Synthesis Of Operating Procedures Research Articles

A Hybrid Metaheuristic Optimization Approach for the Synthesis of Operating Procedures for Optimal Drum-Boiler Startups

A steam generator serves as a power generation equipment that uses the expansive power of steam to generate electricity. The startup process of a steam generator plays an important process in a power plant to adjust its electricity generation in response to changes in load demand. As renewable generation plants increase, the levels of variability in electricity production increase. Fast startups become instrumental as they enable traditional power generation plants to provide the quantity of electricity missing when variable renewable energies cannot satisfy the load demand. The drum boiler is one of the main pieces of equipment involved in the startup process of a steam generator. However, if the startup process is carried out too fast, excessive thermal stresses may occur, thus provoking damage to the components of the drum boiler. This paper proposes a dynamic optimization methodology to synthesize operating procedures that minimize the startup time of the drum boiler while avoiding the excessive formation of thermal stresses. Since valve operations influence the time-varying behavior of the steam, dynamic simulation is needed in order to evaluate the operating procedure. The proposed algorithm is based on two important elements of two metaheuristic algorithms: the acceptance probability of the simulated annealing algorithm and the tabu search memory structures. A case study evaluates the proposed approach by comparing it against results previously published in the literature.

Synthesis, Validation, and Evaluation of Operating Procedures Based on Timed Automata and Dynamic Simulation

Manually generating the operating procedures is often laborious, time-consuming, and error-prone. Because the online sensors may not always be adequate for a designated operation in the plant, the ...

Model-based and rule-based synthesis of operating procedures for planning severe accident management strategies

When severe accidents happen in nuclear power plants (NPPs), although there are candidate high-level actions (CHLAs) that can be selected from the severe accident management guidance (SAMG) to mitigate consequences, operators may still have cognitive challenges to identify available plant sources and then formulate executable action plans to implement the chosen actions. The difficulties faced by humans may be resolved by a decision support system taking advantages of computers’ knowledge representation and inferential capability.This article presents a systematic approach for synthesizing operating procedures that can achieve operational goals with currently available plant resources. Multilevel flow modeling (MFM), whose representation has been proved to be consistent with the general emergency procedure development, is used as knowledge basis for the action planning. A rule reasoning method is proposed to infer about actions from perspective of functions’ state transition. A model-based and rule-based operating procedure synthesis (OPS) system is developed with a rule engine. The OPS system is applied to elaborate existing high level strategies for dealing with station blackout (SBO) in a BWR plant as multiple executable action plans. The results shows some untypical ways of implementing available systems for achieving current safety goals, which may be considered in the further SAM. Moreover, what critical plant resources should be well prepared in advance is also indicated from the case study. Finally, limitation of MFM and the develop OPS system on planning SAM strategies are discussed.

Synthesis and Validation of Operating Procedures Based on Untimed Automata

To facilitate efficient procedure synthesis, the extended finite automata are adopted in this work to model all components in a chemical process. The intended operation is divided into several stages and each characterized with a set of unique features, e.g., stable operation, condition adjustment, material charging and/or unloading, etc. The control specifications of every stage should then be stipulated accordingly and also described with automata. The observable event traces (OETs) embedded in this system can be produced by synchronizing all aforementioned automata. The candidate operating procedures are summarized with sequential function charts (SFCs) on the basis of these OETs. The commercial package ASPEN Plus Dynamic has been used to validate these SFCs in simulation studies.

An automata-based approach to synthesize untimed operating procedures in batch chemical processes

Systematic synthesis of untimed operating procedures has always been considered as an important design issue for batch chemical processes. An automaton-based method is developed in the present study to perform this task automatically. On the basis of the proposed methodical model-building principles, two distinct types of automata can be constructed to characterize the plant behaviors and control specifications, respectively. An admissible supervisor can be produced by applying the parallel composition operation with these models. For the purpose of identifying the most efficient operation procedures, the supervisor can then be integrated with a set of auxiliary automata to set the operation target(s) and, also, to impose upper limits on the total numbers of actuator actions and operation steps. Three examples are presented to demonstrate the feasibility and correctness of the proposed approach.

Operating Procedure Synthesis Subject to Restricted State Transition Using Differential Evolution

Abstract To obtain a near optimal solution for operating procedure synthesis under safety constraint, in this paper, we intended to apply a meta-heuristic method termed differential evolution (DE). Compared with the previous approaches, we have shown DE's ability to derive such an operating sequence that is adaptive to various practical requirements and serves easy operation manner. Since the algorithm is straightforward and flexible to manage various conditions appearing in real-world applications, we can claim great promise of the proposed approach. In a case study, we applied the proposed method to safety mixing operation of acrylic acid synthesis process and validated its adaptability under various significant practical conditions.

Error-free scheduling for batch processes using symbolic model verifier

This paper focuses on the development of a new approach for the synthesis of error-free operating schedules in batch processes. The synthesis of error-free operating procedures for batch processes becomes an important issue in the safe operation of industrial plant. It spends considerable amount of time and effort in scheduling and verifying operating procedures for correctness and completeness. In this study, we adopted SMV (Symbolic Model Verifier), an automatic error finding system, which is applied to various batch processes to test their safety and feasibility. The strength of this method is to minimize safety hazard and operability errors, and adjust process and recipe changes during the planning of operating procedure. The proposed approach identifies embedded errors and finds a minimum makespan and synthesizes an error-free operating sequence at the same time. Several examples are presented to illustrate the effectiveness of the proposed approaches.

Petri-Net Based Binary Integer Programs for Automatic Synthesis of Batch Operating Procedures

Traditionally, the task of conjecturing the operation steps in batch processes is carried out manually on an ad hoc basis. This approach is often time-consuming in industrial applications, and furthermore, the resulting recipes may be error-prone. The aim of this paper is thus to develop a systematic strategy to generate the optimal operation procedures with the Petri-net based binary integer programs (BIPs). Specifically, the system net consists of three types of standard subnets, i.e., the path modules, the equipment modules, and the process modules. The logic constraints in the corresponding BIP are formulated mainly for the purpose of describing the token movements in the system net. Additional constraints are also incorporated to enhance solution efficiency. The specific actions in the optimal operating procedure can be determined by solving this integer program. Two distinct classes of operation modes can be identified: (1) stage-based operating procedures and (2) time-based operating procedures. Several realistic examples are provided in this paper to demonstrate the feasibility of the proposed strategy.

Synthesis of Operating Procedures and Procedural Controllers for Batch Processes Based on Petri Nets

Batch control is characterized by procedural control that is realized according to operating procedures to accomplish tasks. However, operating procedure synthesis takes considerable time and effort as the complexity of a batch process increases. To solve the operating procedure synthesis problem, a modeling technique is needed to represent the concurrent dynamics of a batch process. This paper aims at developing a method to synthesize operating procedures and procedural controllers for batch processes. For this purpose, it first views a batch control system as a discrete event system and next uses hierarchical Petri nets to represent information about process, plant, and schedule. It then presents a method to synthesize operating procedures. It also discusses the verification of synthesized operating procedures and last presents a method to synthesize procedural controllers.

Operating procedure synthesis: science or art

In this paper, we provide a review of concepts and developments in operating procedure synthesis (OPS), starting from its early development through to its current state. Operating procedure synthesis is a problem in which a set of equipment manipulations and their orderings must be generated to take the process from an initial state to a goal state. While there has been ongoing research for about 30 years in this area, only a few systems have been reported to be industrially deployed. The approach taken in this paper is, first, to describe the problem in general terms; second, to discuss previous work in this area; and, finally, to present ideas and directions for future work.

An Operating Procedure Synthesis Method for Shutdown of Boiler Plants

A method is proposed which automatically synthesizes a safe operating procedure based on the knowledge of human operators that are generalized and classified hierarchically. The proposed method automatically generates and orders subgoals that must be achieved between the initial state and the goal state. It searches for the primitive operation device to achieve each subgoal subject to the operational constraints, and evaluates the safety of the operation. A case study of automatic synthesis of a boiler plant shutdown procedure shows the industrial applicability of the proposed method.

Intelligent systems for HAZOP analysis of complex process plants

Process safety, occupational health and environmental issues are ever increasing in importance in response to heightening public concerns and the resultant tightening of regulations. The process industries are addressing these concerns with a systematic and thorough process hazards analysis (PHA) of their new, as well as existing facilities. Given the enormous amounts of time, effort and money involved in performing the PHA reviews, there exists considerable incentive for automating the process hazards analysis of chemical process plants. In this paper, we review the progress in this area over the past few years. We also discuss the progress that has been made in our laboratory on the industrial application of intelligent systems for operating procedure synthesis and HAZOP analysis. Recent advances in this area have promising implications for process hazards analysis, inherently safer design, operator training and real-time fault diagnosis.

AI planning: solutions for real world problems

This paper argues that AI planning is a technology ripe for use on real world problems as shown by a number of current applications. An introduction is given to AI planning, and then followed by discussion of the successful application of this technology to generating operating procedures for chemical plants. A description is given of the methodology for developing planning domains and finally the results of its application to operating procedure synthesis are discussed.

Generating operating procedures for chemical process plants

Operating procedure synthesis (OPS) has been used to generate plant operating procedures for chemical plants. However, the application of AI planning to this domain has been rarely considered, and when it has the scope of the system used has limited it to solving “toy” problems. This paper describes the application of state‐of‐the‐art AI planning techniques to the generation of operating procedures for chemical plant as part of the INT‐OP project at the Universities of Salford and Loughborough. The CEP planner is outlined and its application to a double effect evaporator test rig is discussed in detail. Particular attention is paid to the issues involved in domain modelling, requiring the description of the domain, development of AI planning operators, the definition of safety restrictions, and the definition of the problem. There is then a presentation of the results, lessons learned and problems still remaining.

Integrating operating procedure synthesis and hazards analysis automation tools for batch processes

In this paper we address the problem of integrating two systems iTOPS, an Intelligent Tool for Operating Procedure Synthesis and BHE, BatchHAZOPexpert that are respective used for generating operator instructions and performing process hazards analysis for batch processes. The architecture of the integrated system is described and its application to an industrial case study is presented.

Optimal Simulation-Based Operations Planning with Quantitative Safety Constraints

A new two-layer optimization scheme is presented for operating procedure synthesis in the presence of quantitative safety path contraints. Layer 1 optimizes the overall operations time by varying the operator time constant - the time that an operator is applied to the system. Layer 2 performs the path-constrained optimization by minimizing the sum-of-squared errors between the current system state vector and a prespecified goal state vector by applying the system operators. New system states are calculated using dynamic simulation of the equations describing the system. A detailed example involving mixture control of potentially flammable chemicals is described, illustrating all aspects of the proposed methodology.

Automating operating procedure synthesis for batch processes: Part I. Knowledge representation and planning framework

Automating the synthesis of operating procedures for batch processes is very valuable as plant personnel often spend considerable amount of time and effort in preparing and verifying them for correctness and completeness. Towards this goal, a framework for automating operating procedure synthesis for batch processes is proposed in this paper. We propose an approach based on Grafcet, a discrete event modeling concept, to represent procedural knowledge combined with an object-oriented representation of the declarative knowledge. Grafcet is also used to model the information; called inferred knowledge, that is incrementally generated during operating procedure synthesis. The details of the basic components and the advanced features of Grafcet that make it a suitable technique for modeling the procedural and inferred knowledge are presented. A hierarchical planning strategy is proposed that uses the declarative and procedural knowledge to generate the inferred knowledge incrementally, which leads to the synthesis of the operating procedures. The implementation of this framework and its application to an industrial case study are presented in Part II.

Automating operating procedure synthesis for batch processes: Part II. Implementation and application

A framework for automating operating procedure synthesis for batch processes was presented in Part I of this paper. In this Part, we present iTOPS, an Intelligent Tool for Operating Procedure Synthesis, an automated system which is an implementation of the proposed framework. iTOPS has been developed using Gensym’s G2 expert system environment. The architecture of iTOPS and the implementation and algorithmic details of each of its components are explained. Also, the application of iTOPS to an industrial case study is presented.

ITOPS: An intelligent tool for operating procedures synthesis

Operating procedures are the detailed sequence of instructions an operator has to follow to manage a batch process safely and optimally. The traditional manual synthesis of operating procedures is time-consuming and error-prone and hence can benefit from automation. In this paper a description of iTOPS 4.0, an Intelligent Tool for Operating Procedure Synthesis, is presented. The architecture of iTOPS and its performance for a pharmaceutical industry case study are discussed.

A Two-Tier Methodology for Synthesis of Operating Procedures

A Two-Tier Methodology for Synthesis of Operating Procedures