included in the control problem. In particular, bad conditions and local control loops faults are checked;in addition, thanks to a matrix-based approach, inputs to exploit for the fulfilment of specifications on the process outputs are selected. The developed control framework has been applied on a walking beam billets reheating furnace, located in an Italian steel industry. The application on the plant has shown fine reliability and flexibility properties, reaching profitable working points and leading to an energy efficiency increase.

关键词： Model Predictive control advanced process control status value reheating furnace energy efficiency

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advanced process control APPLICATIONS FOR advanced CMP process

ADVANCED PROCESS CONTROL APPLICATIONS FOR ADVANCED CMP PROCE...

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China Semiconductor Technology International Conference

作者： Yang, Jun Lin, Yi Shih Yang, SiYuan Frank Huang, Yi Shao, Qun Liu, Hongtao Semicond Mfg Int Shanghai Corp Shanghai 201203 Peoples R China

ISBN: (纸本)9781479972425

There are increasing new needs for advanced process control (APC) from chemical mechanical polishing (CMP) process along with the technology nodes advancing to 28nm and below. Besides traditional applications for wafer to wafer and batch to batch thickness variation reduction, and feed-forward based on incoming thickness/depth, the other new needs include within wafer uniformity control based on consumable counts and incoming profile, preventing polishing rate from dropping due to disk and pad deteriorating etc. This paper discusses those APC applications for CMP processes and along with important features which advanced APC software should equip with.

关键词： advanced process control chemical mechanical polishing profile control run to run control partition safety guarding features

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advanced process control Using Partial Least Squares

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2nd International Conference on advanced Engineering Materials and Technology (AEMT)

作者： Fan, Shu-Kai S. Chang, Yuan-Jung Natl Taipei Univ Technol Taipei 106 Taiwan Yuan Ze Univ Ind Engn & Management Taoyuan 243 Taiwan

ISBN: (纸本)9783037854488

This paper applies the partial least squares (PLS) technique to the multiple-input multiple-output (MIMO) semiconductor processes under the paradigm of the advanced process control (APC). First, we present a controller called the PLS-MIMO double exponentially weighted moving average (PLS-MEMO DEWMA) controller. It uses the PLS method as the model building/estimation technique to help the EWMA controller to produce more consistent and robust control outputs than purely using the conventional EWMA controller. To cope with metrology delays, the proposed controller uses the pre-process metrology data to build up a Virtual Metrology (VM) system that can provide the estimated process outputs for the PLS-MIMO DEWMA controller. Finally, a Fault Detection (FD) system is added based upon the principal components of PLS, which supplies the process state for VM and the PLS-MIMO DEWMA controller to respond to the system errors.

关键词： advanced process control partial least squares virtual metrology fault detection

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advanced process control of a cement plant grate cooler 26

Advanced Process Control of a cement plant grate cooler

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26th International Conference on System Theory, control and Computing (ICSTCC)

作者： Zanoli, Silvia Maria Pepe, Crescenzo Astolfi, Giacomo Univ Politecn Marche Dip Ingn dellInformazione DII Ancona Italy Alperia Green Future Falconara Italy

ISBN: (数字)9781665467469

ISBN: (纸本)9781665467469

The present work describes an advanced process control solution applied to a cement plant grate cooler. The grate cooler is located downstream of a clinker rotary kiln with the purpose of suitably cooling the clinker. Clinker is cooled through the action of multiple cold air fan units as it is transported by the clinker rotary kiln. A Model Predictive control strategy was designed in order to minimize the electrical energy consumption of the cold air fan units while guaranteeing the necessary heat recovery for the kiln and the preheater. At the same time, clinker quality constraints are taken into account. The designed controller has been installed on the real plant, obtaining satisfactory results in terms of kiln tertiary air increase and of kiln combustion improvement. In particular, a major process stabilization has been achieved, proven by a significant reduction of the standard deviation related to the pressure of cooler grate.

关键词： cement industry clinker production grate cooler advanced process control Model Predictive control

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advanced process control by machine learning based virtual metrology for high product mix manufacturing 38

Advanced process control by machine learning based virtual m...

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Conference on Metrology, Inspection, and process control XXXVIII

作者： Lee, Hyung Joo Choi, Sanghyun Greeneltch, Nathan Jayaram, Srividya Siemens EDA Digital Ind Software Seongnam 13524 Gyeonggi South Korea Siemens EDA Digital Ind Software 8500 SW Boeckman Rd Wilsonville OR 97070 USA

ISBN: (纸本)9781510672178;9781510672161

The semiconductor foundry industry struggles with challenges in high-product-mix manufacturing, necessitating enhanced flexibility to address diverse customer demands. Coordinating multiple chambers and process steps with varying designs and technology nodes poses complexities leading to reduced yields and increased costs. The chemical vapor deposition (CVD) process introduces thickness variations due to device layout design and chamber condition drift, impacting transistor parameters and yield. Managing chamber-by-chamber variations is critical for high-volume manufacturing, yet traditional solutions fall short in fab line management, resulting in throughput loss. Conventional VM relies on data from the process chamber, referred to as fault detection and classification (FDC), to predict metrology results. In this study, the extraction of design features for better predictive purposes across diverse layouts and technologies are highlighted. Siemens' Calibre (R) software is employed for design feature extraction, and machine learning (ML) methodologies to construct the extended VM model. An advanced process control (APC) system using the extended VM model for run-to-run (R2R) control is proposed. It incorporates design features, FDC, and measurements to achieve the desired thickness target. The system triggers updates to the extended VM model based on prediction errors. Through control simulations, the APC system significantly enhances process capability and reduces film thickness variations, confirming its effectiveness in a high-mix product foundry fab. Responding to the growing demand for custom-designed products, this paper suggests integrating an ML-based extended VM model with design features and FDC into the APC system, presenting a promise solution for high-product-mix manufacturing.

关键词： Virtual metrology advanced process control machine learning high product mix manufacturing chemical vapor deposition design features chamber condition semiconductor foundry

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Big Data Capabilities Applied to Semiconductor Manufacturing advanced process control

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IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2016年第4期29卷 283-291页

作者： Moyne, James Samantaray, Jamini Armacost, Michael Appl Mat Inc Santa Clara CA 95054 USA

As requirements on data volumes, rates, quality, merging, and analytics increase exponentially in the digital universe, semiconductor manufacturers are faced with a need for new approaches to data management and use across the Fab. These are often termed "big data" challenges. In our industry big data solutions will be key to scaling advanced process control (APC) solutions to finer levels of control and diagnostics. However the main impact will be to better enable more effective predictive technologies such as predictive maintenance (PdM), virtual metrology and yield prediction, all of which utilize data from traditional APC capabilities that include fault detection and classification and run-to-run control. PdM represents one area where big data solutions are generating significant benefits across a variety of process types. Moving to big data solutions involves addressing the aforementioned requirements either with enhancements of existing systems or moving to more big data friendly platforms. Big data friendly platforms applied to APC systems provide quantifiable cost-of-ownership and speed improvements, thereby better enabling high quality prediction solutions. Initially, big data solutions will largely be delegated to off-line and on-time critical tasks;over the longer term these big data solutions will increasingly be leveraged for time critical and real-time capabilities.

关键词： advanced process control big data database management systems hadoop prediction methods predictive control predictive maintenance process control virtual metrology yield prediction

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